diff --git a/.github/labeler.yml b/.github/labeler.yml index 32ae6c9b1e..99a38a6d9d 100644 --- a/.github/labeler.yml +++ b/.github/labeler.yml @@ -16,3 +16,13 @@ documentation: - any-glob-to-any-file: - docs/** - '**/*.md' + +# Add 'workflows' label to any change within the dotnet or python workflows src or samples +workflows: +- changed-files: + - any-glob-to-any-file: + - dotnet/src/Microsoft.Agents.Workflows/** + - dotnet/src/Microsoft.Agents.Workflows.Declarative/** + - dotnet/samples/GettingStarted/Workflow/** + - python/packages/workflows/** + - python/samples/getting_started/workflow/** \ No newline at end of file diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index 33faf7afd9..6658ebc9fd 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -20,4 +20,4 @@ Please help reviewers and future users, providing the following information: - [ ] The code builds clean without any errors or warnings - [ ] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md) - [ ] All unit tests pass, and I have added new tests where possible -- [ ] I didn't break anyone :smile: +- [ ] **Is this a breaking change?** If yes, add "[BREAKING]" prefix to the title of the PR. \ No newline at end of file diff --git a/.github/workflows/label-pr.yml b/.github/workflows/label-pr.yml index 11d0f083a8..4aea432e31 100644 --- a/.github/workflows/label-pr.yml +++ b/.github/workflows/label-pr.yml @@ -16,6 +16,6 @@ jobs: pull-requests: write steps: - - uses: actions/labeler@v5 + - uses: actions/labeler@v6 with: repo-token: "${{ secrets.GH_ACTIONS_PR_WRITE }}" diff --git a/.github/workflows/python-merge-tests.yml b/.github/workflows/python-merge-tests.yml index 6378e4520e..9868dc6c80 100644 --- a/.github/workflows/python-merge-tests.yml +++ b/.github/workflows/python-merge-tests.yml @@ -17,6 +17,7 @@ env: # Configure a constant location for the uv cache UV_CACHE_DIR: /tmp/.uv-cache RUN_INTEGRATION_TESTS: "true" + RUN_SAMPLES_TESTS: ${{ vars.RUN_SAMPLES_TESTS }} jobs: paths-filter: @@ -77,7 +78,13 @@ jobs: run: | uv sync --all-packages --all-extras --dev -U --prerelease=if-necessary-or-explicit - name: Test with pytest - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + timeout-minutes: 10 + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml + working-directory: ./python + - name: Test main samples + timeout-minutes: 10 + if: env.RUN_SAMPLES_TESTS == 'true' + run: uv run pytest tests/samples/ -m "openai" working-directory: ./python - name: Move coverage file run: | @@ -139,11 +146,17 @@ jobs: tenant-id: ${{ secrets.AZURE_TENANT_ID }} subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }} - name: Test with pytest - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + timeout-minutes: 10 + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml + working-directory: ./python + - name: Test azure samples + timeout-minutes: 10 + if: env.RUN_SAMPLES_TESTS == 'true' + run: uv run pytest tests/samples/ -m "azure" working-directory: ./python - name: Move coverage file run: | - mv ./packages/${{ env.PACKAGE_NAME }}/coverage.xml coverage_${{ env.PACKAGE_NAME }}.xml + mv ./packages/${{ env.PACKAGE_NAME }}/coverage.xml ./coverage_${{ env.PACKAGE_NAME }}.xml working-directory: ./python - name: Upload coverage artifact uses: actions/upload-artifact@v4 @@ -200,7 +213,13 @@ jobs: tenant-id: ${{ secrets.AZURE_TENANT_ID }} subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }} - name: Test with pytest - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + timeout-minutes: 10 + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml + working-directory: ./python + - name: Test foundry samples + timeout-minutes: 10 + if: env.RUN_SAMPLES_TESTS == 'true' + run: uv run pytest tests/samples/ -m "foundry" working-directory: ./python - name: Move coverage file run: | @@ -220,6 +239,7 @@ jobs: display-options: fEX fail-on-empty: true title: Test results + python-integration-tests-check: if: always() runs-on: ubuntu-latest diff --git a/.github/workflows/python-test-coverage.yml b/.github/workflows/python-test-coverage.yml index 59c8b4b4bf..08ffe47158 100644 --- a/.github/workflows/python-test-coverage.yml +++ b/.github/workflows/python-test-coverage.yml @@ -36,7 +36,7 @@ jobs: - name: Install the project run: uv sync --all-extras --dev - name: Run all tests with coverage report - run: uv run poe all-tests --cov-report=xml:python-coverage.xml -q --junitxml=pytest.xml + run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --cov-report=xml:python-coverage.xml -q --junitxml=pytest.xml - name: Upload coverage report uses: actions/upload-artifact@v4 with: diff --git a/.github/workflows/python-tests.yml b/.github/workflows/python-tests.yml index 2001cb9997..5981f27757 100644 --- a/.github/workflows/python-tests.yml +++ b/.github/workflows/python-tests.yml @@ -37,6 +37,7 @@ jobs: - name: Install the project run: | uv sync --all-packages --all-extras --dev -U --prerelease=if-necessary-or-explicit + # Main package tests - name: Set environment variables - main - win if: ${{ matrix.os == 'windows-latest' }} @@ -47,7 +48,7 @@ jobs: run: | echo "PACKAGE_NAME=main" >> $GITHUB_ENV - name: Test with pytest - main - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml working-directory: ./python - name: Move coverage file - main run: | @@ -58,6 +59,7 @@ jobs: with: name: coverage-${{ matrix.OS }}-${{ matrix.python-version }}-${{ env.PACKAGE_NAME }} path: ./python/coverage_${{ matrix.OS }}_${{ matrix.python-version }}_${{ env.PACKAGE_NAME }}.xml + # Azure package tests - name: Set environment variables - azure - win if: ${{ matrix.os == 'windows-latest' }} @@ -68,7 +70,7 @@ jobs: run: | echo "PACKAGE_NAME=azure" >> $GITHUB_ENV - name: Test with pytest - azure - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml working-directory: ./python - name: Move coverage file - azure run: | @@ -79,6 +81,7 @@ jobs: with: name: coverage-${{ matrix.OS }}-${{ matrix.python-version }}-${{ env.PACKAGE_NAME }} path: ./python/coverage_${{ matrix.OS }}_${{ matrix.python-version }}_${{ env.PACKAGE_NAME }}.xml + # Foundry package tests - name: Set environment variables - foundry - win if: ${{ matrix.os == 'windows-latest' }} @@ -89,7 +92,7 @@ jobs: run: | echo "PACKAGE_NAME=foundry" >> $GITHUB_ENV - name: Test with pytest - foundry - run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test --junitxml=coverage.xml + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml working-directory: ./python - name: Move coverage file - foundry run: | @@ -100,6 +103,30 @@ jobs: with: name: coverage-${{ matrix.OS }}-${{ matrix.python-version }}-${{ env.PACKAGE_NAME }} path: ./python/coverage_${{ matrix.OS }}_${{ matrix.python-version }}_${{ env.PACKAGE_NAME }}.xml + + # Workflow package tests + - name: Set environment variables - workflow - win + if: ${{ matrix.os == 'windows-latest' }} + run: | + echo "PACKAGE_NAME=workflow" | Out-File -FilePath $env:GITHUB_ENV -Append + - name: Set environment variables - workflow + if: ${{ matrix.os != 'windows-latest' }} + run: | + echo "PACKAGE_NAME=workflow" >> $GITHUB_ENV + - name: Test with pytest - workflow + run: uv run poe --directory ./packages/${{ env.PACKAGE_NAME }} test -n logical --dist loadfile --dist worksteal --junitxml=coverage.xml + working-directory: ./python + - name: Move coverage file - workflow + run: | + mv ./packages/${{ env.PACKAGE_NAME }}/coverage.xml coverage_${{ matrix.OS }}_${{ matrix.python-version }}_${{ env.PACKAGE_NAME }}.xml + working-directory: ./python + - name: Upload coverage artifact - workflow + uses: actions/upload-artifact@v4 + with: + name: coverage-${{ matrix.OS }}-${{ matrix.python-version }}-${{ env.PACKAGE_NAME }} + path: ./python/coverage_${{ matrix.OS }}_${{ matrix.python-version }}_${{ env.PACKAGE_NAME }}.xml + + # Surface failing tests - name: Surface failing tests if: always() uses: pmeier/pytest-results-action@v0.7.2 diff --git a/README.md b/README.md index 26eea1db11..3f80b85e41 100644 --- a/README.md +++ b/README.md @@ -4,15 +4,25 @@ You're getting early access to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration. -**A few important notes:** -- There currently are not public pypi or nuget packages for the SDKs. In order for the code and samples to work, please clone this repo and run the code here. -- The repo is an active project so make sure to sync regularly. +### 📋 Important Setup Information +**Package Availability:** Public PyPI and NuGet packages are not yet available. You have two options: -**We want your feedback!** +**Option 1: Run samples directly from this repository (no package installation needed)** +- Clone this repository +- For .NET: Run samples with `dotnet run` from any sample directory (e.g., `dotnet/samples/GettingStarted/Agents/Agent_Step01_Running`) +- For Python: Run samples from any sample directory (e.g., [`python/samples/getting_started/minimal_sample.py`](python/samples/getting_started/minimal_sample.py)) after setting up the local dev environment following this [guide](python/DEV_SETUP.md). + +**Option 2: Install packages in your own project** +- **[.NET Getting Started Guide](./user-documentation-dotnet/getting-started/README.md)** - Instructions for using nightly packages +- **[Python Package Installation Guide](./user-documentation-python/getting-started/package_installation.md)** - Install packages directly from GitHub + +**Stay Updated:** This is an active project - sync your local repository regularly to get the latest updates. + +### 💬 **We want your feedback!** - For bugs, please file a [GitHub issue](https://github.com/microsoft/agent-framework/issues). - For feedback and suggestions for the team, please fill out [this survey](https://forms.office.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR9huAe5pW55CqgnnimXONJJUMlVMUzdCN1ZGOURXODlBSVJOSkxERVNCNS4u). -**Highlights** +### ✨ **Highlights** - Flexible Agent Framework: build, orchestrate, and deploy AI agents and workflows - Multi-Agent Orchestration: group chat, sequential, concurrent, and handoff patterns - Graph-based Workflows: connect agents and deterministic functions using data flows with streaming, checkpointing, time-travel, and Human-in-the-loop. @@ -32,7 +42,7 @@ Below are the basics for each language implementation. For more details on pytho - [Azure Integration](./python/packages/azure): Azure OpenAI and AI Foundry integration - [Getting Started with Workflows](./python/samples/getting_started/workflow): basic workflow creation and integration with agents -### .Net +### .NET - [Getting Started with Agents](./dotnet/samples/GettingStarted/Agents): basic agent creation and tool usage - [Agent Provider Samples](./dotnet/samples/GettingStarted/AgentProviders): samples showing different agent providers - [Orchestration Samples](./dotnet/samples/GettingStarted/Orchestration): advanced multi-agent patterns diff --git a/dotnet/Directory.Packages.props b/dotnet/Directory.Packages.props index 85769f892d..f0e6d3fe0d 100644 --- a/dotnet/Directory.Packages.props +++ b/dotnet/Directory.Packages.props @@ -11,35 +11,36 @@ - - - - - - - - - - - - - - + + + + + + + + + + + + + + - + - + - - - - + + + + + @@ -47,38 +48,41 @@ - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + - - - - - + + + + + + + + diff --git a/dotnet/agent-framework-dotnet.slnx b/dotnet/agent-framework-dotnet.slnx index 8d550c3031..f7a78e5535 100644 --- a/dotnet/agent-framework-dotnet.slnx +++ b/dotnet/agent-framework-dotnet.slnx @@ -7,6 +7,11 @@ + + + + + @@ -25,6 +30,8 @@ + + @@ -41,36 +48,34 @@ + + + + + + - - + + - - + + - - - - + + + + - - - - + + - - - - - - - + @@ -78,6 +83,30 @@ + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dotnet/samples/A2AClientServer/A2AClient/A2AClient.csproj b/dotnet/samples/A2AClientServer/A2AClient/A2AClient.csproj new file mode 100644 index 0000000000..b7699244d4 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AClient/A2AClient.csproj @@ -0,0 +1,26 @@ + + + + Exe + net9.0 + enable + enable + 5ee045b0-aea3-4f08-8d31-32d1a6f8fed0 + $(NoWarn);CS1591;VSTHRD111;CA2007;SKEXP0110 + + + + + + + + + + + + + + + + + diff --git a/dotnet/samples/A2AClientServer/A2AClient/HostClientAgent.cs b/dotnet/samples/A2AClientServer/A2AClient/HostClientAgent.cs new file mode 100644 index 0000000000..db95f49af4 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AClient/HostClientAgent.cs @@ -0,0 +1,64 @@ +// Copyright (c) Microsoft. All rights reserved. +using System.ClientModel; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; +using Microsoft.Extensions.AI.Agents.A2A; +using Microsoft.Extensions.Logging; +using OpenAI; + +namespace A2A; + +internal sealed class HostClientAgent +{ + internal HostClientAgent(ILoggerFactory loggerFactory) + { + this._loggerFactory = loggerFactory; + this._logger = loggerFactory.CreateLogger("HostClientAgent"); + } + + internal async Task InitializeAgentAsync(string modelId, string apiKey, string[] agentUrls) + { + try + { + this._logger.LogInformation("Initializing Agent Framework agent with model: {ModelId}", modelId); + + // Connect to the remote agents via A2A + var createAgentTasks = agentUrls.Select(agentUrl => this.CreateAgentAsync(agentUrl)); + var agents = await Task.WhenAll(createAgentTasks); + var tools = agents.Select(agent => (AITool)AgentAIFunctionFactory.CreateFromAgent(agent)).ToList(); + + // Create the agent that uses the remote agents as tools + this.Agent = new OpenAIClient(new ApiKeyCredential(apiKey)) + .GetChatClient(modelId) + .CreateAIAgent(instructions: "You specialize in handling queries for users and using your tools to provide answers.", name: "HostClient", tools: tools); + } + catch (Exception ex) + { + this._logger.LogError(ex, "Failed to initialize HostClientAgent"); + throw; + } + } + + /// + /// The associated + /// + public AIAgent? Agent { get; private set; } + + #region private + private readonly ILoggerFactory _loggerFactory; + private readonly ILogger _logger; + + private async Task CreateAgentAsync(string agentUri) + { + var url = new Uri(agentUri); + var httpClient = new HttpClient + { + Timeout = TimeSpan.FromSeconds(60) + }; + + var agentCardResolver = new A2ACardResolver(url, httpClient); + + return await agentCardResolver.GetAIAgentAsync(); + } + #endregion +} diff --git a/dotnet/samples/A2AClientServer/A2AClient/Program.cs b/dotnet/samples/A2AClientServer/A2AClient/Program.cs new file mode 100644 index 0000000000..2715fdaf70 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AClient/Program.cs @@ -0,0 +1,80 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.CommandLine; +using System.CommandLine.Invocation; +using System.Reflection; +using Microsoft.Extensions.AI.Agents; +using Microsoft.Extensions.Configuration; +using Microsoft.Extensions.Logging; + +namespace A2A; + +public static class Program +{ + public static async Task Main(string[] args) + { + // Create root command with options + var rootCommand = new RootCommand("A2AClient"); + rootCommand.SetHandler(HandleCommandsAsync); + + // Run the command + return await rootCommand.InvokeAsync(args); + } + + public static async Task HandleCommandsAsync(InvocationContext context) + { + // Set up the logging + using var loggerFactory = LoggerFactory.Create(builder => + { + builder.AddConsole(); + builder.SetMinimumLevel(LogLevel.Information); + }); + var logger = loggerFactory.CreateLogger("A2AClient"); + + // Retrieve configuration settings + IConfigurationRoot configRoot = new ConfigurationBuilder() + .AddEnvironmentVariables() + .AddUserSecrets(Assembly.GetExecutingAssembly()) + .Build(); + var apiKey = configRoot["A2AClient:ApiKey"] ?? throw new ArgumentException("A2AClient:ApiKey must be provided"); + var modelId = configRoot["A2AClient:ModelId"] ?? "gpt-4.1"; + var agentUrls = configRoot["A2AClient:AgentUrls"] ?? "http://localhost:5000/;http://localhost:5001/;http://localhost:5002/"; + + // Create the Host agent + var hostAgent = new HostClientAgent(loggerFactory); + await hostAgent.InitializeAgentAsync(modelId, apiKey, agentUrls!.Split(";")); + AgentThread thread = hostAgent.Agent!.GetNewThread(); + try + { + while (true) + { + // Get user message + Console.Write("\nUser (:q or quit to exit): "); + string? message = Console.ReadLine(); + if (string.IsNullOrWhiteSpace(message)) + { + Console.WriteLine("Request cannot be empty."); + continue; + } + + if (message == ":q" || message == "quit") + { + break; + } + + var agentResponse = await hostAgent.Agent!.RunAsync(message, thread); + foreach (var chatMessage in agentResponse.Messages) + { + Console.ForegroundColor = ConsoleColor.Cyan; + Console.WriteLine($"\nAgent: {chatMessage.Text}"); + Console.ResetColor(); + } + } + } + catch (Exception ex) + { + logger.LogError(ex, "An error occurred while running the A2AClient"); + return; + } + } +} diff --git a/dotnet/samples/A2AClientServer/A2AClient/README.md b/dotnet/samples/A2AClientServer/A2AClient/README.md new file mode 100644 index 0000000000..324aa9aeee --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AClient/README.md @@ -0,0 +1,26 @@ + +# A2A Client Sample +Show how to create an A2A Client with a command line interface which invokes agents using the A2A protocol. + +## Run the Sample + +To run the sample, follow these steps: + +1. Run the A2A client: + ```bash + cd A2AClient + dotnet run + ``` +2. Enter your request e.g. "Show me all invoices for Contoso?" + +## Set Environment Variables + +The agent urls are provided as a ` ` delimited list of strings + +```powershell +cd dotnet/samples/A2AClientServer/A2AClient + +$env:OPENAI_MODEL_ID="gpt-4o-mini" +$env:OPENAI_API_KEY="" +$env:AGENT_URLS="http://localhost:5000/policy;http://localhost:5000/invoice;http://localhost:5000/logistics" +``` diff --git a/dotnet/samples/A2AClientServer/A2AServer/A2AServer.csproj b/dotnet/samples/A2AClientServer/A2AServer/A2AServer.csproj new file mode 100644 index 0000000000..54b038d6b6 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AServer/A2AServer.csproj @@ -0,0 +1,26 @@ + + + + Exe + net9.0 + enable + enable + 5ee045b0-aea3-4f08-8d31-32d1a6f8fed0 + $(NoWarn);CS1591;VSTHRD111;CA2007;SKEXP0110 + + + + + + + + + + + + + + + + + diff --git a/dotnet/samples/A2AClientServer/A2AServer/A2AServer.http b/dotnet/samples/A2AClientServer/A2AServer/A2AServer.http new file mode 100644 index 0000000000..7e543ae005 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AServer/A2AServer.http @@ -0,0 +1,82 @@ +### Each A2A agent is available at a different host address +@hostInvoice = http://localhost:5000 +@hostPolicy = http://localhost:5001 +@hostLogistics = http://localhost:5002 + +### Query agent card for the invoice agent +GET {{hostInvoice}}/.well-known/agent.json + +### Send a message to the invoice agent +POST {{hostInvoice}} +Content-Type: application/json + +{ + "id": "1", + "jsonrpc": "2.0", + "method": "message/send", + "params": { + "id": "12345", + "message": { + "role": "user", + "messageId": "msg_1", + "parts": [ + { + "kind": "text", + "text": "Show me all invoices for Contoso?" + } + ] + } + } +} + +### Query agent card for the policy agent +GET {{hostPolicy}}/.well-known/agent.json + +### Send a message to the policy agent +POST {{hostPolicy}} +Content-Type: application/json + +{ + "id": "1", + "jsonrpc": "2.0", + "method": "message/send", + "params": { + "id": "12345", + "message": { + "role": "user", + "messageId": "msg_1", + "parts": [ + { + "kind": "text", + "text": "What is the policy for short shipments?" + } + ] + } + } +} + +### Query agent card for the logistics agent +GET {{hostLogistics}}/.well-known/agent.json + +### Send a message to the logistics agent +POST {{hostLogistics}} +Content-Type: application/json + +{ + "id": "1", + "jsonrpc": "2.0", + "method": "message/send", + "params": { + "id": "12345", + "message": { + "role": "user", + "messageId": "msg_1", + "parts": [ + { + "kind": "text", + "text": "What is the status for SHPMT-SAP-001?" + } + ] + } + } +} \ No newline at end of file diff --git a/dotnet/samples/A2AClientServer/A2AServer/HostAgentFactory.cs b/dotnet/samples/A2AClientServer/A2AServer/HostAgentFactory.cs new file mode 100644 index 0000000000..4c912133e1 --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AServer/HostAgentFactory.cs @@ -0,0 +1,148 @@ +// Copyright (c) Microsoft. All rights reserved. + +using A2A; +using Azure.AI.Agents.Persistent; +using Azure.Identity; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; +using Microsoft.Extensions.AI.Agents.A2A; +using OpenAI; + +namespace A2AServer; + +internal static class HostAgentFactory +{ + internal static async Task CreateFoundryHostAgentAsync(string agentType, string modelId, string endpoint, string assistantId, IList? tools = null) + { + var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential()); + PersistentAgent persistentAgent = await persistentAgentsClient.Administration.GetAgentAsync(assistantId); + + AIAgent agent = await persistentAgentsClient + .GetAIAgentAsync(persistentAgent.Id, chatOptions: new() { Tools = tools }); + + AgentCard agentCard = agentType.ToUpperInvariant() switch + { + "INVOICE" => GetInvoiceAgentCard(), + "POLICY" => GetPolicyAgentCard(), + "LOGISTICS" => GetLogisticsAgentCard(), + _ => throw new ArgumentException($"Unsupported agent type: {agentType}"), + }; + + return new A2AHostAgent(agent, agentCard); + } + + internal static async Task CreateChatCompletionHostAgentAsync(string agentType, string modelId, string apiKey, string name, string instructions, IList? tools = null) + { + AIAgent agent = new OpenAIClient(apiKey) + .GetChatClient(modelId) + .CreateAIAgent(instructions, name, tools: tools); + + AgentCard agentCard = agentType.ToUpperInvariant() switch + { + "INVOICE" => GetInvoiceAgentCard(), + "POLICY" => GetPolicyAgentCard(), + "LOGISTICS" => GetLogisticsAgentCard(), + _ => throw new ArgumentException($"Unsupported agent type: {agentType}"), + }; + + return new A2AHostAgent(agent, agentCard); + } + + #region private + private static AgentCard GetInvoiceAgentCard() + { + var capabilities = new AgentCapabilities() + { + Streaming = false, + PushNotifications = false, + }; + + var invoiceQuery = new AgentSkill() + { + Id = "id_invoice_agent", + Name = "InvoiceQuery", + Description = "Handles requests relating to invoices.", + Tags = ["invoice", "semantic-kernel"], + Examples = + [ + "List the latest invoices for Contoso.", + ], + }; + + return new() + { + Name = "InvoiceAgent", + Description = "Handles requests relating to invoices.", + Version = "1.0.0", + DefaultInputModes = ["text"], + DefaultOutputModes = ["text"], + Capabilities = capabilities, + Skills = [invoiceQuery], + }; + } + + private static AgentCard GetPolicyAgentCard() + { + var capabilities = new AgentCapabilities() + { + Streaming = false, + PushNotifications = false, + }; + + var invoiceQuery = new AgentSkill() + { + Id = "id_policy_agent", + Name = "PolicyAgent", + Description = "Handles requests relating to policies and customer communications.", + Tags = ["policy", "semantic-kernel"], + Examples = + [ + "What is the policy for short shipments?", + ], + }; + + return new AgentCard() + { + Name = "PolicyAgent", + Description = "Handles requests relating to policies and customer communications.", + Version = "1.0.0", + DefaultInputModes = ["text"], + DefaultOutputModes = ["text"], + Capabilities = capabilities, + Skills = [invoiceQuery], + }; + } + + private static AgentCard GetLogisticsAgentCard() + { + var capabilities = new AgentCapabilities() + { + Streaming = false, + PushNotifications = false, + }; + + var logisticsQuery = new AgentSkill() + { + Id = "id_logistics_agent", + Name = "LogisticsQuery", + Description = "Handles requests relating to logistics.", + Tags = ["logistics", "semantic-kernel"], + Examples = + [ + "What is the status for SHPMT-SAP-001", + ], + }; + + return new AgentCard() + { + Name = "LogisticsAgent", + Description = "Handles requests relating to logistics.", + Version = "1.0.0", + DefaultInputModes = ["text"], + DefaultOutputModes = ["text"], + Capabilities = capabilities, + Skills = [logisticsQuery], + }; + } + #endregion +} diff --git a/dotnet/samples/A2AClientServer/A2AServer/Models/InvoiceQuery.cs b/dotnet/samples/A2AClientServer/A2AServer/Models/InvoiceQuery.cs new file mode 100644 index 0000000000..499e54aa6e --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AServer/Models/InvoiceQuery.cs @@ -0,0 +1,176 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.ComponentModel; + +namespace A2A; + +/// +/// A simple invoice plugin that returns mock data. +/// +public class Product +{ + public string Name { get; set; } + public int Quantity { get; set; } + public decimal Price { get; set; } // Price per unit + + public Product(string name, int quantity, decimal price) + { + this.Name = name; + this.Quantity = quantity; + this.Price = price; + } + + public decimal TotalPrice() + { + return this.Quantity * this.Price; // Total price for this product + } +} + +public class Invoice +{ + public string TransactionId { get; set; } + public string InvoiceId { get; set; } + public string CompanyName { get; set; } + public DateTime InvoiceDate { get; set; } + public List Products { get; set; } // List of products + + public Invoice(string transactionId, string invoiceId, string companyName, DateTime invoiceDate, List products) + { + this.TransactionId = transactionId; + this.InvoiceId = invoiceId; + this.CompanyName = companyName; + this.InvoiceDate = invoiceDate; + this.Products = products; + } + + public decimal TotalInvoicePrice() + { + return this.Products.Sum(product => product.TotalPrice()); // Total price of all products in the invoice + } +} + +public class InvoiceQuery +{ + private readonly List _invoices; + private static readonly Random s_random = new(); + + public InvoiceQuery() + { + // Extended mock data with quantities and prices + this._invoices = + [ + new("TICKET-XYZ987", "INV789", "Contoso", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 150, 10.00m), + new("Hats", 200, 15.00m), + new("Glasses", 300, 5.00m) + }), + new("TICKET-XYZ111", "INV111", "XStore", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 2500, 12.00m), + new("Hats", 1500, 8.00m), + new("Glasses", 200, 20.00m) + }), + new("TICKET-XYZ222", "INV222", "Cymbal Direct", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 1200, 14.00m), + new("Hats", 800, 7.00m), + new("Glasses", 500, 25.00m) + }), + new("TICKET-XYZ333", "INV333", "Contoso", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 400, 11.00m), + new("Hats", 600, 15.00m), + new("Glasses", 700, 5.00m) + }), + new("TICKET-XYZ444", "INV444", "XStore", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 800, 10.00m), + new("Hats", 500, 18.00m), + new("Glasses", 300, 22.00m) + }), + new("TICKET-XYZ555", "INV555", "Cymbal Direct", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 1100, 9.00m), + new("Hats", 900, 12.00m), + new("Glasses", 1200, 15.00m) + }), + new("TICKET-XYZ666", "INV666", "Contoso", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 2500, 8.00m), + new("Hats", 1200, 10.00m), + new("Glasses", 1000, 6.00m) + }), + new("TICKET-XYZ777", "INV777", "XStore", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 1900, 13.00m), + new("Hats", 1300, 16.00m), + new("Glasses", 800, 19.00m) + }), + new("TICKET-XYZ888", "INV888", "Cymbal Direct", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 2200, 11.00m), + new("Hats", 1700, 8.50m), + new("Glasses", 600, 21.00m) + }), + new("TICKET-XYZ999", "INV999", "Contoso", GetRandomDateWithinLastTwoMonths(), new List + { + new("T-Shirts", 1400, 10.50m), + new("Hats", 1100, 9.00m), + new("Glasses", 950, 12.00m) + }) + ]; + } + + public static DateTime GetRandomDateWithinLastTwoMonths() + { + // Get the current date and time + DateTime endDate = DateTime.Now; + + // Calculate the start date, which is two months before the current date + DateTime startDate = endDate.AddMonths(-2); + + // Generate a random number of days between 0 and the total number of days in the range + int totalDays = (endDate - startDate).Days; +#pragma warning disable CA5394 // Do not use insecure randomness + int randomDays = s_random.Next(0, totalDays + 1); // +1 to include the end date +#pragma warning restore CA5394 // Do not use insecure randomness + + // Return the random date + return startDate.AddDays(randomDays); + } + + [Description("Retrieves invoices for the specified company and optionally within the specified time range")] + public IEnumerable QueryInvoices(string companyName, DateTime? startDate = null, DateTime? endDate = null) + { + var query = this._invoices.Where(i => i.CompanyName.Equals(companyName, StringComparison.OrdinalIgnoreCase)); + + if (startDate.HasValue) + { + query = query.Where(i => i.InvoiceDate >= startDate.Value); + } + + if (endDate.HasValue) + { + query = query.Where(i => i.InvoiceDate <= endDate.Value); + } + + return query.ToList(); + } + + [Description("Retrieves invoice using the transaction id")] + public IEnumerable QueryByTransactionId(string transactionId) + { + var query = this._invoices.Where(i => i.TransactionId.Equals(transactionId, StringComparison.OrdinalIgnoreCase)); + + return query.ToList(); + } + + [Description("Retrieves invoice using the invoice id")] + public IEnumerable QueryByInvoiceId(string invoiceId) + { + var query = this._invoices.Where(i => i.InvoiceId.Equals(invoiceId, StringComparison.OrdinalIgnoreCase)); + + return query.ToList(); + } +} diff --git a/dotnet/samples/A2AClientServer/A2AServer/Program.cs b/dotnet/samples/A2AClientServer/A2AServer/Program.cs new file mode 100644 index 0000000000..5c34361ced --- /dev/null +++ b/dotnet/samples/A2AClientServer/A2AServer/Program.cs @@ -0,0 +1,107 @@ +// Copyright (c) Microsoft. All rights reserved. +using A2A; +using A2A.AspNetCore; +using A2AServer; +using Microsoft.AspNetCore.Builder; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents.A2A; +using Microsoft.Extensions.Configuration; +using Microsoft.Extensions.DependencyInjection; + +string agentId = string.Empty; +string agentType = string.Empty; + +for (var i = 0; i < args.Length; i++) +{ + if (args[i].StartsWith("--agentId", StringComparison.InvariantCultureIgnoreCase) && i + 1 < args.Length) + { + agentId = args[++i]; + } + else if (args[i].StartsWith("--agentType", StringComparison.InvariantCultureIgnoreCase) && i + 1 < args.Length) + { + agentType = args[++i]; + } +} + +var builder = WebApplication.CreateBuilder(args); +builder.Services.AddHttpClient().AddLogging(); +var app = builder.Build(); + +var httpClient = app.Services.GetRequiredService().CreateClient(); +var logger = app.Logger; + +IConfigurationRoot configuration = new ConfigurationBuilder() + .AddEnvironmentVariables() + .AddUserSecrets() + .Build(); + +string? apiKey = configuration["OPENAI_API_KEY"]; +string modelId = configuration["OPENAI_MODEL_ID"] ?? "gpt-4o-mini"; +string? endpoint = configuration["FOUNDRY_PROJECT_ENDPOINT"]; + +var invoiceQueryPlugin = new InvoiceQuery(); +IList tools = + [ + AIFunctionFactory.Create(invoiceQueryPlugin.QueryInvoices), + AIFunctionFactory.Create(invoiceQueryPlugin.QueryByTransactionId), + AIFunctionFactory.Create(invoiceQueryPlugin.QueryByInvoiceId) + ]; + +A2AHostAgent? hostAgent = null; +if (!string.IsNullOrEmpty(endpoint) && !string.IsNullOrEmpty(agentId)) +{ + hostAgent = agentType.ToUpperInvariant() switch + { + "INVOICE" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, modelId, endpoint, agentId, tools), + "POLICY" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, modelId, endpoint, agentId), + "LOGISTICS" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, modelId, endpoint, agentId), + _ => throw new ArgumentException($"Unsupported agent type: {agentType}"), + }; +} +else if (!string.IsNullOrEmpty(apiKey)) +{ + hostAgent = agentType.ToUpperInvariant() switch + { + "INVOICE" => await HostAgentFactory.CreateChatCompletionHostAgentAsync( + agentType, modelId, apiKey, "InvoiceAgent", + """ + You specialize in handling queries related to invoices. + """, tools), + "POLICY" => await HostAgentFactory.CreateChatCompletionHostAgentAsync( + agentType, modelId, apiKey, "PolicyAgent", + """ + You specialize in handling queries related to policies and customer communications. + + Always reply with exactly this text: + + Policy: Short Shipment Dispute Handling Policy V2.1 + + Summary: "For short shipments reported by customers, first verify internal shipment records + (SAP) and physical logistics scan data (BigQuery). If discrepancy is confirmed and logistics data + shows fewer items packed than invoiced, issue a credit for the missing items. Document the + resolution in SAP CRM and notify the customer via email within 2 business days, referencing the + original invoice and the credit memo number. Use the 'Formal Credit Notification' email + template." + """), + "LOGISTICS" => await HostAgentFactory.CreateChatCompletionHostAgentAsync( + agentType, modelId, apiKey, "LogisticsAgent", + """ + You specialize in handling queries related to logistics. + + Always reply with exactly: + + Shipment number: SHPMT-SAP-001 + Item: TSHIRT-RED-L + Quantity: 900 + """), + _ => throw new ArgumentException($"Unsupported agent type: {agentType}"), + }; +} +else +{ + throw new ArgumentException("Either A2AServer:ApiKey or A2AServer:ConnectionString & agentId must be provided"); +} + +app.MapA2A(hostAgent!.TaskManager!, "/"); + +await app.RunAsync(); diff --git a/dotnet/samples/A2AClientServer/README.md b/dotnet/samples/A2AClientServer/README.md new file mode 100644 index 0000000000..0311c0a2b7 --- /dev/null +++ b/dotnet/samples/A2AClientServer/README.md @@ -0,0 +1,234 @@ +# A2A Client and Server samples + +> **Warning** +> The [A2A protocol](https://google.github.io/A2A/) is still under development and changing fast. +> We will try to keep these samples updated as the protocol evolves. + +These samples are built with [official A2A C# SDK](https://www.nuget.org/packages/A2A) and demonstrates: + +1. Creating an A2A Server which makes an agent available via the A2A protocol. +2. Creating an A2A Client with a command line interface which invokes agents using the A2A protocol. + +The demonstration has two components: + +1. `A2AServer` - You will run three instances of the server to correspond to three A2A servers each providing a single Agent i.e., the Invoice, Policy and Logistics agents. +2. `A2AClient` - This represents a client application which will connect to the remote A2A servers using the A2A protocol so that it can use those agents when answering questions you will ask. + +Demo Architecture + +## Configuring Environment Variables + +The samples can be configured to use chat completion agents or Azure AI agents. + +### Configuring for use with Chat Completion Agents + +Provide your OpenAI API key via an environment variable + +```powershell +$env:OPENAI_API_KEY="" +``` + +Use the following commands to run each A2A server: + +Execute the following command to build the sample: + +```powershell +cd A2AServer +dotnet build +``` + +```bash +dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentType "invoice" --no-build +``` + +```bash +dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentType "policy" --no-build +``` + +```bash +dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentType "logistics" --no-build +``` + +### Configuring for use with Azure AI Agents + +You must create the agents in an Azure AI Foundry project and then provide the project endpoint and agents ids. The instructions for each agent are as follows: + +- Invoice Agent + ``` + You specialize in handling queries related to invoices. + ``` +- Policy Agent + ``` + You specialize in handling queries related to policies and customer communications. + + Always reply with exactly this text: + + Policy: Short Shipment Dispute Handling Policy V2.1 + + Summary: "For short shipments reported by customers, first verify internal shipment records + (SAP) and physical logistics scan data (BigQuery). If discrepancy is confirmed and logistics data + shows fewer items packed than invoiced, issue a credit for the missing items. Document the + resolution in SAP CRM and notify the customer via email within 2 business days, referencing the + original invoice and the credit memo number. Use the 'Formal Credit Notification' email + template." + ``` +- Logistics Agent + ``` + You specialize in handling queries related to logistics. + + Always reply with exactly: + + Shipment number: SHPMT-SAP-001 + Item: TSHIRT-RED-L + Quantity: 900" + ``` + +```powershell +$env:FOUNDRY_PROJECT_ENDPOINT="https://ai-foundry-your-project.services.ai.azure.com/api/projects/ai-proj-ga-your-project" # Replace with your Foundry Project endpoint +``` + +Use the following commands to run each A2A server + +```bash +dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentId "" --agentType "invoice" --no-build +``` + +```bash +dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentId "" --agentType "policy" --no-build +``` + +```bash +dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentId "" --agentType "logistics" --no-build +``` + +### Testing the Agents using the Rest Client + +This sample contains a [.http file](https://learn.microsoft.com/aspnet/core/test/http-files?view=aspnetcore-9.0) which can be used to test the agent. + +1. In Visual Studio open [./A2AServer/A2AServer.http](./A2AServer/A2AServer.http) +1. There are two sent requests for each agent, e.g., for the invoice agent: + 1. Query agent card for the invoice agent + `GET {{hostInvoice}}/.well-known/agent.json` + 1. Send a message to the invoice agent + ``` + POST {{hostInvoice}} + Content-Type: application/json + + { + "id": "1", + "jsonrpc": "2.0", + "method": "message/send", + "params": { + "id": "12345", + "message": { + "role": "user", + "messageId": "msg_1", + "parts": [ + { + "kind": "text", + "text": "Show me all invoices for Contoso?" + } + ] + } + } + } + ``` + +Sample output from the request to display the agent card: + +Agent Card + +Sample output from the request to send a message to the agent via A2A protocol: + +Send Message + +### Testing the Agents using the A2A Inspector + +The A2A Inspector is a web-based tool designed to help developers inspect, debug, and validate servers that implement the Google A2A (Agent-to-Agent) protocol. It provides a user-friendly interface to interact with an A2A agent, view communication, and ensure specification compliance. + +For more information go [here](https://github.com/a2aproject/a2a-inspector). + +Running the [inspector with Docker](https://github.com/a2aproject/a2a-inspector?tab=readme-ov-file#option-two-run-with-docker) is the easiest way to get started. + +1. Navigate to the A2A Inspector in your browser: [http://127.0.0.1:8080/](http://127.0.0.1:8080/) +1. Enter the URL of the Agent you are running e.g., [http://host.docker.internal:5000](http://host.docker.internal:5000) +1. Connect to the agent and the agent card will be displayed and validated. +1. Type a message and send it to the agent using A2A protocol. + 1. The response will be validated automatically and then displayed in the UI. + 1. You can select the response to view the raw json. + +Agent card after connecting to an agent using the A2A protocol: + +Agent Card + +Sample response after sending a message to the agent via A2A protocol: + +Send Message + +Raw JSON response from an A2A agent: + +Response Raw JSON + +### Configuring Agents for the A2A Client + +The A2A client will connect to remote agents using the A2A protocol. + +By default the client will connect to the invoice, policy and logistics agents provided by the sample A2A Server. + +These are available at the following URL's: + +- Invoice Agent: http://localhost:5000/ +- Policy Agent: http://localhost:5001/ +- Logistics Agent: http://localhost:5002/ + +If you want to change which agents are using then set the agents url as a space delimited string as follows: + +```powershell +$env:A2A_AGENT_URLS="http://localhost:5000/;http://localhost:5001/;http://localhost:5002/" +``` + +## Run the Sample + +To run the sample, follow these steps: + +1. Run the A2A server's using the commands shown earlier +2. Run the A2A client: + ```bash + cd A2AClient + dotnet run + ``` +3. Enter your request e.g. "Customer is disputing transaction TICKET-XYZ987 as they claim the received fewer t-shirts than ordered." +4. The host client agent will call the remote agents, these calls will be displayed as console output. The final answer will use information from the remote agents. The sample below includes all three agents but in your case you may only see the policy and invoice agent. + +Sample output from the A2A client: + +``` +A2AClient> dotnet run +info: HostClientAgent[0] + Initializing Agent Framework agent with model: gpt-4o-mini + +User (:q or quit to exit): Customer is disputing transaction TICKET-XYZ987 as they claim the received fewer t-shirts than ordered. + +Agent: + +Agent: + +Agent: The transaction details for **TICKET-XYZ987** are as follows: + +- **Invoice ID:** INV789 +- **Company Name:** Contoso +- **Invoice Date:** September 4, 2025 +- **Products:** + - **T-Shirts:** 150 units at $10.00 each + - **Hats:** 200 units at $15.00 each + - **Glasses:** 300 units at $5.00 each + +To proceed with the dispute regarding the quantity of t-shirts delivered, please specify the exact quantity issue – how many t-shirts were actually received compared to the ordered amount. + +### Customer Service Policy for Handling Disputes +**Short Shipment Dispute Handling Policy V2.1** +- **Summary:** For short shipments reported by customers, first verify internal shipment records and physical logistics scan data. If a discrepancy is confirmed and the logistics data shows fewer items were packed than invoiced, a credit for the missing items will be issued. +- **Follow-up Actions:** Document the resolution in the SAP CRM and notify the customer via email within 2 business days, referencing the original invoice and the credit memo number, using the 'Formal Credit Notification' email template. + +Please provide me with the information regarding the specific quantity issue so I can assist you further. +``` diff --git a/dotnet/samples/A2AClientServer/a2a-inspector-agent-card.png b/dotnet/samples/A2AClientServer/a2a-inspector-agent-card.png new file mode 100644 index 0000000000..8385a2b68a Binary files /dev/null and b/dotnet/samples/A2AClientServer/a2a-inspector-agent-card.png differ diff --git a/dotnet/samples/A2AClientServer/a2a-inspector-raw-json-response.png b/dotnet/samples/A2AClientServer/a2a-inspector-raw-json-response.png new file mode 100644 index 0000000000..038ef344ed Binary files /dev/null and b/dotnet/samples/A2AClientServer/a2a-inspector-raw-json-response.png differ diff --git a/dotnet/samples/A2AClientServer/a2a-inspector-send-message.png b/dotnet/samples/A2AClientServer/a2a-inspector-send-message.png new file mode 100644 index 0000000000..49fa857955 Binary files /dev/null and b/dotnet/samples/A2AClientServer/a2a-inspector-send-message.png differ diff --git a/dotnet/samples/A2AClientServer/demo-architecture.png b/dotnet/samples/A2AClientServer/demo-architecture.png new file mode 100644 index 0000000000..6ae351907a Binary files /dev/null and b/dotnet/samples/A2AClientServer/demo-architecture.png differ diff --git a/dotnet/samples/A2AClientServer/rest-client-agent-card.png b/dotnet/samples/A2AClientServer/rest-client-agent-card.png new file mode 100644 index 0000000000..44651487a8 Binary files /dev/null and b/dotnet/samples/A2AClientServer/rest-client-agent-card.png differ diff --git a/dotnet/samples/A2AClientServer/rest-client-send-message.png b/dotnet/samples/A2AClientServer/rest-client-send-message.png new file mode 100644 index 0000000000..fe65f5c92d Binary files /dev/null and b/dotnet/samples/A2AClientServer/rest-client-send-message.png differ diff --git a/dotnet/samples/Directory.Build.props b/dotnet/samples/Directory.Build.props index 564527ad9d..065ab34672 100644 --- a/dotnet/samples/Directory.Build.props +++ b/dotnet/samples/Directory.Build.props @@ -7,7 +7,7 @@ false net472;net9.0 5ee045b0-aea3-4f08-8d31-32d1a6f8fed0 - $(NoWarn);CA1707 + $(NoWarn);CA1707;MEAI001 diff --git a/dotnet/samples/GettingStarted/AgentOrchestration/AgentSample.cs b/dotnet/samples/GettingStarted/AgentOrchestration/AgentSample.cs index 004f1bf2e0..0f86869579 100644 --- a/dotnet/samples/GettingStarted/AgentOrchestration/AgentSample.cs +++ b/dotnet/samples/GettingStarted/AgentOrchestration/AgentSample.cs @@ -8,7 +8,6 @@ using Microsoft.Extensions.AI; using Microsoft.Extensions.AI.Agents; using Microsoft.Shared.Diagnostics; using Microsoft.Shared.Samples; -using OpenAI; using OpenAI.Assistants; using OpenAI.Chat; using OpenAI.Responses; @@ -111,13 +110,13 @@ public class AgentSample(ITestOutputHelper output) : BaseSample(output) private IChatClient GetOpenAIResponsesClient() => new OpenAIResponseClient(TestConfiguration.OpenAI.ChatModelId, TestConfiguration.OpenAI.ApiKey) - .AsNewIChatClient(); + .AsIChatClient(); private IChatClient GetAzureAIAgentPersistentClient(ChatClientAgentOptions options) => new PersistentAgentsClient(TestConfiguration.AzureAI.Endpoint, new AzureCliCredential()).AsNewIChatClient(options.Id!); private IChatClient GetOpenAIAssistantChatClient(ChatClientAgentOptions options) - => new AssistantClient(TestConfiguration.OpenAI.ApiKey).AsNewIChatClient(options.Id!); + => new AssistantClient(TestConfiguration.OpenAI.ApiKey).AsIChatClient(options.Id!); #endregion diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj new file mode 100644 index 0000000000..4fa7edf3fc --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Program.cs b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Program.cs new file mode 100644 index 0000000000..df315dbfaa --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Program.cs @@ -0,0 +1,102 @@ +// Copyright (c) Microsoft. All rights reserved. + +// This sample shows all the required steps to create a fully custom agent implementation. +// In this case the agent doesn't use AI at all, and simply parrots back the user input in upper case. +// You can however, build a fully custom agent that uses AI in any way you want. + +using System; +using System.Collections.Generic; +using System.Linq; +using System.Runtime.CompilerServices; +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; +using SampleApp; + +AIAgent agent = new UpperCaseParrotAgent(); + +// Invoke the agent and output the text result. +Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.")); + +// Invoke the agent with streaming support. +await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.")) +{ + Console.WriteLine(update); +} + +namespace SampleApp +{ + // Custom agent that parrot's the user input back in upper case. + internal sealed class UpperCaseParrotAgent : AIAgent + { + public override async Task RunAsync(IReadOnlyCollection messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) + { + // Create a thread if the user didn't supply one. + thread ??= this.GetNewThread(); + + // Clone the input messages and turn them into response messages with upper case text. + List responseMessages = CloneAndToUpperCase(messages, this.DisplayName).ToList(); + + // Notify the thread of the input and output messages. + await NotifyThreadOfNewMessagesAsync(thread, messages, cancellationToken); + await NotifyThreadOfNewMessagesAsync(thread, responseMessages, cancellationToken); + + return new AgentRunResponse + { + AgentId = this.Id, + ResponseId = Guid.NewGuid().ToString(), + Messages = responseMessages + }; + } + + public override async IAsyncEnumerable RunStreamingAsync(IReadOnlyCollection messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default) + { + // Create a thread if the user didn't supply one. + thread ??= this.GetNewThread(); + + // Clone the input messages and turn them into response messages with upper case text. + List responseMessages = CloneAndToUpperCase(messages, this.DisplayName).ToList(); + + // Notify the thread of the input and output messages. + await NotifyThreadOfNewMessagesAsync(thread, messages, cancellationToken); + await NotifyThreadOfNewMessagesAsync(thread, responseMessages, cancellationToken); + + foreach (var message in responseMessages) + { + yield return new AgentRunResponseUpdate + { + AgentId = this.Id, + AuthorName = this.DisplayName, + Role = ChatRole.Assistant, + Contents = message.Contents, + ResponseId = Guid.NewGuid().ToString(), + MessageId = Guid.NewGuid().ToString() + }; + } + } + + private static IEnumerable CloneAndToUpperCase(IReadOnlyCollection messages, string agentName) => messages.Select(x => + { + // Clone the message and update its author to be the agent. + var messageClone = x.Clone(); + messageClone.Role = ChatRole.Assistant; + messageClone.MessageId = Guid.NewGuid().ToString(); + messageClone.AuthorName = agentName; + + // Clone and convert any text content to upper case. + messageClone.Contents = x.Contents.Select(c => c switch + { + TextContent tc => new TextContent(tc.Text.ToUpperInvariant()) + { + AdditionalProperties = tc.AdditionalProperties, + Annotations = tc.Annotations, + RawRepresentation = tc.RawRepresentation + }, + _ => c + }).ToList(); + + return messageClone; + }); + } +} diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/README.md b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/README.md new file mode 100644 index 0000000000..97eb3e87d3 --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/README.md @@ -0,0 +1,3 @@ +# Prerequisites + +This sample has no prerequisites. \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/Program.cs b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/Program.cs index 94994dd92d..8a2579b1ff 100644 --- a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/Program.cs +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/Program.cs @@ -1,6 +1,7 @@ // Copyright (c) Microsoft. All rights reserved. // This sample shows how to create and use a simple AI agent with ONNX as the backend. +// WARNING: ONNX doesn't support function calling, so any function tools passed to the agent will be ignored. using System; using Microsoft.Extensions.AI.Agents; diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/README.md b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/README.md index 7bfacf30e9..cb86e0d7c4 100644 --- a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/README.md +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/README.md @@ -1,10 +1,18 @@ # Prerequisites +WARNING: ONNX doesn't support function calling, so any function tools passed to the agent will be ignored. + Before you begin, ensure you have the following prerequisites: - .NET 8.0 SDK or later - An ONNX model downloaded to your machine +You can download an ONNX model from hugging face, using git clone: + +```powershell +git clone https://huggingface.co/microsoft/Phi-4-mini-instruct-onnx +``` + Set the following environment variables: ```powershell diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj new file mode 100644 index 0000000000..44603cc24c --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj @@ -0,0 +1,20 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Program.cs b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Program.cs new file mode 100644 index 0000000000..9a8b028f5f --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Program.cs @@ -0,0 +1,20 @@ +// Copyright (c) Microsoft. All rights reserved. + +// This sample shows how to create and use a simple AI agent with Ollama as the backend. + +using System; +using Microsoft.Extensions.AI.Agents; +using OllamaSharp; + +var endpoint = Environment.GetEnvironmentVariable("OLLAMA_ENDPOINT") ?? throw new InvalidOperationException("OLLAMA_ENDPOINT is not set."); +var modelName = Environment.GetEnvironmentVariable("OLLAMA_MODEL_NAME") ?? throw new InvalidOperationException("OLLAMA_MODEL_NAME is not set."); + +const string JokerName = "Joker"; +const string JokerInstructions = "You are good at telling jokes."; + +// Get a chat client for Ollama and use it to construct an AIAgent. +using OllamaApiClient chatClient = new(new Uri(endpoint), modelName); +AIAgent agent = new ChatClientAgent(chatClient, JokerInstructions, JokerName); + +// Invoke the agent and output the text result. +Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.")); diff --git a/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/README.md b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/README.md new file mode 100644 index 0000000000..be76a75de0 --- /dev/null +++ b/dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/README.md @@ -0,0 +1,34 @@ +# Prerequisites + +Before you begin, ensure you have the following prerequisites: + +- .NET 8.0 SDK or later +- Docker installed and running on your machine +- An Ollama model downloaded into Ollama + +To download and start Ollama on Docker using CPU, run the following command in your terminal. + +```powershell +docker run -d -v "c:\temp\ollama:/root/.ollama" -p 11434:11434 --name ollama ollama/ollama +``` + +To download and start Ollama on Docker using GPU, run the following command in your terminal. + +```powershell +docker run -d --gpus=all -v "c:\temp\ollama:/root/.ollama" -p 11434:11434 --name ollama ollama/ollama +``` + +After the container has started, launch a Terminal window for the docker container, e.g. if using docker desktop, choose Open in Terminal from actions. + +From this terminal download the required models, e.g. here we are downloading the phi3 model. + +```text +ollama pull gpt-oss +``` + +Set the following environment variables: + +```powershell +$env:OLLAMA_ENDPOINT="http://localhost:11434" +$env:OLLAMA_MODEL_NAME="gpt-oss" +``` diff --git a/dotnet/samples/GettingStarted/AgentProviders/README.md b/dotnet/samples/GettingStarted/AgentProviders/README.md index 981e60d9b8..0b5fbf1a74 100644 --- a/dotnet/samples/GettingStarted/AgentProviders/README.md +++ b/dotnet/samples/GettingStarted/AgentProviders/README.md @@ -9,6 +9,7 @@ see the [Getting Started Steps](../GettingStartedSteps/README.md) samples. ## Prerequisites See the README.md for each sample for the prerequisites for that sample. + ## Samples |Sample|Description| @@ -17,6 +18,8 @@ See the README.md for each sample for the prerequisites for that sample. |[Creating an AIAgent with AzureFoundry](./Agent_With_AzureFoundry/)|This sample demonstrates how to create an Azure Foundry agent and expose it as an AIAgent| |[Creating an AIAgent with Azure OpenAI ChatCompletion](./Agent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service| |[Creating an AIAgent with Azure OpenAI Responses](./Agent_With_AzureOpenAIResponses/)|This sample demonstrates how to create an AIAgent using Azure OpenAI Responses as the underlying inference service| +|[Creating an AIAgent with a custom implementation](./Agent_With_CustomImplementation/)|This sample demonstrates how to create an AIAgent with a custom implementation| +|[Creating an AIAgent with Ollama](./Agent_With_Ollama/)|This sample demonstrates how to create an AIAgent using Ollama as the underlying inference service| |[Creating an AIAgent with ONNX](./Agent_With_ONNX/)|This sample demonstrates how to create an AIAgent using ONNX as the underlying inference service| |[Creating an AIAgent with OpenAI ChatCompletion](./Agent_With_OpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using OpenAI ChatCompletion as the underlying inference service| |[Creating an AIAgent with OpenAI Responses](./Agent_With_OpenAIResponses/)|This sample demonstrates how to create an AIAgent using OpenAI Responses as the underlying inference service| diff --git a/dotnet/samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Program.cs b/dotnet/samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Program.cs index 6625bdad2c..13760a2c89 100644 --- a/dotnet/samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Program.cs +++ b/dotnet/samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Program.cs @@ -22,11 +22,11 @@ AIAgent agent = new OpenAIClient(apiKey) UserChatMessage chatMessage = new("Tell me a joke about a pirate."); // Invoke the agent and output the text result. -ChatCompletion chatCompletion = await agent.RunAsync(chatMessage); +ChatCompletion chatCompletion = await agent.RunAsync([chatMessage]); Console.WriteLine(chatCompletion.Content.Last().Text); // Invoke the agent with streaming support. -AsyncCollectionResult completionUpdates = agent.RunStreamingAsync(chatMessage); +AsyncCollectionResult completionUpdates = agent.RunStreamingAsync([chatMessage]); await foreach (StreamingChatCompletionUpdate completionUpdate in completionUpdates) { if (completionUpdate.ContentUpdate.Count > 0) diff --git a/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Agent_Step11_UsingImages.csproj b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Agent_Step11_UsingImages.csproj new file mode 100644 index 0000000000..a438862616 --- /dev/null +++ b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Agent_Step11_UsingImages.csproj @@ -0,0 +1,22 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + diff --git a/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Program.cs b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Program.cs new file mode 100644 index 0000000000..318788f352 --- /dev/null +++ b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/Program.cs @@ -0,0 +1,30 @@ +// Copyright (c) Microsoft. All rights reserved. + +// This sample shows how to use Image Multi-Modality with an AI agent. + +using System; +using Azure.AI.OpenAI; +using Azure.Identity; +using Microsoft.Extensions.AI; +using OpenAI; + +var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set."); +var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o"; + +var agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()) + .GetChatClient(deploymentName) + .CreateAIAgent( + name: "VisionAgent", + instructions: "You are a helpful agent that can analyze images"); + +ChatMessage message = new(ChatRole.User, [ + new TextContent("What do you see in this image?"), + new UriContent("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg", "image/jpeg") +]); + +var thread = agent.GetNewThread(); + +await foreach (var update in agent.RunStreamingAsync(message, thread)) +{ + Console.WriteLine(update); +} diff --git a/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/README.md b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/README.md new file mode 100644 index 0000000000..49d1bff4a2 --- /dev/null +++ b/dotnet/samples/GettingStarted/Agents/Agent_Step11_UsingImages/README.md @@ -0,0 +1,52 @@ +# Using Images with AI Agents + +This sample demonstrates how to use image multi-modality with an AI agent. It shows how to create a vision-enabled agent that can analyze and describe images using Azure OpenAI. + +## What this sample demonstrates + +- Creating a persistent AI agent with vision capabilities +- Sending both text and image content to an agent in a single message +- Using `UriContent` to Uri referenced images +- Processing multimodal input (text + image) with an AI agent + +## Key features + +- **Vision Agent**: Creates an agent specifically instructed to analyze images +- **Multimodal Input**: Combines text questions with image uri in a single message +- **Azure OpenAI Integration**: Uses AzureOpenAI LLM agents + +## Prerequisites + +Before running this sample, ensure you have: + +1. An Azure OpenAI project set up +2. A compatible model deployment (e.g., gpt-4o) +3. Azure CLI installed and authenticated + +## Environment Variables + +Set the following environment variables: + +```powershell +$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI endpoint +$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o" # Replace with your model deployment name (optional, defaults to gpt-4o) +``` + +## Run the sample + +Navigate to the sample directory and run: + +```powershell +cd Agent_Step11_UsingImages +dotnet run +``` + +## Expected behavior + +The sample will: + +1. Create a vision-enabled agent named "VisionAgent" +2. Send a message containing both text ("What do you see in this image?") and a Uri image of a green walk +3. The agent will analyze the image and provide a description +4. Clean up resources by deleting the thread and agent + diff --git a/dotnet/samples/GettingStarted/Agents/README.md b/dotnet/samples/GettingStarted/Agents/README.md index 03e9edc247..c6959aee65 100644 --- a/dotnet/samples/GettingStarted/Agents/README.md +++ b/dotnet/samples/GettingStarted/Agents/README.md @@ -36,6 +36,7 @@ Before you begin, ensure you have the following prerequisites: |[Telemetry with a simple agent](./Agent_Step08_Telemetry/)|This sample demonstrates how to add telemetry to a simple agent| |[Dependency injection with a simple agent](./Agent_Step09_DependencyInjection/)|This sample demonstrates how to add and resolve an agent with a dependency injection container| |[Exposing a simple agent as MCP tool](./Agent_Step10_AsMcpTool/)|This sample demonstrates how to expose an agent as an MCP tool| +|[Using images with a simple agent](./Agent_Step11_UsingImages/)|This sample demonstrates how to use image multi-modality with an AI agent| ## Running the samples from the console diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Agent_MCP_Server.csproj b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Agent_MCP_Server.csproj new file mode 100644 index 0000000000..759eaae572 --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Agent_MCP_Server.csproj @@ -0,0 +1,25 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + + + + diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Program.cs b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Program.cs new file mode 100644 index 0000000000..8faffd1339 --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Program.cs @@ -0,0 +1,35 @@ +// Copyright (c) Microsoft. All rights reserved. + +// This sample shows how to create and use a simple AI agent with tools from an MCP Server. + +using System; +using System.Linq; +using Azure.AI.OpenAI; +using Azure.Identity; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; +using ModelContextProtocol.Client; +using OpenAI; + +var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set."); +var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini"; + +// Create an MCPClient for the GitHub server +await using var mcpClient = await McpClientFactory.CreateAsync(new StdioClientTransport(new() +{ + Name = "MCPServer", + Command = "npx", + Arguments = ["-y", "--verbose", "@modelcontextprotocol/server-github"], +})); + +// Retrieve the list of tools available on the GitHub server +var mcpTools = await mcpClient.ListToolsAsync().ConfigureAwait(false); + +AIAgent agent = new AzureOpenAIClient( + new Uri(endpoint), + new AzureCliCredential()) + .GetChatClient(deploymentName) + .CreateAIAgent(instructions: "You answer questions related to GitHub repositories only.", tools: [.. mcpTools.Cast()]); + +// Invoke the agent and output the text result. +Console.WriteLine(await agent.RunAsync("Summarize the last four commits to the microsoft/semantic-kernel repository?")); diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/README.md b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/README.md new file mode 100644 index 0000000000..f0996dc1fd --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/README.md @@ -0,0 +1,31 @@ +# Model Context Protocol Sample + +This example demonstrates how to use tools from a Model Context Protocol server with Agent Framework. + +MCP is an open protocol that standardizes how applications provide context to LLMs. + +For information on Model Context Protocol (MCP) please refer to the [documentation](https://modelcontextprotocol.io/introduction). + +The sample shows: + +1. How to connect to an MCP Server +1. Retrieve the list of tools the MCP Server makes available +1. Convert the MCP tools to `AIFunction`'s so they can be added to an agent +1. Invoke the tools from an agent using function calling + +## Configuring Environment Variables + +Set the following environment variables: + +```powershell +$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint +$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini +``` + +## Setup and Running + +Run the ModelContextProtocolPluginAuth sample + +```bash +dotnet run +``` diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Agent_MCP_Server_Auth.csproj b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Agent_MCP_Server_Auth.csproj new file mode 100644 index 0000000000..d26676a576 --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Agent_MCP_Server_Auth.csproj @@ -0,0 +1,27 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + + + + + + diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Program.cs b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Program.cs new file mode 100644 index 0000000000..26e2ae22f1 --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Program.cs @@ -0,0 +1,148 @@ +// Copyright (c) Microsoft. All rights reserved. + +// This sample shows how to create and use a simple AI agent with tools from an MCP Server that requires authentication. + +using System; +using System.Diagnostics; +using System.Linq; +using System.Net; +using System.Net.Http; +using System.Text; +using System.Threading; +using System.Threading.Tasks; +using System.Web; +using Azure.AI.OpenAI; +using Azure.Identity; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; +using Microsoft.Extensions.Logging; +using ModelContextProtocol.Client; +using OpenAI; + +var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set."); +var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini"; + +// We can customize a shared HttpClient with a custom handler if desired +using var sharedHandler = new SocketsHttpHandler +{ + PooledConnectionLifetime = TimeSpan.FromMinutes(2), + PooledConnectionIdleTimeout = TimeSpan.FromMinutes(1) +}; +using var httpClient = new HttpClient(sharedHandler); + +var consoleLoggerFactory = LoggerFactory.Create(builder => +{ + builder.AddConsole(); +}); + +// Create SSE client transport for the MCP server +var serverUrl = "http://localhost:7071/"; +var transport = new SseClientTransport(new() +{ + Endpoint = new Uri(serverUrl), + Name = "Secure Weather Client", + OAuth = new() + { + ClientName = "ProtectedMcpClient", + RedirectUri = new Uri("http://localhost:1179/callback"), + AuthorizationRedirectDelegate = HandleAuthorizationUrlAsync, + } +}, httpClient, consoleLoggerFactory); + +// Create an MCPClient for the protected MCP server +await using var mcpClient = await McpClientFactory.CreateAsync(transport, loggerFactory: consoleLoggerFactory); + +// Retrieve the list of tools available on the GitHub server +var mcpTools = await mcpClient.ListToolsAsync().ConfigureAwait(false); + +AIAgent agent = new AzureOpenAIClient( + new Uri(endpoint), + new AzureCliCredential()) + .GetChatClient(deploymentName) + .CreateAIAgent(instructions: "You answer questions related to the weather.", tools: [.. mcpTools.Select(mcpTool => (AITool)mcpTool)]); + +// Invoke the agent and output the text result. +Console.WriteLine(await agent.RunAsync("Get current weather alerts for New York?")); + +// Handles the OAuth authorization URL by starting a local HTTP server and opening a browser. +// This implementation demonstrates how SDK consumers can provide their own authorization flow. +static async Task HandleAuthorizationUrlAsync(Uri authorizationUrl, Uri redirectUri, CancellationToken cancellationToken) +{ + Console.WriteLine("Starting OAuth authorization flow..."); + Console.WriteLine($"Opening browser to: {authorizationUrl}"); + + var listenerPrefix = redirectUri.GetLeftPart(UriPartial.Authority); + if (!listenerPrefix.EndsWith("/", StringComparison.InvariantCultureIgnoreCase)) + { + listenerPrefix += "/"; + } + + using var listener = new HttpListener(); + listener.Prefixes.Add(listenerPrefix); + + try + { + listener.Start(); + Console.WriteLine($"Listening for OAuth callback on: {listenerPrefix}"); + + OpenBrowser(authorizationUrl); + + var context = await listener.GetContextAsync(); + var query = HttpUtility.ParseQueryString(context.Request.Url?.Query ?? string.Empty); + var code = query["code"]; + var error = query["error"]; + + string responseHtml = "

Authentication complete

You can close this window now.

"; + byte[] buffer = Encoding.UTF8.GetBytes(responseHtml); + context.Response.ContentLength64 = buffer.Length; + context.Response.ContentType = "text/html"; + context.Response.OutputStream.Write(buffer, 0, buffer.Length); + context.Response.Close(); + + if (!string.IsNullOrEmpty(error)) + { + Console.WriteLine($"Auth error: {error}"); + return null; + } + + if (string.IsNullOrEmpty(code)) + { + Console.WriteLine("No authorization code received"); + return null; + } + + Console.WriteLine("Authorization code received successfully."); + return code; + } + catch (Exception ex) + { + Console.WriteLine($"Error getting auth code: {ex.Message}"); + return null; + } + finally + { + if (listener.IsListening) + { + listener.Stop(); + } + } +} + +// Opens the specified URL in the default browser. +static void OpenBrowser(Uri url) +{ + try + { + var psi = new ProcessStartInfo + { + FileName = url.ToString(), + UseShellExecute = true + }; + Process.Start(psi); + } + catch (Exception ex) + { + Console.WriteLine($"Error opening browser. {ex.Message}"); + Console.WriteLine($"Please manually open this URL: {url}"); + } +} diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/README.md b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/README.md new file mode 100644 index 0000000000..ae88df95ee --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/README.md @@ -0,0 +1,125 @@ +# Model Context Protocol Sample + +This example demonstrates how to use tools from a protected Model Context Protocol server with Agent Framework. + +MCP is an open protocol that standardizes how applications provide context to LLMs. + +For information on Model Context Protocol (MCP) please refer to the [documentation](https://modelcontextprotocol.io/introduction). + +The sample shows: + +1. How to connect to a protected MCP Server using OAuth 2.0 authentication +1. How to implement a custom OAuth authorization flow with browser-based authentication +1. Retrieve the list of tools the MCP Server makes available +1. Convert the MCP tools to `AIFunction`'s so they can be added to an agent +1. Invoke the tools from an agent using function calling + +## Installing Prerequisites + +- A self-signed certificate to enable HTTPS use in development, see [dotnet dev-certs](https://learn.microsoft.com/en-us/dotnet/core/tools/dotnet-dev-certs) +- .NET 9.0 or later +- A running TestOAuthServer (for OAuth authentication), see [Start the Test OAuth Server](https://github.com/modelcontextprotocol/csharp-sdk/tree/main/samples/ProtectedMcpClient#step-1-start-the-test-oauth-server) +- A running ProtectedMCPServer (for MCP services), see [Start the Protected MCP Server](https://github.com/modelcontextprotocol/csharp-sdk/tree/main/samples/ProtectedMcpClient#step-2-start-the-protected-mcp-server) + +## Configuring Environment Variables + +Set the following environment variables: + +```powershell +$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint +$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini +``` + +## Setup and Running + +### Step 1: Start the Test OAuth Server + +First, you need to start the TestOAuthServer which provides OAuth authentication: + +```bash +cd \tests\ModelContextProtocol.TestOAuthServer +dotnet run --framework net9.0 +``` + +The OAuth server will start at `https://localhost:7029` + +### Step 2: Start the Protected MCP Server + +Next, start the ProtectedMCPServer which provides the weather tools: + +```bash +cd \samples\ProtectedMCPServer +dotnet run +``` + +The protected server will start at `http://localhost:7071` + +### Step 3: Run the ModelContextProtocolPluginAuth sample + +Finally, run this client: + +```bash +dotnet run +``` + +## What Happens + +1. The client attempts to connect to the protected MCP server at `http://localhost:7071` +2. The server responds with OAuth metadata indicating authentication is required +3. The client initiates OAuth 2.0 authorization code flow: + - Opens a browser to the authorization URL at the OAuth server + - Starts a local HTTP listener on `http://localhost:1179/callback` to receive the authorization code + - Exchanges the authorization code for an access token +4. The client uses the access token to authenticate with the MCP server +5. The client lists available tools and calls the `GetAlerts` tool for New York state + +The following diagram outlines an example OAuth flow: + +```mermaid +sequenceDiagram + participant Client as Client + participant Server as MCP Server (Resource Server) + participant AuthServer as Authorization Server + + Client->>Server: MCP request without access token + Server-->>Client: HTTP 401 Unauthorized with WWW-Authenticate header + Note over Client: Analyze and delegate tasks + Client->>Server: GET /.well-known/oauth-protected-resource + Server-->>Client: Resource metadata with authorization server URL + Note over Client: Validate RS metadata, build AS metadata URL + Client->>AuthServer: GET /.well-known/oauth-authorization-server + AuthServer-->>Client: Authorization server metadata + Note over Client,AuthServer: OAuth 2.0 authorization flow happens here + Client->>AuthServer: Token request + AuthServer-->>Client: Access token + Client->>Server: MCP request with access token + Server-->>Client: MCP response + Note over Client,Server: MCP communication continues with valid token +``` + +## OAuth Configuration + +The client is configured with: +- **Client ID**: `demo-client` +- **Client Secret**: `demo-secret` +- **Redirect URI**: `http://localhost:1179/callback` +- **OAuth Server**: `https://localhost:7029` +- **Protected Resource**: `http://localhost:7071` + +## Available Tools + +Once authenticated, the client can access weather tools including: +- **GetAlerts**: Get weather alerts for a US state +- **GetForecast**: Get weather forecast for a location (latitude/longitude) + +## Troubleshooting + +- Ensure the ASP.NET Core dev certificate is trusted. + ``` + dotnet dev-certs https --clean + dotnet dev-certs https --trust + ``` +- Ensure all three services are running in the correct order +- Check that ports 7029, 7071, and 1179 are available +- If the browser doesn't open automatically, copy the authorization URL from the console and open it manually +- Make sure to allow the OAuth server's self-signed certificate in your browser \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/ModelContextProtocol/README.md b/dotnet/samples/GettingStarted/ModelContextProtocol/README.md new file mode 100644 index 0000000000..be84bff51f --- /dev/null +++ b/dotnet/samples/GettingStarted/ModelContextProtocol/README.md @@ -0,0 +1,64 @@ +# Getting started with Model Content Protocol + +The getting started with Model Content Protocol samples demonstrate how to use MCP Server tools from an agent. + +## Getting started with agents prerequisites + +Before you begin, ensure you have the following prerequisites: + +- .NET 9.0 SDK or later +- Azure OpenAI service endpoint and deployment configured +- Azure CLI installed and authenticated (for Azure credential authentication) +- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource. + +**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai). + +**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively). + +## Samples + +|Sample|Description| +|---|---| +|[Agent with MCP server tools](./Agent_MCP_Server/)|This sample demonstrates how to use MCP server tools with a simple agent| +|[Agent with MCP server tools and authorization](./Agent_MCP_Server_Auth/)|This sample demonstrates how to use MCP Server tools from a protected MCP server with a simple agent| + +## Running the samples from the console + +To run the samples, navigate to the desired sample directory, e.g. + +```powershell +cd Agents_Step01_Running +``` + +Set the following environment variables: + +```powershell +$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint +$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini +``` + +If the variables are not set, you will be prompted for the values when running the samples. + +Execute the following command to build the sample: + +```powershell +dotnet build +``` + +Execute the following command to run the sample: + +```powershell +dotnet run --no-build +``` + +Or just build and run in one step: + +```powershell +dotnet run +``` + +## Running the samples from Visual Studio + +Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`. + +You will be prompted for any required environment variables if they are not already set. diff --git a/dotnet/samples/GettingStarted/README.md b/dotnet/samples/GettingStarted/README.md index 55cc7f7a97..dacf0b92cd 100644 --- a/dotnet/samples/GettingStarted/README.md +++ b/dotnet/samples/GettingStarted/README.md @@ -7,6 +7,9 @@ of the agent framework. |Sample|Description| |---|---| -|[Agents](./Agents/README.md)|Getting started with agents| +|[Agents](./Agents/README.md)|Step by step instructions for getting started with agents| |[Agent Providers](./AgentProviders/README.md)|Getting started with creating agents using various providers| |[Agent Open Telemetry](./AgentOpenTelemetry/README.md)|Getting started with OpenTelemetry for agents| +|[Agent With OpenAI exchange types](./AgentWithOpenAI/README.md)|Using OpenAI exchange types with agents| +|[Workflow](./Workflow/README.md)|Getting started with Workflow| +|[Model Context Protocol](./ModelContextProtocol/README.md)|Getting started with Model Context Protocol| diff --git a/dotnet/samples/GettingStarted/Workflow/README.md b/dotnet/samples/GettingStarted/Workflow/README.md deleted file mode 100644 index 05476e7b8b..0000000000 --- a/dotnet/samples/GettingStarted/Workflow/README.md +++ /dev/null @@ -1,41 +0,0 @@ -# Workflow Getting Started Samples - -The getting started with workflow samples demonstrate the fundamental concepts and functionalities of workflows in Agent Framework. - -## Samples Overview - -### Foundational Concepts - Start Here - -Please begin with the [Foundational](./Foundational) samples in order. These three samples introduce the core concepts of executors, edges, agents in workflows, streaming, and workflow construction. - -| Sample | Concepts | -|--------|----------| -| [Executors and Edges](./Foundational/01_ExecutorsAndEdges) | Minimal workflow with basic executors and edges | -| [Streaming](./Foundational/02_Streaming) | Extends workflows with event streaming | -| [Agents](./Foundational/03_AgentsInWorkflows) | Use agents in workflows | - -Once completed, please proceed to other samples listed below. - -> Note that you don't need to follow a strict order after the foundational samples. However, some samples build upon concepts from previous ones, so it's beneficial to be aware of the dependencies. - -### Concurrent Execution - -| Sample | Concepts | -|--------|----------| -| [Fan-Out and Fan-In](./Concurrent) | Introduces parallel processing with fan-out and fan-in patterns | - -### Workflow Shared States - -| Sample | Concepts | -|--------|----------| -| [Shared States](./SharedStates) | Demonstrates shared states between executors for data sharing and coordination | - -### Conditional Edges - -| Sample | Concepts | -|--------|----------| -| [Edge Conditions](./ConditionalEdges/01_EdgeCondition) | Introduces conditional edges for dynamic routing based on executor outputs | -| [Switch-Case Routing](./ConditionalEdges/02_SwitchCase) | Extends conditional edges with switch-case routing for multiple paths | -| [Multi-Selection Routing](./ConditionalEdges/03_MultiSelection) | Demonstrates multi-selection routing where one executor can trigger multiple downstream executors | - -> These 3 samples build upon each other. It's recommended to explore them in sequence to fully grasp the concepts. diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/03_AgentsInWorkflows/03_AgentsInWorkflows.csproj b/dotnet/samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/CustomAgentExecutors.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Foundational/03_AgentsInWorkflows/03_AgentsInWorkflows.csproj rename to dotnet/samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/CustomAgentExecutors.csproj diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/Program.cs b/dotnet/samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/Program.cs new file mode 100644 index 0000000000..fe1b612603 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/Program.cs @@ -0,0 +1,246 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Text.Json; +using System.Text.Json.Serialization; +using System.Threading.Tasks; +using Azure.AI.OpenAI; +using Azure.Identity; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace WorkflowCustomAgentExecutorsSample; + +/// +/// This sample demonstrates how to create custom executors for AI agents. +/// This is useful when you want more control over the agent's behaviors in a workflow. +/// +/// In this example, we create two custom executors: +/// 1. SloganWriterExecutor: An AI agent that generates slogans based on a given task. +/// 2. FeedbackExecutor: An AI agent that provides feedback on the generated slogans. +/// (These two executors manage the agent instances and their conversation threads.) +/// +/// The workflow alternates between these two executors until the slogan meets a certain +/// quality threshold or a maximum number of attempts is reached. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// - An Azure OpenAI chat completion deployment that supports structured outputs must be configured. +/// +public static class Program +{ + private static async Task Main() + { + // Set up the Azure OpenAI client + var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set."); + var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini"; + var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient(); + + // Create the executors + var sloganWriter = new SloganWriterExecutor(chatClient); + var feedbackProvider = new FeedbackExecutor(chatClient); + + // Build the workflow by adding executors and connecting them + WorkflowBuilder builder = new(sloganWriter); + builder.AddEdge(sloganWriter, feedbackProvider); + builder.AddEdge(feedbackProvider, sloganWriter); + var workflow = builder.Build(); + + // Execute the workflow + var ask = "Create a slogan for a new electric SUV that is affordable and fun to drive."; + StreamingRun run = await InProcessExecution.StreamAsync(workflow, ask); + await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is SloganGeneratedEvent || evt is FeedbackEvent) + { + // Custom events to allow us to monitor the progress of the workflow. + Console.WriteLine($"{evt}"); + } + + if (evt is WorkflowCompletedEvent completedEvent) + { + Console.WriteLine($"{completedEvent}"); + } + } + } +} + +/// +/// A class representing the output of the slogan writer agent. +/// +public sealed class SloganResult +{ + [JsonPropertyName("task")] + public required string Task { get; set; } + + [JsonPropertyName("slogan")] + public required string Slogan { get; set; } +} + +/// +/// A class representing the output of the feedback agent. +/// +public sealed class FeedbackResult +{ + [JsonPropertyName("comments")] + public string Comments { get; set; } = string.Empty; + + [JsonPropertyName("rating")] + public int Rating { get; set; } + + [JsonPropertyName("actions")] + public string Actions { get; set; } = string.Empty; +} + +/// +/// A custom event to indicate that a slogan has been generated. +/// +internal sealed class SloganGeneratedEvent(SloganResult sloganResult) : WorkflowEvent(sloganResult) +{ + public override string ToString() => $"Slogan: {sloganResult.Slogan}"; +} + +/// +/// A custom executor that uses an AI agent to generate slogans based on a given task. +/// Note that this executor has two message handlers: +/// 1. HandleAsync(string message): Handles the initial task to create a slogan. +/// 2. HandleAsync(Feedback message): Handles feedback to improve the slogan. +/// +internal sealed class SloganWriterExecutor + : ReflectingExecutor, + IMessageHandler, + IMessageHandler +{ + private const string Instruction = """ + You are a professional slogan writer. You will be given a task to create a slogan. + """; + + private readonly AIAgent _agent; + private readonly AgentThread _thread; + + /// + /// Initializes a new instance of the class. + /// + /// The chat client to use for the AI agent. + public SloganWriterExecutor(IChatClient chatClient) + { + var agentOptions = new ChatClientAgentOptions(instructions: Instruction) + { + ChatOptions = new() + { + ResponseFormat = ChatResponseFormatJson.ForJsonSchema( + schema: AIJsonUtilities.CreateJsonSchema(typeof(SloganResult)) + ) + } + }; + + this._agent = new ChatClientAgent(chatClient, agentOptions); + this._thread = this._agent.GetNewThread(); + } + + public async ValueTask HandleAsync(string message, IWorkflowContext context) + { + var result = await this._agent.RunAsync(message, this._thread); + + var sloganResult = JsonSerializer.Deserialize(result.Text) ?? throw new InvalidOperationException("Failed to deserialize slogan result."); + + await context.AddEventAsync(new SloganGeneratedEvent(sloganResult)); + return sloganResult; + } + + public async ValueTask HandleAsync(FeedbackResult message, IWorkflowContext context) + { + var feedbackMessage = $""" + Here is the feedback on your previous slogan: + Comments: {message.Comments} + Rating: {message.Rating} + Suggested Actions: {message.Actions} + + Please use this feedback to improve your slogan. + """; + + var result = await this._agent.RunAsync(feedbackMessage, this._thread); + var sloganResult = JsonSerializer.Deserialize(result.Text) ?? throw new InvalidOperationException("Failed to deserialize slogan result."); + + await context.AddEventAsync(new SloganGeneratedEvent(sloganResult)); + return sloganResult; + } +} + +/// +/// A custom event to indicate that feedback has been provided. +/// +internal sealed class FeedbackEvent(FeedbackResult feedbackResult) : WorkflowEvent(feedbackResult) +{ + private readonly JsonSerializerOptions _options = new() { WriteIndented = true }; + public override string ToString() => $"Feedback:\n{JsonSerializer.Serialize(feedbackResult, this._options)}"; +} + +/// +/// A custom executor that uses an AI agent to provide feedback on a slogan. +/// +internal sealed class FeedbackExecutor : ReflectingExecutor, IMessageHandler +{ + private const string Instruction = """ + You are a professional editor. You will be given a slogan and the task it is meant to accomplish. + """; + + private readonly AIAgent _agent; + private readonly AgentThread _thread; + + public int MinimumRating { get; init; } = 8; + + public int MaxAttempts { get; init; } = 3; + + private int _attempts = 0; + + /// + /// Initializes a new instance of the class. + /// + /// The chat client to use for the AI agent. + public FeedbackExecutor(IChatClient chatClient) + { + var agentOptions = new ChatClientAgentOptions(instructions: Instruction) + { + ChatOptions = new() + { + ResponseFormat = ChatResponseFormatJson.ForJsonSchema( + schema: AIJsonUtilities.CreateJsonSchema(typeof(FeedbackResult)) + ) + } + }; + + this._agent = new ChatClientAgent(chatClient, agentOptions); + this._thread = this._agent.GetNewThread(); + } + + public async ValueTask HandleAsync(SloganResult message, IWorkflowContext context) + { + var sloganMessage = $""" + Here is a slogan for the task '{message.Task}': + Slogan: {message.Slogan} + Please provide feedback on this slogan, including comments, a rating from 1 to 10, and suggested actions for improvement. + """; + + var response = await this._agent.RunAsync(sloganMessage, this._thread); + var feedback = JsonSerializer.Deserialize(response.Text) ?? throw new InvalidOperationException("Failed to deserialize feedback."); + + await context.AddEventAsync(new FeedbackEvent(feedback)); + if (feedback.Rating >= this.MinimumRating) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"The following slogan was accepted:\n\n{message.Slogan}")); + return; + } + if (this._attempts >= this.MaxAttempts) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"The slogan was rejected after {this.MaxAttempts} attempts. Final slogan:\n\n{message.Slogan}")); + return; + } + + await context.SendMessageAsync(feedback); + this._attempts++; + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/FoundryAgent.csproj b/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/FoundryAgent.csproj new file mode 100644 index 0000000000..564e214dac --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/FoundryAgent.csproj @@ -0,0 +1,23 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/Program.cs b/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/Program.cs new file mode 100644 index 0000000000..586780f1f3 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/FoundryAgent/Program.cs @@ -0,0 +1,82 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading.Tasks; +using Azure.AI.Agents.Persistent; +using Azure.Identity; +using Microsoft.Agents.Workflows; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace WorkflowFoundryAgentSample; + +/// +/// This sample shows how to use Azure Foundry Agents within a workflow. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// - An Azure Foundry project endpoint and model id. +/// +public static class Program +{ + private static async Task Main() + { + // Set up the Azure OpenAI client + var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") + ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set."); + var model = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_MODEL_ID") ?? "gpt-4o-mini"; + var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential()); + + // Create agents + AIAgent frenchAgent = await GetTranslationAgentAsync("French", persistentAgentsClient, model); + AIAgent spanishAgent = await GetTranslationAgentAsync("Spanish", persistentAgentsClient, model); + AIAgent englishAgent = await GetTranslationAgentAsync("English", persistentAgentsClient, model); + + // Build the workflow by adding executors and connecting them + WorkflowBuilder builder = new(frenchAgent); + builder.AddEdge(frenchAgent, spanishAgent); + builder.AddEdge(spanishAgent, englishAgent); + var workflow = builder.Build(); + + // Execute the workflow + StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!")); + // Must send the turn token to trigger the agents. + // The agents are wrapped as executors. When they receive messages, + // they will cache the messages and only start processing when they receive a TurnToken. + await run.TrySendMessageAsync(new TurnToken(emitEvents: true)); + await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is AgentRunUpdateEvent executorComplete) + { + Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); + } + } + + // Cleanup the agents created for the sample. + await persistentAgentsClient.Administration.DeleteAgentAsync(frenchAgent.Id); + await persistentAgentsClient.Administration.DeleteAgentAsync(spanishAgent.Id); + await persistentAgentsClient.Administration.DeleteAgentAsync(englishAgent.Id); + } + + /// + /// Creates a translation agent for the specified target language. + /// + /// The target language for translation + /// The PersistentAgentsClient to create the agent + /// The model to use for the agent + /// A ChatClientAgent configured for the specified language + private static async Task GetTranslationAgentAsync( + string targetLanguage, + PersistentAgentsClient persistentAgentsClient, + string model) + { + string instructions = $"You are a translation assistant that translates the provided text to {targetLanguage}."; + var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync( + model: model, + name: $"{targetLanguage} Translator", + instructions: instructions); + + return await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id); + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/Program.cs b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/Program.cs new file mode 100644 index 0000000000..7611b14984 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/Program.cs @@ -0,0 +1,90 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading.Tasks; +using Azure.AI.OpenAI; +using Azure.Identity; +using Microsoft.Agents.Workflows; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace WorkflowAsAnAgentsSample; + +/// +/// This sample introduces the concepts workflows as agents, where a workflow can be +/// treated as an . This allows you to interact with a workflow +/// as if it were a single agent. +/// +/// In this example, we create a workflow that uses two language agents to process +/// input concurrently, one that responds in French and another that responds in English. +/// +/// You will interact with the workflow in an interactive loop, sending messages and receiving +/// streaming responses from the workflow as if it were an agent who responds in both languages. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// - This sample uses concurrent processing. +/// - An Azure OpenAI endpoint and deployment name. +/// +public static class Program +{ + private static async Task Main() + { + // Set up the Azure OpenAI client + var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set."); + var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini"; + var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient(); + + // Create the workflow and turn it into an agent + var workflow = WorkflowHelper.GetWorkflow(chatClient); + var agent = workflow.AsAgent("workflow-agent", "Workflow Agent"); + var thread = agent.GetNewThread(); + + // Start an interactive loop to interact with the workflow as if it were an agent + while (true) + { + Console.WriteLine(); + Console.Write("User (or 'exit' to quit): "); + string? input = Console.ReadLine(); + if (string.IsNullOrWhiteSpace(input) || input.Equals("exit", StringComparison.OrdinalIgnoreCase)) + { + break; + } + + await ProcessInputAsync(agent, thread, input); + } + + // Helper method to process user input and display streaming responses. To display + // multiple interleaved responses correctly, we buffer updates by message ID and + // re-render all messages on each update. + static async Task ProcessInputAsync(AIAgent agent, AgentThread thread, string input) + { + Dictionary> buffer = []; + await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(input, thread).ConfigureAwait(false)) + { + if (update.MessageId == null) + { + // skip updates that don't have a message ID + continue; + } + Console.Clear(); + + if (!buffer.TryGetValue(update.MessageId, out List? value)) + { + value = []; + buffer[update.MessageId] = value; + } + value.Add(update); + + foreach (var (messageId, segments) in buffer) + { + string combinedText = string.Concat(segments); + Console.WriteLine($"{segments[0].AuthorName}: {combinedText}"); + Console.WriteLine(); + } + } + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowAsAnAgent.csproj b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowAsAnAgent.csproj new file mode 100644 index 0000000000..b1f90ee600 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowAsAnAgent.csproj @@ -0,0 +1,24 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowHelper.cs b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowHelper.cs new file mode 100644 index 0000000000..9470e22c10 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowHelper.cs @@ -0,0 +1,95 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Collections.Generic; +using System.Linq; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace WorkflowAsAnAgentsSample; + +internal static class WorkflowHelper +{ + /// + /// Creates a workflow that uses two language agents to process input concurrently. + /// + /// The chat client to use for the agents + /// A workflow that processes input using two language agents + internal static Workflow> GetWorkflow(IChatClient chatClient) + { + // Create executors + var startExecutor = new ConcurrentStartExecutor(); + var aggregationExecutor = new ConcurrentAggregationExecutor(); + AIAgent frenchAgent = GetLanguageAgent("French", chatClient); + AIAgent englishAgent = GetLanguageAgent("English", chatClient); + + // Build the workflow by adding executors and connecting them + WorkflowBuilder builder = new(startExecutor); + builder.AddFanOutEdge(startExecutor, targets: [frenchAgent, englishAgent]); + builder.AddFanInEdge(aggregationExecutor, sources: [frenchAgent, englishAgent]); + + return builder.Build>(); + } + + /// + /// Creates a language agent for the specified target language. + /// + /// The target language for translation + /// The chat client to use for the agent + /// A ChatClientAgent configured for the specified language + private static ChatClientAgent GetLanguageAgent(string targetLanguage, IChatClient chatClient) + { + string instructions = $"You're a helpful assistant who always responds in {targetLanguage}."; + return new ChatClientAgent(chatClient, instructions, name: $"{targetLanguage}Agent"); + } + + /// + /// Executor that starts the concurrent processing by sending messages to the agents. + /// + private sealed class ConcurrentStartExecutor() : + ReflectingExecutor("ConcurrentStartExecutor"), + IMessageHandler> + { + /// + /// Starts the concurrent processing by sending messages to the agents. + /// + /// The user message to process + /// Workflow context for accessing workflow services and adding events + public async ValueTask HandleAsync(List message, IWorkflowContext context) + { + // Broadcast the message to all connected agents. Receiving agents will queue + // the message but will not start processing until they receive a turn token. + await context.SendMessageAsync(message); + // Broadcast the turn token to kick off the agents. + await context.SendMessageAsync(new TurnToken(emitEvents: true)); + } + } + + /// + /// Executor that aggregates the results from the concurrent agents. + /// + private sealed class ConcurrentAggregationExecutor() : + ReflectingExecutor("ConcurrentAggregationExecutor"), + IMessageHandler + { + private readonly List _messages = []; + + /// + /// Handles incoming messages from the agents and aggregates their responses. + /// + /// The message from the agent + /// Workflow context for accessing workflow services and adding events + public async ValueTask HandleAsync(ChatMessage message, IWorkflowContext context) + { + this._messages.Add(message); + + if (this._messages.Count == 2) + { + var formattedMessages = string.Join(Environment.NewLine, this._messages.Select(m => $"{m.Text}")); + await context.AddEventAsync(new WorkflowCompletedEvent(formattedMessages)); + } + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/CheckpointAndRehydrate.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj rename to dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/CheckpointAndRehydrate.csproj diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/Program.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/Program.cs new file mode 100644 index 0000000000..d039b889b8 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/Program.cs @@ -0,0 +1,96 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; + +namespace WorkflowCheckpointAndRehydrateSample; + +/// +/// This sample introduces the concepts of check points and shows how to save and restore +/// the state of a workflow using checkpoints. +/// This sample demonstrates checkpoints, which allow you to save and restore a workflow's state. +/// Key concepts: +/// - Super Steps: A workflow executes in stages called "super steps". Each super step runs +/// one or more executors and completes when all those executors finish their work. +/// - Checkpoints: The system automatically saves the workflow's state at the end of each +/// super step. You can use these checkpoints to resume the workflow from any saved point. +/// - Rehydration: You can rehydrate a new workflow instance from a saved checkpoint, allowing +/// you to continue execution from that point. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// +public static class Program +{ + private static async Task Main() + { + // Create the workflow + var workflow = WorkflowHelper.GetWorkflow(); + + // Create checkpoint manager + var checkpointManager = new CheckpointManager(); + var checkpoints = new List(); + + // Execute the workflow and save checkpoints + Checkpointed checkpointedRun = await InProcessExecution + .StreamAsync(workflow, NumberSignal.Init, checkpointManager) + .ConfigureAwait(false); + await foreach (WorkflowEvent evt in checkpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is ExecutorCompletedEvent executorCompletedEvt) + { + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + } + + if (evt is SuperStepCompletedEvent superStepCompletedEvt) + { + // Checkpoints are automatically created at the end of each super step when a + // checkpoint manager is provided. You can store the checkpoint info for later use. + CheckpointInfo? checkpoint = superStepCompletedEvt.CompletionInfo!.Checkpoint; + if (checkpoint != null) + { + checkpoints.Add(checkpoint); + Console.WriteLine($"** Checkpoint created at step {checkpoints.Count}."); + } + } + + if (evt is WorkflowCompletedEvent workflowCompletedEvt) + { + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + } + } + + if (checkpoints.Count == 0) + { + throw new InvalidOperationException("No checkpoints were created during the workflow execution."); + } + Console.WriteLine($"Number of checkpoints created: {checkpoints.Count}"); + + // Rehydrate a new workflow instance from a saved checkpoint and continue execution + var newWorkflow = WorkflowHelper.GetWorkflow(); + var checkpointIndex = 5; + Console.WriteLine($"\n\nHydrating a new workflow instance from the {checkpointIndex + 1}th checkpoint."); + CheckpointInfo savedCheckpoint = checkpoints[checkpointIndex]; + + Checkpointed newCheckpointedRun = await InProcessExecution + .StreamAsync(newWorkflow, NumberSignal.Init, checkpointManager) + .ConfigureAwait(false); + await newCheckpointedRun.RestoreCheckpointAsync(savedCheckpoint, CancellationToken.None).ConfigureAwait(false); + await foreach (WorkflowEvent evt in newCheckpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is ExecutorCompletedEvent executorCompletedEvt) + { + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + } + + if (evt is WorkflowCompletedEvent workflowCompletedEvt) + { + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + } + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/WorkflowHelper.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/WorkflowHelper.cs new file mode 100644 index 0000000000..09ffc8db74 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndRehydrate/WorkflowHelper.cs @@ -0,0 +1,165 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; + +namespace WorkflowCheckpointAndRehydrateSample; + +internal static class WorkflowHelper +{ + /// + /// Get a workflow that plays a number guessing game with checkpointing support. + /// The workflow consists of two executors that are connected in a feedback loop: + /// 1. GuessNumberExecutor: Makes a guess based on the current known bounds. + /// 2. JudgeExecutor: Evaluates the guess and provides feedback. + /// The workflow continues until the correct number is guessed. + /// + internal static Workflow GetWorkflow() + { + // Create the executors + GuessNumberExecutor guessNumberExecutor = new(1, 100); + JudgeExecutor judgeExecutor = new(42); + + // Build the workflow by connecting executors in a loop + var workflow = new WorkflowBuilder(guessNumberExecutor) + .AddEdge(guessNumberExecutor, judgeExecutor) + .AddEdge(judgeExecutor, guessNumberExecutor) + .Build(); + + return workflow; + } +} + +/// +/// Signals used for communication between GuessNumberExecutor and JudgeExecutor. +/// +internal enum NumberSignal +{ + Init, + Above, + Below, +} + +/// +/// Executor that makes a guess based on the current bounds. +/// +internal sealed class GuessNumberExecutor() : ReflectingExecutor("Guess"), IMessageHandler +{ + /// + /// The lower bound of the guessing range. + /// + public int LowerBound { get; private set; } + + /// + /// The upper bound of the guessing range. + /// + public int UpperBound { get; private set; } + + private const string StateKey = "GuessNumberExecutorState"; + + /// + /// Initializes a new instance of the class. + /// + /// The initial lower bound of the guessing range. + /// The initial upper bound of the guessing range. + public GuessNumberExecutor(int lowerBound, int upperBound) : this() + { + this.LowerBound = lowerBound; + this.UpperBound = upperBound; + } + + private int NextGuess => (this.LowerBound + this.UpperBound) / 2; + + public async ValueTask HandleAsync(NumberSignal message, IWorkflowContext context) + { + switch (message) + { + case NumberSignal.Init: + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Above: + this.UpperBound = this.NextGuess - 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Below: + this.LowerBound = this.NextGuess + 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + } + } + + /// + /// Checkpoint the current state of the executor. + /// This must be overridden to save any state that is needed to resume the executor. + /// + protected override ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + return context.QueueStateUpdateAsync(StateKey, (this.LowerBound, this.UpperBound)); + } + + /// + /// Restore the state of the executor from a checkpoint. + /// This must be overridden to restore any state that was saved during checkpointing. + /// + protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + (this.LowerBound, this.UpperBound) = await context.ReadStateAsync<(int, int)>(StateKey).ConfigureAwait(false); + } +} + +/// +/// Executor that judges the guess and provides feedback. +/// +internal sealed class JudgeExecutor() : ReflectingExecutor("Judge"), IMessageHandler +{ + private readonly int _targetNumber; + private int _tries = 0; + private const string StateKey = "JudgeExecutorState"; + + /// + /// Initializes a new instance of the class. + /// + /// The number to be guessed. + public JudgeExecutor(int targetNumber) : this() + { + this._targetNumber = targetNumber; + } + + public async ValueTask HandleAsync(int message, IWorkflowContext context) + { + this._tries++; + if (message == this._targetNumber) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"{this._targetNumber} found in {this._tries} tries!")) + .ConfigureAwait(false); + } + else if (message < this._targetNumber) + { + await context.SendMessageAsync(NumberSignal.Below).ConfigureAwait(false); + } + else + { + await context.SendMessageAsync(NumberSignal.Above).ConfigureAwait(false); + } + } + + /// + /// Checkpoint the current state of the executor. + /// This must be overridden to save any state that is needed to resume the executor. + /// + protected override ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + return context.QueueStateUpdateAsync(StateKey, this._tries); + } + + /// + /// Restore the state of the executor from a checkpoint. + /// This must be overridden to restore any state that was saved during checkpointing. + /// + protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + this._tries = await context.ReadStateAsync(StateKey).ConfigureAwait(false); + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/CheckpointAndResume.csproj b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/CheckpointAndResume.csproj new file mode 100644 index 0000000000..1025cb45c9 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/CheckpointAndResume.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/Program.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/Program.cs new file mode 100644 index 0000000000..ebabba2141 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/Program.cs @@ -0,0 +1,91 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; + +namespace WorkflowCheckpointAndResumeSample; + +/// +/// This sample introduces the concepts of check points and shows how to save and restore +/// the state of a workflow using checkpoints. +/// This sample demonstrates checkpoints, which allow you to save and restore a workflow's state. +/// Key concepts: +/// - Super Steps: A workflow executes in stages called "super steps". Each super step runs +/// one or more executors and completes when all those executors finish their work. +/// - Checkpoints: The system automatically saves the workflow's state at the end of each +/// super step. You can use these checkpoints to resume the workflow from any saved point. +/// - Resume: If needed, you can restore a checkpoint and continue execution from that state. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// +public static class Program +{ + private static async Task Main() + { + // Create the workflow + var workflow = WorkflowHelper.GetWorkflow(); + + // Create checkpoint manager + var checkpointManager = new CheckpointManager(); + var checkpoints = new List(); + + // Execute the workflow and save checkpoints + Checkpointed checkpointedRun = await InProcessExecution + .StreamAsync(workflow, NumberSignal.Init, checkpointManager) + .ConfigureAwait(false); + await foreach (WorkflowEvent evt in checkpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is ExecutorCompletedEvent executorCompletedEvt) + { + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + } + + if (evt is SuperStepCompletedEvent superStepCompletedEvt) + { + // Checkpoints are automatically created at the end of each super step when a + // checkpoint manager is provided. You can store the checkpoint info for later use. + CheckpointInfo? checkpoint = superStepCompletedEvt.CompletionInfo!.Checkpoint; + if (checkpoint != null) + { + checkpoints.Add(checkpoint); + Console.WriteLine($"** Checkpoint created at step {checkpoints.Count}."); + } + } + + if (evt is WorkflowCompletedEvent workflowCompletedEvt) + { + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + } + } + + if (checkpoints.Count == 0) + { + throw new InvalidOperationException("No checkpoints were created during the workflow execution."); + } + Console.WriteLine($"Number of checkpoints created: {checkpoints.Count}"); + + // Restoring from a checkpoint and resuming execution + var checkpointIndex = 5; + Console.WriteLine($"\n\nRestoring from the {checkpointIndex + 1}th checkpoint."); + CheckpointInfo savedCheckpoint = checkpoints[checkpointIndex]; + // Note that we are restoring the state directly to the same run instance. + await checkpointedRun.RestoreCheckpointAsync(savedCheckpoint, CancellationToken.None).ConfigureAwait(false); + await foreach (WorkflowEvent evt in checkpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is ExecutorCompletedEvent executorCompletedEvt) + { + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + } + + if (evt is WorkflowCompletedEvent workflowCompletedEvt) + { + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + } + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/WorkflowHelper.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/WorkflowHelper.cs new file mode 100644 index 0000000000..aa4f5506ac --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointAndResume/WorkflowHelper.cs @@ -0,0 +1,165 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; + +namespace WorkflowCheckpointAndResumeSample; + +internal static class WorkflowHelper +{ + /// + /// Get a workflow that plays a number guessing game with checkpointing support. + /// The workflow consists of two executors that are connected in a feedback loop: + /// 1. GuessNumberExecutor: Makes a guess based on the current known bounds. + /// 2. JudgeExecutor: Evaluates the guess and provides feedback. + /// The workflow continues until the correct number is guessed. + /// + internal static Workflow GetWorkflow() + { + // Create the executors + GuessNumberExecutor guessNumberExecutor = new(1, 100); + JudgeExecutor judgeExecutor = new(42); + + // Build the workflow by connecting executors in a loop + var workflow = new WorkflowBuilder(guessNumberExecutor) + .AddEdge(guessNumberExecutor, judgeExecutor) + .AddEdge(judgeExecutor, guessNumberExecutor) + .Build(); + + return workflow; + } +} + +/// +/// Signals used for communication between GuessNumberExecutor and JudgeExecutor. +/// +internal enum NumberSignal +{ + Init, + Above, + Below, +} + +/// +/// Executor that makes a guess based on the current bounds. +/// +internal sealed class GuessNumberExecutor() : ReflectingExecutor("Guess"), IMessageHandler +{ + /// + /// The lower bound of the guessing range. + /// + public int LowerBound { get; private set; } + + /// + /// The upper bound of the guessing range. + /// + public int UpperBound { get; private set; } + + private const string StateKey = "GuessNumberExecutorState"; + + /// + /// Initializes a new instance of the class. + /// + /// The initial lower bound of the guessing range. + /// The initial upper bound of the guessing range. + public GuessNumberExecutor(int lowerBound, int upperBound) : this() + { + this.LowerBound = lowerBound; + this.UpperBound = upperBound; + } + + private int NextGuess => (this.LowerBound + this.UpperBound) / 2; + + public async ValueTask HandleAsync(NumberSignal message, IWorkflowContext context) + { + switch (message) + { + case NumberSignal.Init: + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Above: + this.UpperBound = this.NextGuess - 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Below: + this.LowerBound = this.NextGuess + 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + } + } + + /// + /// Checkpoint the current state of the executor. + /// This must be overridden to save any state that is needed to resume the executor. + /// + protected override ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + return context.QueueStateUpdateAsync(StateKey, (this.LowerBound, this.UpperBound)); + } + + /// + /// Restore the state of the executor from a checkpoint. + /// This must be overridden to restore any state that was saved during checkpointing. + /// + protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + (this.LowerBound, this.UpperBound) = await context.ReadStateAsync<(int, int)>(StateKey).ConfigureAwait(false); + } +} + +/// +/// Executor that judges the guess and provides feedback. +/// +internal sealed class JudgeExecutor() : ReflectingExecutor("Judge"), IMessageHandler +{ + private readonly int _targetNumber; + private int _tries = 0; + private const string StateKey = "JudgeExecutorState"; + + /// + /// Initializes a new instance of the class. + /// + /// The number to be guessed. + public JudgeExecutor(int targetNumber) : this() + { + this._targetNumber = targetNumber; + } + + public async ValueTask HandleAsync(int message, IWorkflowContext context) + { + this._tries++; + if (message == this._targetNumber) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"{this._targetNumber} found in {this._tries} tries!")) + .ConfigureAwait(false); + } + else if (message < this._targetNumber) + { + await context.SendMessageAsync(NumberSignal.Below).ConfigureAwait(false); + } + else + { + await context.SendMessageAsync(NumberSignal.Above).ConfigureAwait(false); + } + } + + /// + /// Checkpoint the current state of the executor. + /// This must be overridden to save any state that is needed to resume the executor. + /// + protected override ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + return context.QueueStateUpdateAsync(StateKey, this._tries); + } + + /// + /// Restore the state of the executor from a checkpoint. + /// This must be overridden to restore any state that was saved during checkpointing. + /// + protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + this._tries = await context.ReadStateAsync(StateKey).ConfigureAwait(false); + } +} diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/02_Streaming/02_Streaming.csproj b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/CheckpointWithHumanInTheLoop.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Foundational/02_Streaming/02_Streaming.csproj rename to dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/CheckpointWithHumanInTheLoop.csproj diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/Program.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/Program.cs new file mode 100644 index 0000000000..167cc760d3 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/Program.cs @@ -0,0 +1,138 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; + +namespace WorkflowCheckpointWithHumanInTheLoopSample; + +/// +/// This sample demonstrates how to create a workflow with human-in-the-loop interaction and +/// checkpointing support. The workflow plays a number guessing game where the user provides +/// guesses based on feedback from the workflow. The workflow state is checkpointed at the end +/// of each super step, allowing it to be restored and resumed later. +/// Each InputPort request and response cycle takes two super steps: +/// 1. The InputPort sends a RequestInfoEvent to request input from the external world. +/// 2. The external world sends a response back to the InputPort. +/// Thus, two checkpoints are created for each human-in-the-loop interaction. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// - This sample builds upon the HumanInTheLoopBasic sample. It's recommended to go through that +/// sample first to understand the basics of human-in-the-loop workflows. +/// - This sample also builds upon the CheckpointAndResume sample. It's recommended to +/// go through that sample first to understand the basics of checkpointing and resuming workflows. +/// +public static class Program +{ + private static async Task Main() + { + // Create the workflow + var workflow = WorkflowHelper.GetWorkflow(); + + // Create checkpoint manager + var checkpointManager = new CheckpointManager(); + var checkpoints = new List(); + + // Execute the workflow and save checkpoints + Checkpointed checkpointedRun = await InProcessExecution + .StreamAsync(workflow, new SignalWithNumber(NumberSignal.Init), checkpointManager) + .ConfigureAwait(false); + await foreach (WorkflowEvent evt in checkpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + switch (evt) + { + case RequestInfoEvent requestInputEvt: + // Handle `RequestInfoEvent` from the workflow + ExternalResponse response = HandleExternalRequest(requestInputEvt.Request); + await checkpointedRun.Run.SendResponseAsync(response).ConfigureAwait(false); + break; + case ExecutorCompletedEvent executorCompletedEvt: + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + break; + case SuperStepCompletedEvent superStepCompletedEvt: + // Checkpoints are automatically created at the end of each super step when a + // checkpoint manager is provided. You can store the checkpoint info for later use. + CheckpointInfo? checkpoint = superStepCompletedEvt.CompletionInfo!.Checkpoint; + if (checkpoint != null) + { + checkpoints.Add(checkpoint); + Console.WriteLine($"** Checkpoint created at step {checkpoints.Count}."); + } + break; + case WorkflowCompletedEvent workflowCompletedEvt: + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + break; + } + } + + if (checkpoints.Count == 0) + { + throw new InvalidOperationException("No checkpoints were created during the workflow execution."); + } + Console.WriteLine($"Number of checkpoints created: {checkpoints.Count}"); + + // Restoring from a checkpoint and resuming execution + var checkpointIndex = 1; + Console.WriteLine($"\n\nRestoring from the {checkpointIndex + 1}th checkpoint."); + CheckpointInfo savedCheckpoint = checkpoints[checkpointIndex]; + // Note that we are restoring the state directly to the same run instance. + await checkpointedRun.RestoreCheckpointAsync(savedCheckpoint, CancellationToken.None).ConfigureAwait(false); + await foreach (WorkflowEvent evt in checkpointedRun.Run.WatchStreamAsync().ConfigureAwait(false)) + { + switch (evt) + { + case RequestInfoEvent requestInputEvt: + // Handle `RequestInfoEvent` from the workflow + ExternalResponse response = HandleExternalRequest(requestInputEvt.Request); + await checkpointedRun.Run.SendResponseAsync(response).ConfigureAwait(false); + break; + case ExecutorCompletedEvent executorCompletedEvt: + Console.WriteLine($"* Executor {executorCompletedEvt.ExecutorId} completed."); + break; + case WorkflowCompletedEvent workflowCompletedEvt: + Console.WriteLine($"Workflow completed with result: {workflowCompletedEvt.Data}"); + break; + } + } + } + + private static ExternalResponse HandleExternalRequest(ExternalRequest request) + { + if (request.Port.Request == typeof(SignalWithNumber)) + { + var signal = (SignalWithNumber)request.Data; + switch (signal.Signal) + { + case NumberSignal.Init: + int initialGuess = ReadIntegerFromConsole("Please provide your initial guess: "); + return request.CreateResponse(initialGuess); + case NumberSignal.Above: + int lowerGuess = ReadIntegerFromConsole($"You previously guessed {signal.Number} too large. Please provide a new guess: "); + return request.CreateResponse(lowerGuess); + case NumberSignal.Below: + int higherGuess = ReadIntegerFromConsole($"You previously guessed {signal.Number} too small. Please provide a new guess: "); + return request.CreateResponse(higherGuess); + } + } + + throw new NotSupportedException($"Request {request.Port.Request} is not supported"); + } + + private static int ReadIntegerFromConsole(string prompt) + { + while (true) + { + Console.Write(prompt); + string? input = Console.ReadLine(); + if (int.TryParse(input, out int value)) + { + return value; + } + Console.WriteLine("Invalid input. Please enter a valid integer."); + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/WorkflowHelper.cs b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/WorkflowHelper.cs new file mode 100644 index 0000000000..a3e81914b7 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Checkpoint/CheckpointWithHumanInTheLoop/WorkflowHelper.cs @@ -0,0 +1,110 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; + +namespace WorkflowCheckpointWithHumanInTheLoopSample; + +internal static class WorkflowHelper +{ + /// + /// Get a workflow that plays a number guessing game with human-in-the-loop interaction. + /// An input port allows the external world to provide inputs to the workflow upon requests. + /// + internal static Workflow GetWorkflow() + { + // Create the executors + InputPort numberInputPort = InputPort.Create("GuessNumber"); + JudgeExecutor judgeExecutor = new(42); + + // Build the workflow by connecting executors in a loop + var workflow = new WorkflowBuilder(numberInputPort) + .AddEdge(numberInputPort, judgeExecutor) + .AddEdge(judgeExecutor, numberInputPort) + .Build(); + + return workflow; + } +} + +/// +/// Signals indicating if the guess was too high, too low, or an initial guess. +/// +internal enum NumberSignal +{ + Init, + Above, + Below, +} + +/// +/// Signals used for communication between guesses and the JudgeExecutor. +/// +internal sealed class SignalWithNumber +{ + public NumberSignal Signal { get; } + public int? Number { get; } + + public SignalWithNumber(NumberSignal signal, int? number = null) + { + this.Signal = signal; + this.Number = number; + } +} + +/// +/// Executor that judges the guess and provides feedback. +/// +internal sealed class JudgeExecutor() : ReflectingExecutor("Judge"), IMessageHandler +{ + private readonly int _targetNumber; + private int _tries = 0; + private const string StateKey = "JudgeExecutorState"; + + /// + /// Initializes a new instance of the class. + /// + /// The number to be guessed. + public JudgeExecutor(int targetNumber) : this() + { + this._targetNumber = targetNumber; + } + + public async ValueTask HandleAsync(int message, IWorkflowContext context) + { + this._tries++; + if (message == this._targetNumber) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"{this._targetNumber} found in {this._tries} tries!")) + .ConfigureAwait(false); + } + else if (message < this._targetNumber) + { + await context.SendMessageAsync(new SignalWithNumber(NumberSignal.Below, message)).ConfigureAwait(false); + } + else + { + await context.SendMessageAsync(new SignalWithNumber(NumberSignal.Above, message)).ConfigureAwait(false); + } + } + + /// + /// Checkpoint the current state of the executor. + /// This must be overridden to save any state that is needed to resume the executor. + /// + protected override ValueTask OnCheckpointingAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + return context.QueueStateUpdateAsync(StateKey, this._tries); + } + + /// + /// Restore the state of the executor from a checkpoint. + /// This must be overridden to restore any state that was saved during checkpointing. + /// + protected override async ValueTask OnCheckpointRestoredAsync(IWorkflowContext context, CancellationToken cancellation = default) + { + this._tries = await context.ReadStateAsync(StateKey).ConfigureAwait(false); + } +} diff --git a/dotnet/samples/GettingStarted/Workflow/Concurrent/Concurrent.csproj b/dotnet/samples/GettingStarted/Workflows/Concurrent/Concurrent.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Concurrent/Concurrent.csproj rename to dotnet/samples/GettingStarted/Workflows/Concurrent/Concurrent.csproj diff --git a/dotnet/samples/GettingStarted/Workflow/Concurrent/Program.cs b/dotnet/samples/GettingStarted/Workflows/Concurrent/Program.cs similarity index 97% rename from dotnet/samples/GettingStarted/Workflow/Concurrent/Program.cs rename to dotnet/samples/GettingStarted/Workflows/Concurrent/Program.cs index 2c3e1594c6..b6e6cfcc00 100644 --- a/dotnet/samples/GettingStarted/Workflow/Concurrent/Program.cs +++ b/dotnet/samples/GettingStarted/Workflows/Concurrent/Program.cs @@ -85,7 +85,7 @@ internal sealed class ConcurrentStartExecutor() : /// /// The user message to process /// Workflow context for accessing workflow services and adding events - /// + /// A task representing the asynchronous operation public async ValueTask HandleAsync(string message, IWorkflowContext context) { // Broadcast the message to all connected agents. Receiving agents will queue @@ -110,7 +110,7 @@ internal sealed class ConcurrentAggregationExecutor() : /// /// The message from the agent /// Workflow context for accessing workflow services and adding events - /// + /// A task representing the asynchronous operation public async ValueTask HandleAsync(ChatMessage message, IWorkflowContext context) { this._messages.Add(message); diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/01_EdgeCondition.csproj b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/01_EdgeCondition.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/01_EdgeCondition.csproj rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/01_EdgeCondition.csproj diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/Program.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/Program.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/Program.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/Program.cs diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/Resources.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/Resources.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/01_EdgeCondition/Resources.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/01_EdgeCondition/Resources.cs diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/02_SwitchCase.csproj b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/02_SwitchCase.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/02_SwitchCase.csproj rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/02_SwitchCase.csproj diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/Program.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/Program.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/Program.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/Program.cs diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/Resources.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/Resources.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/02_SwitchCase/Resources.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/02_SwitchCase/Resources.cs diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/03_MultiSelection.csproj b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/03_MultiSelection.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/03_MultiSelection.csproj rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/03_MultiSelection.csproj diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/Program.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/Program.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/Program.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/Program.cs diff --git a/dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/Resources.cs b/dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/Resources.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/ConditionalEdges/03_MultiSelection/Resources.cs rename to dotnet/samples/GettingStarted/Workflows/ConditionalEdges/03_MultiSelection/Resources.cs diff --git a/dotnet/samples/DeclarativeWorkflow/DeclarativeWorkflow.csproj b/dotnet/samples/GettingStarted/Workflows/Declarative/DeclarativeWorkflow.csproj similarity index 83% rename from dotnet/samples/DeclarativeWorkflow/DeclarativeWorkflow.csproj rename to dotnet/samples/GettingStarted/Workflows/Declarative/DeclarativeWorkflow.csproj index ee1a58754c..96a9d5df1d 100644 --- a/dotnet/samples/DeclarativeWorkflow/DeclarativeWorkflow.csproj +++ b/dotnet/samples/GettingStarted/Workflows/Declarative/DeclarativeWorkflow.csproj @@ -26,8 +26,8 @@ - - + + diff --git a/dotnet/samples/DeclarativeWorkflow/Program.cs b/dotnet/samples/GettingStarted/Workflows/Declarative/Program.cs similarity index 93% rename from dotnet/samples/DeclarativeWorkflow/Program.cs rename to dotnet/samples/GettingStarted/Workflows/Declarative/Program.cs index c480e96c23..ffacf3123a 100644 --- a/dotnet/samples/DeclarativeWorkflow/Program.cs +++ b/dotnet/samples/GettingStarted/Workflows/Declarative/Program.cs @@ -17,7 +17,7 @@ using Microsoft.Extensions.Configuration; namespace Demo.DeclarativeWorkflow; /// -/// HOW TO: Create a workflow from a declartive (yaml based) definition. +/// HOW TO: Create a workflow from a declarative (yaml based) definition. /// /// /// Configuration @@ -92,13 +92,21 @@ internal sealed class Program await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) { - if (evt is ExecutorInvokeEvent executorInvoked) + if (evt is ExecutorInvokedEvent executorInvoked) { - Debug.WriteLine($"STEP ENTER #{executorInvoked.ExecutorId}"); + Debug.WriteLine($"EXECUTOR ENTER #{executorInvoked.ExecutorId}"); } - else if (evt is ExecutorCompleteEvent executorComplete) + else if (evt is ExecutorCompletedEvent executorCompleted) { - Debug.WriteLine($"STEP EXIT #{executorComplete.ExecutorId}"); + Debug.WriteLine($"EXECUTOR EXIT #{executorCompleted.ExecutorId}"); + } + if (evt is DeclarativeActionInvokeEvent actionInvoked) + { + Debug.WriteLine($"ACTION ENTER #{actionInvoked.ActionId} [{actionInvoked.ActionType}]"); + } + else if (evt is DeclarativeActionCompleteEvent actionComplete) + { + Debug.WriteLine($"ACTION EXIT #{actionComplete.ActionId} [{actionComplete.ActionType}]"); } else if (evt is ExecutorFailureEvent executorFailure) { diff --git a/dotnet/samples/DeclarativeWorkflow/README.md b/dotnet/samples/GettingStarted/Workflows/Declarative/README.md similarity index 80% rename from dotnet/samples/DeclarativeWorkflow/README.md rename to dotnet/samples/GettingStarted/Workflows/Declarative/README.md index 5229bd50c2..0ddda6992d 100644 --- a/dotnet/samples/DeclarativeWorkflow/README.md +++ b/dotnet/samples/GettingStarted/Workflows/Declarative/README.md @@ -21,10 +21,10 @@ $env:FOUNDRY_PROJECT_ENDPOINT="https://..." To set your secrets with .NET Secret Manager: -1. From the root of the respository, navigate the console to the project folder: +1. From the root of the repository, navigate the console to the project folder: ``` - cd dotnet/demos/DeclarativeWorkflow + cd dotnet/samples/GettingStarted/Workflows/Declarative/DeclarativeWorkflow ``` 2. Examine existing secret definitions: @@ -49,16 +49,16 @@ To set your secrets with .NET Secret Manager: Use [_Azure CLI_](https://learn.microsoft.com/cli/azure/authenticate-azure-cli) to authorize access to your Azure Foundry Project: - ``` - az login - az account get-access-token - ``` +``` +az login +az account get-access-token +``` #### Agents The sample workflows rely on agents defined in your Azure Foundry Project. -To create agents, run the [`Create.ps1`](../../../workflows/) script. +To create agents, run the [`Create.ps1`](../../../../../workflows/) script. This will create the agents used in the sample workflows in your Azure Foundry Project and format a script you can copy and use to configure your environment. > Note: `Create.ps1` relies upon the `FOUNDRY_PROJECT_ENDPOINT` setting. @@ -66,13 +66,12 @@ This will create the agents used in the sample workflows in your Azure Foundry P ## Execution Run the demo from the console by specifying a path to a declarative (YAML) workflow file. -The repository has example workflows available in the root [`/workflows`](../../../workflows) folder. +The repository has example workflows available in the root [`/workflows`](../../../../../workflows) folder. -1. From the root of the respository, navigate the console to the project folder: +1. From the root of the repository, navigate the console to the project folder: ```sh - cd dotnet/demos/DeclarativeWorkflow - + cd dotnet/samples/GettingStarted/Workflows/Declarative/DeclarativeWorkflow ``` 2. Run the demo referencing a sample workflow by name: diff --git a/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/HumanInTheLoopBasic.csproj b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/HumanInTheLoopBasic.csproj new file mode 100644 index 0000000000..bbee070910 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/HumanInTheLoopBasic.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/Program.cs b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/Program.cs new file mode 100644 index 0000000000..07ffe8c06d --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/Program.cs @@ -0,0 +1,86 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; + +namespace WorkflowHumanInTheLoopBasicSample; + +/// +/// This sample introduces the concept of InputPort and ExternalRequest to enable +/// human-in-the-loop interaction scenarios. +/// An input port can be used as if it were an executor in the workflow graph. Upon receiving +/// a message, the input port generates an RequestInfoEvent that gets emitted to the external world. +/// The external world can then respond to the request by sending an ExternalResponse back to +/// the workflow. +/// The sample implements a simple number guessing game where the external user tries to guess +/// a pre-defined target number. The workflow consists of a single JudgeExecutor that judges +/// the user's guesses and provides feedback. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// +public static class Program +{ + private static async Task Main() + { + // Create the workflow + var workflow = WorkflowHelper.GetWorkflow(); + + // Execute the workflow + StreamingRun handle = await InProcessExecution.StreamAsync(workflow, NumberSignal.Init).ConfigureAwait(false); + await foreach (WorkflowEvent evt in handle.WatchStreamAsync().ConfigureAwait(false)) + { + switch (evt) + { + case RequestInfoEvent requestInputEvt: + // Handle `RequestInfoEvent` from the workflow + ExternalResponse response = HandleExternalRequest(requestInputEvt.Request); + await handle.SendResponseAsync(response).ConfigureAwait(false); + break; + + case WorkflowCompletedEvent workflowCompleteEvt: + // The workflow has completed successfully + Console.WriteLine($"Workflow completed with result: {workflowCompleteEvt.Data}"); + return; + } + } + } + + private static ExternalResponse HandleExternalRequest(ExternalRequest request) + { + if (request.Port.Request == typeof(NumberSignal)) + { + var signal = (NumberSignal)request.Data; + switch (signal) + { + case NumberSignal.Init: + int initialGuess = ReadIntegerFromConsole("Please provide your initial guess: "); + return request.CreateResponse(initialGuess); + case NumberSignal.Above: + int lowerGuess = ReadIntegerFromConsole("You previously guessed too large. Please provide a new guess: "); + return request.CreateResponse(lowerGuess); + case NumberSignal.Below: + int higherGuess = ReadIntegerFromConsole("You previously guessed too small. Please provide a new guess: "); + return request.CreateResponse(higherGuess); + } + } + + throw new NotSupportedException($"Request {request.Port.Request} is not supported"); + } + + private static int ReadIntegerFromConsole(string prompt) + { + while (true) + { + Console.Write(prompt); + string? input = Console.ReadLine(); + if (int.TryParse(input, out int value)) + { + return value; + } + Console.WriteLine("Invalid input. Please enter a valid integer."); + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/WorkflowHelper.cs b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/WorkflowHelper.cs new file mode 100644 index 0000000000..7e11a4b39d --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/HumanInTheLoop/HumanInTheLoopBasic/WorkflowHelper.cs @@ -0,0 +1,75 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; + +namespace WorkflowHumanInTheLoopBasicSample; + +internal static class WorkflowHelper +{ + /// + /// Get a workflow that plays a number guessing game with human-in-the-loop interaction. + /// An input port allows the external world to provide inputs to the workflow upon requests. + /// + internal static Workflow GetWorkflow() + { + // Create the executors + InputPort numberInputPort = InputPort.Create("GuessNumber"); + JudgeExecutor judgeExecutor = new(42); + + // Build the workflow by connecting executors in a loop + var workflow = new WorkflowBuilder(numberInputPort) + .AddEdge(numberInputPort, judgeExecutor) + .AddEdge(judgeExecutor, numberInputPort) + .Build(); + + return workflow; + } +} + +/// +/// Signals used for communication between guesses and the JudgeExecutor. +/// +internal enum NumberSignal +{ + Init, + Above, + Below, +} + +/// +/// Executor that judges the guess and provides feedback. +/// +internal sealed class JudgeExecutor() : ReflectingExecutor("Judge"), IMessageHandler +{ + private readonly int _targetNumber; + private int _tries = 0; + + /// + /// Initializes a new instance of the class. + /// + /// The number to be guessed. + public JudgeExecutor(int targetNumber) : this() + { + this._targetNumber = targetNumber; + } + + public async ValueTask HandleAsync(int message, IWorkflowContext context) + { + this._tries++; + if (message == this._targetNumber) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"{this._targetNumber} found in {this._tries} tries!")) + .ConfigureAwait(false); + } + else if (message < this._targetNumber) + { + await context.SendMessageAsync(NumberSignal.Below).ConfigureAwait(false); + } + else + { + await context.SendMessageAsync(NumberSignal.Above).ConfigureAwait(false); + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/Loop/Loop.csproj b/dotnet/samples/GettingStarted/Workflows/Loop/Loop.csproj new file mode 100644 index 0000000000..75b48d7b65 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Loop/Loop.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflows/Loop/Program.cs b/dotnet/samples/GettingStarted/Workflows/Loop/Program.cs new file mode 100644 index 0000000000..97a21b8268 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/Loop/Program.cs @@ -0,0 +1,139 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading.Tasks; +using Microsoft.Agents.Workflows; +using Microsoft.Agents.Workflows.Reflection; + +namespace WorkflowLoopSample; + +/// +/// This sample demonstrates a simple number guessing game using a workflow with looping behavior. +/// +/// The workflow consists of two executors that are connected in a feedback loop: +/// 1. GuessNumberExecutor: Makes a guess based on the current known bounds. +/// 2. JudgeExecutor: Evaluates the guess and provides feedback. +/// The workflow continues until the correct number is guessed. +/// +/// +/// Pre-requisites: +/// - Foundational samples should be completed first. +/// +public static class Program +{ + private static async Task Main() + { + // Create the executors + GuessNumberExecutor guessNumberExecutor = new(1, 100); + JudgeExecutor judgeExecutor = new(42); + + // Build the workflow by connecting executors in a loop + var workflow = new WorkflowBuilder(guessNumberExecutor) + .AddEdge(guessNumberExecutor, judgeExecutor) + .AddEdge(judgeExecutor, guessNumberExecutor) + .Build(); + + // Execute the workflow + StreamingRun run = await InProcessExecution.StreamAsync(workflow, NumberSignal.Init).ConfigureAwait(false); + await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) + { + if (evt is WorkflowCompletedEvent workflowCompleteEvt) + { + Console.WriteLine($"Result: {workflowCompleteEvt}"); + } + } + } +} + +/// +/// Signals used for communication between GuessNumberExecutor and JudgeExecutor. +/// +internal enum NumberSignal +{ + Init, + Above, + Below, +} + +/// +/// Executor that makes a guess based on the current bounds. +/// +internal sealed class GuessNumberExecutor : ReflectingExecutor, IMessageHandler +{ + /// + /// The lower bound of the guessing range. + /// + public int LowerBound { get; private set; } + + /// + /// The upper bound of the guessing range. + /// + public int UpperBound { get; private set; } + + /// + /// Initializes a new instance of the class. + /// + /// The initial lower bound of the guessing range. + /// The initial upper bound of the guessing range. + public GuessNumberExecutor(int lowerBound, int upperBound) + { + this.LowerBound = lowerBound; + this.UpperBound = upperBound; + } + + private int NextGuess => (this.LowerBound + this.UpperBound) / 2; + + public async ValueTask HandleAsync(NumberSignal message, IWorkflowContext context) + { + switch (message) + { + case NumberSignal.Init: + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Above: + this.UpperBound = this.NextGuess - 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + case NumberSignal.Below: + this.LowerBound = this.NextGuess + 1; + await context.SendMessageAsync(this.NextGuess).ConfigureAwait(false); + break; + } + } +} + +/// +/// Executor that judges the guess and provides feedback. +/// +internal sealed class JudgeExecutor : ReflectingExecutor, IMessageHandler +{ + private readonly int _targetNumber; + private int _tries = 0; + + /// + /// Initializes a new instance of the class. + /// + /// The number to be guessed. + public JudgeExecutor(int targetNumber) + { + this._targetNumber = targetNumber; + } + + public async ValueTask HandleAsync(int message, IWorkflowContext context) + { + this._tries++; + if (message == this._targetNumber) + { + await context.AddEventAsync(new WorkflowCompletedEvent($"{this._targetNumber} found in {this._tries} tries!")) + .ConfigureAwait(false); + } + else if (message < this._targetNumber) + { + await context.SendMessageAsync(NumberSignal.Below).ConfigureAwait(false); + } + else + { + await context.SendMessageAsync(NumberSignal.Above).ConfigureAwait(false); + } + } +} diff --git a/dotnet/samples/GettingStarted/Workflows/README.md b/dotnet/samples/GettingStarted/Workflows/README.md new file mode 100644 index 0000000000..55ffa1a2df --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/README.md @@ -0,0 +1,77 @@ +# Workflow Getting Started Samples + +The getting started with workflow samples demonstrate the fundamental concepts and functionalities of workflows in Agent Framework. + +## Samples Overview + +### Foundational Concepts - Start Here + +Please begin with the [Foundational](./_Foundational) samples in order. These three samples introduce the core concepts of executors, edges, agents in workflows, streaming, and workflow construction. + +> The folder name starts with an underscore (`_Foundational`) to ensure it appears first in the explorer view. + +| Sample | Concepts | +|--------|----------| +| [Executors and Edges](./_Foundational/01_ExecutorsAndEdges) | Minimal workflow with basic executors and edges | +| [Streaming](./_Foundational/02_Streaming) | Extends workflows with event streaming | +| [Agents](./_Foundational/03_AgentsInWorkflows) | Use agents in workflows | + +Once completed, please proceed to other samples listed below. + +> Note that you don't need to follow a strict order after the foundational samples. However, some samples build upon concepts from previous ones, so it's beneficial to be aware of the dependencies. + +### Agents + +| Sample | Concepts | +|--------|----------| +| [Foundry Agents in Workflows](./Agents/FoundryAgent) | Demonstrates using Azure Foundry Agents within a workflow | +| [Custom Agent Executors](./Agents/CustomAgentExecutors) | Shows how to create a custom agent executor for more complex scenarios | +| [Workflow as an Agent](./Agents/WorkflowAsAgent) | Illustrates how to encapsulate a workflow as an agent | + +### Concurrent Execution + +| Sample | Concepts | +|--------|----------| +| [Fan-Out and Fan-In](./Concurrent) | Introduces parallel processing with fan-out and fan-in patterns | + +### Loop + +| Sample | Concepts | +|--------|----------| +| [Looping](./Loop) | Shows how to create a loop within a workflow | + +### Workflow Shared States + +| Sample | Concepts | +|--------|----------| +| [Shared States](./SharedStates) | Demonstrates shared states between executors for data sharing and coordination | + +### Conditional Edges + +| Sample | Concepts | +|--------|----------| +| [Edge Conditions](./ConditionalEdges/01_EdgeCondition) | Introduces conditional edges for dynamic routing based on executor outputs | +| [Switch-Case Routing](./ConditionalEdges/02_SwitchCase) | Extends conditional edges with switch-case routing for multiple paths | +| [Multi-Selection Routing](./ConditionalEdges/03_MultiSelection) | Demonstrates multi-selection routing where one executor can trigger multiple downstream executors | + +> These 3 samples build upon each other. It's recommended to explore them in sequence to fully grasp the concepts. + +### Declarative Workflows + +| Sample | Concepts | +|--------|----------| +| [DeclarativeWorkflow](./DeclarativeWorkflow) | Demonstrates execution of declartive workflows. | + +### Checkpointing + +| Sample | Concepts | +|--------|----------| +| [Checkpoint and Resume](./Checkpoint/CheckpointAndResume) | Introduces checkpoints for saving and restoring workflow state for time travel purposes | +| [Checkpoint and Rehydrate](./Checkpoint/CheckpointAndRehydrate) | Demonstrates hydrating a new workflow instance from a saved checkpoint | +| [Checkpoint with Human-in-the-Loop](./Checkpoint/CheckpointWithHumanInTheLoop) | Combines checkpointing with human-in-the-loop interactions | + +### Human-in-the-Loop + +| Sample | Concepts | +|--------|----------| +| [Basic Human-in-the-Loop](./HumanInTheLoop/HumanIntheLoopBasic) | Introduces human-in-the-loop interaction using input ports and external requests | diff --git a/dotnet/samples/GettingStarted/Workflow/Resources/Lorem_Ipsum.txt b/dotnet/samples/GettingStarted/Workflows/Resources/Lorem_Ipsum.txt similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Resources/Lorem_Ipsum.txt rename to dotnet/samples/GettingStarted/Workflows/Resources/Lorem_Ipsum.txt diff --git a/dotnet/samples/GettingStarted/Workflow/Resources/ambiguous_email.txt b/dotnet/samples/GettingStarted/Workflows/Resources/ambiguous_email.txt similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Resources/ambiguous_email.txt rename to dotnet/samples/GettingStarted/Workflows/Resources/ambiguous_email.txt diff --git a/dotnet/samples/GettingStarted/Workflow/Resources/email.txt b/dotnet/samples/GettingStarted/Workflows/Resources/email.txt similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Resources/email.txt rename to dotnet/samples/GettingStarted/Workflows/Resources/email.txt diff --git a/dotnet/samples/GettingStarted/Workflow/Resources/spam.txt b/dotnet/samples/GettingStarted/Workflows/Resources/spam.txt similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Resources/spam.txt rename to dotnet/samples/GettingStarted/Workflows/Resources/spam.txt diff --git a/dotnet/samples/GettingStarted/Workflow/SharedStates/Program.cs b/dotnet/samples/GettingStarted/Workflows/SharedStates/Program.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/SharedStates/Program.cs rename to dotnet/samples/GettingStarted/Workflows/SharedStates/Program.cs diff --git a/dotnet/samples/GettingStarted/Workflow/SharedStates/Resources.cs b/dotnet/samples/GettingStarted/Workflows/SharedStates/Resources.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/SharedStates/Resources.cs rename to dotnet/samples/GettingStarted/Workflows/SharedStates/Resources.cs diff --git a/dotnet/samples/GettingStarted/Workflow/SharedStates/SharedStates.csproj b/dotnet/samples/GettingStarted/Workflows/SharedStates/SharedStates.csproj similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/SharedStates/SharedStates.csproj rename to dotnet/samples/GettingStarted/Workflows/SharedStates/SharedStates.csproj diff --git a/dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj b/dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj new file mode 100644 index 0000000000..bbee070910 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/01_ExecutorsAndEdges/Program.cs b/dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/Program.cs similarity index 98% rename from dotnet/samples/GettingStarted/Workflow/Foundational/01_ExecutorsAndEdges/Program.cs rename to dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/Program.cs index 00682a60ef..85fd569605 100644 --- a/dotnet/samples/GettingStarted/Workflow/Foundational/01_ExecutorsAndEdges/Program.cs +++ b/dotnet/samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/Program.cs @@ -35,7 +35,7 @@ public static class Program Run run = await InProcessExecution.RunAsync(workflow, "Hello, World!"); foreach (WorkflowEvent evt in run.NewEvents) { - if (evt is ExecutorCompleteEvent executorComplete) + if (evt is ExecutorCompletedEvent executorComplete) { Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); } diff --git a/dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/02_Streaming.csproj b/dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/02_Streaming.csproj new file mode 100644 index 0000000000..bbee070910 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/02_Streaming.csproj @@ -0,0 +1,16 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/02_Streaming/Program.cs b/dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/Program.cs similarity index 95% rename from dotnet/samples/GettingStarted/Workflow/Foundational/02_Streaming/Program.cs rename to dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/Program.cs index 01bd694a5d..ce0db4a7fd 100644 --- a/dotnet/samples/GettingStarted/Workflow/Foundational/02_Streaming/Program.cs +++ b/dotnet/samples/GettingStarted/Workflows/_Foundational/02_Streaming/Program.cs @@ -34,9 +34,9 @@ public static class Program StreamingRun run = await InProcessExecution.StreamAsync(workflow, "Hello, World!"); await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) { - if (evt is ExecutorCompleteEvent executorComplete) + if (evt is ExecutorCompletedEvent executorCompleted) { - Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); + Console.WriteLine($"{executorCompleted.ExecutorId}: {executorCompleted.Data}"); } } } diff --git a/dotnet/samples/GettingStarted/Workflows/_Foundational/03_AgentsInWorkflows/03_AgentsInWorkflows.csproj b/dotnet/samples/GettingStarted/Workflows/_Foundational/03_AgentsInWorkflows/03_AgentsInWorkflows.csproj new file mode 100644 index 0000000000..b1f90ee600 --- /dev/null +++ b/dotnet/samples/GettingStarted/Workflows/_Foundational/03_AgentsInWorkflows/03_AgentsInWorkflows.csproj @@ -0,0 +1,24 @@ + + + + Exe + net9.0 + 12 + + enable + disable + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/dotnet/samples/GettingStarted/Workflow/Foundational/03_AgentsInWorkflows/Program.cs b/dotnet/samples/GettingStarted/Workflows/_Foundational/03_AgentsInWorkflows/Program.cs similarity index 100% rename from dotnet/samples/GettingStarted/Workflow/Foundational/03_AgentsInWorkflows/Program.cs rename to dotnet/samples/GettingStarted/Workflows/_Foundational/03_AgentsInWorkflows/Program.cs diff --git a/dotnet/samples/SemanticKernelMigration/NotMigratedUseCases/SemanticKernelBasic/.github/SemanticKernelToAgentFrameworkReport.md b/dotnet/samples/SemanticKernelMigration/NotMigratedUseCases/SemanticKernelBasic/.github/SemanticKernelToAgentFrameworkReport.md new file mode 100644 index 0000000000..e69de29bb2 diff --git a/dotnet/src/Microsoft.Agents.Orchestration/ConcurrentOrchestration.cs b/dotnet/src/Microsoft.Agents.Orchestration/ConcurrentOrchestration.cs index 670731efe8..3953b7fd0f 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/ConcurrentOrchestration.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/ConcurrentOrchestration.cs @@ -61,10 +61,13 @@ public partial class ConcurrentOrchestration : OrchestratingAgent this.ResumeAsync(messages, new AgentRunResponse?[this.Agents.Count], context, cancellationToken); /// - protected override Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken) + protected override Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken) { var state = checkpointState.Deserialize(OrchestrationJsonContext.Default.ConcurrentState) ?? throw new InvalidOperationException("The checkpoint state is invalid."); - return this.ResumeAsync(state.Messages, state.Completed, context, cancellationToken); + + // Append the new messages to the checkpoint state + List allMessages = [.. state.Messages, .. newMessages]; + return this.ResumeAsync(allMessages, state.Completed, context, cancellationToken); } /// diff --git a/dotnet/src/Microsoft.Agents.Orchestration/GroupChat/GroupChatOrchestration.cs b/dotnet/src/Microsoft.Agents.Orchestration/GroupChat/GroupChatOrchestration.cs index 46f258715d..0f0973e768 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/GroupChat/GroupChatOrchestration.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/GroupChat/GroupChatOrchestration.cs @@ -51,10 +51,14 @@ public sealed partial class GroupChatOrchestration : OrchestratingAgent } /// - protected override Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken) + protected override Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken) { var state = checkpointState.Deserialize(OrchestrationJsonContext.Default.GroupChatState) ?? throw new InvalidOperationException("The checkpoint state is invalid."); - return this.ResumeAsync(state.AllMessages, state.OriginalMessageCount, context, cancellationToken); + + // Append the new messages to the checkpoint state + List allMessages = [.. state.AllMessages, .. newMessages]; + + return this.ResumeAsync(allMessages, allMessages.Count, context, cancellationToken); } private async Task ResumeAsync( diff --git a/dotnet/src/Microsoft.Agents.Orchestration/Handoffs/HandoffOrchestration.cs b/dotnet/src/Microsoft.Agents.Orchestration/Handoffs/HandoffOrchestration.cs index d1c9c5568e..8ef64910e7 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/Handoffs/HandoffOrchestration.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/Handoffs/HandoffOrchestration.cs @@ -52,26 +52,28 @@ public sealed partial class HandoffOrchestration : OrchestratingAgent } /// - protected override Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken) + protected override Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken) { var state = checkpointState.Deserialize(OrchestrationJsonContext.Default.HandoffState) ?? throw new InvalidOperationException("The checkpoint state is invalid."); AIAgent? nextAgent = null; - foreach (var agent in this.Agents) + if (state.NextAgent is null) { - if (agent.Id == state.NextAgent) + nextAgent = this._handoffs.InitialAgent; + } + else + { + nextAgent = this.Agents.FirstOrDefault(a => a.Id == state.NextAgent); + if (nextAgent is null) { - nextAgent = agent; - break; + Throw.InvalidOperationException($"The next agent '{state.NextAgent}' is not defined in the orchestration."); } } - if (nextAgent is null) - { - Throw.InvalidOperationException($"The next agent '{state.NextAgent}' is not defined in the orchestration."); - } + // Append the new messages to the checkpoint state + List allMessages = [.. state.AllMessages, .. newMessages]; - return this.ResumeAsync(nextAgent, state.AllMessages, state.OriginalMessageCount, context, cancellationToken); + return this.ResumeAsync(nextAgent, allMessages, allMessages.Count, context, cancellationToken); } /// @@ -144,7 +146,7 @@ public sealed partial class HandoffOrchestration : OrchestratingAgent private static void RemoveHandoffFunctionCalls(AgentRunResponse response, List handoffTools) { HashSet? removeToolNames = null; - HashSet? callIds = null; + HashSet? handoffCallIds = null; foreach (var message in response.Messages) { @@ -153,23 +155,22 @@ public sealed partial class HandoffOrchestration : OrchestratingAgent if (message.Contents[i] is FunctionCallContent fcc) { removeToolNames ??= [.. handoffTools.Select(t => t.Name)]; - (callIds ??= new()).Add(fcc.CallId); - if (removeToolNames.Contains(fcc.Name)) { + (handoffCallIds ??= []).Add(fcc.CallId); message.Contents.RemoveAt(i); } } } } - if (callIds is not null) + if (handoffCallIds is not null) { foreach (var message in response.Messages) { for (int i = message.Contents.Count - 1; i >= 0; i--) { - if (message.Contents[i] is FunctionResultContent frc && callIds.Contains(frc.CallId)) + if (message.Contents[i] is FunctionResultContent frc && handoffCallIds.Contains(frc.CallId)) { message.Contents.RemoveAt(i); } diff --git a/dotnet/src/Microsoft.Agents.Orchestration/Microsoft.Agents.Orchestration.csproj b/dotnet/src/Microsoft.Agents.Orchestration/Microsoft.Agents.Orchestration.csproj index de550fc682..9f92f7516a 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/Microsoft.Agents.Orchestration.csproj +++ b/dotnet/src/Microsoft.Agents.Orchestration/Microsoft.Agents.Orchestration.csproj @@ -5,6 +5,7 @@ $(ProjectsDebugTargetFrameworks) Microsoft.Agents.Orchestration alpha + $(NoWarn);MEAI001 diff --git a/dotnet/src/Microsoft.Agents.Orchestration/OrchestratingAgent.cs b/dotnet/src/Microsoft.Agents.Orchestration/OrchestratingAgent.cs index 733003d8c0..8da88c20bc 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/OrchestratingAgent.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/OrchestratingAgent.cs @@ -2,6 +2,7 @@ using System; using System.Collections.Generic; +using System.Linq; using System.Runtime.CompilerServices; using System.Text.Json; using System.Threading; @@ -75,11 +76,7 @@ public abstract partial class OrchestratingAgent : AIAgent throw new InvalidOperationException("An agent service managed thread is not supported by this agent."); } - List messagesList = []; - await foreach (var threadMessage in thread.GetMessagesAsync(cancellationToken).ConfigureAwait(false)) - { - messagesList.Add(threadMessage); - } + List messagesList = (await thread.MessageStore.GetMessagesAsync(cancellationToken).ConfigureAwait(false)).ToList(); messagesList.AddRange(messages); messages = messagesList; } @@ -135,7 +132,7 @@ public abstract partial class OrchestratingAgent : AIAgent JsonElement? checkpoint = await this.ReadCheckpointAsync(context, cancellationToken).ConfigureAwait(false); Task completion = checkpoint is null ? this.RunCoreAsync(messages, context, cancellationToken) : - this.ResumeCoreAsync(checkpoint.Value, context, cancellationToken); + this.ResumeCoreAsync(checkpoint.Value, messages, context, cancellationToken); if (logger.IsEnabled(LogLevel.Trace)) { @@ -157,9 +154,10 @@ public abstract partial class OrchestratingAgent : AIAgent /// Resumes processing of the orchestration. /// /// The last checkpoint state available from which to resume the operation. + /// The new messages to be processed in addition to the checkpoint state. /// The context for this operation. /// A cancellation token that can be used to cancel the operation. - protected abstract Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken); + protected abstract Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken); /// /// Runs the agent with input messages and respond with both streamed and regular messages. diff --git a/dotnet/src/Microsoft.Agents.Orchestration/OrchestrationJsonContext.cs b/dotnet/src/Microsoft.Agents.Orchestration/OrchestrationJsonContext.cs index 1ef15b385a..5066f3e6dc 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/OrchestrationJsonContext.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/OrchestrationJsonContext.cs @@ -1,5 +1,6 @@ // Copyright (c) Microsoft. All rights reserved. +using System.Text.Json; using System.Text.Json.Serialization; namespace Microsoft.Agents.Orchestration; @@ -8,4 +9,5 @@ namespace Microsoft.Agents.Orchestration; [JsonSerializable(typeof(ConcurrentOrchestration.ConcurrentState))] [JsonSerializable(typeof(GroupChatOrchestration.GroupChatState))] [JsonSerializable(typeof(HandoffOrchestration.HandoffState))] +[JsonSerializable(typeof(JsonElement))] internal sealed partial class OrchestrationJsonContext : JsonSerializerContext; diff --git a/dotnet/src/Microsoft.Agents.Orchestration/SequentialOrchestration.cs b/dotnet/src/Microsoft.Agents.Orchestration/SequentialOrchestration.cs index 6f79bb4129..1c113cfbde 100644 --- a/dotnet/src/Microsoft.Agents.Orchestration/SequentialOrchestration.cs +++ b/dotnet/src/Microsoft.Agents.Orchestration/SequentialOrchestration.cs @@ -32,10 +32,13 @@ public sealed partial class SequentialOrchestration : OrchestratingAgent this.ResumeAsync(0, messages, context, cancellationToken); /// - protected override Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken) + protected override Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken) { var state = checkpointState.Deserialize(OrchestrationJsonContext.Default.SequentialState) ?? throw new InvalidOperationException("The checkpoint state is invalid."); - return this.ResumeAsync(state.Index, state.Messages, context, cancellationToken); + + // Append the new messages to the checkpoint state + List allMessages = [.. state.Messages, .. newMessages]; + return this.ResumeAsync(state.Index, allMessages, context, cancellationToken); } /// diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/ConversationUpdateEvent.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/ConversationUpdateEvent.cs deleted file mode 100644 index 7984ffcd11..0000000000 --- a/dotnet/src/Microsoft.Agents.Workflows.Declarative/ConversationUpdateEvent.cs +++ /dev/null @@ -1,14 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -namespace Microsoft.Agents.Workflows.Declarative; - -/// -/// Event that represents a message produced by a declarative workflow. -/// -public class ConversationUpdateEvent(string executorid, string conversationId) : ExecutorEvent(executorid, conversationId) -{ - /// - /// The conversation ID associated with the workflow. - /// - public string ConversationId { get; } = conversationId; -} diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/DeclarativeWorkflowEvents.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/DeclarativeWorkflowEvents.cs new file mode 100644 index 0000000000..74970f62f1 --- /dev/null +++ b/dotnet/src/Microsoft.Agents.Workflows.Declarative/DeclarativeWorkflowEvents.cs @@ -0,0 +1,64 @@ +// Copyright (c) Microsoft. All rights reserved. + +using Microsoft.Agents.Workflows.Declarative.Extensions; +using Microsoft.Bot.ObjectModel; + +namespace Microsoft.Agents.Workflows.Declarative; + +/// +/// Event that broadcasts the conversation identifier. +/// +public class ConversationUpdateEvent(string executorid, string conversationId) : ExecutorEvent(executorid, conversationId) +{ + /// + /// The conversation ID associated with the workflow. + /// + public string ConversationId { get; } = conversationId; +} + +/// +/// Event that indicates a declarative action has been invoked. +/// +public class DeclarativeActionInvokeEvent(string actionId, DialogAction action, string? priorActionId) : WorkflowEvent(action) +{ + /// + /// The declarative action id. + /// + public string ActionId => actionId; + + /// + /// The declarative action type name. + /// + public string ActionType => action.GetType().Name; + + /// + /// Identifier of the parent action. + /// + public string? ParentActionId => action.GetParentId(); + + /// + /// Identifier of the previous action. + /// + public string? PriorActionId => priorActionId; +} + +/// +/// Event that indicates a declarative action has completed. +/// +public class DeclarativeActionCompleteEvent(string actionId, DialogAction action) : WorkflowEvent(action) +{ + /// + /// The declarative action identifier. + /// + public string ActionId => actionId; + + /// + /// The declarative action type name. + /// + public string ActionType => action.GetType().Name; + + /// + /// Identifier of the parent action. + /// + public string? ParentActionId => action.GetParentId(); +} diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeActionExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeActionExecutor.cs index 0d0138f261..2fa157bcca 100644 --- a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeActionExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeActionExecutor.cs @@ -7,7 +7,6 @@ using System.Diagnostics; using System.Threading; using System.Threading.Tasks; using Microsoft.Agents.Workflows.Declarative.Extensions; -using Microsoft.Agents.Workflows.Reflection; using Microsoft.Bot.ObjectModel; using Microsoft.Extensions.Logging; using Microsoft.Extensions.Logging.Abstractions; @@ -25,9 +24,7 @@ internal abstract class DeclarativeActionExecutor(TAction model, Declar public new TAction Model => (TAction)base.Model; } -internal abstract class WorkflowActionExecutor : - ReflectingExecutor, - IMessageHandler +internal abstract class WorkflowActionExecutor : Executor { public const string RootActionId = "(root)"; @@ -60,8 +57,10 @@ internal abstract class WorkflowActionExecutor : protected DeclarativeWorkflowState State { get; } + protected virtual bool IsDiscreteAction => true; + /// - public async ValueTask HandleAsync(DeclarativeExecutorResult message, IWorkflowContext context) + public override async ValueTask HandleAsync(DeclarativeExecutorResult message, IWorkflowContext context) { if (this.Model.Disabled) { @@ -69,6 +68,8 @@ internal abstract class WorkflowActionExecutor : return; } + await this.RaiseInvocationEventAsync(context, message.ExecutorId).ConfigureAwait(false); + await this.State.RestoreAsync(context, default).ConfigureAwait(false); try @@ -87,6 +88,13 @@ internal abstract class WorkflowActionExecutor : Debug.WriteLine($"ERROR [{this.Id}] {exception.GetType().Name}\n{exception.Message}"); throw new DeclarativeActionException($"Unhandled workflow failure - #{this.Id} ({this.Model.GetType().Name})", exception); } + finally + { + if (this.IsDiscreteAction) + { + await this.RaiseCompletionEventAsync(context).ConfigureAwait(false); + } + } } protected abstract ValueTask ExecuteAsync(IWorkflowContext context, CancellationToken cancellationToken = default); @@ -117,4 +125,8 @@ internal abstract class WorkflowActionExecutor : string message = $"Unexpected workflow failure during {this.Model.GetType().Name} [{this.Id}]: {text}"; return exception is null ? new(message) : new(message, exception); } + + protected ValueTask RaiseInvocationEventAsync(IWorkflowContext context, string? priorEventId = null) => context.AddEventAsync(new DeclarativeActionInvokeEvent(this.Id, this.Model, priorEventId)); + + protected ValueTask RaiseCompletionEventAsync(IWorkflowContext context) => context.AddEventAsync(new DeclarativeActionCompleteEvent(this.Id, this.Model)); } diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeWorkflowExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeWorkflowExecutor.cs index 573e931f9c..f65bb7f5f6 100644 --- a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeWorkflowExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DeclarativeWorkflowExecutor.cs @@ -3,7 +3,6 @@ using System; using System.Threading.Tasks; using Microsoft.Agents.Workflows.Declarative.PowerFx; -using Microsoft.Agents.Workflows.Reflection; using Microsoft.Extensions.AI; namespace Microsoft.Agents.Workflows.Declarative.Interpreter; @@ -11,12 +10,14 @@ namespace Microsoft.Agents.Workflows.Declarative.Interpreter; /// /// The root executor for a declarative workflow. /// -internal sealed class DeclarativeWorkflowExecutor(string workflowId, DeclarativeWorkflowState state, Func inputTransform) : - ReflectingExecutor>(workflowId), - IMessageHandler +internal sealed class DeclarativeWorkflowExecutor( + string workflowId, + DeclarativeWorkflowState state, + Func inputTransform) : + Executor(workflowId) where TInput : notnull { - public async ValueTask HandleAsync(TInput message, IWorkflowContext context) + public override async ValueTask HandleAsync(TInput message, IWorkflowContext context) { ChatMessage input = inputTransform.Invoke(message); await state.SetLastMessageAsync(context, input).ConfigureAwait(false); diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DelegateActionExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DelegateActionExecutor.cs index 7bcf0b9868..59afb516ff 100644 --- a/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DelegateActionExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows.Declarative/Interpreter/DelegateActionExecutor.cs @@ -2,13 +2,12 @@ using System.Threading; using System.Threading.Tasks; -using Microsoft.Agents.Workflows.Reflection; namespace Microsoft.Agents.Workflows.Declarative.Interpreter; internal delegate ValueTask DelegateAction(IWorkflowContext context, CancellationToken cancellationToken); -internal sealed class DelegateActionExecutor : ReflectingExecutor, IMessageHandler +internal sealed class DelegateActionExecutor : Executor { private readonly DelegateAction? _action; @@ -18,7 +17,7 @@ internal sealed class DelegateActionExecutor : ReflectingExecutor this.ContinuationFor(parentId, parentId); + private string ContinuationFor(string parentId, DelegateAction? stepAction = null) => this.ContinuationFor(parentId, parentId, stepAction); - private string ContinuationFor(string actionId, string parentId) + private string ContinuationFor(string actionId, string parentId, DelegateAction? stepAction = null) { actionId = PostId(actionId); - this._workflowModel.AddNode(this.CreateStep(actionId), parentId); + this._workflowModel.AddNode(this.CreateStep(actionId, stepAction), parentId); return actionId; } diff --git a/dotnet/src/Microsoft.Agents.Workflows.Declarative/ObjectModel/ConditionGroupExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows.Declarative/ObjectModel/ConditionGroupExecutor.cs index a3cbfb9ff4..b8d1662210 100644 --- a/dotnet/src/Microsoft.Agents.Workflows.Declarative/ObjectModel/ConditionGroupExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows.Declarative/ObjectModel/ConditionGroupExecutor.cs @@ -31,6 +31,8 @@ internal sealed class ConditionGroupExecutor : DeclarativeActionExecutor false; + public bool IsMatch(ConditionItem conditionItem, object? result) { if (result is not DeclarativeExecutorResult message) @@ -72,4 +74,9 @@ internal sealed class ConditionGroupExecutor : DeclarativeActionExecutor public bool HasValue { get; private set; } + protected override bool IsDiscreteAction => false; + protected override async ValueTask ExecuteAsync(IWorkflowContext context, CancellationToken cancellationToken) { this._index = 0; @@ -78,10 +80,17 @@ internal sealed class ForeachExecutor : DeclarativeActionExecutor public async ValueTask ResetAsync(IWorkflowContext context, CancellationToken cancellationToken) { - this.State.Reset(Throw.IfNull(this.Model.Value)); - if (this.Model.Index is not null) + try { - this.State.Reset(this.Model.Index); + this.State.Reset(Throw.IfNull(this.Model.Value)); + if (this.Model.Index is not null) + { + this.State.Reset(this.Model.Index); + } + } + finally + { + await this.RaiseCompletionEventAsync(context).ConfigureAwait(false); } } } diff --git a/dotnet/src/Microsoft.Agents.Workflows/Config.cs b/dotnet/src/Microsoft.Agents.Workflows/Config.cs new file mode 100644 index 0000000000..cdd2ce1534 --- /dev/null +++ b/dotnet/src/Microsoft.Agents.Workflows/Config.cs @@ -0,0 +1,32 @@ +// Copyright (c) Microsoft. All rights reserved. + +namespace Microsoft.Agents.Workflows; + +/// +/// Configuration for an object with a string identifier. For example, object. +/// +/// A unique identifier for the configurable object. +public class Config(string? id = null) +{ + /// + /// A unique identifier for the configurable object. + /// + /// + /// If not provided, the configured object will generate its own identifier. + /// + public string? Id => id; +} + +/// +/// Configuration for an object with a string identifier and options of type . +/// +/// The type of options for the configurable object. +/// The options for the configurable object. +/// A unique identifier for the configurable object. +public class Config(TOptions? options = default, string? id = null) : Config(id) +{ + /// + /// Options for the configured object. + /// + public TOptions? Options => options; +} diff --git a/dotnet/src/Microsoft.Agents.Workflows/ConfigurationExtensions.cs b/dotnet/src/Microsoft.Agents.Workflows/ConfigurationExtensions.cs new file mode 100644 index 0000000000..c3309116c6 --- /dev/null +++ b/dotnet/src/Microsoft.Agents.Workflows/ConfigurationExtensions.cs @@ -0,0 +1,32 @@ +// Copyright (c) Microsoft. All rights reserved. + +namespace Microsoft.Agents.Workflows; + +/// +/// Extensions methods for creating Configured objects +/// +public static class ConfigurationExtensions +{ + /// + /// Creates a new configuration that treats the subject as its base type, allowing configuration to be applied at + /// the parent type level. + /// + /// The type of the original subject being configured. Must inherit from or implement TParent. + /// The base type or interface to which the configuration will be upcast. + /// The existing configuration for the subject type to be upcast to its parent type. Cannot be null. + /// A new instance that applies the original configuration logic to the parent type. + public static Configured Super(this Configured configured) where TSubject : TParent + => new(async config => await configured.FactoryAsync(config).ConfigureAwait(false), configured.Id, configured.Raw); + + /// + /// Creates a new configuration that treats the subject as its base type, allowing configuration to be applied at + /// the parent type level. + /// + /// The type of the original subject being configured. Must inherit from or implement TParent. + /// The base type or interface to which the configuration will be upcast. + /// The type of configuration options for the original subject being configured. + /// The existing configuration for the subject type to be upcast to its parent type. Cannot be null. + /// A new instance that applies the original configuration logic to the parent type. + public static Configured Super(this Configured configured) where TSubject : TParent + => configured.Memoize().Super(); +} diff --git a/dotnet/src/Microsoft.Agents.Workflows/Configured.cs b/dotnet/src/Microsoft.Agents.Workflows/Configured.cs new file mode 100644 index 0000000000..d88da9277f --- /dev/null +++ b/dotnet/src/Microsoft.Agents.Workflows/Configured.cs @@ -0,0 +1,153 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading.Tasks; + +namespace Microsoft.Agents.Workflows; + +/// +/// Helper methods for creating instances. +/// +public static class Configured +{ + /// + /// Creates a instance from an existing subject instance. + /// + /// + /// The subject instance. If the subject implements , its ID will be used + /// and checked against the provided ID (if any). + /// + /// + /// A unique identifier for the configured subject. This is required if the subject does not implement + /// + /// + /// + /// The raw representation of the subject instance. + /// + /// + public static Configured FromInstance(TSubject subject, string? id = null, object? raw = null) + { + if (subject is IIdentified identified) + { + if (id != null && identified.Id != id) + { + throw new ArgumentException($"Provided ID '{id}' does not match subject's ID '{identified.Id}'.", nameof(id)); + } + + return new Configured((_) => new(subject), id: identified.Id, raw: raw ?? subject); + } + + if (id == null) + { + throw new ArgumentNullException(nameof(id), "ID must be provided when the subject does not implement IIdentified."); + } + + return new Configured((_) => new(subject), id, raw: raw ?? subject); + } +} + +/// +/// A representation of a preconfigured, lazy-instantiatable instance of . +/// +/// The type of the preconfigured subject. +/// A factory to intantiate the subject when desired. +/// The unique identifier for the configured subject. +/// +public class Configured(Func> factoryAsync, string id, object? raw = null) +{ + /// + /// The raw representation of the configured object, if any. + /// + public object? Raw => raw; + + /// + /// Gets the configured identifier for the subject. + /// + public string Id => id; + + /// + /// Gets the factory function to create an instance of given a . + /// + public Func> FactoryAsync => factoryAsync; + + /// + /// The configuration for this configured instance. + /// + public Config Configuration => new(this.Id); + + /// + /// Gets a "partially" applied factory function that only requires no parameters to create an instance of + /// with the provided instance. + /// + internal Func> BoundFactoryAsync => () => this.FactoryAsync(this.Configuration); +} + +/// +/// A representation of a preconfigured, lazy-instantiatable instance of . +/// +/// The type of the preconfigured subject. +/// The type of configuration options for the preconfigured subject. +/// A factory to intantiate the subject when desired. +/// The unique identifier for the configured subject. +/// Additional configuration options for the subject. +/// +public class Configured(Func, ValueTask> factoryAsync, string id, TOptions? options = default, object? raw = null) +{ + /// + /// The raw representation of the configured object, if any. + /// + public object? Raw => raw; + + /// + /// Gets the configured identifier for the subject. + /// + public string Id => id; + + /// + /// Gets the options associated with this instance. + /// + public TOptions? Options => options; + + /// + /// Gets the factory function to create an instance of given a . + /// + public Func, ValueTask> FactoryAsync => factoryAsync; + + /// + /// The configuration for this configured instance. + /// + public Config Configuration => new(this.Options, this.Id); + + /// + /// Gets a "partially" applied factory function that only requires no parameters to create an instance of + /// with the provided instance. + /// + internal Func> BoundFactoryAsync => () => this.CreateValidatingMemoizedFactory()(this.Configuration); + + private Func> CreateValidatingMemoizedFactory() + { + return FactoryAsync; + + async ValueTask FactoryAsync(Config configuration) + { + if (this.Id != configuration.Id) + { + throw new InvalidOperationException($"Requested instance ID '{configuration.Id}' does not match configured ID '{this.Id}'."); + } + + TSubject subject = await this.FactoryAsync(this.Configuration).ConfigureAwait(false); + + if (this.Id != null && subject is IIdentified identified && identified.Id != this.Id) + { + throw new InvalidOperationException($"Created instance ID '{identified.Id}' does not match configured ID '{this.Id}'."); + } + + return subject; + } + } + + /// + /// Memoizes and erases the typed configuration options for the subject. + /// + public Configured Memoize() => new(this.CreateValidatingMemoizedFactory(), this.Id); +} diff --git a/dotnet/src/Microsoft.Agents.Workflows/Execution/RunnerStateData.cs b/dotnet/src/Microsoft.Agents.Workflows/Execution/RunnerStateData.cs index 9677ce6e57..877518718a 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/Execution/RunnerStateData.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/Execution/RunnerStateData.cs @@ -5,8 +5,9 @@ using Microsoft.Agents.Workflows.Checkpointing; namespace Microsoft.Agents.Workflows.Execution; -internal class RunnerStateData(Dictionary> queuedMessages, List outstandingRequests) +internal class RunnerStateData(HashSet instantiatedExecutors, Dictionary> queuedMessages, List outstandingRequests) { + public HashSet InstantiatedExecutors { get; } = instantiatedExecutors; public Dictionary> QueuedMessages { get; } = queuedMessages; public List OutstandingRequests { get; } = outstandingRequests; } diff --git a/dotnet/src/Microsoft.Agents.Workflows/Executor.cs b/dotnet/src/Microsoft.Agents.Workflows/Executor.cs index 97519ec0ad..8b813c08c6 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/Executor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/Executor.cs @@ -7,6 +7,7 @@ using System.Reflection; using System.Threading; using System.Threading.Tasks; using Microsoft.Agents.Workflows.Execution; +using Microsoft.Agents.Workflows.Reflection; namespace Microsoft.Agents.Workflows; @@ -21,20 +22,17 @@ public abstract class Executor : IIdentified /// public string Id { get; } + private readonly ExecutorOptions _options; + /// /// Initialize the executor with a unique identifier /// - /// A optional unique identifier for the executor. If null, a type-tagged - /// UUID will be generated. - protected Executor(string? id = null) : this(ExecutorOptions.Default, id) - { - } - - private readonly ExecutorOptions _options; - internal Executor(ExecutorOptions options, string? id = null) + /// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. + /// Configuration options for the executor. If null, default options will be used. + protected Executor(string? id = null, ExecutorOptions? options = null) { this.Id = id ?? $"{this.GetType().Name}/{Guid.NewGuid():N}"; - this._options = options; + this._options = options ?? ExecutorOptions.Default; } /// @@ -69,7 +67,7 @@ public abstract class Executor : IIdentified /// An exception is generated while handling the message. public async ValueTask ExecuteAsync(object message, Type messageType, IWorkflowContext context) { - await context.AddEventAsync(new ExecutorInvokeEvent(this.Id, message)).ConfigureAwait(false); + await context.AddEventAsync(new ExecutorInvokedEvent(this.Id, message)).ConfigureAwait(false); CallResult? result = await this.Router.RouteMessageAsync(message, context, requireRoute: true) .ConfigureAwait(false); @@ -77,7 +75,7 @@ public abstract class Executor : IIdentified ExecutorEvent executionResult; if (result == null || result.IsSuccess) { - executionResult = new ExecutorCompleteEvent(this.Id, result?.Result); + executionResult = new ExecutorCompletedEvent(this.Id, result?.Result); } else { @@ -144,3 +142,43 @@ public abstract class Executor : IIdentified /// public bool CanHandle(Type messageType) => this.Router.CanHandle(messageType); } + +/// +/// Provides a simple executor implementation that uses a single message handler function to process incoming messages. +/// +/// The type of input message. +/// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. +/// Configuration options for the executor. If null, default options will be used. +public abstract class Executor(string? id = null, ExecutorOptions? options = null) + : Executor(id, options), IMessageHandler +{ + /// + protected override RouteBuilder ConfigureRoutes(RouteBuilder routeBuilder) + { + return routeBuilder.AddHandler(this.HandleAsync); + } + + /// + public abstract ValueTask HandleAsync(TInput message, IWorkflowContext context); +} + +/// +/// Provides a simple executor implementation that uses a single message handler function to process incoming messages. +/// +/// The type of input message. +/// The type of output message. +/// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. +/// Configuration options for the executor. If null, default options will be used. +public abstract class Executor(string? id = null, ExecutorOptions? options = null) + : Executor(id, options ?? ExecutorOptions.Default), + IMessageHandler +{ + /// + protected override RouteBuilder ConfigureRoutes(RouteBuilder routeBuilder) + { + return routeBuilder.AddHandler(this.HandleAsync); + } + + /// + public abstract ValueTask HandleAsync(TInput message, IWorkflowContext context); +} diff --git a/dotnet/src/Microsoft.Agents.Workflows/ExecutorCompleteEvent.cs b/dotnet/src/Microsoft.Agents.Workflows/ExecutorCompletedEvent.cs similarity index 76% rename from dotnet/src/Microsoft.Agents.Workflows/ExecutorCompleteEvent.cs rename to dotnet/src/Microsoft.Agents.Workflows/ExecutorCompletedEvent.cs index 01a4de058e..43472af7e0 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/ExecutorCompleteEvent.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/ExecutorCompletedEvent.cs @@ -7,4 +7,4 @@ namespace Microsoft.Agents.Workflows; /// /// The unique identifier of the executor that has completed. /// The result produced by the executor upon completion, or null if no result is available. -public sealed class ExecutorCompleteEvent(string executorId, object? result) : ExecutorEvent(executorId, data: result); +public sealed class ExecutorCompletedEvent(string executorId, object? result) : ExecutorEvent(executorId, data: result); diff --git a/dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokeEvent.cs b/dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokedEvent.cs similarity index 73% rename from dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokeEvent.cs rename to dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokedEvent.cs index 022245924b..444da140e3 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokeEvent.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/ExecutorInvokedEvent.cs @@ -7,4 +7,4 @@ namespace Microsoft.Agents.Workflows; /// /// The unique identifier of the executor being invoked. /// The invocation message. -public sealed class ExecutorInvokeEvent(string executorId, object message) : ExecutorEvent(executorId, data: message); +public sealed class ExecutorInvokedEvent(string executorId, object message) : ExecutorEvent(executorId, data: message); diff --git a/dotnet/src/Microsoft.Agents.Workflows/ExecutorIsh.cs b/dotnet/src/Microsoft.Agents.Workflows/ExecutorIsh.cs index dd026f541d..53a2fb201f 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/ExecutorIsh.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/ExecutorIsh.cs @@ -1,12 +1,86 @@ // Copyright (c) Microsoft. All rights reserved. using System; +using System.Threading; +using System.Threading.Tasks; using Microsoft.Agents.Workflows.Specialized; using Microsoft.Extensions.AI.Agents; using Microsoft.Shared.Diagnostics; namespace Microsoft.Agents.Workflows; +/// +/// Extension methods for configuring executors and functions as instances. +/// +public static class ExecutorIshConfigurationExtensions +{ + /// + /// Configures a factory method for creating an of type , with + /// the specified id and options. + /// + /// + /// Although this will generally result in a delay-instantiated once messages are available + /// for it, if this is used as a start node of a typed via , + /// it will be instantiated as part of the workflow's construction, to validate that its input type matches the + /// demanded TInput. + /// + /// The type of the resulting executor + /// The type of options object to be passed to the factory method. + /// The factory method. + /// An id for the executor to be instantiated. + /// An optional parameter specifying the options. + /// An ExecutorIsh instance that resolves to the result of the factory call when messages get sent to it. + public static ExecutorIsh ConfigureFactory(this Func, ValueTask> factoryAsync, string id, TOptions? options = null) + where TExecutor : Executor + where TOptions : ExecutorOptions + { + Configured configured = new(factoryAsync, id, options); + + return new ExecutorIsh(configured.Super(), typeof(TExecutor), ExecutorIsh.Type.Executor); + } + + private static ExecutorIsh ToExecutorIsh(this FunctionExecutor executor, Delegate raw) + { + return new ExecutorIsh(Configured.FromInstance(executor, raw: raw) + .Super, Executor>(), + typeof(FunctionExecutor), + ExecutorIsh.Type.Function); + } + + private static ExecutorIsh ToExecutorIsh(this FunctionExecutor executor, Delegate raw) + { + return new ExecutorIsh(Configured.FromInstance(executor, raw: raw) + .Super, Executor>(), + typeof(FunctionExecutor), + ExecutorIsh.Type.Function); + } + + /// + /// Configures a function-based asynchronous message handler as an executor with the specified identifier and + /// options. + /// + /// The type of input message. + /// A delegate that defines the asynchronous function to execute for each input message. + /// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. + /// Configuration options for the executor. If null, default options will be used. + /// An ExecutorIsh instance that wraps the provided asynchronous message handler and configuration. + public static ExecutorIsh AsExecutor(this Func messageHandlerAsync, string id, ExecutorOptions? options = null) + => new FunctionExecutor(messageHandlerAsync, id, options).ToExecutorIsh(messageHandlerAsync); + + /// + /// Configures a function-based asynchronous message handler as an executor with the specified identifier and + /// options. + /// + /// The type of input message. + /// The type of output message. + /// A delegate that defines the asynchronous function to execute for each input message. + /// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. + /// Configuration options for the executor. If null, default options will be used. + /// An ExecutorIsh instance that wraps the provided asynchronous message handler and configuration. + public static ExecutorIsh AsExecutor(this Func> messageHandlerAsync, string id, ExecutorOptions? options = null) + => new FunctionExecutor(messageHandlerAsync, id, options).ToExecutorIsh(messageHandlerAsync); +} + /// /// A tagged union representing an object that can function like an in a , /// or a reference to one by ID. @@ -31,6 +105,10 @@ public sealed class ExecutorIsh : /// Executor, /// + /// A function delegate to be wrapped as an executor. + /// + Function, + /// /// An for servicing external requests. /// InputPort, @@ -46,7 +124,10 @@ public sealed class ExecutorIsh : public Type ExecutorType { get; init; } private readonly string? _idValue; - private readonly Executor? _executorValue; + + private readonly Configured? _configuredExecutor; + private readonly System.Type? _configuredExecutorType; + internal readonly InputPort? _inputPortValue; private readonly AIAgent? _aiAgentValue; @@ -60,6 +141,13 @@ public sealed class ExecutorIsh : this._idValue = Throw.IfNull(id); } + internal ExecutorIsh(Configured configured, System.Type configuredExecutorType, ExecutorIsh.Type type) + { + this.ExecutorType = type; + this._configuredExecutor = configured; + this._configuredExecutorType = configuredExecutorType; + } + /// /// Initializes a new instance of the ExecutorIsh class using the specified executor. /// @@ -67,7 +155,8 @@ public sealed class ExecutorIsh : public ExecutorIsh(Executor executor) { this.ExecutorType = Type.Executor; - this._executorValue = Throw.IfNull(executor); + this._configuredExecutor = Configured.FromInstance(Throw.IfNull(executor)); + this._configuredExecutorType = executor.GetType(); } /// @@ -96,18 +185,20 @@ public sealed class ExecutorIsh : public string Id => this.ExecutorType switch { Type.Unbound => this._idValue ?? throw new InvalidOperationException("This ExecutorIsh is unbound and has no ID."), - Type.Executor => this._executorValue!.Id, + Type.Executor => this._configuredExecutor!.Id, Type.InputPort => this._inputPortValue!.Id, Type.Agent => this._aiAgentValue!.Id, + Type.Function => this._configuredExecutor!.Id, _ => throw new InvalidOperationException($"Unknown ExecutorIsh type: {this.ExecutorType}") }; internal object? RawData => this.ExecutorType switch { Type.Unbound => this._idValue, - Type.Executor => this._executorValue, + Type.Executor => this._configuredExecutor!.Raw ?? this._configuredExecutor, Type.InputPort => this._inputPortValue, Type.Agent => this._aiAgentValue, + Type.Function => this._configuredExecutor!.Raw ?? this._configuredExecutor, _ => throw new InvalidOperationException($"Unknown ExecutorIsh type: {this.ExecutorType}") }; @@ -122,9 +213,10 @@ public sealed class ExecutorIsh : private System.Type RuntimeType => this.ExecutorType switch { Type.Unbound => throw new InvalidOperationException($"ExecutorIsh with ID '{this.Id}' is unbound."), - Type.Executor => this._executorValue!.GetType(), + Type.Executor => this._configuredExecutorType!, Type.InputPort => typeof(RequestInfoExecutor), Type.Agent => typeof(AIAgentHostExecutor), + Type.Function => this._configuredExecutorType!, _ => throw new InvalidOperationException($"Unknown ExecutorIsh type: {this.ExecutorType}") }; @@ -132,12 +224,13 @@ public sealed class ExecutorIsh : /// Gets an that can be used to obtain an instance /// corresponding to this . /// - private Func ExecutorProvider => this.ExecutorType switch + private Func> ExecutorProvider => this.ExecutorType switch { Type.Unbound => throw new InvalidOperationException($"Executor with ID '{this.Id}' is unbound."), - Type.Executor => () => this._executorValue!, - Type.InputPort => () => new RequestInfoExecutor(this._inputPortValue!), - Type.Agent => () => new AIAgentHostExecutor(this._aiAgentValue!), + Type.Executor => this._configuredExecutor!.BoundFactoryAsync, + Type.InputPort => () => new(new RequestInfoExecutor(this._inputPortValue!)), + Type.Agent => () => new(new AIAgentHostExecutor(this._aiAgentValue!)), + Type.Function => this._configuredExecutor!.BoundFactoryAsync, _ => throw new InvalidOperationException($"Unknown ExecutorIsh type: {this.ExecutorType}") }; @@ -225,9 +318,10 @@ public sealed class ExecutorIsh : return this.ExecutorType switch { Type.Unbound => $"'{this.Id}':", - Type.Executor => $"'{this.Id}':{this._executorValue!.GetType().Name}", + Type.Executor => $"'{this.Id}':{this._configuredExecutorType!.Name}", Type.InputPort => $"'{this.Id}':Input({this._inputPortValue!.Request.Name}->{this._inputPortValue!.Response.Name})", Type.Agent => $"{this.Id}':AIAgent(@{this._aiAgentValue!.GetType().Name})", + Type.Function => $"'{this.Id}':{this._configuredExecutorType!.Name}", _ => $"'{this.Id}':" }; } diff --git a/dotnet/src/Microsoft.Agents.Workflows/ExecutorOptions.cs b/dotnet/src/Microsoft.Agents.Workflows/ExecutorOptions.cs index a19630bf31..02cadf601f 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/ExecutorOptions.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/ExecutorOptions.cs @@ -5,7 +5,7 @@ namespace Microsoft.Agents.Workflows; /// /// Configuration options for Executor behavior. /// -public sealed class ExecutorOptions +public class ExecutorOptions { /// /// The default runner configuration. diff --git a/dotnet/src/Microsoft.Agents.Workflows/ExecutorRegistration.cs b/dotnet/src/Microsoft.Agents.Workflows/ExecutorRegistration.cs index bb1e060107..76dbba8ed3 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/ExecutorRegistration.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/ExecutorRegistration.cs @@ -1,9 +1,10 @@ // Copyright (c) Microsoft. All rights reserved. using System; +using System.Threading.Tasks; using Microsoft.Shared.Diagnostics; -using ExecutorFactoryF = System.Func; +using ExecutorFactoryF = System.Func>; namespace Microsoft.Agents.Workflows; @@ -11,7 +12,7 @@ internal class ExecutorRegistration(string id, Type executorType, ExecutorFactor { public string Id { get; } = Throw.IfNullOrEmpty(id); public Type ExecutorType { get; } = Throw.IfNull(executorType); - public ExecutorFactoryF Provider { get; } = Throw.IfNull(provider); + public ExecutorFactoryF ProviderAsync { get; } = Throw.IfNull(provider); internal object? RawExecutorishData { get; } = rawData; @@ -28,5 +29,5 @@ internal class ExecutorRegistration(string id, Type executorType, ExecutorFactor return executor; } - public Executor CreateInstance() => this.CheckId(this.Provider()); + public async ValueTask CreateInstanceAsync() => this.CheckId(await this.ProviderAsync().ConfigureAwait(false)); } diff --git a/dotnet/src/Microsoft.Agents.Workflows/FunctionExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows/FunctionExecutor.cs new file mode 100644 index 0000000000..502e58008b --- /dev/null +++ b/dotnet/src/Microsoft.Agents.Workflows/FunctionExecutor.cs @@ -0,0 +1,72 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading; +using System.Threading.Tasks; + +namespace Microsoft.Agents.Workflows; + +/// +/// Executes a user-provided asynchronous function in response to workflow messages of the specified input type. +/// +/// The type of input message. +/// A delegate that defines the asynchronous function to execute for each input message. +/// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. +/// Configuration options for the executor. If null, default options will be used. +public class FunctionExecutor(Func handlerAsync, + string? id = null, + ExecutorOptions? options = null) : Executor(id, options) +{ + internal static Func WrapAction(Action handlerSync) + { + return RunActionAsync; + + ValueTask RunActionAsync(TInput input, IWorkflowContext workflowContext, CancellationToken cancellation) + { + handlerSync(input, workflowContext, cancellation); + return default; + } + } + + /// + public override ValueTask HandleAsync(TInput message, IWorkflowContext context) => handlerAsync(message, context, default); + + /// + /// Creates a new instance of the class. + /// + /// A synchronous function to execute for each input message and workflow context. + public FunctionExecutor(Action handlerSync) : this(WrapAction(handlerSync)) + { } +} + +/// +/// Executes a user-provided asynchronous function in response to workflow messages of the specified input type, +/// +/// The type of input message. +/// The type of output message. +/// A delegate that defines the asynchronous function to execute for each input message. +/// A optional unique identifier for the executor. If null, a type-tagged UUID will be generated. +/// Configuration options for the executor. If null, default options will be used. +public class FunctionExecutor(Func> handlerAsync, + string? id = null, + ExecutorOptions? options = null) : Executor(id, options) +{ + internal static Func> WrapFunc(Func handlerSync) + { + return RunFuncAsync; + + ValueTask RunFuncAsync(TInput input, IWorkflowContext workflowContext, CancellationToken cancellation) + { + TOutput result = handlerSync(input, workflowContext, cancellation); + return new ValueTask(result); + } + } + /// + public override ValueTask HandleAsync(TInput message, IWorkflowContext context) => handlerAsync(message, context, default); + /// + /// Creates a new instance of the class. + /// + /// A synchronous function to execute for each input message and workflow context. + public FunctionExecutor(Func handlerSync) : this(WrapFunc(handlerSync)) + { } +} diff --git a/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunner.cs b/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunner.cs index a6d7081c1c..4bf2f50e8c 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunner.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunner.cs @@ -228,12 +228,12 @@ internal class InProcessRunner : ISuperStepRunner, ICheckpointingRunner this._workflowInfoCache = this.Workflow.ToWorkflowInfo(); } - RunnerStateData runnerData = await this.RunContext.ExportStateAsync().ConfigureAwait(false); Dictionary edgeData = await this.EdgeMap.ExportStateAsync().ConfigureAwait(false); await prepareTask.ConfigureAwait(false); await this.RunContext.StateManager.PublishUpdatesAsync(this.StepTracer).ConfigureAwait(false); + RunnerStateData runnerData = await this.RunContext.ExportStateAsync().ConfigureAwait(false); Dictionary stateData = await this.RunContext.StateManager.ExportStateAsync().ConfigureAwait(false); Checkpoint checkpoint = new(this.StepTracer.StepNumber, this._workflowInfoCache, runnerData, stateData, edgeData); @@ -261,9 +261,9 @@ internal class InProcessRunner : ISuperStepRunner, ICheckpointingRunner } await this.RunContext.StateManager.ImportStateAsync(checkpoint).ConfigureAwait(false); - Task executorNotifyTask = this.RunContext.NotifyCheckpointLoadedAsync(cancellation); - await this.RunContext.ImportStateAsync(checkpoint).ConfigureAwait(false); + + Task executorNotifyTask = this.RunContext.NotifyCheckpointLoadedAsync(cancellation); ValueTask republishRequestsTask = this.RunContext.RepublishUnservicedRequestsAsync(cancellation); await this.EdgeMap.ImportStateAsync(checkpoint).ConfigureAwait(false); diff --git a/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunnerContext.cs b/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunnerContext.cs index 15c4b9c8b2..b2d30f21f4 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunnerContext.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/InProc/InProcessRunnerContext.cs @@ -35,7 +35,7 @@ internal class InProcessRunnerContext : IRunnerContext throw new InvalidOperationException($"Executor with ID '{executorId}' is not registered."); } - this._executors[executorId] = executor = registration.Provider(); + this._executors[executorId] = executor = await registration.ProviderAsync().ConfigureAwait(false); tracer?.TraceActivated(executorId); if (executor is RequestInfoExecutor requestInputExecutor) @@ -136,8 +136,9 @@ internal class InProcessRunnerContext : IRunnerContext } Dictionary> queuedMessages = this._nextStep.ExportMessages(); - - RunnerStateData result = new(queuedMessages, this._externalRequests.Values.ToList()); + RunnerStateData result = new(instantiatedExecutors: [.. this._executors.Keys], + queuedMessages, + outstandingRequests: [.. this._externalRequests.Values]); return new(result); } @@ -154,7 +155,7 @@ internal class InProcessRunnerContext : IRunnerContext } } - internal ValueTask ImportStateAsync(Checkpoint checkpoint) + internal async ValueTask ImportStateAsync(Checkpoint checkpoint) { if (this.QueuedEvents.Count > 0) { @@ -163,6 +164,11 @@ internal class InProcessRunnerContext : IRunnerContext RunnerStateData importedState = checkpoint.RunnerData; + Task[] executorTasks = importedState.InstantiatedExecutors + .Where(id => !this._executors.ContainsKey(id)) + .Select(id => this.EnsureExecutorAsync(id, tracer: null).AsTask()) + .ToArray(); + this._nextStep = new StepContext(); this._nextStep.ImportMessages(importedState.QueuedMessages); @@ -176,6 +182,6 @@ internal class InProcessRunnerContext : IRunnerContext this._externalRequests[request.RequestId] = request; } - return default; + await Task.WhenAll(executorTasks).ConfigureAwait(false); } } diff --git a/dotnet/src/Microsoft.Agents.Workflows/MessageMerger.cs b/dotnet/src/Microsoft.Agents.Workflows/MessageMerger.cs index 021330a90d..52e0df960c 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/MessageMerger.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/MessageMerger.cs @@ -62,7 +62,11 @@ internal class MessageMerger List result = this.UpdatesByMessageId.Keys.Select(AggregateUpdatesToMessage) .ToList(); - result.AddRange(this.ComputeDangling().Messages); + if (this.DanglingUpdates.Count > 0) + { + result.AddRange(this.ComputeDangling().Messages); + } + return result; ChatMessage AggregateUpdatesToMessage(string messageId) @@ -126,16 +130,17 @@ internal class MessageMerger return left.CreatedAt.Value.CompareTo(right.CreatedAt.Value); } - public AgentRunResponse ComputeMerged(string primaryResponseId) + public AgentRunResponse ComputeMerged(string primaryResponseId, string? primaryAgentId = null, string? primaryAgentName = null) { List messages = []; Dictionary responses = new(); + HashSet agentIds = new(); foreach (string responseId in this._mergeStates.Keys) { ResponseMergeState mergeState = this._mergeStates[responseId]; - List responseList = mergeState.UpdatesByMessageId.Keys.Select(messageId => mergeState.ComputeMerged(messageId)).ToList(); + List responseList = mergeState.UpdatesByMessageId.Keys.Select(mergeState.ComputeMerged).ToList(); if (mergeState.DanglingUpdates.Count > 0) { responseList.Add(mergeState.ComputeDangling()); @@ -143,13 +148,39 @@ internal class MessageMerger responseList.Sort(this.CompareByDateTimeOffset); responses[responseId] = responseList.Aggregate(MergeResponses); - messages.AddRange(responses[responseId].Messages); + messages.AddRange(GetMessagesWithCreatedAt(responses[responseId])); + } + + UsageDetails? usage = null; + AdditionalPropertiesDictionary? additionalProperties = null; + HashSet createdTimes = new(); + + foreach (AgentRunResponse response in responses.Values) + { + if (response.AgentId != null) + { + agentIds.Add(response.AgentId); + } + + if (response.CreatedAt.HasValue) + { + createdTimes.Add(response.CreatedAt.Value); + } + + usage = MergeUsage(usage, response.Usage); + additionalProperties = MergeProperties(additionalProperties, response.AdditionalProperties); } messages.AddRange(this._danglingState.ComputeFlattened()); return new AgentRunResponse(messages) { ResponseId = primaryResponseId, + AgentId = primaryAgentId + ?? primaryAgentName + ?? (agentIds.Count == 1 ? agentIds.First() : null), + CreatedAt = DateTimeOffset.Now, + Usage = usage, + AdditionalProperties = additionalProperties }; AgentRunResponse MergeResponses(AgentRunResponse? current, AgentRunResponse incoming) @@ -170,16 +201,62 @@ internal class MessageMerger return new() { AgentId = incoming.AgentId ?? current.AgentId, - AdditionalProperties = incoming.AdditionalProperties ?? current.AdditionalProperties, + AdditionalProperties = MergeProperties(current.AdditionalProperties, incoming.AdditionalProperties), CreatedAt = incoming.CreatedAt ?? current.CreatedAt, Messages = current.Messages.Concat(incoming.Messages).ToList(), ResponseId = current.ResponseId, RawRepresentation = rawRepresentation, - Usage = Merge(current.Usage, incoming.Usage), + Usage = MergeUsage(current.Usage, incoming.Usage), }; } - static UsageDetails? Merge(UsageDetails? current, UsageDetails? incoming) + static IEnumerable GetMessagesWithCreatedAt(AgentRunResponse response) + { + if (response.Messages.Count == 0) + { + return []; + } + + if (response.CreatedAt is null) + { + return response.Messages; + } + + DateTimeOffset? createdAt = response.CreatedAt; + return response.Messages.Select( + message => new ChatMessage + { + Role = message.Role, + AuthorName = message.AuthorName, + Contents = message.Contents, + MessageId = message.MessageId, + CreatedAt = createdAt, + RawRepresentation = message.RawRepresentation + }); + } + + static AdditionalPropertiesDictionary? MergeProperties(AdditionalPropertiesDictionary? current, AdditionalPropertiesDictionary? incoming) + { + if (current == null) + { + return incoming; + } + + if (incoming == null) + { + return current; + } + + AdditionalPropertiesDictionary merged = new(current); + foreach (string key in incoming.Keys) + { + merged[key] = incoming[key]; + } + + return merged; + } + + static UsageDetails? MergeUsage(UsageDetails? current, UsageDetails? incoming) { if (current == null) { diff --git a/dotnet/src/Microsoft.Agents.Workflows/Reflection/ReflectingExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows/Reflection/ReflectingExecutor.cs index 9b0ca4a74e..f5854bf29d 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/Reflection/ReflectingExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/Reflection/ReflectingExecutor.cs @@ -16,8 +16,8 @@ public class ReflectingExecutor< ] TExecutor > : Executor where TExecutor : ReflectingExecutor { - /// - protected ReflectingExecutor(string? id = null) : base(id) + /// + protected ReflectingExecutor(string? id = null, ExecutorOptions? options = null) : base(id, options) { } /// diff --git a/dotnet/src/Microsoft.Agents.Workflows/Specialized/RequestInfoExecutor.cs b/dotnet/src/Microsoft.Agents.Workflows/Specialized/RequestInfoExecutor.cs index 4cb151666f..9b12ff1515 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/Specialized/RequestInfoExecutor.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/Specialized/RequestInfoExecutor.cs @@ -20,7 +20,7 @@ internal class RequestInfoExecutor : Executor }; private readonly bool _allowWrapped; - public RequestInfoExecutor(InputPort port, bool allowWrapped = true) : base(RequestInfoExecutor.DefaultOptions, port.Id) + public RequestInfoExecutor(InputPort port, bool allowWrapped = true) : base(port.Id, RequestInfoExecutor.DefaultOptions) { this.Port = port; diff --git a/dotnet/src/Microsoft.Agents.Workflows/WorkflowBuilder.cs b/dotnet/src/Microsoft.Agents.Workflows/WorkflowBuilder.cs index 1a37415d19..49ad08c33b 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/WorkflowBuilder.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/WorkflowBuilder.cs @@ -2,7 +2,10 @@ using System; using System.Collections.Generic; +using System.Diagnostics.CodeAnalysis; using System.Linq; +using System.Threading; +using System.Threading.Tasks; using Microsoft.Shared.Diagnostics; namespace Microsoft.Agents.Workflows; @@ -205,6 +208,32 @@ public class WorkflowBuilder return this; } + [SuppressMessage("Reliability", "CA2008:Do not create tasks without passing a TaskScheduler", + Justification = "We explicitly set the TaskScheduler when we create the TaskFactory")] + [SuppressMessage("Usage", "VSTHRD002:Avoid problematic synchronous waits", + Justification = "This runs the thread on the thread pool")] + private static TResult RunSync(Func> funcAsync) + { + TaskFactory factory = new(CancellationToken.None, TaskCreationOptions.None, TaskContinuationOptions.None, TaskScheduler.Default); + + // See ASP.Net.Identity's implementation of AsyncHelper + // https://github.com/aspnet/AspNetIdentity/blob/main/src/Microsoft.AspNet.Identity.Core/AsyncHelper.cs + + // Capture the current culture and UI culture + var culture = System.Globalization.CultureInfo.CurrentCulture; + var uiCulture = System.Globalization.CultureInfo.CurrentUICulture; + + return factory.StartNew(PropagateCultureAndInvoke).Unwrap().GetAwaiter().GetResult(); + + Task PropagateCultureAndInvoke() + { + // Set the culture and UI culture to the captured values + System.Globalization.CultureInfo.CurrentCulture = culture; + System.Globalization.CultureInfo.CurrentUICulture = uiCulture; + return funcAsync().AsTask(); + } + } + /// /// Builds and returns a workflow instance configured to process messages of the specified input type. /// @@ -228,9 +257,7 @@ public class WorkflowBuilder throw new InvalidOperationException($"Start executor with ID '{this._startExecutorId}' is not bound."); } - // TODO: Delay-instantiate the start executor, and ensure it take input of type T - Executor startExecutor = startRegistration.Provider(); - + Executor startExecutor = RunSync(startRegistration.CreateInstanceAsync); if (!startExecutor.InputTypes.Any(t => t.IsAssignableFrom(typeof(T)))) { // We have no handlers for the input type T, which means the built workflow will not be able to diff --git a/dotnet/src/Microsoft.Agents.Workflows/WorkflowHostAgent.cs b/dotnet/src/Microsoft.Agents.Workflows/WorkflowHostAgent.cs index 98b7a05fda..3751cd2c9f 100644 --- a/dotnet/src/Microsoft.Agents.Workflows/WorkflowHostAgent.cs +++ b/dotnet/src/Microsoft.Agents.Workflows/WorkflowHostAgent.cs @@ -129,7 +129,7 @@ internal class WorkflowHostAgent : AIAgent merger.AddUpdate(update); } - return merger.ComputeMerged(workflowThread.ResponseId); + return merger.ComputeMerged(workflowThread.ResponseId, this.Id, this.Name); } public override async diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AAgent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AAgent.cs index fd24832755..061b988137 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AAgent.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AAgent.cs @@ -69,7 +69,7 @@ internal sealed class A2AAgent : AIAgent if (a2aResponse is Message message) { - UpdateThreadConversationId(thread, message); + UpdateThreadConversationId(thread, message.ContextId); return new AgentRunResponse { @@ -80,8 +80,21 @@ internal sealed class A2AAgent : AIAgent AdditionalProperties = message.Metadata.ToAdditionalProperties(), }; } + if (a2aResponse is AgentTask agentTask) + { + UpdateThreadConversationId(thread, agentTask.ContextId); - throw new NotSupportedException($"Only message responses are supported from A2A agents. Received: {a2aResponse.GetType().FullName ?? "null"}"); + return new AgentRunResponse + { + AgentId = this.Id, + ResponseId = agentTask.Id, + RawRepresentation = agentTask, + Messages = agentTask.ToChatMessages(), + AdditionalProperties = agentTask.Metadata.ToAdditionalProperties(), + }; + } + + throw new NotSupportedException($"Only Message and AgentTask responses are supported from A2A agents. Received: {a2aResponse.GetType().FullName ?? "null"}"); } /// @@ -107,7 +120,7 @@ internal sealed class A2AAgent : AIAgent throw new NotSupportedException($"Only message responses are supported from A2A agents. Received: {sseEvent.Data?.GetType().FullName ?? "null"}"); } - UpdateThreadConversationId(thread, message); + UpdateThreadConversationId(thread, message.ContextId); yield return new AgentRunResponseUpdate { @@ -147,22 +160,22 @@ internal sealed class A2AAgent : AIAgent } } - private static void UpdateThreadConversationId(AgentThread? thread, Message message) + private static void UpdateThreadConversationId(AgentThread? thread, string? contextId) { if (thread is null) { return; } - // Surface cases where the A2A agent responds with a message that + // Surface cases where the A2A agent responds with a response that // has a different context Id than the thread's conversation Id. - if (thread.ConversationId is not null && message.ContextId is not null && thread.ConversationId != message.ContextId) + if (thread.ConversationId is not null && contextId is not null && thread.ConversationId != contextId) { throw new InvalidOperationException( - $"The {nameof(message.ContextId)} returned from the A2A agent is different from the conversation Id of the provided {nameof(AgentThread)}."); + $"The {nameof(contextId)} returned from the A2A agent is different from the conversation Id of the provided {nameof(AgentThread)}."); } // Assign a server-generated context Id to the thread if it's not already set. - thread.ConversationId ??= message.ContextId; + thread.ConversationId ??= contextId; } } diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AHostAgent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AHostAgent.cs new file mode 100644 index 0000000000..86f273bc0e --- /dev/null +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/A2AHostAgent.cs @@ -0,0 +1,112 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Threading; +using System.Threading.Tasks; +using A2A; +using Microsoft.Shared.Diagnostics; + +namespace Microsoft.Extensions.AI.Agents.A2A; + +/// +/// Host which will attach an to a +/// +/// +/// This implementation only handles: +/// +/// TaskManager.OnMessageReceived +/// TaskManager.OnAgentCardQuery +/// +/// Support for task management will be added later as part of the long-running task execution work. +/// +public sealed class A2AHostAgent +{ + /// + /// Initializes a new instance of the SemanticKernelTravelAgent + /// + public A2AHostAgent(AIAgent agent, AgentCard agentCard, TaskManager? taskManager = null) + { + Throw.IfNull(agent); + Throw.IfNull(agentCard); + + this.Agent = agent; + this._agentCard = agentCard; + + this.Attach(taskManager ?? new TaskManager()); + } + + /// + /// The associated + /// + public AIAgent? Agent { get; private set; } + + /// + /// The associated + /// + public TaskManager? TaskManager => this._taskManager; + + /// + /// Attach the to the provided + /// + /// + public void Attach(TaskManager taskManager) + { + Throw.IfNull(taskManager); + + this._taskManager = taskManager; + taskManager.OnMessageReceived = this.OnMessageReceivedAsync; + taskManager.OnAgentCardQuery = this.GetAgentCardAsync; + } + + /// + /// Handle a received message + /// + /// The to handle + /// The to cancel the operation + public async Task OnMessageReceivedAsync(MessageSendParams messageSend, CancellationToken cancellationToken = default) + { + Throw.IfNull(messageSend); + Throw.IfNull(this.Agent); + + if (this._taskManager is null) + { + throw new InvalidOperationException("TaskManager must be attached before handling an agent message."); + } + + // Get message from the user + var userMessage = messageSend.Message.ToChatMessage(); + + // Get the response from the agent + var message = new Message(); + var agentResponse = await this.Agent.RunAsync(userMessage, cancellationToken: cancellationToken).ConfigureAwait(false); + foreach (var chatMessage in agentResponse.Messages) + { + var content = chatMessage.Text; + message.Parts.Add(new TextPart() { Text = content! }); + } + + return message; + } + + /// + /// Return the associated with this hosted agent. + /// + /// Current URL for the agent + /// The to cancel the operation +#pragma warning disable CA1054 // URI-like parameters should not be strings + public Task GetAgentCardAsync(string agentUrl, CancellationToken cancellationToken) + { + // Ensure the URL is in the correct format + Uri uri = new(agentUrl); + agentUrl = $"{uri.Scheme}://{uri.Host}:{uri.Port}/"; + + this._agentCard.Url = agentUrl; + return Task.FromResult(this._agentCard); + } +#pragma warning restore CA1054 // URI-like parameters should not be strings + + #region private + private readonly AgentCard _agentCard; + private TaskManager? _taskManager; + #endregion +} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AAgentTaskExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AAgentTaskExtensions.cs new file mode 100644 index 0000000000..858be41753 --- /dev/null +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AAgentTaskExtensions.cs @@ -0,0 +1,30 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Collections.Generic; +using A2A; +using Microsoft.Shared.Diagnostics; + +namespace Microsoft.Extensions.AI.Agents.A2A; + +/// +/// Extension methods for the class. +/// +internal static class A2AAgentTaskExtensions +{ + internal static IList ToChatMessages(this AgentTask agentTask) + { + _ = Throw.IfNull(agentTask); + + List messages = []; + + if (agentTask.Artifacts is not null) + { + foreach (var artifact in agentTask.Artifacts) + { + messages.Add(artifact.ToChatMessage()); + } + } + + return messages; + } +} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AArtifactExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AArtifactExtensions.cs new file mode 100644 index 0000000000..66f1b6e5a2 --- /dev/null +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AArtifactExtensions.cs @@ -0,0 +1,28 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Collections.Generic; +using A2A; + +namespace Microsoft.Extensions.AI.Agents.A2A; + +/// +/// Extension methods for the class. +/// +internal static class A2AArtifactExtensions +{ + internal static ChatMessage ToChatMessage(this Artifact artifact) + { + List? aiContents = null; + + foreach (var part in artifact.Parts) + { + (aiContents ??= []).Add(part.ToAIContent()); + } + + return new ChatMessage(ChatRole.Assistant, aiContents) + { + AdditionalProperties = artifact.Metadata.ToAdditionalProperties(), + RawRepresentation = artifact, + }; + } +} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMessageExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMessageExtensions.cs index b7acca952d..918235869e 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMessageExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMessageExtensions.cs @@ -10,7 +10,7 @@ namespace Microsoft.Extensions.AI.Agents.A2A; /// internal static class A2AMessageExtensions { - public static ChatMessage ToChatMessage(this Message message) + internal static ChatMessage ToChatMessage(this Message message) { List? aiContents = null; diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMetadataExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMetadataExtensions.cs index c41f5f6b53..05b1293c24 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMetadataExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2AMetadataExtensions.cs @@ -15,7 +15,7 @@ internal static class A2AMetadataExtensions /// /// The metadata dictionary to convert. /// The converted , or null if the input is null or empty. - public static AdditionalPropertiesDictionary? ToAdditionalProperties(this Dictionary? metadata) + internal static AdditionalPropertiesDictionary? ToAdditionalProperties(this Dictionary? metadata) { if (metadata is not { Count: > 0 }) { diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2APartExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2APartExtensions.cs index d3b1ef9f83..4e14b07ff5 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2APartExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/A2APartExtensions.cs @@ -15,7 +15,7 @@ internal static class A2APartExtensions /// /// The A2A part to convert. /// The corresponding . - public static AIContent ToAIContent(this Part part) + internal static AIContent ToAIContent(this Part part) { return part switch { diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/AIContentExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/AIContentExtensions.cs index ca4442ba66..eb80439e0e 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/AIContentExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/AIContentExtensions.cs @@ -16,7 +16,7 @@ internal static class AIContentExtensions /// /// The collection of AI contents to convert." /// The list of A2A objects. - public static List? ToA2AParts(this IEnumerable contents) + internal static List? ToA2AParts(this IEnumerable contents) { List? parts = null; @@ -33,7 +33,7 @@ internal static class AIContentExtensions /// /// AI content to convert. /// The corresponding A2A object. - public static Part ToA2APart(this AIContent content) + internal static Part ToA2APart(this AIContent content) { return content switch { diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/ChatMessageExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/ChatMessageExtensions.cs index 930b8c4295..f030750dcd 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/ChatMessageExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.A2A/Extensions/ChatMessageExtensions.cs @@ -11,7 +11,7 @@ namespace Microsoft.Extensions.AI.Agents.A2A; /// internal static class ChatMessageExtensions { - public static Message ToA2AMessage(this IReadOnlyCollection messages) + internal static Message ToA2AMessage(this IReadOnlyCollection messages) { List allParts = []; diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/AgentThread.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/AgentThread.cs index 63b8f07f69..afc92bc60d 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/AgentThread.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/AgentThread.cs @@ -3,7 +3,6 @@ using System; using System.Collections.Generic; using System.Diagnostics; -using System.Runtime.CompilerServices; using System.Text.Json; using System.Threading; using System.Threading.Tasks; @@ -109,23 +108,6 @@ public class AgentThread } } - /// - /// Retrieves any messages stored in the of the thread, otherwise returns an empty collection. - /// - /// The to monitor for cancellation requests. The default is . - /// The messages from the in ascending chronological order, with the oldest message first. - public virtual async IAsyncEnumerable GetMessagesAsync([EnumeratorCancellation] CancellationToken cancellationToken = default) - { - if (this._messageStore is not null) - { - var messages = await this._messageStore!.GetMessagesAsync(cancellationToken).ConfigureAwait(false); - foreach (var message in messages) - { - yield return message; - } - } - } - /// /// Serializes the current object's state to a using the specified serialization options. /// diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/DelegatingAIAgent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/DelegatingAIAgent.cs new file mode 100644 index 0000000000..e2e0fd7f2d --- /dev/null +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/DelegatingAIAgent.cs @@ -0,0 +1,70 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Shared.Diagnostics; + +namespace Microsoft.Extensions.AI.Agents; + +/// +/// Provides an optional base class for an that passes through calls to another instance. +/// +/// +/// This is recommended as a base type when building agents that can be chained around an underlying . +/// The default implementation simply passes each call to the inner agent instance. +/// +public class DelegatingAIAgent : AIAgent +{ + /// + /// Initializes a new instance of the class. + /// + /// The wrapped agent instance. + protected DelegatingAIAgent(AIAgent innerAgent) + { + this.InnerAgent = Throw.IfNull(innerAgent); + } + + /// Gets the inner . + protected AIAgent InnerAgent { get; } + + /// + public override string Id => this.InnerAgent.Id; + + /// + public override string? Name => this.InnerAgent.Name; + + /// + public override string? Description => this.InnerAgent.Description; + + /// + public override object? GetService(Type serviceType, object? serviceKey = null) + { + _ = Throw.IfNull(serviceType); + + // If the key is non-null, we don't know what it means so pass through to the inner service. + return + serviceKey is null && serviceType.IsInstanceOfType(this) ? this : + this.InnerAgent.GetService(serviceType, serviceKey); + } + + /// + public override AgentThread GetNewThread() => this.InnerAgent.GetNewThread(); + + /// + public override Task RunAsync( + IReadOnlyCollection messages, + AgentThread? thread = null, + AgentRunOptions? options = null, + CancellationToken cancellationToken = default) + => this.InnerAgent.RunAsync(messages, thread, options, cancellationToken); + + /// + public override IAsyncEnumerable RunStreamingAsync( + IReadOnlyCollection messages, + AgentThread? thread = null, + AgentRunOptions? options = null, + CancellationToken cancellationToken = default) + => this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken); +} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/IChatMessageStore.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/IChatMessageStore.cs index d1713e9336..ad6303f36e 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/IChatMessageStore.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/IChatMessageStore.cs @@ -34,7 +34,7 @@ public interface IChatMessageStore /// since they may contain state that is specific to a thread. /// /// - Task> GetMessagesAsync(CancellationToken cancellationToken); + Task> GetMessagesAsync(CancellationToken cancellationToken = default); /// /// Adds messages to the store. @@ -42,7 +42,7 @@ public interface IChatMessageStore /// The messages to add. /// The to monitor for cancellation requests. The default is . /// An async task. - Task AddMessagesAsync(IReadOnlyCollection messages, CancellationToken cancellationToken); + Task AddMessagesAsync(IReadOnlyCollection messages, CancellationToken cancellationToken = default); /// /// Deserializes the state contained in the provided into the properties on this store. diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalRequestContent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalRequestContent.cs deleted file mode 100644 index b6c561411f..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalRequestContent.cs +++ /dev/null @@ -1,35 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -using Microsoft.Shared.Diagnostics; - -namespace Microsoft.Extensions.AI; - -/// -/// Represents a request for user approval of a function call. -/// -public sealed class FunctionApprovalRequestContent : UserInputRequestContent -{ - /// - /// Initializes a new instance of the class. - /// - /// The ID to uniquely identify the function approval request/response pair. - /// The function call that requires user approval. - public FunctionApprovalRequestContent(string id, FunctionCallContent functionCall) - : base(id) - { - this.FunctionCall = Throw.IfNull(functionCall); - } - - /// - /// Gets the function call that pre-invoke approval is required for. - /// - public FunctionCallContent FunctionCall { get; } - - /// - /// Creates a to indicate whether the function call is approved or rejected based on the value of . - /// - /// if the function call is approved; otherwise, . - /// The representing the approval response. - public FunctionApprovalResponseContent CreateResponse(bool approved) - => new(this.Id, approved, this.FunctionCall); -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalResponseContent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalResponseContent.cs deleted file mode 100644 index 11bb01b5f6..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/FunctionApprovalResponseContent.cs +++ /dev/null @@ -1,34 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -using Microsoft.Shared.Diagnostics; - -namespace Microsoft.Extensions.AI; - -/// -/// Represents a response to a function approval request. -/// -public sealed class FunctionApprovalResponseContent : UserInputResponseContent -{ - /// - /// Initializes a new instance of the class. - /// - /// The ID to uniquely identify the function approval request/response pair. - /// Indicates whether the request was approved. - /// The function call that requires user approval. - public FunctionApprovalResponseContent(string id, bool approved, FunctionCallContent functionCall) - : base(id) - { - this.Approved = approved; - this.FunctionCall = Throw.IfNull(functionCall); - } - - /// - /// Gets or sets a value indicating whether the user approved the request. - /// - public bool Approved { get; } - - /// - /// Gets the function call that pre-invoke approval is required for. - /// - public FunctionCallContent FunctionCall { get; } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputRequestContent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputRequestContent.cs deleted file mode 100644 index ba327b6717..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputRequestContent.cs +++ /dev/null @@ -1,25 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -using Microsoft.Shared.Diagnostics; - -namespace Microsoft.Extensions.AI; - -/// -/// Base class for user input request content. -/// -public abstract class UserInputRequestContent : AIContent -{ - /// - /// Initializes a new instance of the class. - /// - /// The ID to uniquely identify the user input request/response pair. - protected UserInputRequestContent(string id) - { - Id = Throw.IfNullOrWhitespace(id); - } - - /// - /// Gets the ID to uniquely identify the user input request/response pair. - /// - public string Id { get; } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputResponseContent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputResponseContent.cs deleted file mode 100644 index 78b138779e..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/MEAI.A/UserInputResponseContent.cs +++ /dev/null @@ -1,25 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -using Microsoft.Shared.Diagnostics; - -namespace Microsoft.Extensions.AI; - -/// -/// Base class for user input response content. -/// -public abstract class UserInputResponseContent : AIContent -{ - /// - /// Initializes a new instance of the class. - /// - /// The ID to uniquely identify the user input request/response pair. - protected UserInputResponseContent(string id) - { - Id = Throw.IfNullOrWhitespace(id); - } - - /// - /// Gets the ID to uniquely identify the user input request/response pair. - /// - public string Id { get; } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/Microsoft.Extensions.AI.Agents.Abstractions.csproj b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/Microsoft.Extensions.AI.Agents.Abstractions.csproj index 37c7bc871b..0bdc6a5b49 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/Microsoft.Extensions.AI.Agents.Abstractions.csproj +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.Abstractions/Microsoft.Extensions.AI.Agents.Abstractions.csproj @@ -4,7 +4,7 @@ $(ProjectsTargetFrameworks) $(ProjectsDebugTargetFrameworks) Microsoft.Extensions.AI.Agents - $(NoWarn);CA1716;IDE0009; + $(NoWarn);CA1716;IDE0009;MEAI001 alpha diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/AIAgentWithOpenAIExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/AIAgentWithOpenAIExtensions.cs index c1a8373cfd..37bee66e61 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/AIAgentWithOpenAIExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/AIAgentWithOpenAIExtensions.cs @@ -1,8 +1,6 @@ // Copyright (c) Microsoft. All rights reserved. using System.ClientModel; -using System.Text; -using Microsoft.Extensions.AI; using Microsoft.Extensions.AI.Agents; using Microsoft.Extensions.AI.Agents.OpenAI.ChatCompletion; using Microsoft.Shared.Diagnostics; @@ -22,33 +20,6 @@ namespace OpenAI; /// public static class AIAgentWithOpenAIExtensions { - /// - /// Runs the AI agent with a single OpenAI chat message and returns the response as a native OpenAI . - /// - /// The AI agent to run. - /// The OpenAI chat message to send to the agent. - /// The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided message and agent response. - /// Optional parameters for agent invocation. - /// The to monitor for cancellation requests. The default is . - /// A representing the asynchronous operation that returns a native OpenAI response. - /// Thrown when or is . - /// Thrown when the agent's response cannot be converted to a , typically when the underlying representation is not an OpenAI response. - /// Thrown when the type is not supported by the message conversion method. - /// - /// This method converts the OpenAI chat message to the Microsoft Extensions AI format using the appropriate conversion method, - /// runs the agent, and then extracts the native OpenAI from the response using . - /// - public static async Task RunAsync(this AIAgent agent, OpenAI.Chat.ChatMessage message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) - { - Throw.IfNull(agent); - Throw.IfNull(message); - - var response = await agent.RunAsync(message.AsChatMessage(), thread, options, cancellationToken).ConfigureAwait(false); - - var chatCompletion = response.AsChatCompletion(); - return chatCompletion; - } - /// /// Runs the AI agent with a collection of OpenAI chat messages and returns the response as a native OpenAI . /// @@ -62,7 +33,7 @@ public static class AIAgentWithOpenAIExtensions /// Thrown when the agent's response cannot be converted to a , typically when the underlying representation is not an OpenAI response. /// Thrown when any message in has a type that is not supported by the message conversion method. /// - /// This method converts each OpenAI chat message to the Microsoft Extensions AI format using , + /// This method converts the OpenAI chat messages to the Microsoft Extensions AI format using the appropriate conversion method, /// runs the agent with the converted message collection, and then extracts the native OpenAI from the response using . /// public static async Task RunAsync(this AIAgent agent, IEnumerable messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) @@ -76,32 +47,6 @@ public static class AIAgentWithOpenAIExtensions return chatCompletion; } - /// - /// Runs the AI agent with a single OpenAI chat message and returns the response as collection of native OpenAI . - /// - /// The AI agent to run. - /// The OpenAI chat message to send to the agent. - /// The conversation thread to continue with this invocation. If not provided, creates a new thread. The thread will be mutated with the provided message and agent response. - /// Optional parameters for agent invocation. - /// The to monitor for cancellation requests. The default is . - /// A representing the asynchronous operation that returns a native OpenAI response. - /// Thrown when or is . - /// Thrown when the agent's response cannot be converted to a , typically when the underlying representation is not an OpenAI response. - /// Thrown when the type is not supported by the message conversion method. - /// - /// This method converts the OpenAI chat message to the Microsoft Extensions AI format using the appropriate conversion method, - /// runs the agent, and then extracts the native OpenAI from the response using . - /// - public static AsyncCollectionResult RunStreamingAsync(this AIAgent agent, OpenAI.Chat.ChatMessage message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) - { - Throw.IfNull(agent); - Throw.IfNull(message); - - IAsyncEnumerable response = agent.RunStreamingAsync(message.AsChatMessage(), thread, options, cancellationToken); - - return new AsyncStreamingUpdateCollectionResult(response); - } - /// /// Runs the AI agent with a single OpenAI chat message and returns the response as collection of native OpenAI . /// @@ -115,7 +60,7 @@ public static class AIAgentWithOpenAIExtensions /// Thrown when the agent's response cannot be converted to a , typically when the underlying representation is not an OpenAI response. /// Thrown when the type is not supported by the message conversion method. /// - /// This method converts the OpenAI chat message to the Microsoft Extensions AI format using the appropriate conversion method, + /// This method converts the OpenAI chat messages to the Microsoft Extensions AI format using the appropriate conversion method, /// runs the agent, and then extracts the native OpenAI from the response using . /// public static AsyncCollectionResult RunStreamingAsync(this AIAgent agent, IEnumerable messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) @@ -127,284 +72,4 @@ public static class AIAgentWithOpenAIExtensions return new AsyncStreamingUpdateCollectionResult(response); } - - /// - /// Creates a sequence of instances from the specified OpenAI input messages. - /// - /// The OpenAI input messages to convert. - /// A sequence of Microsoft Extensions AI chat messages converted from the OpenAI messages. - /// Thrown when is . - /// Thrown when a message type is encountered that cannot be converted. - /// - /// This method supports conversion of the following OpenAI message types: - /// - /// - /// - /// (obsolete) - /// - /// - /// - /// - /// - internal static IEnumerable AsChatMessages(this IEnumerable messages) - { - Throw.IfNull(messages); - - foreach (OpenAI.Chat.ChatMessage message in messages) - { - switch (message) - { - case OpenAI.Chat.AssistantChatMessage assistantMessage: - yield return assistantMessage.AsChatMessage(); - break; - case OpenAI.Chat.DeveloperChatMessage developerMessage: - yield return developerMessage.AsChatMessage(); - break; -#pragma warning disable CS0618 // Type or member is obsolete - case OpenAI.Chat.FunctionChatMessage functionMessage: - yield return functionMessage.AsChatMessage(); - break; -#pragma warning restore CS0618 // Type or member is obsolete - case OpenAI.Chat.SystemChatMessage systemMessage: - yield return systemMessage.AsChatMessage(); - break; - case OpenAI.Chat.ToolChatMessage toolMessage: - yield return toolMessage.AsChatMessage(); - break; - case OpenAI.Chat.UserChatMessage userMessage: - yield return userMessage.AsChatMessage(); - break; - } - } - } - - /// - /// Converts an OpenAI chat message to a Microsoft Extensions AI . - /// - /// The OpenAI chat message to convert. - /// A equivalent of the input OpenAI message. - /// Thrown when is . - /// Thrown when the type is not supported for conversion. - /// - /// This method provides a bridge between OpenAI SDK message types and Microsoft Extensions AI message types. - /// It handles the conversion by switching on the concrete type of the OpenAI message and calling the appropriate - /// specialized conversion method. - /// - internal static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this OpenAI.Chat.ChatMessage chatMessage) - { - Throw.IfNull(chatMessage); - - return chatMessage switch - { - AssistantChatMessage assistantMessage => assistantMessage.AsChatMessage(), - DeveloperChatMessage developerMessage => developerMessage.AsChatMessage(), - SystemChatMessage systemMessage => systemMessage.AsChatMessage(), - ToolChatMessage toolMessage => toolMessage.AsChatMessage(), - UserChatMessage userMessage => userMessage.AsChatMessage(), - _ => throw new NotSupportedException($"Message type {chatMessage.GetType().Name} is not supported for conversion.") - }; - } - - /// - /// Converts OpenAI chat message content to Microsoft Extensions AI content items. - /// - /// The OpenAI chat message content to convert. - /// A sequence of items converted from the OpenAI content. - /// - /// This method supports conversion of the following OpenAI content part types: - /// - /// Text content (converted to ) - /// Refusal content (converted to ) - /// Image content (converted to or ) - /// Input audio content (converted to ) - /// File content (converted to ) - /// - /// - private static IEnumerable AsAIContent(this OpenAI.Chat.ChatMessageContent content) - { - Throw.IfNull(content); - - foreach (OpenAI.Chat.ChatMessageContentPart part in content) - { - switch (part.Kind) - { - case OpenAI.Chat.ChatMessageContentPartKind.Text: - yield return new TextContent(part.Text) - { - RawRepresentation = content - }; - break; - case OpenAI.Chat.ChatMessageContentPartKind.Refusal: - yield return new TextContent(part.Refusal) - { - RawRepresentation = content - }; - break; - case OpenAI.Chat.ChatMessageContentPartKind.Image: - if (part.ImageBytes is not null) - { - yield return new DataContent(part.ImageBytes, part.ImageBytesMediaType) - { - RawRepresentation = content - }; - } - else - { - yield return new UriContent(part.ImageUri, "image/*") - { - RawRepresentation = content - }; - } - break; - case OpenAI.Chat.ChatMessageContentPartKind.InputAudio: - yield return new DataContent(part.InputAudioBytes, "audio/*") - { - RawRepresentation = content - }; - break; - case OpenAI.Chat.ChatMessageContentPartKind.File: - yield return new DataContent(part.FileBytes, part.FileBytesMediaType) - { - RawRepresentation = content - }; - break; - default: - throw new NotSupportedException($"Content part kind '{part.Kind}' is not supported for conversion to AIContent."); - } - } - } - - /// - /// Converts OpenAI chat message content to text. - /// - /// The OpenAI chat message content to convert. - /// A string created from the text and refusal parts of the OpenAI content. - /// - /// Using when converting OpenAI For tool messages, the contents can only be of type text. - /// - private static string AsText(this OpenAI.Chat.ChatMessageContent content) - { - Throw.IfNull(content); - - StringBuilder text = new(); - foreach (OpenAI.Chat.ChatMessageContentPart part in content) - { - switch (part.Kind) - { - case OpenAI.Chat.ChatMessageContentPartKind.Text: - text.Append(part.Text); - break; - case OpenAI.Chat.ChatMessageContentPartKind.Refusal: - text.Append(part.Refusal); - break; - default: - throw new NotSupportedException($"Content part kind '{part.Kind}' is not supported for conversion to text."); - } - } - return text.ToString(); - } - - /// - /// Converts an OpenAI to a Microsoft Extensions AI . - /// - /// The OpenAI assistant message to convert. - /// A Microsoft Extensions AI chat message with assistant role. - /// - /// This method converts the assistant message content using and preserves - /// the participant name as the author name in the resulting message. - /// - private static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this AssistantChatMessage assistantMessage) - { - Throw.IfNull(assistantMessage); - - return new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.Assistant, [.. assistantMessage.Content.AsAIContent()]) - { - AuthorName = assistantMessage.ParticipantName, - RawRepresentation = assistantMessage - }; - } - - /// - /// Converts an OpenAI to a Microsoft Extensions AI . - /// - /// The OpenAI developer message to convert. - /// A Microsoft Extensions AI chat message with system role. - /// - /// Developer messages are treated as system messages in the Microsoft Extensions AI framework. - /// The participant name is preserved as the author name. - /// - private static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this DeveloperChatMessage developerMessage) - { - Throw.IfNull(developerMessage); - - return new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.System, [.. developerMessage.Content.AsAIContent()]) - { - AuthorName = developerMessage.ParticipantName, - RawRepresentation = developerMessage - }; - } - - /// - /// Converts an OpenAI to a Microsoft Extensions AI . - /// - /// The OpenAI system message to convert. - /// A Microsoft Extensions AI chat message with system role. - /// - /// This method converts the system message content using and preserves - /// the participant name as the author name in the resulting message. - /// - private static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this SystemChatMessage systemMessage) - { - Throw.IfNull(systemMessage); - - return new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.System, [.. systemMessage.Content.AsAIContent()]) - { - AuthorName = systemMessage.ParticipantName, - RawRepresentation = systemMessage - }; - } - - /// - /// Converts an OpenAI to a Microsoft Extensions AI . - /// - /// The OpenAI tool message to convert. - /// A Microsoft Extensions AI chat message with tool role. - /// - /// This method converts tool message content using and includes the tool call ID - /// in the resulting message's additional properties for traceability. - /// - private static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this ToolChatMessage toolMessage) - { - Throw.IfNull(toolMessage); - - var content = new FunctionResultContent(toolMessage.ToolCallId, toolMessage.Content.AsText()) - { - RawRepresentation = toolMessage - }; - return new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.Tool, [content]) - { - RawRepresentation = toolMessage, - AdditionalProperties = new() { ["tool_call_id"] = toolMessage.ToolCallId } - }; - } - - /// - /// Converts an OpenAI to a Microsoft Extensions AI . - /// - /// The OpenAI user message to convert. - /// A Microsoft Extensions AI chat message with user role. - /// - /// This method converts the user message content using and preserves - /// the participant name as the author name in the resulting message. - /// - private static Microsoft.Extensions.AI.ChatMessage AsChatMessage(this UserChatMessage userMessage) - { - Throw.IfNull(userMessage); - - return new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.User, [.. userMessage.Content.AsAIContent()]) - { - AuthorName = userMessage.ParticipantName, - RawRepresentation = userMessage - }; - } } diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/ChatOptionsExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/ChatOptionsExtensions.cs deleted file mode 100644 index f8052f9498..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/ChatOptionsExtensions.cs +++ /dev/null @@ -1,28 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. -using Microsoft.Shared.Diagnostics; -using OpenAI.Responses; - -namespace Microsoft.Extensions.AI.Agents; - -/// -/// Extension methods for -/// -public static class ChatOptionsExtensions -{ - /// - /// Disables the storage of response output in the chat options. - /// - /// Instance of - /// - public static ChatOptions WithResponseStoredOutputDisabled(this ChatOptions options) - { - Throw.IfNull(options); - - // We can use the RawRepresentationFactory to provide Response service specific - // options. Here we can indicate that we do not want the service to store the - // conversation in a service managed thread. - options.RawRepresentationFactory = (_) => new ResponseCreationOptions() { StoredOutputEnabled = false }; - - return options; - } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIAssistantClientExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIAssistantClientExtensions.cs index e048c78fae..cfba779c1e 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIAssistantClientExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIAssistantClientExtensions.cs @@ -1,9 +1,5 @@ // Copyright (c) Microsoft. All rights reserved. -using System.Text; -using System.Text.Json; -using System.Text.Json.Nodes; -using System.Text.Json.Serialization; using Microsoft.Extensions.AI; using Microsoft.Extensions.AI.Agents; using Microsoft.Extensions.Logging; @@ -24,9 +20,6 @@ namespace OpenAI; /// public static class OpenAIAssistantClientExtensions { - /// Key into AdditionalProperties used to store a strict option. - private const string StrictKey = "strictJsonSchema"; - /// /// Creates an AI agent from an using the OpenAI Assistant API. /// @@ -209,140 +202,6 @@ public static class OpenAIAssistantClientExtensions } }; -#pragma warning disable CA2000 // Dispose objects before losing scope - var chatClient = client.AsNewIChatClient(assistantId); -#pragma warning restore CA2000 // Dispose objects before losing scope - return new ChatClientAgent(chatClient, agentOptions, loggerFactory); - } - - /// Converts an Extensions function to an OpenAI assistants function tool. - private static FunctionToolDefinition ToOpenAIAssistantsFunctionToolDefinition(AIFunction aiFunction, ChatOptions? options = null) - { - bool? strict = - HasStrict(aiFunction.AdditionalProperties) ?? - HasStrict(options?.AdditionalProperties); - - return new FunctionToolDefinition(aiFunction.Name) - { - Description = aiFunction.Description, - Parameters = ToOpenAIFunctionParameters(aiFunction, strict), - StrictParameterSchemaEnabled = strict, - }; - } - - /// Extracts from an the parameters and strictness setting for use with OpenAI's APIs. - private static BinaryData ToOpenAIFunctionParameters(AIFunction aiFunction, bool? strict) - { - // Perform any desirable transformations on the function's JSON schema, if it'll be used in a strict setting. - JsonElement jsonSchema = strict is true ? - StrictSchemaTransformCache.GetOrCreateTransformedSchema(aiFunction) : - aiFunction.JsonSchema; - - // Roundtrip the schema through the ToolJson model type to remove extra properties - // and force missing ones into existence, then return the serialized UTF8 bytes as BinaryData. - var tool = jsonSchema.Deserialize(OpenAIJsonContext.Default.ToolJson)!; - var functionParameters = BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes(tool, OpenAIJsonContext.Default.ToolJson)); - - return functionParameters; - } - - /// Gets whether the properties specify that strict schema handling is desired. - private static bool? HasStrict(IReadOnlyDictionary? additionalProperties) => - additionalProperties?.TryGetValue(StrictKey, out object? strictObj) is true && - strictObj is bool strictValue ? - strictValue : null; - - private static AIJsonSchemaTransformCache StrictSchemaTransformCache { get; } = new(new() - { - DisallowAdditionalProperties = true, - ConvertBooleanSchemas = true, - MoveDefaultKeywordToDescription = true, - RequireAllProperties = true, - TransformSchemaNode = (ctx, node) => - { - // Move content from common but unsupported properties to description. In particular, we focus on properties that - // the AIJsonUtilities schema generator might produce and/or that are explicitly mentioned in the OpenAI documentation. - - if (node is JsonObject schemaObj) - { - StringBuilder? additionalDescription = null; - - ReadOnlySpan unsupportedProperties = - [ - // Produced by AIJsonUtilities but not in allow list at https://platform.openai.com/docs/guides/structured-outputs#supported-properties: - "contentEncoding", "contentMediaType", "not", - - // Explicitly mentioned at https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#key-ordering as being unsupported with some models: - "minLength", "maxLength", "pattern", "format", - "minimum", "maximum", "multipleOf", - "patternProperties", - "minItems", "maxItems", - - // Explicitly mentioned at https://learn.microsoft.com/azure/ai-services/openai/how-to/structured-outputs?pivots=programming-language-csharp&tabs=python-secure%2Cdotnet-entra-id#unsupported-type-specific-keywords - // as being unsupported with Azure OpenAI: - "unevaluatedProperties", "propertyNames", "minProperties", "maxProperties", - "unevaluatedItems", "contains", "minContains", "maxContains", "uniqueItems", - ]; - - foreach (string propName in unsupportedProperties) - { - if (schemaObj[propName] is { } propNode) - { - _ = schemaObj.Remove(propName); - AppendLine(ref additionalDescription, propName, propNode); - } - } - - if (additionalDescription is not null) - { - schemaObj["description"] = schemaObj["description"] is { } descriptionNode && descriptionNode.GetValueKind() == JsonValueKind.String ? - $"{descriptionNode.GetValue()}{Environment.NewLine}{additionalDescription}" : - additionalDescription.ToString(); - } - - return node; - - static void AppendLine(ref StringBuilder? sb, string propName, JsonNode propNode) - { - sb ??= new(); - - if (sb.Length > 0) - { - _ = sb.AppendLine(); - } - - _ = sb.Append(propName).Append(": ").Append(propNode); - } - } - - return node; - }, - }); - - /// Used to create the JSON payload for an OpenAI tool description. - internal sealed class ToolJson - { - [JsonPropertyName("type")] - public string Type { get; set; } = "object"; - - [JsonPropertyName("required")] - public HashSet Required { get; set; } = []; - - [JsonPropertyName("properties")] - public Dictionary Properties { get; set; } = []; - - [JsonPropertyName("additionalProperties")] - public bool AdditionalProperties { get; set; } + return new ChatClientAgent(client.AsIChatClient(assistantId), agentOptions, loggerFactory); } } - -/// Source-generated JSON type information for use by all OpenAI implementations. -[JsonSourceGenerationOptions(JsonSerializerDefaults.Web, - UseStringEnumConverter = true, - DefaultIgnoreCondition = JsonIgnoreCondition.WhenWritingNull, - WriteIndented = true)] -[JsonSerializable(typeof(OpenAIAssistantClientExtensions.ToolJson))] -[JsonSerializable(typeof(IDictionary))] -[JsonSerializable(typeof(string[]))] -[JsonSerializable(typeof(JsonElement))] -internal sealed partial class OpenAIJsonContext : JsonSerializerContext; diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIResponseClientExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIResponseClientExtensions.cs index c387be1e5c..fc2a6522fd 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIResponseClientExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/OpenAIResponseClientExtensions.cs @@ -33,6 +33,8 @@ public static class OpenAIResponseClientExtensions /// Thrown when is . public static AIAgent CreateAIAgent(this OpenAIResponseClient client, string? instructions = null, string? name = null, string? description = null, IList? tools = null, ILoggerFactory? loggerFactory = null) { + Throw.IfNull(client); + return client.CreateAIAgent( new ChatClientAgentOptions() { @@ -60,17 +62,6 @@ public static class OpenAIResponseClientExtensions Throw.IfNull(client); Throw.IfNull(options); -#pragma warning disable CA2000 // Dispose objects before losing scope - var chatClient = client.AsNewIChatClient(); -#pragma warning restore CA2000 // Dispose objects before losing scope - ChatClientAgent agent = new(chatClient, options, loggerFactory); - return agent; + return new ChatClientAgent(client.AsIChatClient(), options, loggerFactory); } - - /// Gets an for use with this . - /// The client. - /// An that can be used to converse via the . - /// is . - public static IChatClient AsNewIChatClient(this OpenAIResponseClient responseClient) => - new NewOpenAIResponsesChatClient(responseClient); } diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIAssistantChatClient.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIAssistantChatClient.cs deleted file mode 100644 index d02646d4d0..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIAssistantChatClient.cs +++ /dev/null @@ -1,722 +0,0 @@ -#pragma warning disable IDE0005 // Using directive is unnecessary. -#pragma warning disable IDE0073 // The file header does not match the required text -#pragma warning disable CS0436 // Type conflicts with imported type -#pragma warning disable CA1063 // Implement IDisposable Correctly - -// Licensed to the .NET Foundation under one or more agreements. -// The .NET Foundation licenses this file to you under the MIT license. - -using System.Reflection; -using System.Runtime.CompilerServices; -using System.Text; -using System.Text.Json; -using System.Text.Json.Nodes; -using Microsoft.Shared.Diagnostics; -using OpenAI; -using OpenAI.Assistants; - -#pragma warning disable CA1031 // Do not catch general exception types -#pragma warning disable SA1005 // Single line comments should begin with single space -#pragma warning disable SA1204 // Static elements should appear before instance elements -#pragma warning disable S125 // Sections of code should not be commented out -#pragma warning disable S907 // "goto" statement should not be used -#pragma warning disable S1067 // Expressions should not be too complex -#pragma warning disable S1751 // Loops with at most one iteration should be refactored -#pragma warning disable S3011 // Reflection should not be used to increase accessibility of classes, methods, or fields -#pragma warning disable S4456 // Parameter validation in yielding methods should be wrapped -#pragma warning disable S4457 // Parameter validation in "async"/"await" methods should be wrapped - -namespace Microsoft.Extensions.AI; - -/// Represents an for an OpenAI . -internal sealed class NewOpenAIAssistantsChatClient : IChatClient -{ - /// The underlying . - private readonly AssistantClient _client; - - /// Metadata for the client. - private readonly ChatClientMetadata _metadata; - - /// The ID of the agent to use. - private readonly string _assistantId; - - /// The thread ID to use if none is supplied in . - private readonly string? _defaultThreadId; - - /// List of tools associated with the assistant. - private IReadOnlyList? _assistantTools; - - /// Initializes a new instance of the class for the specified . - public NewOpenAIAssistantsChatClient(AssistantClient assistantClient, string assistantId, string? defaultThreadId) - { - _client = Throw.IfNull(assistantClient); - _assistantId = Throw.IfNullOrWhitespace(assistantId); - - _defaultThreadId = defaultThreadId; - - // https://github.com/openai/openai-dotnet/issues/215 - // The endpoint isn't currently exposed, so use reflection to get at it, temporarily. Once packages - // implement the abstractions directly rather than providing adapters on top of the public APIs, - // the package can provide such implementations separate from what's exposed in the public API. - Uri providerUrl = typeof(AssistantClient).GetField("_endpoint", BindingFlags.Public | BindingFlags.NonPublic | BindingFlags.Instance) - ?.GetValue(assistantClient) as Uri ?? OpenAIClientExtensions2.DefaultOpenAIEndpoint; - - _metadata = new("openai", providerUrl); - } - - /// Initializes a new instance of the class for the specified . - public NewOpenAIAssistantsChatClient(AssistantClient assistantClient, Assistant assistant, string? defaultThreadId) - : this(assistantClient, Throw.IfNull(assistant).Id, defaultThreadId) - { - _assistantTools = assistant.Tools; - } - - /// - public object? GetService(Type serviceType, object? serviceKey = null) => - serviceType is null ? throw new ArgumentNullException(nameof(serviceType)) : - serviceKey is not null ? null : - serviceType == typeof(ChatClientMetadata) ? _metadata : - serviceType == typeof(AssistantClient) ? _client : - serviceType.IsInstanceOfType(this) ? this : - null; - - /// - public async Task GetResponseAsync( - IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - { - // Changing the original implementation to provide a RawRepresentation as a list of RawRepresentations of the updates. - // This wouldn't be needed if the API Change Proposal below is accepted: - // https://github.com/dotnet/extensions/issues/6746 - var updates = await GetStreamingResponseAsync(messages, options, cancellationToken).ToListAsync(cancellationToken).ConfigureAwait(false); - var response = updates.ToChatResponse(); - - // Expose all the raw representations of the updates. - response.RawRepresentation = updates.Select(u => u.RawRepresentation).ToArray(); - return response; - } - - /// - public async IAsyncEnumerable GetStreamingResponseAsync( - IEnumerable messages, ChatOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default) - { - _ = Throw.IfNull(messages); - - // Extract necessary state from messages and options. - (RunCreationOptions runOptions, ToolResources? toolResources, List? toolResults) = await CreateRunOptionsAsync(messages, options, cancellationToken).ConfigureAwait(false); - - // Get the thread ID. - string? threadId = options?.ConversationId ?? _defaultThreadId; - if (threadId is null && toolResults is not null) - { - Throw.ArgumentException(nameof(messages), "No thread ID was provided, but chat messages includes tool results."); - } - - // Get any active run ID for this thread. This is necessary in case a thread has been left with an - // active run, in which all attempts other than submitting tools will fail. We thus need to cancel - // any active run on the thread. - ThreadRun? threadRun = null; - if (threadId is not null) - { - await foreach (var run in _client.GetRunsAsync( - threadId, - new RunCollectionOptions { Order = RunCollectionOrder.Descending, PageSizeLimit = 1 }, - cancellationToken: cancellationToken).ConfigureAwait(false)) - { - if (run.Status != RunStatus.Completed && run.Status != RunStatus.Cancelled && run.Status != RunStatus.Failed && run.Status != RunStatus.Expired) - { - threadRun = run; - } - - break; - } - } - - // Submit the request. - IAsyncEnumerable updates; - if (threadRun is not null && - ConvertFunctionResultsToToolOutput(toolResults, out List? toolOutputs) is { } toolRunId && - toolRunId == threadRun.Id) - { - // There's an active run and we have tool results to submit, so submit the results and continue streaming. - // This is going to ignore any additional messages in the run options, as we are only submitting tool outputs, - // but there doesn't appear to be a way to submit additional messages, and having such additional messages is rare. - updates = _client.SubmitToolOutputsToRunStreamingAsync(threadRun.ThreadId, threadRun.Id, toolOutputs, cancellationToken); - } - else - { - if (threadId is null) - { - // No thread ID was provided, so create a new thread. - ThreadCreationOptions threadCreationOptions = new() - { - ToolResources = toolResources, - }; - - foreach (var message in runOptions.AdditionalMessages) - { - threadCreationOptions.InitialMessages.Add(message); - } - - runOptions.AdditionalMessages.Clear(); - - var thread = await _client.CreateThreadAsync(threadCreationOptions, cancellationToken).ConfigureAwait(false); - threadId = thread.Value.Id; - } - else if (threadRun is not null) - { - // There was an active run; we need to cancel it before starting a new run. - _ = await _client.CancelRunAsync(threadId, threadRun.Id, cancellationToken).ConfigureAwait(false); - threadRun = null; - } - - // Now create a new run and stream the results. - updates = _client.CreateRunStreamingAsync( - threadId: threadId, - _assistantId, - runOptions, - cancellationToken); - } - - // Process each update. - string? responseId = null; - await foreach (var update in updates.ConfigureAwait(false)) - { - switch (update) - { - case ThreadUpdate tu: - threadId ??= tu.Value.Id; - goto default; - - case RunUpdate ru: - threadId ??= ru.Value.ThreadId; - responseId ??= ru.Value.Id; - - ChatResponseUpdate ruUpdate = new() - { - AuthorName = _assistantId, - ConversationId = threadId, - CreatedAt = ru.Value.CreatedAt, - MessageId = responseId, - ModelId = ru.Value.Model, - RawRepresentation = ru, - ResponseId = responseId, - Role = ChatRole.Assistant, - }; - - if (ru.Value.Usage is { } usage) - { - ruUpdate.Contents.Add(new UsageContent(new() - { - InputTokenCount = usage.InputTokenCount, - OutputTokenCount = usage.OutputTokenCount, - TotalTokenCount = usage.TotalTokenCount, - })); - } - - if (ru is RequiredActionUpdate rau && rau.ToolCallId is string toolCallId && rau.FunctionName is string functionName) - { - var fcc = OpenAIClientExtensions2.ParseCallContent( - rau.FunctionArguments, - JsonSerializer.Serialize([ru.Value.Id, toolCallId], OpenAIJsonContext.Default.StringArray), - functionName); - fcc.RawRepresentation = ru; - ruUpdate.Contents.Add(fcc); - } - - yield return ruUpdate; - break; - - case MessageContentUpdate mcu: - ChatResponseUpdate textUpdate = new(mcu.Role == MessageRole.User ? ChatRole.User : ChatRole.Assistant, mcu.Text) - { - AuthorName = _assistantId, - ConversationId = threadId, - MessageId = responseId, - RawRepresentation = mcu, - ResponseId = responseId, - }; - - // Add any annotations from the text update. The OpenAI Assistants API does not support passing these back - // into the model (MessageContent.FromXx does not support providing annotations), so they end up being one way and are dropped - // on subsequent requests. - if (mcu.TextAnnotation is { } tau) - { - string? fileId = null; - string? toolName = null; - if (!string.IsNullOrWhiteSpace(tau.InputFileId)) - { - fileId = tau.InputFileId; - toolName = "file_search"; - } - else if (!string.IsNullOrWhiteSpace(tau.OutputFileId)) - { - fileId = tau.OutputFileId; - toolName = "code_interpreter"; - } - - if (fileId is not null) - { - if (textUpdate.Contents.Count == 0) - { - // In case a chunk doesn't have text content, create one with empty text to hold the annotation. - textUpdate.Contents.Add(new TextContent(string.Empty)); - } - - (((TextContent)textUpdate.Contents[0]).Annotations ??= []).Add(new CitationAnnotation - { - RawRepresentation = tau, - AnnotatedRegions = [new TextSpanAnnotatedRegion { StartIndex = tau.StartIndex, EndIndex = tau.EndIndex }], - FileId = fileId, - ToolName = toolName, - }); - } - } - - yield return textUpdate; - break; - - default: - yield return new() - { - AuthorName = _assistantId, - ConversationId = threadId, - MessageId = responseId, - RawRepresentation = update, - ResponseId = responseId, - Role = ChatRole.Assistant, - }; - break; - } - } - } - - /// - void IDisposable.Dispose() - { - // nop - } - - /// Converts an Extensions function to an OpenAI assistants function tool. - internal static FunctionToolDefinition ToOpenAIAssistantsFunctionToolDefinition(AIFunction aiFunction, ChatOptions? options = null) - { - bool? strict = - OpenAIClientExtensions2.HasStrict(aiFunction.AdditionalProperties) ?? - OpenAIClientExtensions2.HasStrict(options?.AdditionalProperties); - - return new FunctionToolDefinition(aiFunction.Name) - { - Description = aiFunction.Description, - Parameters = OpenAIClientExtensions2.ToOpenAIFunctionParameters(aiFunction, strict), - StrictParameterSchemaEnabled = strict, - }; - } - - /// - /// Creates the to use for the request and extracts any function result contents - /// that need to be submitted as tool results. - /// - private async ValueTask<(RunCreationOptions RunOptions, ToolResources? Resources, List? ToolResults)> CreateRunOptionsAsync( - IEnumerable messages, ChatOptions? options, CancellationToken cancellationToken) - { - // Create the options instance to populate, either a fresh or using one the caller provides. - RunCreationOptions runOptions = - options?.RawRepresentationFactory?.Invoke(this) as RunCreationOptions ?? - new(); - - ToolResources? resources = null; - - // Populate the run options from the ChatOptions, if provided. - if (options is not null) - { - runOptions.MaxOutputTokenCount ??= options.MaxOutputTokens; - runOptions.ModelOverride ??= options.ModelId; - runOptions.NucleusSamplingFactor ??= options.TopP; - runOptions.Temperature ??= options.Temperature; - runOptions.AllowParallelToolCalls ??= options.AllowMultipleToolCalls; - - if (options.Tools is { Count: > 0 } tools) - { - // If the caller has provided any tool overrides, we'll assume they don't want to use the assistant's tools. - // But if they haven't, the only way we can provide our tools is via an override, whereas we'd really like to - // just add them. To handle that, we'll get all of the assistant's tools and add them to the override list - // along with our tools. - if (runOptions.ToolsOverride.Count == 0) - { - if (_assistantTools is null) - { - var assistant = await _client.GetAssistantAsync(_assistantId, cancellationToken).ConfigureAwait(false); - _assistantTools = assistant.Value.Tools; - } - - foreach (var tool in _assistantTools) - { - runOptions.ToolsOverride.Add(tool); - } - } - - // The caller can provide tools in the supplied ThreadAndRunOptions. Augment it with any supplied via ChatOptions.Tools. - foreach (AITool tool in tools) - { - switch (tool) - { - case AIFunction aiFunction: - runOptions.ToolsOverride.Add(ToOpenAIAssistantsFunctionToolDefinition(aiFunction, options)); - break; - - case HostedCodeInterpreterTool codeInterpreterTool: - var interpreterToolDef = ToolDefinition.CreateCodeInterpreter(); - runOptions.ToolsOverride.Add(interpreterToolDef); - - if (codeInterpreterTool.Inputs?.Count is > 0) - { - ThreadInitializationMessage? threadInitializationMessage = null; - foreach (var input in codeInterpreterTool.Inputs) - { - if (input is HostedFileContent hostedFile) - { - threadInitializationMessage ??= new(MessageRole.User, [MessageContent.FromText("attachments")]); - threadInitializationMessage.Attachments.Add(new(hostedFile.FileId, [interpreterToolDef])); - } - } - - if (threadInitializationMessage is not null) - { - runOptions.AdditionalMessages.Add(threadInitializationMessage); - } - } - - break; - - case HostedFileSearchTool fileSearchTool: - runOptions.ToolsOverride.Add(ToolDefinition.CreateFileSearch(fileSearchTool.MaximumResultCount)); - if (fileSearchTool.Inputs is { Count: > 0 } fileSearchInputs) - { - foreach (var input in fileSearchInputs) - { - if (input is HostedVectorStoreContent file) - { - (resources ??= new()).FileSearch ??= new(); - resources.FileSearch.VectorStoreIds.Add(file.VectorStoreId); - } - } - } - - break; - } - } - } - - // Store the tool mode, if relevant. - if (runOptions.ToolConstraint is null) - { - switch (options.ToolMode) - { - case NoneChatToolMode: - runOptions.ToolConstraint = ToolConstraint.None; - break; - - case AutoChatToolMode: - runOptions.ToolConstraint = ToolConstraint.Auto; - break; - - case RequiredChatToolMode required when required.RequiredFunctionName is { } functionName: - runOptions.ToolConstraint = new ToolConstraint(ToolDefinition.CreateFunction(functionName)); - break; - - case RequiredChatToolMode required: - runOptions.ToolConstraint = ToolConstraint.Required; - break; - } - } - - // Store the response format, if relevant. - if (runOptions.ResponseFormat is null) - { - switch (options.ResponseFormat) - { - case ChatResponseFormatText: - runOptions.ResponseFormat = AssistantResponseFormat.CreateTextFormat(); - break; - - case ChatResponseFormatJson jsonFormat when OpenAIClientExtensions2.StrictSchemaTransformCache.GetOrCreateTransformedSchema(jsonFormat) is { } jsonSchema: - runOptions.ResponseFormat = AssistantResponseFormat.CreateJsonSchemaFormat( - jsonFormat.SchemaName, - BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes(jsonSchema, OpenAIJsonContext.Default.JsonElement)), - jsonFormat.SchemaDescription, - OpenAIClientExtensions2.HasStrict(options.AdditionalProperties)); - break; - - case ChatResponseFormatJson jsonFormat: - runOptions.ResponseFormat = AssistantResponseFormat.CreateJsonObjectFormat(); - break; - } - } - } - - // Configure system instructions. - StringBuilder? instructions = null; - void AppendSystemInstructions(string? toAppend) - { - if (!string.IsNullOrEmpty(toAppend)) - { - if (instructions is null) - { - instructions = new(toAppend); - } - else - { - _ = instructions.AppendLine().AppendLine(toAppend); - } - } - } - - AppendSystemInstructions(runOptions.AdditionalInstructions); - AppendSystemInstructions(options?.Instructions); - - // Process ChatMessages. - List? functionResults = null; - foreach (var chatMessage in messages) - { - List messageContents = []; - - // Assistants doesn't support system/developer messages directly. It does support transient per-request instructions, - // so we can use the system/developer messages to build up a set of instructions that will be passed to the assistant - // as part of this request. However, in doing so, on a subsequent request that information will be lost, as there's no - // way to store per-thread instructions in the OpenAI Assistants API. We don't want to convert these to user messages, - // however, as that would then expose the system/developer messages in a way that might make the model more likely - // to include that information in its responses. System messages should ideally be instead done as instructions to - // the assistant when the assistant is created. - if (chatMessage.Role == ChatRole.System || - chatMessage.Role == OpenAIClientExtensions2.ChatRoleDeveloper) - { - foreach (var textContent in chatMessage.Contents.OfType()) - { - AppendSystemInstructions(textContent.Text); - } - - continue; - } - - foreach (AIContent content in chatMessage.Contents) - { - switch (content) - { - case AIContent when content.RawRepresentation is MessageContent rawRep: - messageContents.Add(rawRep); - break; - - case TextContent text: - messageContents.Add(MessageContent.FromText(text.Text)); - break; - - case UriContent image when image.HasTopLevelMediaType("image"): - messageContents.Add(MessageContent.FromImageUri(image.Uri)); - break; - - case FunctionResultContent result: - (functionResults ??= []).Add(result); - break; - } - } - - if (messageContents.Count > 0) - { - runOptions.AdditionalMessages.Add(new ThreadInitializationMessage( - chatMessage.Role == ChatRole.Assistant ? MessageRole.Assistant : MessageRole.User, - messageContents)); - } - } - - runOptions.AdditionalInstructions = instructions?.ToString(); - - return (runOptions, resources, functionResults); - } - - /// Convert instances to instances. - /// The tool results to process. - /// The generated list of tool outputs, if any could be created. - /// The run ID associated with the corresponding function call requests. - private static string? ConvertFunctionResultsToToolOutput(List? toolResults, out List? toolOutputs) - { - string? runId = null; - toolOutputs = null; - if (toolResults?.Count > 0) - { - foreach (var frc in toolResults) - { - // When creating the FunctionCallContext, we created it with a CallId == [runId, callId]. - // We need to extract the run ID and ensure that the ToolOutput we send back to Azure - // is only the call ID. - string[]? runAndCallIDs; - try - { - runAndCallIDs = JsonSerializer.Deserialize(frc.CallId, OpenAIJsonContext.Default.StringArray); - } - catch - { - continue; - } - - if (runAndCallIDs is null || - runAndCallIDs.Length != 2 || - string.IsNullOrWhiteSpace(runAndCallIDs[0]) || // run ID - string.IsNullOrWhiteSpace(runAndCallIDs[1]) || // call ID - (runId is not null && runId != runAndCallIDs[0])) - { - continue; - } - - runId = runAndCallIDs[0]; - (toolOutputs ??= []).Add(new(runAndCallIDs[1], frc.Result?.ToString() ?? string.Empty)); - } - } - - return runId; - } -} - -/// Provides extension methods for working with s. -internal static class OpenAIClientExtensions2 -{ - /// Key into AdditionalProperties used to store a strict option. - private const string StrictKey = "strictJsonSchema"; - - /// Gets the default OpenAI endpoint. - internal static Uri DefaultOpenAIEndpoint { get; } = new("https://api.openai.com/v1"); - - /// Gets a for "developer". - internal static ChatRole ChatRoleDeveloper { get; } = new ChatRole("developer"); - - /// Creates a new instance of parsing arguments using a specified encoding and parser. - /// The input arguments to be parsed. - /// The function call ID. - /// The function name. - /// A new instance of containing the parse result. - /// is . - /// is . - internal static FunctionCallContent ParseCallContent(string json, string callId, string name) => - FunctionCallContent.CreateFromParsedArguments(json, callId, name, - static json => JsonSerializer.Deserialize(json, OpenAIJsonContext.Default.IDictionaryStringObject)!); - - /// Creates a new instance of parsing arguments using a specified encoding and parser. - /// The input arguments to be parsed. - /// The function call ID. - /// The function name. - /// A new instance of containing the parse result. - /// is . - /// is . - internal static FunctionCallContent ParseCallContent(BinaryData utf8json, string callId, string name) => - FunctionCallContent.CreateFromParsedArguments(utf8json, callId, name, - static utf8json => JsonSerializer.Deserialize(utf8json, OpenAIJsonContext.Default.IDictionaryStringObject)!); - - /// - /// Gets the JSON schema transformer cache conforming to OpenAI strict / structured output restrictions per - /// https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#supported-schemas. - /// - internal static AIJsonSchemaTransformCache StrictSchemaTransformCache { get; } = new(new() - { - DisallowAdditionalProperties = true, - ConvertBooleanSchemas = true, - MoveDefaultKeywordToDescription = true, - RequireAllProperties = true, - TransformSchemaNode = (ctx, node) => - { - // Move content from common but unsupported properties to description. In particular, we focus on properties that - // the AIJsonUtilities schema generator might produce and/or that are explicitly mentioned in the OpenAI documentation. - - if (node is JsonObject schemaObj) - { - StringBuilder? additionalDescription = null; - - ReadOnlySpan unsupportedProperties = - [ - // Produced by AIJsonUtilities but not in allow list at https://platform.openai.com/docs/guides/structured-outputs#supported-properties: - "contentEncoding", "contentMediaType", "not", - - // Explicitly mentioned at https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#key-ordering as being unsupported with some models: - "minLength", "maxLength", "pattern", "format", - "minimum", "maximum", "multipleOf", - "patternProperties", - "minItems", "maxItems", - - // Explicitly mentioned at https://learn.microsoft.com/azure/ai-services/openai/how-to/structured-outputs?pivots=programming-language-csharp&tabs=python-secure%2Cdotnet-entra-id#unsupported-type-specific-keywords - // as being unsupported with Azure OpenAI: - "unevaluatedProperties", "propertyNames", "minProperties", "maxProperties", - "unevaluatedItems", "contains", "minContains", "maxContains", "uniqueItems", - ]; - - foreach (string propName in unsupportedProperties) - { - if (schemaObj[propName] is { } propNode) - { - _ = schemaObj.Remove(propName); - AppendLine(ref additionalDescription, propName, propNode); - } - } - - if (additionalDescription is not null) - { - schemaObj["description"] = schemaObj["description"] is { } descriptionNode && descriptionNode.GetValueKind() == JsonValueKind.String ? - $"{descriptionNode.GetValue()}{Environment.NewLine}{additionalDescription}" : - additionalDescription.ToString(); - } - - return node; - - static void AppendLine(ref StringBuilder? sb, string propName, JsonNode propNode) - { - sb ??= new(); - - if (sb.Length > 0) - { - _ = sb.AppendLine(); - } - - _ = sb.Append(propName).Append(": ").Append(propNode); - } - } - - return node; - }, - }); - - // TODO: Once we're ready to rely on C# 14 features, add an extension property ChatOptions.Strict. - - /// Gets whether the properties specify that strict schema handling is desired. - internal static bool? HasStrict(IReadOnlyDictionary? additionalProperties) => - additionalProperties?.TryGetValue(StrictKey, out object? strictObj) is true && - strictObj is bool strictValue ? - strictValue : null; - - /// Extracts from an the parameters and strictness setting for use with OpenAI's APIs. - internal static BinaryData ToOpenAIFunctionParameters(AIFunction aiFunction, bool? strict) - { - // Perform any desirable transformations on the function's JSON schema, if it'll be used in a strict setting. - JsonElement jsonSchema = strict is true ? - StrictSchemaTransformCache.GetOrCreateTransformedSchema(aiFunction) : - aiFunction.JsonSchema; - - // Roundtrip the schema through the ToolJson model type to remove extra properties - // and force missing ones into existence, then return the serialized UTF8 bytes as BinaryData. - var tool = jsonSchema.Deserialize(OpenAIJsonContext.Default.ToolJson)!; - var functionParameters = BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes(tool, OpenAIJsonContext.Default.ToolJson)); - - return functionParameters; - } -} - -/// -/// Temporary extension methods to assist with creating proposed changed instances -/// -public static class OpenAIAssistantsExtensions -{ - /// - /// Creates a new instance of an configured for the specified assistant. - /// - /// The instance used to initialize the chat client. Cannot be . - /// The unique identifier of the assistant. Cannot be or whitespace. - /// The optional default thread identifier for the chat client. Can be . - /// A new instance configured with the specified assistant and optional default thread. - public static IChatClient AsNewIChatClient(this AssistantClient client, string assistantId, string? defaultThreadId = null) => - new NewOpenAIAssistantsChatClient(Throw.IfNull(client), Throw.IfNullOrWhitespace(assistantId), defaultThreadId); -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIResponsesChatClient.cs b/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIResponsesChatClient.cs deleted file mode 100644 index bd849ad320..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/NewOpenAIResponsesChatClient.cs +++ /dev/null @@ -1,918 +0,0 @@ -#pragma warning disable IDE0073 // The file header does not match the required text -#pragma warning disable CA1063 // Implement IDisposable Correctly - -// Licensed to the .NET Foundation under one or more agreements. -// The .NET Foundation licenses this file to you under the MIT license. - -using System.ClientModel.Primitives; -using System.Reflection; -using System.Runtime.CompilerServices; -using System.Text; -using System.Text.Json; -using System.Text.Json.Nodes; -using System.Text.Json.Serialization; -using System.Text.Json.Serialization.Metadata; -using Microsoft.Shared.Diagnostics; -using OpenAI.Responses; - -#pragma warning disable S907 // "goto" statement should not be used -#pragma warning disable S1067 // Expressions should not be too complex -#pragma warning disable S3011 // Reflection should not be used to increase accessibility of classes, methods, or fields -#pragma warning disable S3604 // Member initializer values should not be redundant -#pragma warning disable SA1202 // Elements should be ordered by access -#pragma warning disable SA1204 // Static elements should appear before instance elements - -namespace Microsoft.Extensions.AI; - -/// Represents an for an . -internal sealed class NewOpenAIResponsesChatClient : IChatClient -{ - /// Type info for serializing and deserializing arbitrary JSON objects. - private static readonly JsonTypeInfo s_jsonTypeInfo = AIJsonUtilities.DefaultOptions.GetTypeInfo(typeof(object)); - - /// Metadata about the client. - private readonly ChatClientMetadata _metadata; - - /// The underlying . - private readonly OpenAIResponseClient _responseClient; - - /// Initializes a new instance of the class for the specified . - /// The underlying client. - /// is . - public NewOpenAIResponsesChatClient(OpenAIResponseClient responseClient) - { - _ = Throw.IfNull(responseClient); - - _responseClient = responseClient; - - // https://github.com/openai/openai-dotnet/issues/215 - // The endpoint and model aren't currently exposed, so use reflection to get at them, temporarily. Once packages - // implement the abstractions directly rather than providing adapters on top of the public APIs, - // the package can provide such implementations separate from what's exposed in the public API. - Uri providerUrl = typeof(OpenAIResponseClient).GetField("_endpoint", BindingFlags.Public | BindingFlags.NonPublic | BindingFlags.Instance) - ?.GetValue(responseClient) as Uri ?? OpenAIClientExtensions3.DefaultOpenAIEndpoint; - string? model = typeof(OpenAIResponseClient).GetField("_model", BindingFlags.Public | BindingFlags.NonPublic | BindingFlags.Instance) - ?.GetValue(responseClient) as string; - - _metadata = new("openai", providerUrl, model); - } - - /// - object? IChatClient.GetService(Type serviceType, object? serviceKey) - { - _ = Throw.IfNull(serviceType); - - return - serviceKey is not null ? null : - serviceType == typeof(ChatClientMetadata) ? _metadata : - serviceType == typeof(OpenAIResponseClient) ? _responseClient : - serviceType.IsInstanceOfType(this) ? this : - null; - } - - /// - public async Task GetResponseAsync( - IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - { - _ = Throw.IfNull(messages); - - // Convert the inputs into what OpenAIResponseClient expects. - var openAIResponseItems = ToOpenAIResponseItems(messages, options); - var openAIOptions = ToOpenAIResponseCreationOptions(options); - - // Make the call to the OpenAIResponseClient. - var openAIResponse = (await _responseClient.CreateResponseAsync(openAIResponseItems, openAIOptions, cancellationToken).ConfigureAwait(false)).Value; - - // Convert the response to a ChatResponse. - return FromOpenAIResponse(openAIResponse, openAIOptions); - } - - internal static ChatResponse FromOpenAIResponse(OpenAIResponse openAIResponse, ResponseCreationOptions? openAIOptions) - { - // Convert and return the results. - ChatResponse response = new() - { - ConversationId = openAIOptions?.StoredOutputEnabled is false ? null : openAIResponse.Id, - CreatedAt = openAIResponse.CreatedAt, - FinishReason = ToFinishReason(openAIResponse.IncompleteStatusDetails?.Reason), - ModelId = openAIResponse.Model, - RawRepresentation = openAIResponse, - ResponseId = openAIResponse.Id, - Usage = ToUsageDetails(openAIResponse), - }; - - if (!string.IsNullOrEmpty(openAIResponse.EndUserId)) - { - (response.AdditionalProperties ??= [])[nameof(openAIResponse.EndUserId)] = openAIResponse.EndUserId; - } - - if (openAIResponse.Error is not null) - { - (response.AdditionalProperties ??= [])[nameof(openAIResponse.Error)] = openAIResponse.Error; - } - - if (openAIResponse.OutputItems is not null) - { - response.Messages = [.. ToChatMessages(openAIResponse.OutputItems)]; - - if (response.Messages.LastOrDefault() is { } lastMessage && openAIResponse.Error is { } error) - { - lastMessage.Contents.Add(new ErrorContent(error.Message) { ErrorCode = error.Code.ToString() }); - } - - foreach (var message in response.Messages) - { - message.CreatedAt ??= openAIResponse.CreatedAt; - } - } - - return response; - } - - internal static IEnumerable ToChatMessages(IEnumerable items) - { - ChatMessage? message = null; - - foreach (ResponseItem outputItem in items) - { - message ??= new(ChatRole.Assistant, (string?)null); - - switch (outputItem) - { - case MessageResponseItem messageItem: - if (message.MessageId is not null && message.MessageId != messageItem.Id) - { - yield return message; - message = new ChatMessage(); - } - - message.MessageId = messageItem.Id; - message.RawRepresentation = messageItem; - message.Role = ToChatRole(messageItem.Role); - ((List)message.Contents).AddRange(ToAIContents(messageItem.Content)); - break; - - case ReasoningResponseItem reasoningItem when reasoningItem.GetSummaryText() is string summary: - message.Contents.Add(new TextReasoningContent(summary) { RawRepresentation = outputItem }); - break; - - case FunctionCallResponseItem functionCall: - var fcc = OpenAIClientExtensions3.ParseCallContent(functionCall.FunctionArguments, functionCall.CallId, functionCall.FunctionName); - fcc.RawRepresentation = outputItem; - message.Contents.Add(fcc); - break; - - case FunctionCallOutputResponseItem functionCallOutputItem: - message.Contents.Add(new FunctionResultContent(functionCallOutputItem.CallId, functionCallOutputItem.FunctionOutput) { RawRepresentation = functionCallOutputItem }); - break; - - default: - message.Contents.Add(new() { RawRepresentation = outputItem }); - break; - } - } - - if (message is not null) - { - yield return message; - } - } - - /// - public IAsyncEnumerable GetStreamingResponseAsync( - IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - { - _ = Throw.IfNull(messages); - - var openAIResponseItems = ToOpenAIResponseItems(messages, options); - var openAIOptions = ToOpenAIResponseCreationOptions(options); - - var streamingUpdates = _responseClient.CreateResponseStreamingAsync(openAIResponseItems, openAIOptions, cancellationToken); - - return FromOpenAIStreamingResponseUpdatesAsync(streamingUpdates, openAIOptions, cancellationToken); - } - - internal static async IAsyncEnumerable FromOpenAIStreamingResponseUpdatesAsync( - IAsyncEnumerable streamingResponseUpdates, ResponseCreationOptions? options, [EnumeratorCancellation] CancellationToken cancellationToken = default) - { - DateTimeOffset? createdAt = null; - string? responseId = null; - string? conversationId = null; - string? modelId = null; - string? lastMessageId = null; - ChatRole? lastRole = null; - Dictionary outputIndexToMessages = []; - Dictionary? functionCallInfos = null; - - await foreach (var streamingUpdate in streamingResponseUpdates.WithCancellation(cancellationToken).ConfigureAwait(false)) - { - // Create an update populated with the current state of the response. - ChatResponseUpdate CreateUpdate(AIContent? content = null) => - new(lastRole, content is not null ? [content] : null) - { - ConversationId = conversationId, - CreatedAt = createdAt, - MessageId = lastMessageId, - ModelId = modelId, - RawRepresentation = streamingUpdate, - ResponseId = responseId, - }; - - switch (streamingUpdate) - { - case StreamingResponseCreatedUpdate createdUpdate: - createdAt = createdUpdate.Response.CreatedAt; - responseId = createdUpdate.Response.Id; - conversationId = options?.StoredOutputEnabled is false ? null : responseId; - modelId = createdUpdate.Response.Model; - goto default; - - case StreamingResponseCompletedUpdate completedUpdate: - { - var update = CreateUpdate(ToUsageDetails(completedUpdate.Response) is { } usage ? new UsageContent(usage) : null); - update.FinishReason = - ToFinishReason(completedUpdate.Response?.IncompleteStatusDetails?.Reason) ?? - (functionCallInfos is not null ? ChatFinishReason.ToolCalls : - ChatFinishReason.Stop); - yield return update; - break; - } - - case StreamingResponseOutputItemAddedUpdate outputItemAddedUpdate: - switch (outputItemAddedUpdate.Item) - { - case MessageResponseItem mri: - outputIndexToMessages[outputItemAddedUpdate.OutputIndex] = mri; - break; - - case FunctionCallResponseItem fcri: - (functionCallInfos ??= [])[outputItemAddedUpdate.OutputIndex] = new(fcri); - break; - } - - goto default; - - case StreamingResponseOutputItemDoneUpdate outputItemDoneUpdate: - _ = outputIndexToMessages.Remove(outputItemDoneUpdate.OutputIndex); - - if (outputItemDoneUpdate.Item is MessageResponseItem item && - item.Content is { Count: > 0 } content && - content.Any(c => c.OutputTextAnnotations is { Count: > 0 })) - { - AIContent annotatedContent = new(); - foreach (var c in content) - { - PopulateAnnotations(c, annotatedContent); - } - - yield return CreateUpdate(annotatedContent); - break; - } - - goto default; - - case StreamingResponseOutputTextDeltaUpdate outputTextDeltaUpdate: - { - _ = outputIndexToMessages.TryGetValue(outputTextDeltaUpdate.OutputIndex, out MessageResponseItem? messageItem); - lastMessageId = messageItem?.Id; - lastRole = ToChatRole(messageItem?.Role); - - yield return CreateUpdate(new TextContent(outputTextDeltaUpdate.Delta)); - break; - } - - case StreamingResponseFunctionCallArgumentsDeltaUpdate functionCallArgumentsDeltaUpdate: - { - if (functionCallInfos?.TryGetValue(functionCallArgumentsDeltaUpdate.OutputIndex, out FunctionCallInfo? callInfo) is true) - { - _ = (callInfo.Arguments ??= new()).Append(functionCallArgumentsDeltaUpdate.Delta); - } - - goto default; - } - - case StreamingResponseFunctionCallArgumentsDoneUpdate functionCallOutputDoneUpdate: - { - if (functionCallInfos?.TryGetValue(functionCallOutputDoneUpdate.OutputIndex, out FunctionCallInfo? callInfo) is true) - { - _ = functionCallInfos.Remove(functionCallOutputDoneUpdate.OutputIndex); - - var fcc = OpenAIClientExtensions3.ParseCallContent( - callInfo.Arguments?.ToString() ?? string.Empty, - callInfo.ResponseItem.CallId, - callInfo.ResponseItem.FunctionName); - - lastMessageId = callInfo.ResponseItem.Id; - lastRole = ChatRole.Assistant; - - yield return CreateUpdate(fcc); - break; - } - - goto default; - } - - case StreamingResponseErrorUpdate errorUpdate: - yield return CreateUpdate(new ErrorContent(errorUpdate.Message) - { - ErrorCode = errorUpdate.Code, - Details = errorUpdate.Param, - }); - break; - - case StreamingResponseRefusalDoneUpdate refusalDone: - yield return CreateUpdate(new ErrorContent(refusalDone.Refusal) - { - ErrorCode = nameof(ResponseContentPart.Refusal), - }); - break; - - default: - { - // Capture streaming thinking contents - if (streamingUpdate.GetType().Name == "InternalResponseReasoningSummaryTextDeltaEvent") - { - var updateJson = JsonSerializer.Deserialize( - JsonSerializer.Serialize(streamingUpdate, s_jsonTypeInfo), - OpenAIJsonContext2.Default.JsonElement); - - if (updateJson.TryGetProperty("delta", out var deltaProperty)) - { - yield return CreateUpdate(new TextReasoningContent(deltaProperty.GetString())); - break; - } - } - - yield return CreateUpdate(); - break; - } - } - } - } - - /// - void IDisposable.Dispose() - { - // Nothing to dispose. Implementation required for the IChatClient interface. - } - - internal static ResponseTool ToResponseTool(AIFunction aiFunction, ChatOptions? options = null) - { - bool? strict = - OpenAIClientExtensions3.HasStrict(aiFunction.AdditionalProperties) ?? - OpenAIClientExtensions3.HasStrict(options?.AdditionalProperties); - - return ResponseTool.CreateFunctionTool( - aiFunction.Name, - aiFunction.Description, - OpenAIClientExtensions3.ToOpenAIFunctionParameters(aiFunction, strict), - strict ?? false); - } - - /// Creates a from a . - private static ChatRole ToChatRole(OpenAI.Responses.MessageRole? role) => - role switch - { - OpenAI.Responses.MessageRole.System => ChatRole.System, - OpenAI.Responses.MessageRole.Developer => OpenAIClientExtensions3.ChatRoleDeveloper, - OpenAI.Responses.MessageRole.User => ChatRole.User, - _ => ChatRole.Assistant, - }; - - /// Creates a from a . - private static ChatFinishReason? ToFinishReason(ResponseIncompleteStatusReason? statusReason) => - statusReason == ResponseIncompleteStatusReason.ContentFilter ? ChatFinishReason.ContentFilter : - statusReason == ResponseIncompleteStatusReason.MaxOutputTokens ? ChatFinishReason.Length : - null; - - /// Converts a to a . - private ResponseCreationOptions ToOpenAIResponseCreationOptions(ChatOptions? options) - { - if (options is null) - { - return new ResponseCreationOptions(); - } - - if (options.RawRepresentationFactory?.Invoke(this) is not ResponseCreationOptions result) - { - result = new ResponseCreationOptions(); - } - - // Handle strongly-typed properties. - result.MaxOutputTokenCount ??= options.MaxOutputTokens; - result.ParallelToolCallsEnabled ??= options.AllowMultipleToolCalls; - result.PreviousResponseId ??= options.ConversationId; - result.Temperature ??= options.Temperature; - result.TopP ??= options.TopP; - - if (options.Instructions is { } instructions) - { - result.Instructions = string.IsNullOrEmpty(result.Instructions) ? - instructions : - $"{result.Instructions}{Environment.NewLine}{instructions}"; - } - - // Populate tools if there are any. - if (options.Tools is { Count: > 0 } tools) - { - foreach (AITool tool in tools) - { - switch (tool) - { - case AIFunction aiFunction: - result.Tools.Add(ToResponseTool(aiFunction, options)); - break; - - case HostedWebSearchTool webSearchTool: - WebSearchUserLocation? location = null; - if (webSearchTool.AdditionalProperties.TryGetValue(nameof(WebSearchUserLocation), out object? objLocation)) - { - location = objLocation as WebSearchUserLocation; - } - - WebSearchContextSize? size = null; - if (webSearchTool.AdditionalProperties.TryGetValue(nameof(WebSearchContextSize), out object? objSize) && - objSize is WebSearchContextSize) - { - size = (WebSearchContextSize)objSize; - } - - result.Tools.Add(ResponseTool.CreateWebSearchTool(location, size)); - break; - - case HostedFileSearchTool fileSearchTool: - result.Tools.Add(ResponseTool.CreateFileSearchTool( - fileSearchTool.Inputs?.OfType().Select(c => c.VectorStoreId) ?? [], - fileSearchTool.MaximumResultCount)); - break; - - case HostedCodeInterpreterTool codeTool: - string json; - if (codeTool.Inputs is { Count: > 0 } inputs) - { - string jsonArray = JsonSerializer.Serialize( - inputs.OfType().Select(c => c.FileId), - OpenAIJsonContext2.Default.IEnumerableString); - json = $$"""{"type":"code_interpreter","container":{"type":"auto",files:{{jsonArray}}} }"""; - } - else - { - json = """{"type":"code_interpreter","container":"auto"}"""; - } - - result.Tools.Add(ModelReaderWriter.Read(BinaryData.FromString(json))); - break; - } - } - - if (result.ToolChoice is null && result.Tools.Count > 0) - { - switch (options.ToolMode) - { - case NoneChatToolMode: - result.ToolChoice = ResponseToolChoice.CreateNoneChoice(); - break; - - case AutoChatToolMode: - case null: - result.ToolChoice = ResponseToolChoice.CreateAutoChoice(); - break; - - case RequiredChatToolMode required: - result.ToolChoice = required.RequiredFunctionName is not null ? - ResponseToolChoice.CreateFunctionChoice(required.RequiredFunctionName) : - ResponseToolChoice.CreateRequiredChoice(); - break; - } - } - } - - if (result.TextOptions is null) - { - if (options.ResponseFormat is ChatResponseFormatText) - { - result.TextOptions = new() - { - TextFormat = ResponseTextFormat.CreateTextFormat() - }; - } - else if (options.ResponseFormat is ChatResponseFormatJson jsonFormat) - { - result.TextOptions = new() - { - TextFormat = OpenAIClientExtensions3.StrictSchemaTransformCache.GetOrCreateTransformedSchema(jsonFormat) is { } jsonSchema ? - ResponseTextFormat.CreateJsonSchemaFormat( - jsonFormat.SchemaName ?? "json_schema", - BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes(jsonSchema, OpenAIJsonContext2.Default.JsonElement)), - jsonFormat.SchemaDescription, - OpenAIClientExtensions3.HasStrict(options.AdditionalProperties)) : - ResponseTextFormat.CreateJsonObjectFormat(), - }; - } - } - - return result; - } - - /// Convert a sequence of s to s. - internal static IEnumerable ToOpenAIResponseItems(IEnumerable inputs, ChatOptions? options) - { - _ = options; // currently unused - - foreach (ChatMessage input in inputs) - { - if (input.Role == ChatRole.System || - input.Role == OpenAIClientExtensions3.ChatRoleDeveloper) - { - string text = input.Text; - if (!string.IsNullOrWhiteSpace(text)) - { - yield return input.Role == ChatRole.System ? - ResponseItem.CreateSystemMessageItem(text) : - ResponseItem.CreateDeveloperMessageItem(text); - } - - continue; - } - - if (input.Role == ChatRole.User) - { - yield return ResponseItem.CreateUserMessageItem(ToResponseContentParts(input.Contents)); - continue; - } - - if (input.Role == ChatRole.Tool) - { - foreach (AIContent item in input.Contents) - { - switch (item) - { - case AIContent when item.RawRepresentation is ResponseItem rawRep: - yield return rawRep; - break; - - case FunctionResultContent resultContent: - string? result = resultContent.Result as string; - if (result is null && resultContent.Result is not null) - { - try - { - result = JsonSerializer.Serialize(resultContent.Result, AIJsonUtilities.DefaultOptions.GetTypeInfo(typeof(object))); - } - catch (NotSupportedException) - { - // If the type can't be serialized, skip it. - } - } - - yield return ResponseItem.CreateFunctionCallOutputItem(resultContent.CallId, result ?? string.Empty); - break; - } - } - - continue; - } - - if (input.Role == ChatRole.Assistant) - { - foreach (AIContent item in input.Contents) - { - switch (item) - { - case AIContent when item.RawRepresentation is ResponseItem rawRep: - yield return rawRep; - break; - - case TextContent textContent: - yield return ResponseItem.CreateAssistantMessageItem(textContent.Text); - break; - - case TextReasoningContent reasoningContent: - yield return ResponseItem.CreateReasoningItem(reasoningContent.Text); - break; - - case FunctionCallContent callContent: - yield return ResponseItem.CreateFunctionCallItem( - callContent.CallId, - callContent.Name, - BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes( - callContent.Arguments, - AIJsonUtilities.DefaultOptions.GetTypeInfo(typeof(IDictionary))))); - break; - } - } - - continue; - } - } - } - - /// Extract usage details from an . - private static UsageDetails? ToUsageDetails(OpenAIResponse? openAIResponse) - { - UsageDetails? ud = null; - if (openAIResponse?.Usage is { } usage) - { - ud = new() - { - InputTokenCount = usage.InputTokenCount, - OutputTokenCount = usage.OutputTokenCount, - TotalTokenCount = usage.TotalTokenCount, - }; - - if (usage.InputTokenDetails is { } inputDetails) - { - ud.AdditionalCounts ??= []; - ud.AdditionalCounts.Add($"{nameof(usage.InputTokenDetails)}.{nameof(inputDetails.CachedTokenCount)}", inputDetails.CachedTokenCount); - } - - if (usage.OutputTokenDetails is { } outputDetails) - { - ud.AdditionalCounts ??= []; - ud.AdditionalCounts.Add($"{nameof(usage.OutputTokenDetails)}.{nameof(outputDetails.ReasoningTokenCount)}", outputDetails.ReasoningTokenCount); - } - } - - return ud; - } - - /// Convert a sequence of s to a list of . - private static List ToAIContents(IEnumerable contents) - { - List results = []; - - foreach (ResponseContentPart part in contents) - { - switch (part.Kind) - { - case ResponseContentPartKind.InputText or ResponseContentPartKind.OutputText: - TextContent text = new(part.Text) { RawRepresentation = part }; - PopulateAnnotations(part, text); - results.Add(text); - break; - - case ResponseContentPartKind.InputFile: - if (!string.IsNullOrWhiteSpace(part.InputImageFileId)) - { - results.Add(new HostedFileContent(part.InputImageFileId) { RawRepresentation = part }); - } - else if (!string.IsNullOrWhiteSpace(part.InputFileId)) - { - results.Add(new HostedFileContent(part.InputFileId) { RawRepresentation = part }); - } - else if (part.InputFileBytes is not null) - { - results.Add(new DataContent(part.InputFileBytes, part.InputFileBytesMediaType ?? "application/octet-stream") - { - Name = part.InputFilename, - RawRepresentation = part, - }); - } - - break; - - case ResponseContentPartKind.Refusal: - results.Add(new ErrorContent(part.Refusal) - { - ErrorCode = nameof(ResponseContentPartKind.Refusal), - RawRepresentation = part, - }); - break; - - default: - results.Add(new() { RawRepresentation = part }); - break; - } - } - - return results; - } - - /// Converts any annotations from and stores them in . - private static void PopulateAnnotations(ResponseContentPart source, AIContent destination) - { - if (source.OutputTextAnnotations is { Count: > 0 }) - { - foreach (var ota in source.OutputTextAnnotations) - { - (destination.Annotations ??= []).Add(new CitationAnnotation - { - RawRepresentation = ota, - AnnotatedRegions = [new TextSpanAnnotatedRegion { StartIndex = ota.UriCitationStartIndex, EndIndex = ota.UriCitationEndIndex }], - Title = ota.UriCitationTitle, - Url = ota.UriCitationUri, - FileId = ota.FileCitationFileId ?? ota.FilePathFileId, - }); - } - } - } - - /// Convert a list of s to a list of . - private static List ToResponseContentParts(IList contents) - { - List parts = []; - foreach (var content in contents) - { - switch (content) - { - case AIContent when content.RawRepresentation is ResponseContentPart rawRep: - parts.Add(rawRep); - break; - - case TextContent textContent: - parts.Add(ResponseContentPart.CreateInputTextPart(textContent.Text)); - break; - - case UriContent uriContent when uriContent.HasTopLevelMediaType("image"): - parts.Add(ResponseContentPart.CreateInputImagePart(uriContent.Uri)); - break; - - case DataContent dataContent when dataContent.HasTopLevelMediaType("image"): - parts.Add(ResponseContentPart.CreateInputImagePart(BinaryData.FromBytes(dataContent.Data), dataContent.MediaType)); - break; - - case DataContent dataContent when dataContent.MediaType.StartsWith("application/pdf", StringComparison.OrdinalIgnoreCase): - parts.Add(ResponseContentPart.CreateInputFilePart(BinaryData.FromBytes(dataContent.Data), dataContent.MediaType, dataContent.Name ?? $"{Guid.NewGuid():N}.pdf")); - break; - - case HostedFileContent fileContent: - parts.Add(ResponseContentPart.CreateInputFilePart(fileContent.FileId)); - break; - - case ErrorContent errorContent when errorContent.ErrorCode == nameof(ResponseContentPartKind.Refusal): - parts.Add(ResponseContentPart.CreateRefusalPart(errorContent.Message)); - break; - } - } - - if (parts.Count == 0) - { - parts.Add(ResponseContentPart.CreateInputTextPart(string.Empty)); - } - - return parts; - } - - /// POCO representing function calling info. - /// Used to concatenation information for a single function call from across multiple streaming updates. - private sealed class FunctionCallInfo(FunctionCallResponseItem item) - { - public readonly FunctionCallResponseItem ResponseItem = item; - public StringBuilder? Arguments; - } -} - -internal static class OpenAIClientExtensions3 -{ - /// Key into AdditionalProperties used to store a strict option. - private const string StrictKey = "strictJsonSchema"; - - /// Gets the default OpenAI endpoint. - internal static Uri DefaultOpenAIEndpoint { get; } = new("https://api.openai.com/v1"); - - /// Gets a for "developer". - internal static ChatRole ChatRoleDeveloper { get; } = new ChatRole("developer"); - - /// - /// Gets the JSON schema transformer cache conforming to OpenAI strict / structured output restrictions per - /// https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#supported-schemas. - /// - internal static AIJsonSchemaTransformCache StrictSchemaTransformCache { get; } = new(new() - { - DisallowAdditionalProperties = true, - ConvertBooleanSchemas = true, - MoveDefaultKeywordToDescription = true, - RequireAllProperties = true, - TransformSchemaNode = (ctx, node) => - { - // Move content from common but unsupported properties to description. In particular, we focus on properties that - // the AIJsonUtilities schema generator might produce and/or that are explicitly mentioned in the OpenAI documentation. - - if (node is JsonObject schemaObj) - { - StringBuilder? additionalDescription = null; - - ReadOnlySpan unsupportedProperties = - [ - // Produced by AIJsonUtilities but not in allow list at https://platform.openai.com/docs/guides/structured-outputs#supported-properties: - "contentEncoding", "contentMediaType", "not", - - // Explicitly mentioned at https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses#key-ordering as being unsupported with some models: - "minLength", "maxLength", "pattern", "format", - "minimum", "maximum", "multipleOf", - "patternProperties", - "minItems", "maxItems", - - // Explicitly mentioned at https://learn.microsoft.com/azure/ai-services/openai/how-to/structured-outputs?pivots=programming-language-csharp&tabs=python-secure%2Cdotnet-entra-id#unsupported-type-specific-keywords - // as being unsupported with Azure OpenAI: - "unevaluatedProperties", "propertyNames", "minProperties", "maxProperties", - "unevaluatedItems", "contains", "minContains", "maxContains", "uniqueItems", - ]; - - foreach (string propName in unsupportedProperties) - { - if (schemaObj[propName] is { } propNode) - { - _ = schemaObj.Remove(propName); - AppendLine(ref additionalDescription, propName, propNode); - } - } - - if (additionalDescription is not null) - { - schemaObj["description"] = schemaObj["description"] is { } descriptionNode && descriptionNode.GetValueKind() == JsonValueKind.String ? - $"{descriptionNode.GetValue()}{Environment.NewLine}{additionalDescription}" : - additionalDescription.ToString(); - } - - return node; - - static void AppendLine(ref StringBuilder? sb, string propName, JsonNode propNode) - { - sb ??= new(); - - if (sb.Length > 0) - { - _ = sb.AppendLine(); - } - - _ = sb.Append(propName).Append(": ").Append(propNode); - } - } - - return node; - }, - }); - - /// Gets whether the properties specify that strict schema handling is desired. - internal static bool? HasStrict(IReadOnlyDictionary? additionalProperties) => - additionalProperties?.TryGetValue(StrictKey, out object? strictObj) is true && - strictObj is bool strictValue ? - strictValue : null; - - /// Extracts from an the parameters and strictness setting for use with OpenAI's APIs. - internal static BinaryData ToOpenAIFunctionParameters(AIFunction aiFunction, bool? strict) - { - // Perform any desirable transformations on the function's JSON schema, if it'll be used in a strict setting. - JsonElement jsonSchema = strict is true ? - StrictSchemaTransformCache.GetOrCreateTransformedSchema(aiFunction) : - aiFunction.JsonSchema; - - // Roundtrip the schema through the ToolJson model type to remove extra properties - // and force missing ones into existence, then return the serialized UTF8 bytes as BinaryData. - var tool = JsonSerializer.Deserialize(jsonSchema, OpenAIJsonContext2.Default.ToolJson)!; - var functionParameters = BinaryData.FromBytes(JsonSerializer.SerializeToUtf8Bytes(tool, OpenAIJsonContext2.Default.ToolJson)); - - return functionParameters; - } - - /// Creates a new instance of parsing arguments using a specified encoding and parser. - /// The input arguments to be parsed. - /// The function call ID. - /// The function name. - /// A new instance of containing the parse result. - /// is . - /// is . - internal static FunctionCallContent ParseCallContent(string json, string callId, string name) => - FunctionCallContent.CreateFromParsedArguments(json, callId, name, - static json => JsonSerializer.Deserialize(json, OpenAIJsonContext2.Default.IDictionaryStringObject)!); - - /// Creates a new instance of parsing arguments using a specified encoding and parser. - /// The input arguments to be parsed. - /// The function call ID. - /// The function name. - /// A new instance of containing the parse result. - /// is . - /// is . - internal static FunctionCallContent ParseCallContent(BinaryData utf8json, string callId, string name) => - FunctionCallContent.CreateFromParsedArguments(utf8json, callId, name, - static utf8json => JsonSerializer.Deserialize(utf8json, OpenAIJsonContext2.Default.IDictionaryStringObject)!); - - /// Used to create the JSON payload for an OpenAI tool description. - internal sealed class ToolJson - { - [JsonPropertyName("type")] - public string Type { get; set; } = "object"; - - [JsonPropertyName("required")] - public HashSet Required { get; set; } = []; - - [JsonPropertyName("properties")] - public Dictionary Properties { get; set; } = []; - - [JsonPropertyName("additionalProperties")] - public bool AdditionalProperties { get; set; } - } -} - -/// Source-generated JSON type information for use by all OpenAI implementations. -[JsonSourceGenerationOptions(JsonSerializerDefaults.Web, - UseStringEnumConverter = true, - DefaultIgnoreCondition = JsonIgnoreCondition.WhenWritingNull, - WriteIndented = true)] -[JsonSerializable(typeof(OpenAIClientExtensions3.ToolJson))] -[JsonSerializable(typeof(IDictionary))] -[JsonSerializable(typeof(string[]))] -[JsonSerializable(typeof(IEnumerable))] -[JsonSerializable(typeof(JsonElement))] -internal sealed partial class OpenAIJsonContext2 : JsonSerializerContext; diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/AgentAIFunctionFactory.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/AgentAIFunctionFactory.cs new file mode 100644 index 0000000000..76f8f8fe12 --- /dev/null +++ b/dotnet/src/Microsoft.Extensions.AI.Agents/AgentAIFunctionFactory.cs @@ -0,0 +1,39 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System.Threading; +using System.Threading.Tasks; +using Microsoft.Shared.Diagnostics; +using static Microsoft.Extensions.AI.Agents.OpenTelemetryConsts.GenAI; + +namespace Microsoft.Extensions.AI.Agents; + +/// +/// Provides factory methods for creating implementations of backed by an . +/// +public static class AgentAIFunctionFactory +{ + /// + /// Creates a that will invoke the provided Agent. + /// + /// The to be represented via the created . + /// Metadata to use to override defaults inferred from . + /// The created for invoking the . + public static AIFunction CreateFromAgent( + AIAgent agent, + AIFunctionFactoryOptions? options = null) + { + Throw.IfNull(agent); + + async Task RunAgentAsync(string query, CancellationToken cancellationToken) + { + var response = await agent.RunAsync(query, cancellationToken: cancellationToken).ConfigureAwait(false); + return response.Text; + } + + return AIFunctionFactory.Create(RunAgentAsync, options ?? new() + { + Name = agent.Name, + Description = agent.Description, + }); + } +} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientAgent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientAgent.cs index 76bb906a8d..f100fee198 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientAgent.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientAgent.cs @@ -344,9 +344,9 @@ public sealed class ChatClientAgent : AIAgent // Add any existing messages from the thread to the messages to be sent to the chat client. List threadMessages = []; - await foreach (ChatMessage message in thread.GetMessagesAsync(cancellationToken).ConfigureAwait(false)) + if (thread.MessageStore is not null) { - threadMessages.Add(message); + threadMessages.AddRange(await thread.MessageStore.GetMessagesAsync(cancellationToken).ConfigureAwait(false)); } // Add the input messages to the end of thread messages. diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientExtensions.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientExtensions.cs index 045dc3ef27..1abe056741 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientExtensions.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents/ChatCompletion/ChatClientExtensions.cs @@ -1,6 +1,7 @@ // Copyright (c) Microsoft. All rights reserved. using System; +using System.Diagnostics; using Microsoft.Extensions.DependencyInjection; using Microsoft.Extensions.Logging; @@ -18,13 +19,13 @@ internal static class ChatClientExtensions chatBuilder.UseAgentInvocation(); } - if (chatClient.GetService() is null && chatClient.GetService() is null) + if (chatClient.GetService() is null) { _ = chatBuilder.Use((IChatClient innerClient, IServiceProvider services) => { var loggerFactory = services.GetService(); - return new NewFunctionInvokingChatClient(innerClient, loggerFactory, services); + return new FunctionInvokingChatClient(innerClient, loggerFactory, services); }); } @@ -33,17 +34,9 @@ internal static class ChatClientExtensions if (options?.ChatOptions?.Tools is { Count: > 0 }) { // When tools are provided in the constructor, set the tools for the whole lifecycle of the chat client - var newFunctionService = agentChatClient.GetService(); - var oldFunctionService = agentChatClient.GetService(); - - if (newFunctionService is not null) - { - newFunctionService.AdditionalTools = options.ChatOptions.Tools; - } - else - { - oldFunctionService!.AdditionalTools = options.ChatOptions.Tools; - } + var functionService = agentChatClient.GetService(); + Debug.Assert(functionService is not null, "FunctionInvokingChatClient should be registered in the chat client."); + functionService!.AdditionalTools = options.ChatOptions.Tools; } return agentChatClient; diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/ApprovalRequiredAIFunction.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/ApprovalRequiredAIFunction.cs deleted file mode 100644 index f1913efb0f..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/ApprovalRequiredAIFunction.cs +++ /dev/null @@ -1,40 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -using System; -using System.Threading.Tasks; -using Microsoft.Shared.Diagnostics; - -namespace Microsoft.Extensions.AI; - -/// -/// Marks an existing with additional metadata to indicate that it requires approval. -/// -/// The that requires approval. -public sealed class ApprovalRequiredAIFunction(AIFunction function) : DelegatingAIFunction(function) -{ - /// - /// An optional callback that can be used to determine if the function call requires approval, instead of the default behavior, which is to always require approval. - /// - public Func> RequiresApprovalCallback { get; set; } = _ => new(true); - - /// - /// Context object that provides information about the function call that requires approval. - /// - public sealed class ApprovalContext - { - /// - /// Initializes a new instance of the class. - /// - /// The containing the details of the invocation. - /// is null. - public ApprovalContext(FunctionCallContent functionCall) - { - this.FunctionCall = Throw.IfNull(functionCall); - } - - /// - /// Gets the containing the details of the invocation that will be made if approval is granted. - /// - public FunctionCallContent FunctionCall { get; } - } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/LoggingHelpers.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/LoggingHelpers.cs deleted file mode 100644 index 6a0e13677f..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/LoggingHelpers.cs +++ /dev/null @@ -1,40 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// WARNING: -// This class has been temporarily copied here from MEAI, to allow prototyping -// functionality that will be moved to MEAI in the future. -// This file is not intended to be modified. - -#pragma warning disable CA1031 // Do not catch general exception types -#pragma warning disable S108 // Nested blocks of code should not be left empty -#pragma warning disable S2486 // Generic exceptions should not be ignored - -using System.Diagnostics.CodeAnalysis; -using System.Text.Json; - -namespace Microsoft.Extensions.AI; - -/// Provides internal helpers for implementing logging. -[ExcludeFromCodeCoverage] -internal static class LoggingHelpers -{ - /// Serializes as JSON for logging purposes. - public static string AsJson(T value, JsonSerializerOptions? options) - { - if (options?.TryGetTypeInfo(typeof(T), out var typeInfo) is true || - AIJsonUtilities.DefaultOptions.TryGetTypeInfo(typeof(T), out typeInfo)) - { - try - { - return JsonSerializer.Serialize(value, typeInfo); - } - catch - { - } - } - - // If we're unable to get a type info for the value, or if we fail to serialize, - // return an empty JSON object. We do not want lack of type info to disrupt application behavior with exceptions. - return "{}"; - } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/NewFunctionInvokingChatClient.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/NewFunctionInvokingChatClient.cs deleted file mode 100644 index 2b41af5671..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/NewFunctionInvokingChatClient.cs +++ /dev/null @@ -1,1553 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// WARNING: -// This class is a copy of FunctionInvokingChatClient from MEAI, and is intended to be modified with -// changes that we want to prototype here, before updating FunctionInvokingChatClient in MEAI. -// The intention is to keep the changes in this file to a minimum, so that we can easily -// merge them back into MEAI when ready. - -// AF repo suppressions for code copied from MEAI. -#pragma warning disable IDE1006 // Naming Styles -#pragma warning disable IDE0009 // Member access should be qualified. -#pragma warning disable CA2007 // Consider calling ConfigureAwait on the awaited task -#pragma warning disable VSTHRD111 // Use ConfigureAwait(bool) - -using System; -using System.Collections.Generic; -using System.Diagnostics; -using System.Diagnostics.CodeAnalysis; -using System.Linq; -using System.Runtime.CompilerServices; -using System.Runtime.ExceptionServices; -using System.Threading; -using System.Threading.Tasks; -using Microsoft.Extensions.Logging; -using Microsoft.Extensions.Logging.Abstractions; -using Microsoft.Shared.Diagnostics; - -#pragma warning disable CA2213 // Disposable fields should be disposed -#pragma warning disable EA0002 // Use 'System.TimeProvider' to make the code easier to test -#pragma warning disable SA1202 // 'protected' members should come before 'private' members -#pragma warning disable S107 // Methods should not have too many parameters - -namespace Microsoft.Extensions.AI; - -/// -/// A delegating chat client that invokes functions defined on . -/// Include this in a chat pipeline to resolve function calls automatically. -/// -/// -/// -/// When this client receives a in a chat response, it responds -/// by calling the corresponding defined in , -/// producing a that it sends back to the inner client. This loop -/// is repeated until there are no more function calls to make, or until another stop condition is met, -/// such as hitting . -/// -/// -/// The provided implementation of is thread-safe for concurrent use so long as the -/// instances employed as part of the supplied are also safe. -/// The property can be used to control whether multiple function invocation -/// requests as part of the same request are invocable concurrently, but even with that set to -/// (the default), multiple concurrent requests to this same instance and using the same tools could result in those -/// tools being used concurrently (one per request). For example, a function that accesses the HttpContext of a specific -/// ASP.NET web request should only be used as part of a single at a time, and only with -/// set to , in case the inner client decided to issue multiple -/// invocation requests to that same function. -/// -/// -public partial class NewFunctionInvokingChatClient : DelegatingChatClient -{ - /// The for the current function invocation. - private static readonly AsyncLocal _currentContext = new(); - - /// Gets the specified when constructing the , if any. - protected IServiceProvider? FunctionInvocationServices { get; } - - /// The logger to use for logging information about function invocation. - private readonly ILogger _logger; - - /// The to use for telemetry. - /// This component does not own the instance and should not dispose it. - private readonly ActivitySource? _activitySource; - - /// Maximum number of roundtrips allowed to the inner client. - private int _maximumIterationsPerRequest = 40; // arbitrary default to prevent runaway execution - - /// Maximum number of consecutive iterations that are allowed contain at least one exception result. If the limit is exceeded, we rethrow the exception instead of continuing. - private int _maximumConsecutiveErrorsPerRequest = 3; - - /// - /// Initializes a new instance of the class. - /// - /// The underlying , or the next instance in a chain of clients. - /// An to use for logging information about function invocation. - /// An optional to use for resolving services required by the instances being invoked. - public NewFunctionInvokingChatClient(IChatClient innerClient, ILoggerFactory? loggerFactory = null, IServiceProvider? functionInvocationServices = null) - : base(innerClient) - { - _logger = (ILogger?)loggerFactory?.CreateLogger() ?? NullLogger.Instance; - _activitySource = innerClient.GetService(); - FunctionInvocationServices = functionInvocationServices; - } - - /// - /// Gets or sets the for the current function invocation. - /// - /// - /// This value flows across async calls. - /// - public static FunctionInvocationContext? CurrentContext - { - get => _currentContext.Value; - protected set => _currentContext.Value = value; - } - - /// - /// Gets or sets a value indicating whether detailed exception information should be included - /// in the chat history when calling the underlying . - /// - /// - /// if the full exception message is added to the chat history - /// when calling the underlying . - /// if a generic error message is included in the chat history. - /// The default value is . - /// - /// - /// - /// Setting the value to prevents the underlying language model from disclosing - /// raw exception details to the end user, since it doesn't receive that information. Even in this - /// case, the raw object is available to application code by inspecting - /// the property. - /// - /// - /// Setting the value to can help the underlying bypass problems on - /// its own, for example by retrying the function call with different arguments. However it might - /// result in disclosing the raw exception information to external users, which can be a security - /// concern depending on the application scenario. - /// - /// - /// Changing the value of this property while the client is in use might result in inconsistencies - /// as to whether detailed errors are provided during an in-flight request. - /// - /// - public bool IncludeDetailedErrors { get; set; } - - /// - /// Gets or sets a value indicating whether to allow concurrent invocation of functions. - /// - /// - /// if multiple function calls can execute in parallel. - /// if function calls are processed serially. - /// The default value is . - /// - /// - /// An individual response from the inner client might contain multiple function call requests. - /// By default, such function calls are processed serially. Set to - /// to enable concurrent invocation such that multiple function calls can execute in parallel. - /// - public bool AllowConcurrentInvocation { get; set; } - - /// - /// Gets or sets the maximum number of iterations per request. - /// - /// - /// The maximum number of iterations per request. - /// The default value is 40. - /// - /// - /// - /// Each request to this might end up making - /// multiple requests to the inner client. Each time the inner client responds with - /// a function call request, this client might perform that invocation and send the results - /// back to the inner client in a new request. This property limits the number of times - /// such a roundtrip is performed. The value must be at least one, as it includes the initial request. - /// - /// - /// Changing the value of this property while the client is in use might result in inconsistencies - /// as to how many iterations are allowed for an in-flight request. - /// - /// - public int MaximumIterationsPerRequest - { - get => _maximumIterationsPerRequest; - set - { - if (value < 1) - { - Throw.ArgumentOutOfRangeException(nameof(value)); - } - - _maximumIterationsPerRequest = value; - } - } - - /// - /// Gets or sets the maximum number of consecutive iterations that are allowed to fail with an error. - /// - /// - /// The maximum number of consecutive iterations that are allowed to fail with an error. - /// The default value is 3. - /// - /// - /// - /// When function invocations fail with an exception, the - /// continues to make requests to the inner client, optionally supplying exception information (as - /// controlled by ). This allows the to - /// recover from errors by trying other function parameters that may succeed. - /// - /// - /// However, in case function invocations continue to produce exceptions, this property can be used to - /// limit the number of consecutive failing attempts. When the limit is reached, the exception will be - /// rethrown to the caller. - /// - /// - /// If the value is set to zero, all function calling exceptions immediately terminate the function - /// invocation loop and the exception will be rethrown to the caller. - /// - /// - /// Changing the value of this property while the client is in use might result in inconsistencies - /// as to how many iterations are allowed for an in-flight request. - /// - /// - public int MaximumConsecutiveErrorsPerRequest - { - get => _maximumConsecutiveErrorsPerRequest; - set => _maximumConsecutiveErrorsPerRequest = Throw.IfLessThan(value, 0); - } - - /// Gets or sets a collection of additional tools the client is able to invoke. - /// - /// These will not impact the requests sent by the , which will pass through the - /// unmodified. However, if the inner client requests the invocation of a tool - /// that was not in , this collection will also be consulted - /// to look for a corresponding tool to invoke. This is useful when the service may have been pre-configured to be aware - /// of certain tools that aren't also sent on each individual request. - /// - public IList? AdditionalTools { get; set; } - - /// Gets or sets a delegate used to invoke instances. - /// - /// By default, the protected method is called for each to be invoked, - /// invoking the instance and returning its result. If this delegate is set to a non- value, - /// will replace its normal invocation with a call to this delegate, enabling - /// this delegate to assume all invocation handling of the function. - /// - public Func>? FunctionInvoker { get; set; } - - /// - public override async Task GetResponseAsync( - IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - { - _ = Throw.IfNull(messages); - - // A single request into this GetResponseAsync may result in multiple requests to the inner client. - // Create an activity to group them together for better observability. - using Activity? activity = _activitySource?.StartActivity($"{nameof(FunctionInvokingChatClient)}.{nameof(GetResponseAsync)}"); - - // Copy the original messages in order to avoid enumerating the original messages multiple times. - // The IEnumerable can represent an arbitrary amount of work. - List originalMessages = [.. messages]; - messages = originalMessages; - - List? augmentedHistory = null; // the actual history of messages sent on turns other than the first - ChatResponse? response = null; // the response from the inner client, which is possibly modified and then eventually returned - List? responseMessages = null; // tracked list of messages, across multiple turns, to be used for the final response - UsageDetails? totalUsage = null; // tracked usage across all turns, to be used for the final response - List? functionCallContents = null; // function call contents that need responding to in the current turn - bool lastIterationHadConversationId = false; // whether the last iteration's response had a ConversationId set - int consecutiveErrorCount = 0; - - // Process approval requests (remove from originalMessages) and rejected approval responses (re-create FCC and create failed FRC). - var (preDownstreamCallHistory, notInvokedApprovals) = ProcessFunctionApprovalResponses(originalMessages, !string.IsNullOrWhiteSpace(options?.ConversationId), toolResponseId: null, functionCallContentFallbackMessageId: null); - - // Invoke approved approval responses, which generates some additional FRC wrapped in ChatMessage. - (IList? invokedApprovedFunctionApprovalResponses, bool shouldTerminate, consecutiveErrorCount) = - await InvokeApprovedFunctionApprovalResponses(notInvokedApprovals, originalMessages, options, consecutiveErrorCount, isStreaming: false, cancellationToken); - - if (invokedApprovedFunctionApprovalResponses is not null) - { - // We need to add the generated FRC to the list we'll return to callers as part of the next response. - preDownstreamCallHistory ??= []; - preDownstreamCallHistory.AddRange(invokedApprovedFunctionApprovalResponses); - } - - if (shouldTerminate) - { - return new ChatResponse(preDownstreamCallHistory); - } - - for (int iteration = 0; ; iteration++) - { - functionCallContents?.Clear(); - - // Make the call to the inner client. - response = await base.GetResponseAsync(messages, options, cancellationToken); - if (response is null) - { - Throw.InvalidOperationException($"The inner {nameof(IChatClient)} returned a null {nameof(ChatResponse)}."); - } - - // Before we do any function execution, make sure that any functions that require approval, have been turned into approval requests - // so that they don't get executed here. - response.Messages = await ReplaceFunctionCallsWithApprovalRequests(response.Messages, options?.Tools, AdditionalTools); - - // Any function call work to do? If yes, ensure we're tracking that work in functionCallContents. - bool requiresFunctionInvocation = - (options?.Tools is { Count: > 0 } || AdditionalTools is { Count: > 0 }) && - iteration < MaximumIterationsPerRequest && - CopyFunctionCalls(response.Messages, ref functionCallContents); - - // In a common case where we make a request and there's no function calling work required, - // fast path out by just returning the original response. - if (iteration == 0 && !requiresFunctionInvocation) - { - // Insert any pre-invocation FCC and FRC that were converted from approval responses into the response here, - // so they are returned to the caller. - response.Messages = UpdateResponseMessagesWithPreDownstreamCallHistory(response.Messages, preDownstreamCallHistory); - preDownstreamCallHistory = null; - - return response; - } - - // Track aggregate details from the response, including all of the response messages and usage details. - (responseMessages ??= []).AddRange(response.Messages); - if (response.Usage is not null) - { - if (totalUsage is not null) - { - totalUsage.Add(response.Usage); - } - else - { - totalUsage = response.Usage; - } - } - - // If there are no tools to call, or for any other reason we should stop, we're done. - // Break out of the loop and allow the handling at the end to configure the response - // with aggregated data from previous requests. - if (!requiresFunctionInvocation) - { - break; - } - - // Prepare the history for the next iteration. - FixupHistories(originalMessages, ref messages, ref augmentedHistory, response, responseMessages, ref lastIterationHadConversationId); - - // Add the responses from the function calls into the augmented history and also into the tracked - // list of response messages. - var modeAndMessages = await ProcessFunctionCallsAsync(augmentedHistory, options, functionCallContents!, iteration, consecutiveErrorCount, isStreaming: false, cancellationToken); - responseMessages.AddRange(modeAndMessages.MessagesAdded); - consecutiveErrorCount = modeAndMessages.NewConsecutiveErrorCount; - - if (modeAndMessages.ShouldTerminate) - { - break; - } - - UpdateOptionsForNextIteration(ref options, response.ConversationId); - } - - Debug.Assert(responseMessages is not null, "Expected to only be here if we have response messages."); - response.Messages = responseMessages!; - response.Usage = totalUsage; - - AddUsageTags(activity, totalUsage); - - return response; - } - - /// - public override async IAsyncEnumerable GetStreamingResponseAsync( - IEnumerable messages, ChatOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default) - { - _ = Throw.IfNull(messages); - - // A single request into this GetStreamingResponseAsync may result in multiple requests to the inner client. - // Create an activity to group them together for better observability. - using Activity? activity = _activitySource?.StartActivity($"{nameof(FunctionInvokingChatClient)}.{nameof(GetStreamingResponseAsync)}"); - UsageDetails? totalUsage = activity is { IsAllDataRequested: true } ? new() : null; // tracked usage across all turns, to be used for activity purposes - - // Copy the original messages in order to avoid enumerating the original messages multiple times. - // The IEnumerable can represent an arbitrary amount of work. - List originalMessages = [.. messages]; - messages = originalMessages; - - List? augmentedHistory = null; // the actual history of messages sent on turns other than the first - List? functionCallContents = null; // function call contents that need responding to in the current turn - List? responseMessages = null; // tracked list of messages, across multiple turns, to be used in fallback cases to reconstitute history - bool lastIterationHadConversationId = false; // whether the last iteration's response had a ConversationId set - List updates = []; // updates from the current response - int consecutiveErrorCount = 0; - - // This is a synthetic ID since we're generating the tool messages instead of getting them from - // the underlying provider. When emitting the streamed chunks, it's perfectly valid for us to - // use the same message ID for all of them within a given iteration, as this is a single logical - // message with multiple content items. We could also use different message IDs per tool content, - // but there's no benefit to doing so. - string toolResponseId = Guid.NewGuid().ToString("N"); - - // We also need a synthetic ID for the function call content for approved function calls - // where we don't know what the original message id of the function call was. - string functionCallContentFallbackMessageId = Guid.NewGuid().ToString("N"); - - ApprovalRequiredAIFunction[]? approvalRequiredFunctions = (options?.Tools ?? []).Concat(AdditionalTools ?? []).OfType().ToArray(); - bool hasApprovalRequiringFunctions = approvalRequiredFunctions.Length > 0; - - // Process approval requests (remove from original messages) and rejected approval responses (re-create FCC and create failed FRC). - var (preDownstreamCallHistory, notInvokedApprovals) = ProcessFunctionApprovalResponses(originalMessages, !string.IsNullOrWhiteSpace(options?.ConversationId), toolResponseId, functionCallContentFallbackMessageId); - if (preDownstreamCallHistory is not null) - { - foreach (var message in preDownstreamCallHistory) - { - yield return ConvertToolResultMessageToUpdate(message, options?.ConversationId, message.MessageId); - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - } - - // Invoke approved approval responses, which generates some additional FRC wrapped in ChatMessage. - (IList? invokedApprovedFunctionApprovalResponses, bool shouldTerminate, consecutiveErrorCount) = - await InvokeApprovedFunctionApprovalResponses(notInvokedApprovals, originalMessages, options, consecutiveErrorCount, isStreaming: true, cancellationToken); - - if (invokedApprovedFunctionApprovalResponses is not null) - { - foreach (var message in invokedApprovedFunctionApprovalResponses) - { - message.MessageId = toolResponseId; - yield return ConvertToolResultMessageToUpdate(message, options?.ConversationId, message.MessageId); - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - - if (shouldTerminate) - { - yield break; - } - } - - for (int iteration = 0; ; iteration++) - { - updates.Clear(); - functionCallContents?.Clear(); - - bool hasApprovalRequiringFcc = false; - int lastApprovalCheckedFCCIndex = 0; - int lastYieldedUpdateIndex = 0; - - await foreach (var update in base.GetStreamingResponseAsync(messages, options, cancellationToken)) - { - if (update is null) - { - Throw.InvalidOperationException($"The inner {nameof(IChatClient)} streamed a null {nameof(ChatResponseUpdate)}."); - } - - updates.Add(update); - - _ = CopyFunctionCalls(update.Contents, ref functionCallContents); - - if (totalUsage is not null) - { - IList contents = update.Contents; - int contentsCount = contents.Count; - for (int i = 0; i < contentsCount; i++) - { - if (contents[i] is UsageContent uc) - { - totalUsage.Add(uc.Details); - } - } - } - - if (functionCallContents?.Count is not > 0 || !hasApprovalRequiringFunctions) - { - // If there are no function calls to make yet, or if none of the functions require approval at all, - // we can yield the update as-is. - lastYieldedUpdateIndex++; - yield return update; - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - else - { - // Check if any of the function call contents in this update requires approval. - // Once we find the first one that requires approval, this method becomes a no-op. - (hasApprovalRequiringFcc, lastApprovalCheckedFCCIndex) = await CheckForApprovalRequiringFCCAsync( - functionCallContents, approvalRequiredFunctions, hasApprovalRequiringFcc, lastApprovalCheckedFCCIndex); - - // We've encountered a function call content that requires approval (either in this update or ealier) - // so we need to ask for approval for all functions, since we cannot mix and match. - if (hasApprovalRequiringFcc) - { - // Convert all function call contents into approval requests from the last yielded update index - // and yield all those updates. - for (; lastYieldedUpdateIndex < updates.Count; lastYieldedUpdateIndex++) - { - var updateToYield = updates[lastYieldedUpdateIndex]; - if (TryReplaceFunctionCallsWithApprovalRequests(updateToYield.Contents, out var updatedContents)) - { - updateToYield.Contents = updatedContents; - } - yield return updateToYield; - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - } - else - { - // We don't have any appoval requiring function calls yet, but we may receive some in future - // so we cannot yield the updates yet. We'll just keep them in the updates list - // for later. - // We will yield the updates as soon as we receive a function call content that requires approval or - // when we reach the end of the updates stream. - } - } - - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - - // If there are no tools to call, or for any other reason we should stop, return the response. - if (functionCallContents is not { Count: > 0 } || - hasApprovalRequiringFcc || - (options?.Tools is not { Count: > 0 } && AdditionalTools is not { Count: > 0 }) || - iteration >= _maximumIterationsPerRequest) - { - break; - } - - // Reconstitute a response from the response updates. - var response = updates.ToChatResponse(); - (responseMessages ??= []).AddRange(response.Messages); - - // Prepare the history for the next iteration. - FixupHistories(originalMessages, ref messages, ref augmentedHistory, response, responseMessages, ref lastIterationHadConversationId); - - // Process all of the functions, adding their results into the history. - var modeAndMessages = await ProcessFunctionCallsAsync(augmentedHistory, options, functionCallContents, iteration, consecutiveErrorCount, isStreaming: true, cancellationToken); - responseMessages.AddRange(modeAndMessages.MessagesAdded); - consecutiveErrorCount = modeAndMessages.NewConsecutiveErrorCount; - - // Stream any generated function results. This mirrors what's done for GetResponseAsync, where the returned messages - // includes all activities, including generated function results. - foreach (var message in modeAndMessages.MessagesAdded) - { - yield return ConvertToolResultMessageToUpdate(message, response.ConversationId, toolResponseId); - Activity.Current = activity; // workaround for https://github.com/dotnet/runtime/issues/47802 - } - - if (modeAndMessages.ShouldTerminate) - { - break; - } - - UpdateOptionsForNextIteration(ref options, response.ConversationId); - } - - AddUsageTags(activity, totalUsage); - } - - /// Adds tags to for usage details in . - private static void AddUsageTags(Activity? activity, UsageDetails? usage) - { - if (usage is not null && activity is { IsAllDataRequested: true }) - { - if (usage.InputTokenCount is long inputTokens) - { - _ = activity.AddTag(OpenTelemetryConsts.GenAI.Usage.InputTokens, (int)inputTokens); - } - - if (usage.OutputTokenCount is long outputTokens) - { - _ = activity.AddTag(OpenTelemetryConsts.GenAI.Usage.OutputTokens, (int)outputTokens); - } - } - } - - /// Prepares the various chat message lists after a response from the inner client and before invoking functions. - /// The original messages provided by the caller. - /// The messages reference passed to the inner client. - /// The augmented history containing all the messages to be sent. - /// The most recent response being handled. - /// A list of all response messages received up until this point. - /// Whether the previous iteration's response had a conversation ID. - private static void FixupHistories( - IEnumerable originalMessages, - ref IEnumerable messages, - [NotNull] ref List? augmentedHistory, - ChatResponse response, - List allTurnsResponseMessages, - ref bool lastIterationHadConversationId) - { - // We're now going to need to augment the history with function result contents. - // That means we need a separate list to store the augmented history. - if (response.ConversationId is not null) - { - // The response indicates the inner client is tracking the history, so we don't want to send - // anything we've already sent or received. - if (augmentedHistory is not null) - { - augmentedHistory.Clear(); - } - else - { - augmentedHistory = []; - } - - lastIterationHadConversationId = true; - } - else if (lastIterationHadConversationId) - { - // In the very rare case where the inner client returned a response with a conversation ID but then - // returned a subsequent response without one, we want to reconstitute the full history. To do that, - // we can populate the history with the original chat messages and then all of the response - // messages up until this point, which includes the most recent ones. - augmentedHistory ??= []; - augmentedHistory.Clear(); - augmentedHistory.AddRange(originalMessages); - augmentedHistory.AddRange(allTurnsResponseMessages); - - lastIterationHadConversationId = false; - } - else - { - // If augmentedHistory is already non-null, then we've already populated it with everything up - // until this point (except for the most recent response). If it's null, we need to seed it with - // the chat history provided by the caller. - augmentedHistory ??= originalMessages.ToList(); - - // Now add the most recent response messages. - augmentedHistory.AddMessages(response); - - lastIterationHadConversationId = false; - } - - // Use the augmented history as the new set of messages to send. - messages = augmentedHistory; - } - - /// Copies any from to . - private static bool CopyFunctionCalls( - IList messages, [NotNullWhen(true)] ref List? functionCalls) - { - bool any = false; - int count = messages.Count; - for (int i = 0; i < count; i++) - { - any |= CopyFunctionCalls(messages[i].Contents, ref functionCalls); - } - - return any; - } - - /// Copies any from to . - private static bool CopyFunctionCalls( - IList content, [NotNullWhen(true)] ref List? functionCalls) - { - bool any = false; - int count = content.Count; - for (int i = 0; i < count; i++) - { - if (content[i] is FunctionCallContent functionCall) - { - (functionCalls ??= []).Add(functionCall); - any = true; - } - } - - return any; - } - - private static void UpdateOptionsForNextIteration(ref ChatOptions? options, string? conversationId) - { - if (options is null) - { - if (conversationId is not null) - { - options = new() { ConversationId = conversationId }; - } - } - else if (options.ToolMode is RequiredChatToolMode) - { - // We have to reset the tool mode to be non-required after the first iteration, - // as otherwise we'll be in an infinite loop. - options = options.Clone(); - options.ToolMode = null; - options.ConversationId = conversationId; - } - else if (options.ConversationId != conversationId) - { - // As with the other modes, ensure we've propagated the chat conversation ID to the options. - // We only need to clone the options if we're actually mutating it. - options = options.Clone(); - options.ConversationId = conversationId; - } - } - - /// - /// Processes the function calls in the list. - /// - /// The current chat contents, inclusive of the function call contents being processed. - /// The options used for the response being processed. - /// The function call contents representing the functions to be invoked. - /// The iteration number of how many roundtrips have been made to the inner client. - /// The number of consecutive iterations, prior to this one, that were recorded as having function invocation errors. - /// Whether the function calls are being processed in a streaming context. - /// The to monitor for cancellation requests. - /// A value indicating how the caller should proceed. - private async Task<(bool ShouldTerminate, int NewConsecutiveErrorCount, IList MessagesAdded)> ProcessFunctionCallsAsync( - List messages, ChatOptions? options, List functionCallContents, int iteration, int consecutiveErrorCount, - bool isStreaming, CancellationToken cancellationToken) - { - // We must add a response for every tool call, regardless of whether we successfully executed it or not. - // If we successfully execute it, we'll add the result. If we don't, we'll add an error. - - Debug.Assert(functionCallContents.Count > 0, "Expected at least one function call."); - var shouldTerminate = false; - var captureCurrentIterationExceptions = consecutiveErrorCount < _maximumConsecutiveErrorsPerRequest; - - // Process all functions. If there's more than one and concurrent invocation is enabled, do so in parallel. - if (functionCallContents.Count == 1) - { - FunctionInvocationResult result = await ProcessFunctionCallAsync( - messages, options, functionCallContents, - iteration, 0, captureCurrentIterationExceptions, isStreaming, cancellationToken); - - IList addedMessages = CreateResponseMessages([result]); - ThrowIfNoFunctionResultsAdded(addedMessages); - UpdateConsecutiveErrorCountOrThrow(addedMessages, ref consecutiveErrorCount); - messages.AddRange(addedMessages); - - return (result.Terminate, consecutiveErrorCount, addedMessages); - } - else - { - List results = []; - - if (AllowConcurrentInvocation) - { - // Rather than awaiting each function before invoking the next, invoke all of them - // and then await all of them. We avoid forcibly introducing parallelism via Task.Run, - // but if a function invocation completes asynchronously, its processing can overlap - // with the processing of other the other invocation invocations. - results.AddRange(await Task.WhenAll( - from callIndex in Enumerable.Range(0, functionCallContents.Count) - select ProcessFunctionCallAsync( - messages, options, functionCallContents, - iteration, callIndex, captureExceptions: true, isStreaming, cancellationToken))); - - shouldTerminate = results.Any(r => r.Terminate); - } - else - { - // Invoke each function serially. - for (int callIndex = 0; callIndex < functionCallContents.Count; callIndex++) - { - var functionResult = await ProcessFunctionCallAsync( - messages, options, functionCallContents, - iteration, callIndex, captureCurrentIterationExceptions, isStreaming, cancellationToken); - - results.Add(functionResult); - - // If any function requested termination, we should stop right away. - if (functionResult.Terminate) - { - shouldTerminate = true; - break; - } - } - } - - IList addedMessages = CreateResponseMessages(results.ToArray()); - ThrowIfNoFunctionResultsAdded(addedMessages); - UpdateConsecutiveErrorCountOrThrow(addedMessages, ref consecutiveErrorCount); - messages.AddRange(addedMessages); - - return (shouldTerminate, consecutiveErrorCount, addedMessages); - } - } - -#pragma warning disable CA1851 // Possible multiple enumerations of 'IEnumerable' collection - /// - /// Updates the consecutive error count, and throws an exception if the count exceeds the maximum. - /// - /// Added messages. - /// Consecutive error count. - /// Thrown if the maximum consecutive error count is exceeded. - private void UpdateConsecutiveErrorCountOrThrow(IList added, ref int consecutiveErrorCount) - { - var allExceptions = added.SelectMany(m => m.Contents.OfType()) - .Select(frc => frc.Exception!) - .Where(e => e is not null); - - if (allExceptions.Any()) - { - consecutiveErrorCount++; - if (consecutiveErrorCount > _maximumConsecutiveErrorsPerRequest) - { - var allExceptionsArray = allExceptions.ToArray(); - if (allExceptionsArray.Length == 1) - { - ExceptionDispatchInfo.Capture(allExceptionsArray[0]).Throw(); - } - else - { - throw new AggregateException(allExceptionsArray); - } - } - } - else - { - consecutiveErrorCount = 0; - } - } -#pragma warning restore CA1851 - - /// - /// Throws an exception if doesn't create any messages. - /// - private void ThrowIfNoFunctionResultsAdded(IList? messages) - { - if (messages is null || messages.Count == 0) - { - Throw.InvalidOperationException($"{GetType().Name}.{nameof(CreateResponseMessages)} returned null or an empty collection of messages."); - } - } - - /// Processes the function call described in []. - /// The current chat contents, inclusive of the function call contents being processed. - /// The options used for the response being processed. - /// The function call contents representing all the functions being invoked. - /// The iteration number of how many roundtrips have been made to the inner client. - /// The 0-based index of the function being called out of . - /// If true, handles function-invocation exceptions by returning a value with . Otherwise, rethrows. - /// Whether the function calls are being processed in a streaming context. - /// The to monitor for cancellation requests. - /// A value indicating how the caller should proceed. - private async Task ProcessFunctionCallAsync( - List messages, ChatOptions? options, List callContents, - int iteration, int functionCallIndex, bool captureExceptions, bool isStreaming, CancellationToken cancellationToken) - { - var callContent = callContents[functionCallIndex]; - - // Look up the AIFunction for the function call. If the requested function isn't available, send back an error. - AIFunction? aiFunction = FindAIFunction(options?.Tools, callContent.Name) ?? FindAIFunction(AdditionalTools, callContent.Name); - if (aiFunction is null) - { - return new(terminate: false, FunctionInvocationStatus.NotFound, callContent, result: null, exception: null); - } - - FunctionInvocationContext context = new() - { - Function = aiFunction, - Arguments = new(callContent.Arguments) { Services = FunctionInvocationServices }, - Messages = messages, - Options = options, - CallContent = callContent, - Iteration = iteration, - FunctionCallIndex = functionCallIndex, - FunctionCount = callContents.Count, - IsStreaming = isStreaming - }; - - object? result; - try - { - result = await InstrumentedInvokeFunctionAsync(context, cancellationToken); - } - catch (Exception e) when (!cancellationToken.IsCancellationRequested) - { - if (!captureExceptions) - { - throw; - } - - return new( - terminate: false, - FunctionInvocationStatus.Exception, - callContent, - result: null, - exception: e); - } - - return new( - terminate: context.Terminate, - FunctionInvocationStatus.RanToCompletion, - callContent, - result, - exception: null); - - static AIFunction? FindAIFunction(IList? tools, string functionName) - { - if (tools is not null) - { - int count = tools.Count; - for (int i = 0; i < count; i++) - { - if (tools[i] is AIFunction function && function.Name == functionName) - { - return function; - } - } - } - - return null; - } - } - - /// Creates one or more response messages for function invocation results. - /// Information about the function call invocations and results. - /// A list of all chat messages created from . - protected virtual IList CreateResponseMessages( - ReadOnlySpan results) - { - var contents = new List(results.Length); - for (int i = 0; i < results.Length; i++) - { - contents.Add(CreateFunctionResultContent(results[i])); - } - - return [new(ChatRole.Tool, contents)]; - - FunctionResultContent CreateFunctionResultContent(FunctionInvocationResult result) - { - _ = Throw.IfNull(result); - - object? functionResult; - if (result.Status == FunctionInvocationStatus.RanToCompletion) - { - functionResult = result.Result ?? "Success: Function completed."; - } - else - { - string message = result.Status switch - { - FunctionInvocationStatus.NotFound => $"Error: Requested function \"{result.CallContent.Name}\" not found.", - FunctionInvocationStatus.Exception => "Error: Function failed.", - _ => "Error: Unknown error.", - }; - - if (IncludeDetailedErrors && result.Exception is not null) - { - message = $"{message} Exception: {result.Exception.Message}"; - } - - functionResult = message; - } - - return new FunctionResultContent(result.CallContent.CallId, functionResult) { Exception = result.Exception }; - } - } - - /// Invokes the function asynchronously. - /// - /// The function invocation context detailing the function to be invoked and its arguments along with additional request information. - /// - /// The to monitor for cancellation requests. The default is . - /// The result of the function invocation, or if the function invocation returned . - /// is . - private async Task InstrumentedInvokeFunctionAsync(FunctionInvocationContext context, CancellationToken cancellationToken) - { - _ = Throw.IfNull(context); - - using Activity? activity = _activitySource?.StartActivity( - $"{OpenTelemetryConsts.GenAI.ExecuteTool} {context.Function.Name}", - ActivityKind.Internal, - default(ActivityContext), - [ - new(OpenTelemetryConsts.GenAI.Operation.Name, "execute_tool"), - new(OpenTelemetryConsts.GenAI.Tool.Call.Id, context.CallContent.CallId), - new(OpenTelemetryConsts.GenAI.Tool.Name, context.Function.Name), - new(OpenTelemetryConsts.GenAI.Tool.Description, context.Function.Description), - ]); - - long startingTimestamp = 0; - if (_logger.IsEnabled(LogLevel.Debug)) - { - startingTimestamp = Stopwatch.GetTimestamp(); - if (_logger.IsEnabled(LogLevel.Trace)) - { - LogInvokingSensitive(context.Function.Name, LoggingHelpers.AsJson(context.Arguments, context.Function.JsonSerializerOptions)); - } - else - { - LogInvoking(context.Function.Name); - } - } - - object? result = null; - try - { - CurrentContext = context; // doesn't need to be explicitly reset after, as that's handled automatically at async method exit - result = await InvokeFunctionAsync(context, cancellationToken); - } - catch (Exception e) - { - if (activity is not null) - { - _ = activity.SetTag("error.type", e.GetType().FullName) - .SetStatus(ActivityStatusCode.Error, e.Message); - } - - if (e is OperationCanceledException) - { - LogInvocationCanceled(context.Function.Name); - } - else - { - LogInvocationFailed(context.Function.Name, e); - } - - throw; - } - finally - { - if (_logger.IsEnabled(LogLevel.Debug)) - { - TimeSpan elapsed = GetElapsedTime(startingTimestamp); - - if (result is not null && _logger.IsEnabled(LogLevel.Trace)) - { - LogInvocationCompletedSensitive(context.Function.Name, elapsed, LoggingHelpers.AsJson(result, context.Function.JsonSerializerOptions)); - } - else - { - LogInvocationCompleted(context.Function.Name, elapsed); - } - } - } - - return result; - } - - /// This method will invoke the function within the try block. - /// The function invocation context. - /// Cancellation token. - /// The function result. - protected virtual ValueTask InvokeFunctionAsync(FunctionInvocationContext context, CancellationToken cancellationToken) - { - _ = Throw.IfNull(context); - - return FunctionInvoker is { } invoker ? - invoker(context, cancellationToken) : - context.Function.InvokeAsync(context.Arguments, cancellationToken); - } - - /// - /// 1. Remove all and from the . - /// 2. Recreate for any that haven't been executed yet. - /// 3. Genreate failed for any rejected . - /// 4. add all the new content items to and return them as the pre-invocation history. - /// - private static (List? preDownstreamCallHistory, List? approvals) ProcessFunctionApprovalResponses( - List originalMessages, bool hasConversationId, string? toolResponseId, string? functionCallContentFallbackMessageId) - { - // Extract any approval responses where we need to execute or reject the function calls. - // The original messages are also modified to remove all approval requests and responses. - var notInvokedResponses = ExtractAndRemoveApprovalRequestsAndResponses(originalMessages); - - // Wrap the function call content in message(s). - ICollection? allPreDownstreamCallMessages = ConvertToFunctionCallContentMessages( - [.. notInvokedResponses.rejections ?? [], .. notInvokedResponses.approvals ?? []], functionCallContentFallbackMessageId); - - // Generate failed function result contents for any rejected requests and wrap it in a message. - List? rejectedFunctionCallResults = GenerateRejectedFunctionResults(notInvokedResponses.rejections, toolResponseId); - ChatMessage? rejectedPreDownstreamCallResultsMessage = rejectedFunctionCallResults != null ? - new ChatMessage(ChatRole.Tool, rejectedFunctionCallResults) { MessageId = toolResponseId } : - null; - - // Add all the FCC that we generated to the pre-downstream-call history so that they can be returned to the caller as part of the next response. - // Also, if we are not dealing with a service thread (i.e. we don't have a conversation ID), add them - // into the original messages list so that they are passed to the inner client and can be used to generate a result. - List? preDownstreamCallHistory = null; - if (allPreDownstreamCallMessages is not null) - { - preDownstreamCallHistory ??= []; - foreach (var message in allPreDownstreamCallMessages) - { - preDownstreamCallHistory.Add(message); - if (!hasConversationId) - { - originalMessages.Add(message); - } - } - } - - // Add all the FRC that we generated to the pre-downstream-call history so that they can be returned to the caller as part of the next response. - // Also, add them into the original messages list so that they are passed to the inner client and can be used to generate a result. - if (rejectedPreDownstreamCallResultsMessage is not null) - { - preDownstreamCallHistory ??= []; - originalMessages.Add(rejectedPreDownstreamCallResultsMessage); - preDownstreamCallHistory.Add(rejectedPreDownstreamCallResultsMessage); - } - - return (preDownstreamCallHistory, notInvokedResponses.approvals); - } - - /// - /// Execute the provided and return the resulting . - /// - private async Task<(IList? FunctionResultContent, bool ShouldTerminate, int ConsecutiveErrorCount)> InvokeApprovedFunctionApprovalResponses( - List? notInvokedApprovals, List originalMessages, ChatOptions? options, int consecutiveErrorCount, bool isStreaming, CancellationToken cancellationToken) - { - // Check if there are any function calls to do for any approved functions and execute them. - if (notInvokedApprovals is { Count: > 0 }) - { - // The FRC that is generated here is already added to originalMessages by ProcessFunctionCallsAsync. - var modeAndMessages = await ProcessFunctionCallsAsync(originalMessages, options, notInvokedApprovals.Select(x => x.Response.FunctionCall).ToList(), 0, consecutiveErrorCount, isStreaming, cancellationToken); - consecutiveErrorCount = modeAndMessages.NewConsecutiveErrorCount; - - return (modeAndMessages.MessagesAdded, modeAndMessages.ShouldTerminate, consecutiveErrorCount); - } - - return (null, false, consecutiveErrorCount); - } - - /// - /// This method extracts the approval requests and responses from the provided list of messages, validates them, filters them to ones that require execution and splits them into approved and rejected. - /// - /// - /// 1st iteration: over all messages and content - /// ===== - /// Build a list of all function call ids that are already executed. - /// Build a list of all function approval requests and responses. - /// Build a list of the content we want to keep (everything except approval requests and responses) and create a new list of messages for those. - /// Validate that we have an approval response for each approval request. - /// - /// 2nd iteration: over all approval responses - /// ===== - /// Filter out any approval responses that already have a matching function result (i.e. already executed). - /// Find the matching function approval request for any response (where available). - /// Split the approval responses into two lists: approved and rejected, with their request messages (where available). - /// - /// We return the messages containing the approval requests since these are the same messages that originally contained the FunctionCallContent from the downstream service. - /// We can then use the metadata from these messages when we re-create the FunctionCallContent messages/updates to return to the caller. This way, when we finally do return - /// the FuncionCallContent to users it's part of a message/update that contains the same metadata as originally returned to the downstream service. - /// - private static (List? approvals, List? rejections) ExtractAndRemoveApprovalRequestsAndResponses(List messages) - { - Dictionary? allApprovalRequestsMessages = null; - List? allApprovalResponses = null; - HashSet? approvalRequestCallIds = null; - HashSet? functionResultCallIds = null; - - for (int i = 0; i < messages.Count; i++) - { - var message = messages[i]; - - List? keptContents = null; - - // Find contents we want to keep. - for (int j = 0; j < message.Contents.Count; j++) - { - var content = message.Contents[j]; - - // Maintain a list of function calls that have already been executed, so we can avoid executing them a second time. - if (content is FunctionResultContent functionResultContent) - { - functionResultCallIds ??= []; - functionResultCallIds.Add(functionResultContent.CallId); - } - - // Validation: Capture each call id for each approval request so that we can ensure that we have a matching response later. - if (content is FunctionApprovalRequestContent request_) - { - approvalRequestCallIds ??= []; - approvalRequestCallIds.Add(request_.FunctionCall.CallId); - } - - // Validation: Remove the call id for each approval response, to check it off the list of requests we need responses for. - if (content is FunctionApprovalResponseContent response_ && approvalRequestCallIds is not null) - { - approvalRequestCallIds.Remove(response_.FunctionCall.CallId); - } - - // Build the list of requets and responses and keep them out of the updated message list - // since they will be handled in this class, and don't need to be passed further down the stack. - if (content is FunctionApprovalRequestContent approvalRequest) - { - allApprovalRequestsMessages ??= new Dictionary(); - allApprovalRequestsMessages.Add(approvalRequest.Id, message); - continue; - } - - if (content is FunctionApprovalResponseContent approvalResponse) - { - allApprovalResponses ??= []; - allApprovalResponses.Add(approvalResponse); - continue; - } - - // If we get to here, we should have just the contents that we want to keep. - keptContents ??= []; - keptContents.Add(content); - } - - if (message.Contents.Count > 0 && keptContents?.Count != message.Contents.Count) - { - if (keptContents is null || keptContents.Count == 0) - { - // If we have no contents left after filtering, we can remove the message. - messages.RemoveAt(i); - i--; // Adjust index since we removed an item. - continue; - } - - // If we have any contents left after filtering, we can keep the message with the new remaining content. - var newMessage = message.Clone(); - newMessage.Contents = keptContents; - messages[i] = newMessage; - } - } - - // Validation: If we got an approval for each request, we should have no call ids left. - if (approvalRequestCallIds?.Count is > 0) - { - Throw.InvalidOperationException($"FunctionApprovalRequestContent found with FunctionCall.CallId(s) '{string.Join(", ", approvalRequestCallIds)}' that have no matching FunctionApprovalResponseContent."); - } - - List? approvedFunctionCalls = null; - List? rejectedFunctionCalls = null; - - for (int i = 0; i < (allApprovalResponses?.Count ?? 0); i++) - { - var approvalResponse = allApprovalResponses![i]; - - // Skip any approval responses that have already been executed. - if (functionResultCallIds?.Contains(approvalResponse.FunctionCall.CallId) is not true) - { - ChatMessage? requestMessage = null; - allApprovalRequestsMessages?.TryGetValue(approvalResponse.FunctionCall.CallId, out requestMessage); - - // Split the responses into approved and rejected. - if (approvalResponse.Approved) - { - approvedFunctionCalls ??= []; - approvedFunctionCalls.Add(new ApprovalResultWithRequestMessage { Response = approvalResponse, RequestMessage = requestMessage }); - } - else - { - rejectedFunctionCalls ??= []; - rejectedFunctionCalls.Add(new ApprovalResultWithRequestMessage { Response = approvalResponse, RequestMessage = requestMessage }); - } - } - } - - return (approvedFunctionCalls, rejectedFunctionCalls); - } - - /// - /// If we have any rejected approval responses, we need to generate failed function results for them. - /// - /// Any rejected approval responses. - /// The message id to use for the tool response. - /// The for the rejected function calls. - private static List? GenerateRejectedFunctionResults( - List? rejections, - string? toolResponseId) - { - List? functionResultContent = null; - - if (rejections is { Count: > 0 }) - { - functionResultContent = []; - - foreach (var rejectedCall in rejections) - { - // Create a FunctionResultContent for the rejected function call. - var functionResult = new FunctionResultContent(rejectedCall.Response.FunctionCall.CallId, "Error: Function invocation approval was not granted."); - functionResultContent.Add(functionResult); - } - } - - return functionResultContent; - } - - /// - /// Extracts the from the provided to recreate the original function call messages. - /// The output messages tries to mimic the original messages that contained the , e.g. if the had been split into separate messages, - /// this method will recreate similarly split messages, each with their own . - /// -#pragma warning disable CA1859 // Use concrete types when possible for improved performance - private static ICollection? ConvertToFunctionCallContentMessages(IEnumerable? resultWithRequestMessages, string? fallbackMessageId) -#pragma warning restore CA1859 // Use concrete types when possible for improved performance - { - if (resultWithRequestMessages is not null) - { - ChatMessage? currentMessage = null; - Dictionary? messagesById = null; - - foreach (var resultWithRequestMessage in resultWithRequestMessages) - { - if (currentMessage is not null && messagesById is null // Don't need to create a dictionary on the first iteration or if we alrady have one. - && !(resultWithRequestMessage.RequestMessage is null && currentMessage.MessageId == fallbackMessageId) // Everywhere we have no RequestMessage we use the fallbackMessageId, so in this case there is only one message. - && (resultWithRequestMessage.RequestMessage is not null && currentMessage.MessageId != resultWithRequestMessage.RequestMessage?.MessageId)) // Where we do have a RequestMessage, we can check if its message id differs from the current one. - { - // The majority of the time, all FCC would be part of a single message, so no need to create a dictionary for this case. - // If we are dealing with multiple messages though, we need to keep track of them by their message ID. - messagesById ??= new(); - messagesById[currentMessage.MessageId ?? string.Empty] = currentMessage; - } - - if (messagesById is not null) - { - messagesById.TryGetValue(resultWithRequestMessage.RequestMessage?.MessageId ?? string.Empty, out currentMessage); - } - - if (currentMessage is null) - { - currentMessage = ConvertToFunctionCallContentMessage(resultWithRequestMessage, fallbackMessageId); - } - else - { - currentMessage.Contents.Add(resultWithRequestMessage.Response.FunctionCall); - } - - if (messagesById is not null) - { - messagesById[currentMessage.MessageId ?? string.Empty] = currentMessage; - } - } - - return messagesById?.Values as ICollection ?? (currentMessage != null ? [currentMessage!] : null); - } - - return null; - } - - /// - /// Takes the from the and wraps it in a - /// using the same message id that the was originally returned with from the downstream . - /// - private static ChatMessage ConvertToFunctionCallContentMessage(ApprovalResultWithRequestMessage resultWithRequestMessage, string? fallbackMessageId) - { - if (resultWithRequestMessage.RequestMessage is not null) - { - var functionCallMessage = resultWithRequestMessage.RequestMessage.Clone(); - functionCallMessage.Contents = [resultWithRequestMessage.Response.FunctionCall]; - functionCallMessage.MessageId ??= fallbackMessageId; - return functionCallMessage; - } - - return new ChatMessage(ChatRole.Assistant, [resultWithRequestMessage.Response.FunctionCall]) { MessageId = fallbackMessageId }; - } - - /// - /// Check if any of the provided require approval. - /// Supports checking from a provided index up to the end of the list, to allow efficient incremental checking - /// when streaming. - /// - private static async Task<(bool hasApprovalRequiringFcc, int lastApprovalCheckedFCCIndex)> CheckForApprovalRequiringFCCAsync( - List? functionCallContents, - ApprovalRequiredAIFunction[] approvalRequiredFunctions, - bool hasApprovalRequiringFcc, - int lastApprovalCheckedFCCIndex) - { - // If we already found an approval requiring FCC, we can skip checking the rest. - if (hasApprovalRequiringFcc) - { - return (true, functionCallContents?.Count ?? 0); - } - - for (; lastApprovalCheckedFCCIndex < (functionCallContents?.Count ?? 0); lastApprovalCheckedFCCIndex++) - { - var fcc = functionCallContents![lastApprovalCheckedFCCIndex]; - if (approvalRequiredFunctions.FirstOrDefault(y => y.Name == fcc.Name) is ApprovalRequiredAIFunction approvalFunction && - await approvalFunction.RequiresApprovalCallback(new(fcc))) - { - hasApprovalRequiringFcc |= true; - } - } - - return (hasApprovalRequiringFcc, lastApprovalCheckedFCCIndex); - } - - /// - /// Replaces all with and ouputs a new list if any of them were replaced. - /// - /// true if any was replaced, false otherwise. - private static bool TryReplaceFunctionCallsWithApprovalRequests(IList content, out IList? updatedContent) - { - updatedContent = null; - - if (content is { Count: > 0 }) - { - for (int i = 0; i < content.Count; i++) - { - if (content[i] is FunctionCallContent fcc) - { - updatedContent ??= [.. content]; // Clone the list if we haven't already - var approvalRequest = new FunctionApprovalRequestContent(fcc.CallId, fcc); - updatedContent[i] = approvalRequest; - } - } - } - - return updatedContent is not null; - } - - /// - /// Replaces all from with - /// if any one of them requires approval. - /// - private static async Task> ReplaceFunctionCallsWithApprovalRequests(IList messages, IList? requestOptionsTools, IList? additionalTools) - { - var outputMessages = messages; - ApprovalRequiredAIFunction[]? approvalRequiredFunctions = null; - - bool anyApprovalRequired = false; - List<(int, int)>? allFunctionCallContentIndices = null; - - // Build a list of the indices of all FunctionCallContent items. - // Also check if any of them require approval. - for (int i = 0; i < messages.Count; i++) - { - var content = messages[i].Contents; - for (int j = 0; j < content.Count; j++) - { - if (content[j] is FunctionCallContent functionCall) - { - allFunctionCallContentIndices ??= []; - allFunctionCallContentIndices.Add((i, j)); - - approvalRequiredFunctions ??= (requestOptionsTools ?? []).Concat(additionalTools ?? []) - .OfType() - .ToArray(); - - anyApprovalRequired |= approvalRequiredFunctions.FirstOrDefault(x => x.Name == functionCall.Name) is { } approvalFunction && await approvalFunction.RequiresApprovalCallback(new(functionCall)); - } - } - } - - // If any function calls were found, and any of them required approval, we should replace all of them with approval requests. - // This is because we do not have a way to deal with cases where some function calls require approval and others do not, so we just replace all of them. - if (allFunctionCallContentIndices is not null && anyApprovalRequired) - { - // Clone the list so, we don't mutate the input. - outputMessages = [.. messages]; - int lastMessageIndex = -1; - - foreach (var (messageIndex, contentIndex) in allFunctionCallContentIndices) - { - // Clone the message if we didn't already clone it in a previous iteration. - var message = lastMessageIndex != messageIndex ? outputMessages[messageIndex].Clone() : outputMessages[messageIndex]; - message.Contents = [.. message.Contents]; - - var functionCall = (FunctionCallContent)message.Contents[contentIndex]; - message.Contents[contentIndex] = new FunctionApprovalRequestContent(functionCall.CallId, functionCall); - outputMessages[messageIndex] = message; - - lastMessageIndex = messageIndex; - } - } - - return outputMessages; - } - - /// - /// Insert the given at the start of the . - /// - private static IList UpdateResponseMessagesWithPreDownstreamCallHistory(IList responseMessages, List? preDownstreamCallHistory) - { - if (preDownstreamCallHistory?.Count > 0) - { - // Since these messages are pre-invocation, we want to insert them at the start of the response messages. - return [.. preDownstreamCallHistory, .. responseMessages]; - } - - return responseMessages; - } - - private static ChatResponseUpdate ConvertToolResultMessageToUpdate(ChatMessage message, string? conversationId, string? messageId) - { - return new() - { - AdditionalProperties = message.AdditionalProperties, - AuthorName = message.AuthorName, - ConversationId = conversationId, - CreatedAt = DateTimeOffset.UtcNow, - Contents = message.Contents, - RawRepresentation = message.RawRepresentation, - ResponseId = messageId, - MessageId = messageId, - Role = message.Role, - }; - } - - private static TimeSpan GetElapsedTime(long startingTimestamp) => -#if NET - Stopwatch.GetElapsedTime(startingTimestamp); -#else - new((long)((Stopwatch.GetTimestamp() - startingTimestamp) * ((double)TimeSpan.TicksPerSecond / Stopwatch.Frequency))); -#endif - - [LoggerMessage(LogLevel.Debug, "Invoking {MethodName}.", SkipEnabledCheck = true)] - private partial void LogInvoking(string methodName); - - [LoggerMessage(LogLevel.Trace, "Invoking {MethodName}({Arguments}).", SkipEnabledCheck = true)] - private partial void LogInvokingSensitive(string methodName, string arguments); - - [LoggerMessage(LogLevel.Debug, "{MethodName} invocation completed. Duration: {Duration}", SkipEnabledCheck = true)] - private partial void LogInvocationCompleted(string methodName, TimeSpan duration); - - [LoggerMessage(LogLevel.Trace, "{MethodName} invocation completed. Duration: {Duration}. Result: {Result}", SkipEnabledCheck = true)] - private partial void LogInvocationCompletedSensitive(string methodName, TimeSpan duration, string result); - - [LoggerMessage(LogLevel.Debug, "{MethodName} invocation canceled.")] - private partial void LogInvocationCanceled(string methodName); - - [LoggerMessage(LogLevel.Error, "{MethodName} invocation failed.")] - private partial void LogInvocationFailed(string methodName, Exception error); - - /// Provides information about the invocation of a function call. - public sealed class FunctionInvocationResult - { - /// - /// Initializes a new instance of the class. - /// - /// Indicates whether the caller should terminate the processing loop. - /// Indicates the status of the function invocation. - /// Contains information about the function call. - /// The result of the function call. - /// The exception thrown by the function call, if any. - internal FunctionInvocationResult(bool terminate, FunctionInvocationStatus status, FunctionCallContent callContent, object? result, Exception? exception) - { - Terminate = terminate; - Status = status; - CallContent = callContent; - Result = result; - Exception = exception; - } - - /// Gets status about how the function invocation completed. - public FunctionInvocationStatus Status { get; } - - /// Gets the function call content information associated with this invocation. - public FunctionCallContent CallContent { get; } - - /// Gets the result of the function call. - public object? Result { get; } - - /// Gets any exception the function call threw. - public Exception? Exception { get; } - - /// Gets a value indicating whether the caller should terminate the processing loop. - public bool Terminate { get; } - } - - /// Provides error codes for when errors occur as part of the function calling loop. - public enum FunctionInvocationStatus - { - /// The operation completed successfully. - RanToCompletion, - - /// The requested function could not be found. - NotFound, - - /// The function call failed with an exception. - Exception, - } - - private struct ApprovalResultWithRequestMessage - { - public FunctionApprovalResponseContent Response { get; set; } - public ChatMessage? RequestMessage { get; set; } - } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/OpenTelemetryConsts.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/OpenTelemetryConsts.cs deleted file mode 100644 index 89eebe9f61..0000000000 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/MEAI/OpenTelemetryConsts.cs +++ /dev/null @@ -1,144 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// WARNING: -// This class has been temporarily copied here from MEAI, to allow prototyping -// functionality that will be moved to MEAI in the future. -// This file is not intended to be modified. - -using System.Diagnostics.CodeAnalysis; - -namespace Microsoft.Extensions.AI; - -#pragma warning disable CA1716 // Identifiers should not match keywords -#pragma warning disable S4041 // Type names should not match namespaces - -/// Provides constants used by various telemetry services. -[ExcludeFromCodeCoverage] -internal static class OpenTelemetryConsts -{ - public const string DefaultSourceName = "Experimental.Microsoft.Extensions.AI"; - - public const string SecondsUnit = "s"; - public const string TokensUnit = "token"; - - public static class Event - { - public const string Name = "event.name"; - } - - public static class Error - { - public const string Type = "error.type"; - } - - public static class GenAI - { - public const string Choice = "gen_ai.choice"; - public const string SystemName = "gen_ai.system"; - - public const string Chat = "chat"; - public const string Embeddings = "embeddings"; - public const string ExecuteTool = "execute_tool"; - - public static class Assistant - { - public const string Message = "gen_ai.assistant.message"; - } - - public static class Client - { - public static class OperationDuration - { - public const string Description = "Measures the duration of a GenAI operation"; - public const string Name = "gen_ai.client.operation.duration"; - public static readonly double[] ExplicitBucketBoundaries = [0.01, 0.02, 0.04, 0.08, 0.16, 0.32, 0.64, 1.28, 2.56, 5.12, 10.24, 20.48, 40.96, 81.92]; - } - - public static class TokenUsage - { - public const string Description = "Measures number of input and output tokens used"; - public const string Name = "gen_ai.client.token.usage"; - public static readonly int[] ExplicitBucketBoundaries = [1, 4, 16, 64, 256, 1_024, 4_096, 16_384, 65_536, 262_144, 1_048_576, 4_194_304, 16_777_216, 67_108_864]; - } - } - - public static class Conversation - { - public const string Id = "gen_ai.conversation.id"; - } - - public static class Operation - { - public const string Name = "gen_ai.operation.name"; - } - - public static class Output - { - public const string Type = "gen_ai.output.type"; - } - - public static class Request - { - public const string EmbeddingDimensions = "gen_ai.request.embedding.dimensions"; - public const string FrequencyPenalty = "gen_ai.request.frequency_penalty"; - public const string Model = "gen_ai.request.model"; - public const string MaxTokens = "gen_ai.request.max_tokens"; - public const string PresencePenalty = "gen_ai.request.presence_penalty"; - public const string Seed = "gen_ai.request.seed"; - public const string StopSequences = "gen_ai.request.stop_sequences"; - public const string Temperature = "gen_ai.request.temperature"; - public const string TopK = "gen_ai.request.top_k"; - public const string TopP = "gen_ai.request.top_p"; - - public static string PerProvider(string providerName, string parameterName) => $"gen_ai.{providerName}.request.{parameterName}"; - } - - public static class Response - { - public const string FinishReasons = "gen_ai.response.finish_reasons"; - public const string Id = "gen_ai.response.id"; - public const string Model = "gen_ai.response.model"; - - public static string PerProvider(string providerName, string parameterName) => $"gen_ai.{providerName}.response.{parameterName}"; - } - - public static class System - { - public const string Message = "gen_ai.system.message"; - } - - public static class Token - { - public const string Type = "gen_ai.token.type"; - } - - public static class Tool - { - public const string Name = "gen_ai.tool.name"; - public const string Description = "gen_ai.tool.description"; - public const string Message = "gen_ai.tool.message"; - - public static class Call - { - public const string Id = "gen_ai.tool.call.id"; - } - } - - public static class Usage - { - public const string InputTokens = "gen_ai.usage.input_tokens"; - public const string OutputTokens = "gen_ai.usage.output_tokens"; - } - - public static class User - { - public const string Message = "gen_ai.user.message"; - } - } - - public static class Server - { - public const string Address = "server.address"; - public const string Port = "server.port"; - } -} diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/Microsoft.Extensions.AI.Agents.csproj b/dotnet/src/Microsoft.Extensions.AI.Agents/Microsoft.Extensions.AI.Agents.csproj index b7f37ba4b4..0548b595e2 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/Microsoft.Extensions.AI.Agents.csproj +++ b/dotnet/src/Microsoft.Extensions.AI.Agents/Microsoft.Extensions.AI.Agents.csproj @@ -4,6 +4,7 @@ $(ProjectsTargetFrameworks) $(ProjectsDebugTargetFrameworks) alpha + $(NoWarn);MEAI001 diff --git a/dotnet/src/Microsoft.Extensions.AI.Agents/OpenTelemetryAgent.cs b/dotnet/src/Microsoft.Extensions.AI.Agents/OpenTelemetryAgent.cs index fd81f7cd3e..7f8b46c82b 100644 --- a/dotnet/src/Microsoft.Extensions.AI.Agents/OpenTelemetryAgent.cs +++ b/dotnet/src/Microsoft.Extensions.AI.Agents/OpenTelemetryAgent.cs @@ -24,13 +24,12 @@ namespace Microsoft.Extensions.AI.Agents; /// This class provides telemetry instrumentation for agent operations including activities, metrics, and logging. /// The telemetry output follows OpenTelemetry semantic conventions in and is subject to change as the conventions evolve. /// -public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable +public sealed partial class OpenTelemetryAgent : DelegatingAIAgent, IDisposable { private const LogLevel EventLogLevel = LogLevel.Information; private JsonSerializerOptions _jsonSerializerOptions; private readonly OpenTelemetryChatClient? _openTelemetryChatClient; private readonly string? _system; - private readonly AIAgent _innerAgent; private readonly ActivitySource _activitySource; private readonly Meter _meter; private readonly Histogram _operationDurationHistogram; @@ -44,9 +43,8 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable /// The to use for emitting events. /// An optional source name that will be used on the telemetry data. public OpenTelemetryAgent(AIAgent innerAgent, ILogger? logger = null, string? sourceName = null) + : base(innerAgent) { - this._innerAgent = Throw.IfNull(innerAgent); - string name = string.IsNullOrEmpty(sourceName) ? OpenTelemetryConsts.DefaultSourceName : sourceName!; this._activitySource = new(name); this._meter = new(name); @@ -54,7 +52,7 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable this._system = this.GetService()?.ProviderName ?? OpenTelemetryConsts.GenAI.SystemNameValues.MicrosoftExtensionsAIAgents; // Attempt to get the open telemetry chat client if the inner agent is a ChatClientAgent. - this._openTelemetryChatClient = (innerAgent as ChatClientAgent)?.ChatClient.GetService(); + this._openTelemetryChatClient = (this.InnerAgent as ChatClientAgent)?.ChatClient.GetService(); // Inherit by default the EnableSensitiveData setting from the TelemetryChatClient if available. this.EnableSensitiveData = this._openTelemetryChatClient?.EnableSensitiveData ?? false; @@ -112,21 +110,16 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable /// public override object? GetService(Type serviceType, object? serviceKey = null) - => base.GetService(serviceType, serviceKey) - ?? (serviceType == typeof(ActivitySource) ? this._activitySource - : this._innerAgent.GetService(serviceType, serviceKey)); + { + // Handle ActivitySource requests directly - always return our own ActivitySource + if (serviceType == typeof(ActivitySource)) + { + return this._activitySource; + } - /// - public override string Id => this._innerAgent.Id; - - /// - public override string? Name => this._innerAgent.Name; - - /// - public override string? Description => this._innerAgent.Description; - - /// - public override AgentThread GetNewThread() => this._innerAgent.GetNewThread(); + // For other service types, use the base delegation logic + return base.GetService(serviceType, serviceKey); + } /// public override async Task RunAsync( @@ -146,7 +139,7 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable Exception? error = null; try { - response = await this._innerAgent.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false); + response = await base.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false); return response; } catch (Exception ex) @@ -175,7 +168,7 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable IAsyncEnumerable updates; try { - updates = this._innerAgent.RunStreamingAsync(messages, thread, options, cancellationToken); + updates = base.RunStreamingAsync(messages, thread, options, cancellationToken); } catch (Exception ex) { @@ -224,7 +217,7 @@ public sealed partial class OpenTelemetryAgent : AIAgent, IDisposable private Activity? CreateAndConfigureActivity(string operationName, IReadOnlyCollection messages, AgentThread? thread) { // Get the GenAI system name for telemetry - var chatClientAgent = this._innerAgent as ChatClientAgent; + var chatClientAgent = this.InnerAgent as ChatClientAgent; Activity? activity = null; if (this._activitySource.HasListeners()) { diff --git a/dotnet/tests/Microsoft.Agents.Orchestration.UnitTests/OrchestrationResultTests.cs b/dotnet/tests/Microsoft.Agents.Orchestration.UnitTests/OrchestrationResultTests.cs index bbc79b661c..9d9f238cca 100644 --- a/dotnet/tests/Microsoft.Agents.Orchestration.UnitTests/OrchestrationResultTests.cs +++ b/dotnet/tests/Microsoft.Agents.Orchestration.UnitTests/OrchestrationResultTests.cs @@ -83,7 +83,7 @@ public class OrchestrationResultTests protected override Task RunCoreAsync(IReadOnlyCollection messages, OrchestratingAgentContext context, CancellationToken cancellationToken) => throw new NotSupportedException(); - protected override Task ResumeCoreAsync(JsonElement checkpointState, OrchestratingAgentContext context, CancellationToken cancellationToken) => + protected override Task ResumeCoreAsync(JsonElement checkpointState, IReadOnlyCollection newMessages, OrchestratingAgentContext context, CancellationToken cancellationToken) => throw new NotSupportedException(); } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/DeclarativeWorkflowTest.cs b/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/DeclarativeWorkflowTest.cs index 701bdf04d1..fc7ee92cbf 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/DeclarativeWorkflowTest.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/DeclarativeWorkflowTest.cs @@ -208,20 +208,20 @@ public sealed class DeclarativeWorkflowTest(ITestOutputHelper output) : Workflow private void AssertExecutionCount(int expectedCount) { - Assert.Equal(expectedCount + 2, this.WorkflowEventCounts[typeof(ExecutorInvokeEvent)]); - Assert.Equal(expectedCount + 2, this.WorkflowEventCounts[typeof(ExecutorCompleteEvent)]); + Assert.Equal(expectedCount + 2, this.WorkflowEventCounts[typeof(ExecutorInvokedEvent)]); + Assert.Equal(expectedCount + 2, this.WorkflowEventCounts[typeof(ExecutorCompletedEvent)]); } private void AssertNotExecuted(string executorId) { - Assert.DoesNotContain(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); - Assert.DoesNotContain(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); + Assert.DoesNotContain(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); + Assert.DoesNotContain(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); } private void AssertExecuted(string executorId) { - Assert.Contains(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); - Assert.Contains(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); + Assert.Contains(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); + Assert.Contains(this.WorkflowEvents.OfType(), e => e.ExecutorId == executorId); } private void AssertMessage(string message) @@ -244,7 +244,7 @@ public sealed class DeclarativeWorkflowTest(ITestOutputHelper output) : Workflow this.WorkflowEvents = run.WatchStreamAsync().ToEnumerable().ToImmutableList(); foreach (WorkflowEvent workflowEvent in this.WorkflowEvents) { - if (workflowEvent is ExecutorInvokeEvent invokeEvent) + if (workflowEvent is ExecutorInvokedEvent invokeEvent) { DeclarativeExecutorResult? message = invokeEvent.Data as DeclarativeExecutorResult; this.Output.WriteLine($"EXEC: {invokeEvent.ExecutorId} << {message?.ExecutorId ?? "?"} [{message?.Result ?? "-"}]"); diff --git a/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/ObjectModel/WorkflowActionExecutorTest.cs b/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/ObjectModel/WorkflowActionExecutorTest.cs index 13ce04e1b9..8d7393864b 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/ObjectModel/WorkflowActionExecutorTest.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.Declarative.UnitTests/ObjectModel/WorkflowActionExecutorTest.cs @@ -33,6 +33,8 @@ public abstract class WorkflowActionExecutorTest(ITestOutputHelper output) : Wor workflowBuilder.AddEdge(workflowExecutor, executor); StreamingRun run = await InProcessExecution.StreamAsync(workflowBuilder.Build(), this.Scopes); WorkflowEvent[] events = await run.WatchStreamAsync().ToArrayAsync(); + Assert.Contains(events, e => e is DeclarativeActionInvokeEvent); + Assert.Contains(events, e => e is DeclarativeActionCompleteEvent); return events; } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/ChatMessageBuilder.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/ChatMessageBuilder.cs new file mode 100644 index 0000000000..54495efbd4 --- /dev/null +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/ChatMessageBuilder.cs @@ -0,0 +1,92 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Linq; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace Microsoft.Agents.Workflows.UnitTests; + +internal static class TextMessageStreamingExtensions +{ + public static IEnumerable ToContentStream(this string? message) + { + if (string.IsNullOrEmpty(message)) + { + return []; + } + + string[] splits = message.Split(' '); + for (int i = 0; i < splits.Length - 1; i++) + { + splits[i] = splits[i] + ' '; + } + + return splits.Select(text => (AIContent)new TextContent(text) { RawRepresentation = text }); + } + + public static AgentRunResponseUpdate ToResponseUpdate(this AIContent content, string? messageId = null, DateTimeOffset? createdAt = null, string? responseId = null, string? agentId = null, string? authorName = null) + { + return new AgentRunResponseUpdate() + { + Role = ChatRole.Assistant, + CreatedAt = createdAt ?? DateTimeOffset.Now, + MessageId = messageId ?? Guid.NewGuid().ToString("N"), + ResponseId = responseId, + AgentId = agentId, + AuthorName = authorName, + Contents = [content], + }; + } + + public static IEnumerable ToAgentRunStream(this string message, DateTimeOffset? createdAt = null, string? messageId = null, string? responseId = null, string? agentId = null, string? authorName = null) + { + messageId ??= Guid.NewGuid().ToString("N"); + + IEnumerable contents = message.ToContentStream(); + return contents.Select(content => content.ToResponseUpdate(messageId, createdAt, responseId, agentId, authorName)); + } + + public static ChatMessage ToChatMessage(this IEnumerable contents, string? messageId = null, DateTimeOffset? createdAt = null, string? responseId = null, string? agentId = null, string? authorName = null, string? rawRepresentation = null) + { + return new ChatMessage(ChatRole.Assistant, contents is List contentsList ? contentsList : contents.ToList()) + { + AuthorName = authorName, + CreatedAt = createdAt ?? DateTimeOffset.Now, + MessageId = messageId ?? Guid.NewGuid().ToString("N"), + RawRepresentation = rawRepresentation, + }; + } + + public static IEnumerable StreamMessage(this ChatMessage message, string? responseId = null, string? agentId = null) + { + responseId ??= Guid.NewGuid().ToString("N"); + string messageId = message.MessageId ?? Guid.NewGuid().ToString("N"); + + return message.Contents.Select(content => content.ToResponseUpdate(messageId, message.CreatedAt, responseId: responseId, agentId: agentId, authorName: message.AuthorName)); + } + + public static IEnumerable StreamMessages(this List messages, string? agentId = null) + { + return messages.SelectMany(message => message.StreamMessage(agentId)); + } + + public static List ToChatMessages(this IEnumerable messages, string? authorName = null) + { + List result = messages.Select(ToMessage).ToList(); + + ChatMessage ToMessage(string text) + { + return new(ChatRole.Assistant, text.ToContentStream().ToList()) + { + AuthorName = authorName, + MessageId = Guid.NewGuid().ToString("N"), + RawRepresentation = text, + CreatedAt = DateTimeOffset.Now, + }; + } + + return result; + } +} diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/MessageMergerTests.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/MessageMergerTests.cs new file mode 100644 index 0000000000..6654d42000 --- /dev/null +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/MessageMergerTests.cs @@ -0,0 +1,42 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using FluentAssertions; +using Microsoft.Extensions.AI; +using Microsoft.Extensions.AI.Agents; + +namespace Microsoft.Agents.Workflows.UnitTests; + +public class MessageMergerTests +{ + public static string TestAgentId1 => "TestAgent1"; + public static string TestAgentId2 => "TestAgent2"; + + public static string TestAuthorName1 => "Assistant1"; + public static string TestAuthorName2 => "Assistant2"; + + [Fact] + public void Test_MessageMerger_AssemblesMessage() + { + DateTimeOffset creationTime = DateTimeOffset.UtcNow; + string responseId = Guid.NewGuid().ToString("N"); + string messageId = Guid.NewGuid().ToString("N"); + + MessageMerger merger = new(); + + foreach (AgentRunResponseUpdate update in "Hello Agent Framework Workflows!".ToAgentRunStream(authorName: TestAuthorName1, agentId: TestAgentId1, messageId: messageId, createdAt: creationTime, responseId: responseId)) + { + merger.AddUpdate(update); + } + + AgentRunResponse response = merger.ComputeMerged(responseId); + + response.Messages.Should().HaveCount(1); + response.Messages[0].Role.Should().Be(ChatRole.Assistant); + response.Messages[0].AuthorName.Should().Be(TestAuthorName1); + response.AgentId.Should().Be(TestAgentId1); + response.CreatedAt.Should().NotBe(creationTime); + response.Messages[0].CreatedAt.Should().Be(creationTime); + response.Messages[0].Contents.Should().HaveCount(1); + } +} diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/RepresentationTests.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/RepresentationTests.cs index 1809d0d908..294b58a4de 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/RepresentationTests.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/RepresentationTests.cs @@ -47,42 +47,49 @@ public class RepresentationTests return current; } - private static void RunExecutorishInfoMatchTest(ExecutorIsh target) + private static async ValueTask RunExecutorishInfoMatchTestAsync(ExecutorIsh target) { ExecutorRegistration registration = target.Registration; ExecutorInfo info = registration.ToExecutorInfo(); - info.IsMatch(registration.Provider()).Should().BeTrue(); + info.IsMatch(await registration.ProviderAsync()).Should().BeTrue(); } [Fact] - public void Test_Executorish_Infos() + public async Task Test_Executorish_InfosAsync() { int testsRun = 0; - RunExecutorishTest(new TestExecutor()); - RunExecutorishTest(TestInputPort); - RunExecutorishTest(new TestAgent()); + await RunExecutorishTest(new TestExecutor()); + await RunExecutorishTest(TestInputPort); + await RunExecutorishTest(new TestAgent()); + + Func function = MessageHandlerAsync; + await RunExecutorishTest(function.AsExecutor("FunctionExecutor")); if (Enum.GetValues(typeof(ExecutorIsh.Type)).Length > testsRun + 1) { Assert.Fail("Not all ExecutorIsh types were tested."); } - void RunExecutorishTest(ExecutorIsh executorish) + async ValueTask RunExecutorishTest(ExecutorIsh executorish) { - RunExecutorishInfoMatchTest(executorish); + await RunExecutorishInfoMatchTestAsync(executorish); testsRun++; } + + async ValueTask MessageHandlerAsync(int message, IWorkflowContext workflowContext, CancellationToken cancellation = default) + { + } } [Fact] - public void Test_SpecializedExecutor_Infos() + public async Task Test_SpecializedExecutor_InfosAsync() { - RunExecutorishInfoMatchTest(new AIAgentHostExecutor(new TestAgent())); - RunExecutorishInfoMatchTest(new RequestInfoExecutor(TestInputPort)); + await RunExecutorishInfoMatchTestAsync(new AIAgentHostExecutor(new TestAgent())); + await RunExecutorishInfoMatchTestAsync(new RequestInfoExecutor(TestInputPort)); OutputCollectorExecutor> outputCollector = new(StreamingAggregators.Union()); - RunExecutorishInfoMatchTest(outputCollector); + await RunExecutorishInfoMatchTestAsync(outputCollector); } private static string Source(string id) => $"Source/{id}"; diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01_Simple_Workflow_Sequential.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01_Simple_Workflow_Sequential.cs index 229e6c3b39..169c805348 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01_Simple_Workflow_Sequential.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01_Simple_Workflow_Sequential.cs @@ -28,9 +28,9 @@ internal static class Step1EntryPoint await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) { - if (evt is ExecutorCompleteEvent executorComplete) + if (evt is ExecutorCompletedEvent executorCompleted) { - writer.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); + writer.WriteLine($"{executorCompleted.ExecutorId}: {executorCompleted.Data}"); } } } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01a_Simple_Workflow_Sequential.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01a_Simple_Workflow_Sequential.cs index cf78998bf5..62b7ead009 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01a_Simple_Workflow_Sequential.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/01a_Simple_Workflow_Sequential.cs @@ -17,9 +17,9 @@ internal static class Step1aEntryPoint foreach (WorkflowEvent evt in run.NewEvents) { - if (evt is ExecutorCompleteEvent executorComplete) + if (evt is ExecutorCompletedEvent executorCompleted) { - writer.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); + writer.WriteLine($"{executorCompleted.ExecutorId}: {executorCompleted.Data}"); } } } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/02_Simple_Workflow_Condition.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/02_Simple_Workflow_Condition.cs index 25a726c893..9a5cbf64c0 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/02_Simple_Workflow_Condition.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/02_Simple_Workflow_Condition.cs @@ -39,8 +39,8 @@ internal static class Step2EntryPoint string workflowResult = workflowCompleteEvt.Data!.ToString()!; writer.WriteLine($"Result: {workflowResult}"); return workflowResult; - case ExecutorCompleteEvent executorCompleteEvt: - writer.WriteLine($"'{executorCompleteEvt.ExecutorId}: {executorCompleteEvt.Data}"); + case ExecutorCompletedEvent executorCompletedEvt: + writer.WriteLine($"'{executorCompletedEvt.ExecutorId}: {executorCompletedEvt.Data}"); break; } } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/03_Simple_Workflow_Loop.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/03_Simple_Workflow_Loop.cs index d886f2a6c7..b56efaff50 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/03_Simple_Workflow_Loop.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/03_Simple_Workflow_Loop.cs @@ -37,8 +37,8 @@ internal static class Step3EntryPoint string workflowResult = workflowCompleteEvt.Data!.ToString()!; writer.WriteLine($"Result: {workflowResult}"); return workflowResult; - case ExecutorCompleteEvent executorCompleteEvt: - writer.WriteLine($"'{executorCompleteEvt.ExecutorId}: {executorCompleteEvt.Data}"); + case ExecutorCompletedEvent executorCompletedEvt: + writer.WriteLine($"'{executorCompletedEvt.ExecutorId}: {executorCompletedEvt.Data}"); break; } } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/04_Simple_Workflow_ExternalRequest.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/04_Simple_Workflow_ExternalRequest.cs index 1f078ecd29..5f94475cb3 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/04_Simple_Workflow_ExternalRequest.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/04_Simple_Workflow_ExternalRequest.cs @@ -46,8 +46,8 @@ internal static class Step4EntryPoint string workflowResult = workflowCompleteEvt.Data!.ToString()!; writer.WriteLine($"Result: {workflowResult}"); return workflowResult; - case ExecutorCompleteEvent executorCompleteEvt: - writer.WriteLine($"'{executorCompleteEvt.ExecutorId}: {executorCompleteEvt.Data}"); + case ExecutorCompletedEvent executorCompletedEvt: + writer.WriteLine($"'{executorCompletedEvt.ExecutorId}: {executorCompletedEvt.Data}"); break; } } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/05_Simple_Workflow_Checkpointing.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/05_Simple_Workflow_Checkpointing.cs index f0755c064a..9093645810 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/05_Simple_Workflow_Checkpointing.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/05_Simple_Workflow_Checkpointing.cs @@ -13,7 +13,7 @@ internal static class Step5EntryPoint { private static CheckpointManager CheckpointManager { get; } = new(); - public static async ValueTask RunAsync(TextWriter writer, Func userGuessCallback) + public static async ValueTask RunAsync(TextWriter writer, Func userGuessCallback, bool rehydrateToRestore = false) { Workflow workflow = Step4EntryPoint.CreateWorkflowInstance(out JudgeExecutor judge); Checkpointed> checkpointed = @@ -30,7 +30,19 @@ internal static class Step5EntryPoint checkpoints.Should().HaveCount(6, "we should have two checkpoints, one for each step"); judge.Tries.Should().Be(2); - await checkpointed.RestoreCheckpointAsync(checkpoints[2], CancellationToken.None).ConfigureAwait(false); + CheckpointInfo targetCheckpoint = checkpoints[2]; + + if (rehydrateToRestore) + { + checkpointed = await InProcessExecution.ResumeStreamAsync(workflow, targetCheckpoint, CheckpointManager, CancellationToken.None) + .ConfigureAwait(false); + handle = checkpointed.Run; + } + else + { + await checkpointed.RestoreCheckpointAsync(checkpoints[2], CancellationToken.None).ConfigureAwait(false); + } + judge.Tries.Should().Be(1); cancellationSource.Dispose(); @@ -73,7 +85,7 @@ internal static class Step5EntryPoint string workflowResult = workflowCompleteEvt.Data!.ToString()!; writer.WriteLine($"Result: {workflowResult}"); return workflowResult; - case ExecutorCompleteEvent executorCompleteEvt: + case ExecutorCompletedEvent executorCompleteEvt: writer.WriteLine($"'{executorCompleteEvt.ExecutorId}: {executorCompleteEvt.Data}"); break; } diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/06_GroupChat_Workflow.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/06_GroupChat_Workflow.cs index df818a932c..47e5128cd9 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/06_GroupChat_Workflow.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/Sample/06_GroupChat_Workflow.cs @@ -37,9 +37,9 @@ internal static class Step6EntryPoint await foreach (WorkflowEvent evt in run.WatchStreamAsync().ConfigureAwait(false)) { - if (evt is ExecutorCompleteEvent executorComplete) + if (evt is ExecutorCompletedEvent executorCompleted) { - Debug.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}"); + Debug.WriteLine($"{executorCompleted.ExecutorId}: {executorCompleted.Data}"); } else if (evt is AgentRunUpdateEvent update) { diff --git a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/SampleSmokeTest.cs b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/SampleSmokeTest.cs index 9e3277dfaf..ed1fec105b 100644 --- a/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/SampleSmokeTest.cs +++ b/dotnet/tests/Microsoft.Agents.Workflows.UnitTests/SampleSmokeTest.cs @@ -103,6 +103,25 @@ public class SampleSmokeTest Assert.Equal("You guessed correctly! You Win!", guessResult); } + [Fact] + public async Task Test_RunSample_Step5aAsync() + { + using StringWriter writer = new(); + + VerifyingPlaybackResponder responder = new( + // Iteration 1 + ("Guess the number.", 50), + ("Your guess was too high. Try again.", 23), + + // Iteration 2 + ("Your guess was too high. Try again.", 23), + ("Your guess was too low. Try again.", 42) + ); + + string guessResult = await Step5EntryPoint.RunAsync(writer, userGuessCallback: responder.InvokeNext, rehydrateToRestore: true); + Assert.Equal("You guessed correctly! You Win!", guessResult); + } + [Fact] public async Task Test_RunSample_Step6Async() { diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/AgentThreadTests.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/AgentThreadTests.cs index 157fb30fdc..305fc1cd45 100644 --- a/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/AgentThreadTests.cs +++ b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/AgentThreadTests.cs @@ -88,56 +88,6 @@ public class AgentThreadTests #endregion Constructor and Property Tests - #region GetMessagesAsync Tests - - [Fact] - public async Task GetMessagesAsyncReturnsEmptyListWhenNoStoreAsync() - { - // Arrange - var thread = new AgentThread(); - - // Act - var messages = await ToListAsync(thread.GetMessagesAsync(CancellationToken.None)); - - // Assert - Assert.Empty(messages); - } - - [Fact] - public async Task GetMessagesAsyncReturnsEmptyListWhenAgentServiceIdAsync() - { - // Arrange - var thread = new AgentThread { ConversationId = "thread-123" }; - - // Act - var messages = await ToListAsync(thread.GetMessagesAsync(CancellationToken.None)); - - // Assert - Assert.Empty(messages); - } - - [Fact] - public async Task GetMessagesAsyncReturnsMessagesFromStoreAsync() - { - // Arrange - var store = new InMemoryChatMessageStore - { - new ChatMessage(ChatRole.User, "Hello"), - new ChatMessage(ChatRole.Assistant, "Hi there!") - }; - var thread = new AgentThread { MessageStore = store }; - - // Act - var messages = await ToListAsync(thread.GetMessagesAsync(CancellationToken.None)); - - // Assert - Assert.Equal(2, messages.Count); - Assert.Equal("Hello", messages[0].Text); - Assert.Equal("Hi there!", messages[1].Text); - } - - #endregion GetMessagesAsync Tests - #region OnNewMessagesAsync Tests [Fact] diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/DelegatingAIAgentTests.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/DelegatingAIAgentTests.cs new file mode 100644 index 0000000000..22abf8e0ba --- /dev/null +++ b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/DelegatingAIAgentTests.cs @@ -0,0 +1,308 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Threading; +using System.Threading.Tasks; +using Moq; + +namespace Microsoft.Extensions.AI.Agents.Abstractions.UnitTests; + +/// +/// Unit tests for the class. +/// +public class DelegatingAIAgentTests +{ + private readonly Mock _innerAgentMock; + private readonly TestDelegatingAIAgent _delegatingAgent; + private readonly AgentRunResponse _testResponse; + private readonly List _testStreamingResponses; + private readonly AgentThread _testThread; + + /// + /// Initializes a new instance of the class. + /// + public DelegatingAIAgentTests() + { + this._innerAgentMock = new Mock(); + this._testResponse = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, "Test response")); + this._testStreamingResponses = [new AgentRunResponseUpdate(ChatRole.Assistant, "Test streaming response")]; + this._testThread = new AgentThread(); + + // Setup inner agent mock + this._innerAgentMock.Setup(x => x.Id).Returns("test-agent-id"); + this._innerAgentMock.Setup(x => x.Name).Returns("Test Agent"); + this._innerAgentMock.Setup(x => x.Description).Returns("Test Description"); + this._innerAgentMock.Setup(x => x.GetNewThread()).Returns(this._testThread); + + this._innerAgentMock + .Setup(x => x.RunAsync( + It.IsAny>(), + It.IsAny(), + It.IsAny(), + It.IsAny())) + .ReturnsAsync(this._testResponse); + + this._innerAgentMock + .Setup(x => x.RunStreamingAsync( + It.IsAny>(), + It.IsAny(), + It.IsAny(), + It.IsAny())) + .Returns(ToAsyncEnumerableAsync(this._testStreamingResponses)); + + this._delegatingAgent = new TestDelegatingAIAgent(this._innerAgentMock.Object); + } + + #region Constructor Tests + + /// + /// Verify that constructor throws ArgumentNullException when innerAgent is null. + /// + [Fact] + public void RequiresInnerAgent() + { + // Act & Assert + Assert.Throws("innerAgent", () => new TestDelegatingAIAgent(null!)); + } + + /// + /// Verify that constructor sets the inner agent correctly. + /// + [Fact] + public void Constructor_WithValidInnerAgent_SetsInnerAgent() + { + // Act + var delegatingAgent = new TestDelegatingAIAgent(this._innerAgentMock.Object); + + // Assert + Assert.Same(this._innerAgentMock.Object, delegatingAgent.InnerAgent); + } + + #endregion + + #region Property Delegation Tests + + /// + /// Verify that Id property delegates to inner agent. + /// + [Fact] + public void Id_DelegatesToInnerAgent() + { + // Act + var id = this._delegatingAgent.Id; + + // Assert + Assert.Equal("test-agent-id", id); + this._innerAgentMock.Verify(x => x.Id, Times.Once); + } + + /// + /// Verify that Name property delegates to inner agent. + /// + [Fact] + public void Name_DelegatesToInnerAgent() + { + // Act + var name = this._delegatingAgent.Name; + + // Assert + Assert.Equal("Test Agent", name); + this._innerAgentMock.Verify(x => x.Name, Times.Once); + } + + /// + /// Verify that Description property delegates to inner agent. + /// + [Fact] + public void Description_DelegatesToInnerAgent() + { + // Act + var description = this._delegatingAgent.Description; + + // Assert + Assert.Equal("Test Description", description); + this._innerAgentMock.Verify(x => x.Description, Times.Once); + } + + #endregion + + #region Method Delegation Tests + + /// + /// Verify that GetNewThread delegates to inner agent. + /// + [Fact] + public void GetNewThread_DelegatesToInnerAgent() + { + // Act + var thread = this._delegatingAgent.GetNewThread(); + + // Assert + Assert.Same(this._testThread, thread); + this._innerAgentMock.Verify(x => x.GetNewThread(), Times.Once); + } + + /// + /// Verify that RunAsync delegates to inner agent with correct parameters. + /// + [Fact] + public async Task RunAsyncDefaultsToInnerAgentAsync() + { + // Arrange + var expectedMessages = new[] { new ChatMessage(ChatRole.User, "Test message") }; + var expectedThread = new AgentThread(); + var expectedOptions = new AgentRunOptions(); + var expectedCancellationToken = new CancellationToken(); + var expectedResult = new TaskCompletionSource(); + var expectedResponse = new AgentRunResponse(); + + var innerAgentMock = new Mock(); + innerAgentMock + .Setup(x => x.RunAsync(expectedMessages, expectedThread, expectedOptions, expectedCancellationToken)) + .Returns(expectedResult.Task); + + var delegatingAgent = new TestDelegatingAIAgent(innerAgentMock.Object); + + // Act + var resultTask = delegatingAgent.RunAsync(expectedMessages, expectedThread, expectedOptions, expectedCancellationToken); + + // Assert + Assert.False(resultTask.IsCompleted); + expectedResult.SetResult(expectedResponse); + Assert.True(resultTask.IsCompleted); + Assert.Same(expectedResponse, await resultTask); + } + + /// + /// Verify that RunStreamingAsync delegates to inner agent with correct parameters. + /// + [Fact] + public async Task RunStreamingAsyncDefaultsToInnerAgentAsync() + { + // Arrange + var expectedMessages = new[] { new ChatMessage(ChatRole.User, "Test message") }; + var expectedThread = new AgentThread(); + var expectedOptions = new AgentRunOptions(); + var expectedCancellationToken = new CancellationToken(); + AgentRunResponseUpdate[] expectedResults = + [ + new(ChatRole.Assistant, "Message 1"), + new(ChatRole.Assistant, "Message 2") + ]; + + var innerAgentMock = new Mock(); + innerAgentMock + .Setup(x => x.RunStreamingAsync(expectedMessages, expectedThread, expectedOptions, expectedCancellationToken)) + .Returns(ToAsyncEnumerableAsync(expectedResults)); + + var delegatingAgent = new TestDelegatingAIAgent(innerAgentMock.Object); + + // Act + var resultAsyncEnumerable = delegatingAgent.RunStreamingAsync(expectedMessages, expectedThread, expectedOptions, expectedCancellationToken); + + // Assert + var enumerator = resultAsyncEnumerable.GetAsyncEnumerator(); + Assert.True(await enumerator.MoveNextAsync()); + Assert.Same(expectedResults[0], enumerator.Current); + Assert.True(await enumerator.MoveNextAsync()); + Assert.Same(expectedResults[1], enumerator.Current); + Assert.False(await enumerator.MoveNextAsync()); + } + + #endregion + + #region GetService Tests + + /// + /// Verify that GetService throws ArgumentNullException when serviceType is null. + /// + [Fact] + public void GetServiceThrowsForNullType() + { + // Act & Assert + Assert.Throws("serviceType", () => this._delegatingAgent.GetService(null!)); + } + + /// + /// Verify that GetService returns the delegating agent itself when requesting compatible type and key is null. + /// + [Fact] + public void GetServiceReturnsSelfIfCompatibleWithRequestAndKeyIsNull() + { + // Act + var agent = this._delegatingAgent.GetService(); + + // Assert + Assert.Same(this._delegatingAgent, agent); + } + + /// + /// Verify that GetService delegates to inner agent when service key is not null. + /// + [Fact] + public void GetServiceDelegatesToInnerIfKeyIsNotNull() + { + // Arrange + var expectedKey = new object(); + var expectedResult = new Mock().Object; + var innerAgentMock = new Mock(); + innerAgentMock.Setup(x => x.GetService(typeof(AIAgent), expectedKey)).Returns(expectedResult); + var delegatingAgent = new TestDelegatingAIAgent(innerAgentMock.Object); + + // Act + var agent = delegatingAgent.GetService(expectedKey); + + // Assert + Assert.Same(expectedResult, agent); + } + + /// + /// Verify that GetService delegates to inner agent when not compatible with request. + /// + [Fact] + public void GetServiceDelegatesToInnerIfNotCompatibleWithRequest() + { + // Arrange + var expectedResult = TimeZoneInfo.Local; + var expectedKey = new object(); + var innerAgentMock = new Mock(); + innerAgentMock + .Setup(x => x.GetService(typeof(TimeZoneInfo), expectedKey)) + .Returns(expectedResult); + var delegatingAgent = new TestDelegatingAIAgent(innerAgentMock.Object); + + // Act + var tzi = delegatingAgent.GetService(expectedKey); + + // Assert + Assert.Same(expectedResult, tzi); + } + + #endregion + + #region Helper Methods + + private static async IAsyncEnumerable ToAsyncEnumerableAsync(IEnumerable values) + { + await Task.Yield(); + foreach (var value in values) + { + yield return value; + } + } + + #endregion + + #region Test Implementation + + /// + /// Test implementation of DelegatingAIAgent for testing purposes. + /// + private sealed class TestDelegatingAIAgent(AIAgent innerAgent) : DelegatingAIAgent(innerAgent) + { + public new AIAgent InnerAgent => base.InnerAgent; + } + + #endregion +} diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests.csproj b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests.csproj index 38ae8712cb..ee3bc2d9fb 100644 --- a/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests.csproj +++ b/dotnet/tests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests/Microsoft.Extensions.AI.Agents.Abstractions.UnitTests.csproj @@ -2,6 +2,7 @@ $(ProjectsTargetFrameworks) + $(NoWarn);MEAI001 diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/AgentAIFunctionFactoryTests.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/AgentAIFunctionFactoryTests.cs new file mode 100644 index 0000000000..d1c10c5f40 --- /dev/null +++ b/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/AgentAIFunctionFactoryTests.cs @@ -0,0 +1,339 @@ +// Copyright (c) Microsoft. All rights reserved. + +using System; +using System.Collections.Generic; +using System.Runtime.CompilerServices; +using System.Threading; +using System.Threading.Tasks; +using Moq; + +namespace Microsoft.Extensions.AI.Agents.UnitTests; + +/// +/// Unit tests for the class. +/// +public class AgentAIFunctionFactoryTests +{ + [Fact] + public void CreateFromAgent_WithNullAgent_ThrowsArgumentNullException() + { + // Act & Assert + var exception = Assert.Throws(() => + AgentAIFunctionFactory.CreateFromAgent(null!)); + + Assert.Equal("agent", exception.ParamName); + } + + [Fact] + public void CreateFromAgent_WithValidAgent_ReturnsAIFunction() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns("Test agent description"); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + Assert.True(result is AIFunction); + Assert.Equal("TestAgent", result.Name); + Assert.Equal("Test agent description", result.Description); + } + + [Fact] + public void CreateFromAgent_WithAgentHavingNullName_UsesDefaultName() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns((string?)null); + mockAgent.Setup(a => a.Description).Returns("Test description"); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + Assert.NotNull(result.Name); + Assert.Equal("Test description", result.Description); + } + + [Fact] + public void CreateFromAgent_WithAgentHavingNullDescription_UsesEmptyDescription() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns((string?)null); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + Assert.Equal("TestAgent", result.Name); + Assert.Equal(string.Empty, result.Description); + } + + [Fact] + public void CreateFromAgent_WithCustomOptions_UsesCustomOptions() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns("Test agent description"); + + var customOptions = new AIFunctionFactoryOptions + { + Name = "CustomName", + Description = "Custom description" + }; + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object, customOptions); + + // Assert + Assert.NotNull(result); + Assert.Equal("CustomName", result.Name); + Assert.Equal("Custom description", result.Description); + } + + [Fact] + public void CreateFromAgent_WithNullOptions_UsesAgentProperties() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns("Test agent description"); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object, null); + + // Assert + Assert.NotNull(result); + Assert.Equal("TestAgent", result.Name); + Assert.Equal("Test agent description", result.Description); + } + + [Fact] + public async Task CreateFromAgent_WhenFunctionInvokedAsync_CallsAgentRunAsync() + { + // Arrange + var expectedResponse = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, "Test response")); + var testAgent = new TestAgent("TestAgent", "Test description", expectedResponse); + + var aiFunction = AgentAIFunctionFactory.CreateFromAgent(testAgent); + + // Act + var arguments = new AIFunctionArguments() { ["query"] = "Test query" }; + var result = await aiFunction.InvokeAsync(arguments); + + // Assert + Assert.NotNull(result); + Assert.Equal("Test response", result.ToString()); + } + + [Fact] + public async Task CreateFromAgent_WhenFunctionInvokedWithCancellationTokenAsync_PassesCancellationTokenAsync() + { + // Arrange + var expectedResponse = new AgentRunResponse(new ChatMessage(ChatRole.Assistant, "Test response")); + var testAgent = new TestAgent("TestAgent", "Test description", expectedResponse); + using var cancellationTokenSource = new CancellationTokenSource(); + var cancellationToken = cancellationTokenSource.Token; + + var aiFunction = AgentAIFunctionFactory.CreateFromAgent(testAgent); + + // Act + var arguments = new AIFunctionArguments() { ["query"] = "Test query" }; + var result = await aiFunction.InvokeAsync(arguments, cancellationToken); + + // Assert + Assert.NotNull(result); + Assert.Equal("Test response", result.ToString()); + } + + [Fact] + public async Task CreateFromAgent_WhenAgentThrowsExceptionAsync_PropagatesExceptionAsync() + { + // Arrange + var expectedException = new InvalidOperationException("Test exception"); + var testAgent = new TestAgent("TestAgent", "Test description", expectedException); + + var aiFunction = AgentAIFunctionFactory.CreateFromAgent(testAgent); + + // Act & Assert + var arguments = new AIFunctionArguments() { ["query"] = "Test query" }; + var actualException = await Assert.ThrowsAsync(async () => + await aiFunction.InvokeAsync(arguments)); + + Assert.Same(expectedException, actualException); + } + + [Fact] + public void CreateFromAgent_ReturnsInvokableFunction() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns("Test description"); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + + // Verify the function has the expected parameter schema + var parameters = result.JsonSchema; + + // Verify it has a query parameter + Assert.True(parameters.TryGetProperty("properties", out var properties)); + Assert.True(properties.TryGetProperty("query", out var queryProperty)); + Assert.True(queryProperty.TryGetProperty("type", out var typeProperty)); + Assert.Equal("string", typeProperty.GetString()); + } + + [Fact] + public void CreateFromAgent_WithEmptyAgentName_CreatesValidFunction() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns(string.Empty); + mockAgent.Setup(a => a.Description).Returns("Test description"); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + Assert.Equal(string.Empty, result.Name); + Assert.Equal("Test description", result.Description); + } + + [Fact] + public void CreateFromAgent_WithEmptyAgentDescription_CreatesValidFunction() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns("TestAgent"); + mockAgent.Setup(a => a.Description).Returns(string.Empty); + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object); + + // Assert + Assert.NotNull(result); + Assert.Equal("TestAgent", result.Name); + Assert.Equal(string.Empty, result.Description); + } + + [Fact] + public void CreateFromAgent_WithCustomOptionsOverridingNullAgentProperties_UsesCustomOptions() + { + // Arrange + var mockAgent = new Mock(); + mockAgent.Setup(a => a.Name).Returns((string?)null); + mockAgent.Setup(a => a.Description).Returns((string?)null); + + var customOptions = new AIFunctionFactoryOptions + { + Name = "OverrideName", + Description = "Override description" + }; + + // Act + var result = AgentAIFunctionFactory.CreateFromAgent(mockAgent.Object, customOptions); + + // Assert + Assert.NotNull(result); + Assert.Equal("OverrideName", result.Name); + Assert.Equal("Override description", result.Description); + } + + [Fact] + public async Task CreateFromAgent_InvokeWithComplexResponseFromAgentAsync_ReturnsCorrectResponseAsync() + { + // Arrange + var expectedResponse = new AgentRunResponse + { + AgentId = "agent-123", + ResponseId = "response-456", + CreatedAt = DateTimeOffset.UtcNow, + Messages = { new ChatMessage(ChatRole.Assistant, "Complex response") } + }; + + var testAgent = new TestAgent("TestAgent", "Test description", expectedResponse); + var aiFunction = AgentAIFunctionFactory.CreateFromAgent(testAgent); + + // Act + var arguments = new AIFunctionArguments() { ["query"] = "Test query" }; + var result = await aiFunction.InvokeAsync(arguments); + + // Assert + Assert.NotNull(result); + Assert.Equal("Complex response", result.ToString()); + } + + /// + /// Test implementation of AIAgent for testing purposes. + /// + private sealed class TestAgent : AIAgent + { + private readonly AgentRunResponse? _responseToReturn; + private readonly Exception? _exceptionToThrow; + + public TestAgent(string? name, string? description, AgentRunResponse responseToReturn) + { + this.Name = name; + this.Description = description; + this._responseToReturn = responseToReturn; + } + + public TestAgent(string? name, string? description, Exception exceptionToThrow) + { + this.Name = name; + this.Description = description; + this._exceptionToThrow = exceptionToThrow; + } + + public override string? Name { get; } + public override string? Description { get; } + + public List ReceivedMessages { get; } = new(); + public CancellationToken LastCancellationToken { get; private set; } + public int RunAsyncCallCount { get; private set; } + + public override Task RunAsync( + IReadOnlyCollection messages, + AgentThread? thread = null, + AgentRunOptions? options = null, + CancellationToken cancellationToken = default) + { + this.RunAsyncCallCount++; + this.LastCancellationToken = cancellationToken; + this.ReceivedMessages.AddRange(messages); + + if (this._exceptionToThrow != null) + { + throw this._exceptionToThrow; + } + + return Task.FromResult(this._responseToReturn!); + } + + public override async IAsyncEnumerable RunStreamingAsync( + IReadOnlyCollection messages, + AgentThread? thread = null, + AgentRunOptions? options = null, + [EnumeratorCancellation] CancellationToken cancellationToken = default) + { + var response = await this.RunAsync(messages, thread, options, cancellationToken); + foreach (var update in response.ToAgentRunResponseUpdates()) + { + yield return update; + } + } + } +} diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/AssertExtensions.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/AssertExtensions.cs deleted file mode 100644 index da95df83d0..0000000000 --- a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/AssertExtensions.cs +++ /dev/null @@ -1,86 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// WARNING: -// This class has been temporarily copied here from MEAI, to allow prototyping -// functionality that will be moved to MEAI in the future. -// This file is not intended to be modified. - -using System.Collections.Generic; -using System.Linq; -using System.Text.Json; -using System.Text.Json.Nodes; -using Xunit.Sdk; - -namespace Microsoft.Extensions.AI; - -internal static class AssertExtensions -{ - /// - /// Asserts that the two function call parameters are equal, up to JSON equivalence. - /// - public static void EqualFunctionCallParameters( - IDictionary? expected, - IDictionary? actual, - JsonSerializerOptions? options = null) - { - if (expected is null || actual is null) - { - Assert.Equal(expected, actual); - return; - } - - foreach (var expectedEntry in expected) - { - if (!actual.TryGetValue(expectedEntry.Key, out object? actualValue)) - { - throw new XunitException($"Expected parameter '{expectedEntry.Key}' not found in actual value."); - } - - AreJsonEquivalentValues(expectedEntry.Value, actualValue, options, propertyName: expectedEntry.Key); - } - - if (expected.Count != actual.Count) - { - var extraParameters = actual - .Where(e => !expected.ContainsKey(e.Key)) - .Select(e => $"'{e.Key}'") - .First(); - - throw new XunitException($"Actual value contains additional parameters {string.Join(", ", extraParameters)} not found in expected value."); - } - } - - /// - /// Asserts that the two function call results are equal, up to JSON equivalence. - /// - public static void EqualFunctionCallResults(object? expected, object? actual, JsonSerializerOptions? options = null) - => AreJsonEquivalentValues(expected, actual, options); - - /// - /// Asserts that the two JSON values are equal. - /// - public static void EqualJsonValues(JsonElement expectedJson, JsonElement actualJson, string? propertyName = null) - { - if (!JsonNode.DeepEquals( - JsonSerializer.SerializeToNode(expectedJson, AIJsonUtilities.DefaultOptions), - JsonSerializer.SerializeToNode(actualJson, AIJsonUtilities.DefaultOptions))) - { - string message = propertyName is null - ? $"JSON result does not match expected JSON.\r\nExpected: {expectedJson.GetRawText()}\r\nActual: {actualJson.GetRawText()}" - : $"Parameter '{propertyName}' does not match expected JSON.\r\nExpected: {expectedJson.GetRawText()}\r\nActual: {actualJson.GetRawText()}"; - - throw new XunitException(message); - } - } - - private static void AreJsonEquivalentValues(object? expected, object? actual, JsonSerializerOptions? options, string? propertyName = null) - { - options ??= AIJsonUtilities.DefaultOptions; - JsonElement expectedElement = NormalizeToElement(expected, options); - JsonElement actualElement = NormalizeToElement(actual, options); - EqualJsonValues(expectedElement, actualElement, propertyName); - - static JsonElement NormalizeToElement(object? value, JsonSerializerOptions options) - => value is JsonElement e ? e : JsonSerializer.SerializeToElement(value, options); - } -} diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/NewFunctionInvokingChatClientTests.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/NewFunctionInvokingChatClientTests.cs deleted file mode 100644 index b03ac5fdd3..0000000000 --- a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/NewFunctionInvokingChatClientTests.cs +++ /dev/null @@ -1,931 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// AF repo suppressions for code copied from MEAI. -#pragma warning disable CA5394 // Do not use insecure randomness -#pragma warning disable IDE0009 // Member access should be qualified. -#pragma warning disable IDE0039 // Use local function - -using System; -using System.Collections; -using System.Collections.Generic; -using System.Linq; -using System.Runtime.CompilerServices; -using System.Threading; -using System.Threading.Tasks; - -namespace Microsoft.Extensions.AI; - -public class NewFunctionInvokingChatClientTests -{ - [Theory] - [InlineData(false)] - [InlineData(true)] - public async Task AllFunctionCallsReplacedWithApprovalsWhenAllRequireApprovalAsync(bool useAdditionalTools) - { - AITool[] tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - new ApprovalRequiredAIFunction(AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2")) { RequiresApprovalCallback = async (context) => context.FunctionCall.Name == "Func2" }, - ]; - - var options = new ChatOptions - { - Tools = useAdditionalTools ? null : tools - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - ]; - - List expectedOutput = - [ - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, expectedOutput, additionalTools: useAdditionalTools ? tools : null); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, expectedOutput, additionalTools: useAdditionalTools ? tools : null); - } - - [Fact] - public async Task AllFunctionCallsReplacedWithApprovalsWhenAnyRequireApprovalAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - ]; - - List expectedOutput = - [ - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, expectedOutput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, expectedOutput); - } - - [Theory] - [InlineData(false)] - [InlineData(true)] - public async Task AllFunctionCallsReplacedWithApprovalsWhenAnyRequestOrAdditionalRequireApprovalAsync(bool additionalToolsRequireApproval) - { - AIFunction func1 = AIFunctionFactory.Create(() => "Result 1", "Func1"); - AIFunction func2 = AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"); - AITool[] additionalTools = - [ - additionalToolsRequireApproval ? new ApprovalRequiredAIFunction(func1) : func1, - ]; - - var options = new ChatOptions - { - Tools = - [ - additionalToolsRequireApproval ? func2 : new ApprovalRequiredAIFunction(func2), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - ]; - - List expectedOutput = - [ - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, expectedOutput, additionalTools: additionalTools); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, expectedOutput, additionalTools: additionalTools); - } - - [Fact] - public async Task ApprovedApprovalResponsesAreExecutedAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task ApprovedApprovalResponsesFromSeparateFCCMessagesAreExecutedAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp2" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - ]), - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1")]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]) { MessageId = "resp2" }, - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1")]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]) { MessageId = "resp2" }, - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task RejectedApprovalResponsesAreFailedAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", false, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", false, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Error: Function invocation approval was not granted."), new FunctionResultContent("callId2", result: "Error: Function invocation approval was not granted.")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Error: Function invocation approval was not granted."), new FunctionResultContent("callId2", result: "Error: Function invocation approval was not granted.")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task MixedApprovedAndRejectedApprovalResponsesAreExecutedAndFailedAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", false, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Error: Function invocation approval was not granted.")]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List nonStreamingOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Error: Function invocation approval was not granted.")]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List streamingOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Error: Function invocation approval was not granted."), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, nonStreamingOutput, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, streamingOutput, expectedDownstreamClientInput); - } - - [Fact] - public async Task ApprovedInputsAreExecutedAndFunctionResultsAreConvertedAsync() - { - var options = new ChatOptions - { - Tools = - [ - AIFunctionFactory.Create(() => "Result 1", "Func1"), - new ApprovalRequiredAIFunction(AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2")), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 3 } })]), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, [new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 3 } }))]), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task AlreadyExecutedApprovalsAreIgnoredAsync() - { - var options = new ChatOptions - { - Tools = - [ - AIFunctionFactory.Create(() => "Result 1", "Func1"), - new ApprovalRequiredAIFunction(AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2")), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalRequestContent("callId2", new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]) { MessageId = "resp1" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId3", new FunctionCallContent("callId3", "Func1")), - ]) { MessageId = "resp2" }, - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId3", true, new FunctionCallContent("callId3", "Func1")), - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId3", "Func1")]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId3", result: "Result 1")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "World"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId3", "Func1")]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId3", result: "Result 1")]), - new ChatMessage(ChatRole.Assistant, "World"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task ApprovalRequestWithoutApprovalResponseThrowsAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, - [ - new FunctionApprovalRequestContent("callId1", new FunctionCallContent("callId1", "Func1")), - ]) { MessageId = "resp1" }, - ]; - - var invokeException = await Assert.ThrowsAsync( - async () => await InvokeAndAssertAsync(options, input, [], [], [])); - Assert.Equal("FunctionApprovalRequestContent found with FunctionCall.CallId(s) 'callId1' that have no matching FunctionApprovalResponseContent.", invokeException.Message); - - var invokeStreamingException = await Assert.ThrowsAsync( - async () => await InvokeAndAssertStreamingAsync(options, input, [], [], [])); - Assert.Equal("FunctionApprovalRequestContent found with FunctionCall.CallId(s) 'callId1' that have no matching FunctionApprovalResponseContent.", invokeStreamingException.Message); - } - - [Fact] - public async Task ApprovedApprovalResponsesWithoutApprovalRequestAreExecutedAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.User, "hello"), - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - [Fact] - public async Task FunctionCallContentIsNotPassedToDownstreamServiceWithServiceThreadsAsync() - { - var options = new ChatOptions - { - Tools = - [ - new ApprovalRequiredAIFunction(AIFunctionFactory.Create(() => "Result 1", "Func1")), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ], - ConversationId = "test-conversation", - }; - - List input = - [ - new ChatMessage(ChatRole.User, - [ - new FunctionApprovalResponseContent("callId1", true, new FunctionCallContent("callId1", "Func1")), - new FunctionApprovalResponseContent("callId2", true, new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })) - ]), - ]; - - List expectedDownstreamClientInput = - [ - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - ]; - - List downstreamClientOutput = - [ - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - List output = - [ - new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1"), new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]), - new ChatMessage(ChatRole.Tool, [new FunctionResultContent("callId1", result: "Result 1"), new FunctionResultContent("callId2", result: "Result 2: 42")]), - new ChatMessage(ChatRole.Assistant, "world"), - ]; - - await InvokeAndAssertAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - - await InvokeAndAssertStreamingAsync(options, input, downstreamClientOutput, output, expectedDownstreamClientInput); - } - - /// - /// Since we do not have a way of supporting both functions that require approval and those that do not - /// in one invocation, we always require all function calls to be approved if any require approval. - /// If we are therefore unsure as to whether we will encounter a function call that requires approval, - /// we have to wait until we find one before yielding any function call content. - /// If we don't have any function calls that require approval at all though, we can just yield all content normally - /// since this issue won't apply. - /// - [Fact] - public async Task FunctionCallContentIsYieldedImmediatelyIfNoApprovalRequiredWhenStreamingAsync() - { - var options = new ChatOptions - { - Tools = - [ - AIFunctionFactory.Create(() => "Result 1", "Func1"), - AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2"), - ] - }; - - List input = [new ChatMessage(ChatRole.User, "hello")]; - - Func configurePipeline = b => b.Use(s => new NewFunctionInvokingChatClient(s)); - using CancellationTokenSource cts = new(); - - var updateYieldCount = 0; - - async IAsyncEnumerable YieldInnerClientUpdates(IEnumerable contents, ChatOptions? actualOptions, [EnumeratorCancellation] CancellationToken actualCancellationToken) - { - Assert.Equal(cts.Token, actualCancellationToken); - await Task.Yield(); - var messageId = Guid.NewGuid().ToString("N"); - - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1")]) { MessageId = messageId }; - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]) { MessageId = messageId }; - } - - using var innerClient = new TestChatClient { GetStreamingResponseAsyncCallback = YieldInnerClientUpdates }; - IChatClient service = configurePipeline(innerClient.AsBuilder()).Build(); - - var updates = service.GetStreamingResponseAsync(new EnumeratedOnceEnumerable(input), options, cts.Token); - - var updateCount = 0; - await foreach (var update in updates) - { - if (updateCount < 2) - { - var functionCall = update.Contents.OfType().First(); - if (functionCall.CallId == "callId1") - { - Assert.Equal("Func1", functionCall.Name); - Assert.Equal(1, updateYieldCount); - } - else if (functionCall.CallId == "callId2") - { - Assert.Equal("Func2", functionCall.Name); - Assert.Equal(2, updateYieldCount); - } - } - - updateCount++; - } - } - - /// - /// Since we do not have a way of supporting both functions that require approval and those that do not - /// in one invocation, we always require all function calls to be approved if any require approval. - /// If we are therefore unsure as to whether we will encounter a function call that requires approval, - /// we have to wait until we find one before yielding any function call content. - /// We can however, yield any other content until we encounter the first function call. - /// - [Fact] - public async Task FunctionCalsAreBufferedUntilApprovalRequirementEncounteredWhenStreamingAsync() - { - var options = new ChatOptions - { - Tools = - [ - AIFunctionFactory.Create(() => "Result 1", "Func1"), - new ApprovalRequiredAIFunction(AIFunctionFactory.Create((int i) => $"Result 2: {i}", "Func2")), - AIFunctionFactory.Create(() => "Result 3", "Func3"), - ] - }; - - List input = [new ChatMessage(ChatRole.User, "hello")]; - - Func configurePipeline = b => b.Use(s => new NewFunctionInvokingChatClient(s)); - using CancellationTokenSource cts = new(); - - var updateYieldCount = 0; - - async IAsyncEnumerable YieldInnerClientUpdates(IEnumerable contents, ChatOptions? actualOptions, [EnumeratorCancellation] CancellationToken actualCancellationToken) - { - Assert.Equal(cts.Token, actualCancellationToken); - await Task.Yield(); - var messageId = Guid.NewGuid().ToString("N"); - - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new TextContent("Text 1")]) { MessageId = messageId }; - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new TextContent("Text 2")]) { MessageId = messageId }; - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func1")]) { MessageId = messageId }; - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new FunctionCallContent("callId2", "Func2", arguments: new Dictionary { { "i", 42 } })]) { MessageId = messageId }; - updateYieldCount++; - yield return new ChatResponseUpdate(ChatRole.Assistant, [new FunctionCallContent("callId1", "Func3")]) { MessageId = messageId }; - } - - using var innerClient = new TestChatClient { GetStreamingResponseAsyncCallback = YieldInnerClientUpdates }; - IChatClient service = configurePipeline(innerClient.AsBuilder()).Build(); - - var updates = service.GetStreamingResponseAsync(new EnumeratedOnceEnumerable(input), options, cts.Token); - - var updateCount = 0; - await foreach (var update in updates) - { - switch (updateCount) - { - case 0: - Assert.Equal("Text 1", update.Contents.OfType().First().Text); - // First content should be yielded immedately, since we don't have any function calls yet. - Assert.Equal(1, updateYieldCount); - break; - case 1: - Assert.Equal("Text 2", update.Contents.OfType().First().Text); - // Second content should be yielded immedately, since we don't have any function calls yet. - Assert.Equal(2, updateYieldCount); - break; - case 2: - var approvalRequest1 = update.Contents.OfType().First(); - Assert.Equal("callId1", approvalRequest1.FunctionCall.CallId); - Assert.Equal("Func1", approvalRequest1.FunctionCall.Name); - // Third content should have been buffered, since we have not yet encountered a function call that requires approval. - Assert.Equal(4, updateYieldCount); - break; - case 3: - var approvalRequest2 = update.Contents.OfType().First(); - Assert.Equal("callId2", approvalRequest2.FunctionCall.CallId); - Assert.Equal("Func2", approvalRequest2.FunctionCall.Name); - // Fourth content can be yielded immediately, since it is the first function call that requires approval. - Assert.Equal(4, updateYieldCount); - break; - case 4: - var approvalRequest3 = update.Contents.OfType().First(); - Assert.Equal("callId1", approvalRequest3.FunctionCall.CallId); - Assert.Equal("Func3", approvalRequest3.FunctionCall.Name); - // Fifth content can be yielded immediately, since we previously encountered a function call that requires approval. - Assert.Equal(5, updateYieldCount); - break; - } - - updateCount++; - } - } - - private static async Task> InvokeAndAssertAsync( - ChatOptions? options, - List input, - List downstreamClientOutput, - List expectedOutput, - List? expectedDownstreamClientInput = null, - Func? configurePipeline = null, - AITool[]? additionalTools = null, - IServiceProvider? services = null) - { - Assert.NotEmpty(input); - - configurePipeline ??= b => b.Use(s => new NewFunctionInvokingChatClient(s) { AdditionalTools = additionalTools }); - - using CancellationTokenSource cts = new(); - long expectedTotalTokenCounts = 0; - - using var innerClient = new TestChatClient - { - GetResponseAsyncCallback = async (contents, actualOptions, actualCancellationToken) => - { - Assert.Equal(cts.Token, actualCancellationToken); - if (expectedDownstreamClientInput is not null) - { - CompareMessageLists(expectedDownstreamClientInput, contents.ToList()); - } - - await Task.Yield(); - - var usage = CreateRandomUsage(); - expectedTotalTokenCounts += usage.InputTokenCount!.Value; - - downstreamClientOutput.ForEach(m => m.MessageId = Guid.NewGuid().ToString("N")); - return new ChatResponse(downstreamClientOutput) { Usage = usage }; - } - }; - - IChatClient service = configurePipeline(innerClient.AsBuilder()).Build(services); - - var result = await service.GetResponseAsync(new EnumeratedOnceEnumerable(input), options, cts.Token); - Assert.NotNull(result); - - var actualOutput = result.Messages as List ?? result.Messages.ToList(); - CompareMessageLists(expectedOutput, actualOutput); - - // Usage should be aggregated over all responses, including AdditionalUsage - var actualUsage = result.Usage!; - Assert.Equal(expectedTotalTokenCounts, actualUsage.InputTokenCount); - Assert.Equal(expectedTotalTokenCounts, actualUsage.OutputTokenCount); - Assert.Equal(expectedTotalTokenCounts, actualUsage.TotalTokenCount); - Assert.Equal(2, actualUsage.AdditionalCounts!.Count); - Assert.Equal(expectedTotalTokenCounts, actualUsage.AdditionalCounts["firstValue"]); - Assert.Equal(expectedTotalTokenCounts, actualUsage.AdditionalCounts["secondValue"]); - - return actualOutput; - } - - private static UsageDetails CreateRandomUsage() - { - // We'll set the same random number on all the properties so that, when determining the - // correct sum in tests, we only have to total the values once - var value = new Random().Next(100); - return new UsageDetails - { - InputTokenCount = value, - OutputTokenCount = value, - TotalTokenCount = value, - AdditionalCounts = new() { ["firstValue"] = value, ["secondValue"] = value }, - }; - } - - private static async Task> InvokeAndAssertStreamingAsync( - ChatOptions? options, - List input, - List downstreamClientOutput, - List expectedOutput, - List? expectedDownstreamClientInput = null, - Func? configurePipeline = null, - AITool[]? additionalTools = null, - IServiceProvider? services = null) - { - Assert.NotEmpty(input); - - configurePipeline ??= b => b.Use(s => new NewFunctionInvokingChatClient(s) { AdditionalTools = additionalTools }); - - using CancellationTokenSource cts = new(); - - using var innerClient = new TestChatClient - { - GetStreamingResponseAsyncCallback = (contents, actualOptions, actualCancellationToken) => - { - Assert.Equal(cts.Token, actualCancellationToken); - if (expectedDownstreamClientInput is not null) - { - CompareMessageLists(expectedDownstreamClientInput, contents.ToList()); - } - - downstreamClientOutput.ForEach(m => m.MessageId = Guid.NewGuid().ToString("N")); - return YieldAsync(new ChatResponse(downstreamClientOutput).ToChatResponseUpdates()); - } - }; - - IChatClient service = configurePipeline(innerClient.AsBuilder()).Build(services); - - var result = await service.GetStreamingResponseAsync(new EnumeratedOnceEnumerable(input), options, cts.Token).ToChatResponseAsync(); - Assert.NotNull(result); - - var actualOutput = result.Messages as List ?? result.Messages.ToList(); - - expectedOutput ??= input; - CompareMessageLists(expectedOutput, actualOutput); - - return actualOutput; - } - - private static async IAsyncEnumerable YieldAsync(params T[] items) - { - await Task.Yield(); - foreach (var item in items) - { - yield return item; - } - } - - private static void CompareMessageLists(List expectedMessages, List actualMessages) - { - Assert.Equal(expectedMessages.Count, actualMessages.Count); - for (int i = 0; i < expectedMessages.Count; i++) - { - var expectedMessage = expectedMessages[i]; - var chatMessage = actualMessages[i]; - - Assert.Equal(expectedMessage.Role, chatMessage.Role); - Assert.Equal(expectedMessage.Text, chatMessage.Text); - Assert.Equal(expectedMessage.GetType(), chatMessage.GetType()); - - Assert.Equal(expectedMessage.Contents.Count, chatMessage.Contents.Count); - for (int j = 0; j < expectedMessage.Contents.Count; j++) - { - var expectedItem = expectedMessage.Contents[j]; - var chatItem = chatMessage.Contents[j]; - - Assert.Equal(expectedItem.GetType(), chatItem.GetType()); - Assert.Equal(expectedItem.ToString(), chatItem.ToString()); - if (expectedItem is FunctionCallContent expectedFunctionCall) - { - var chatFunctionCall = (FunctionCallContent)chatItem; - Assert.Equal(expectedFunctionCall.Name, chatFunctionCall.Name); - AssertExtensions.EqualFunctionCallParameters(expectedFunctionCall.Arguments, chatFunctionCall.Arguments); - } - else if (expectedItem is FunctionResultContent expectedFunctionResult) - { - var chatFunctionResult = (FunctionResultContent)chatItem; - AssertExtensions.EqualFunctionCallResults(expectedFunctionResult.Result, chatFunctionResult.Result); - } - } - } - } - - private sealed class EnumeratedOnceEnumerable(IEnumerable items) : IEnumerable - { - private int _iterated; - - public IEnumerator GetEnumerator() - { - if (Interlocked.Exchange(ref _iterated, 1) != 0) - { - throw new InvalidOperationException("This enumerable can only be enumerated once."); - } - - foreach (var item in items) - { - yield return item; - } - } - - IEnumerator IEnumerable.GetEnumerator() => GetEnumerator(); - } -} diff --git a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/TestChatClient.cs b/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/TestChatClient.cs deleted file mode 100644 index 436d4308ab..0000000000 --- a/dotnet/tests/Microsoft.Extensions.AI.Agents.UnitTests/MEAI/TestChatClient.cs +++ /dev/null @@ -1,51 +0,0 @@ -// Copyright (c) Microsoft. All rights reserved. - -// WARNING: -// This class has been temporarily copied here from MEAI, to allow prototyping -// functionality that will be moved to MEAI in the future. -// This file is not intended to be modified. - -// AF repo suppressions for code copied from MEAI. -#pragma warning disable IDE0009 // Member access should be qualified. -#pragma warning disable CA1859 // Use concrete types when possible for improved performance -#pragma warning disable CA1063 // Implement IDisposable Correctly - -using System; -using System.Collections.Generic; -using System.Threading; -using System.Threading.Tasks; - -namespace Microsoft.Extensions.AI; - -public sealed class TestChatClient : IChatClient -{ - public TestChatClient() - { - GetServiceCallback = DefaultGetServiceCallback; - } - - public IServiceProvider? Services { get; set; } - - public Func, ChatOptions?, CancellationToken, Task>? GetResponseAsyncCallback { get; set; } - - public Func, ChatOptions?, CancellationToken, IAsyncEnumerable>? GetStreamingResponseAsyncCallback { get; set; } - - public Func GetServiceCallback { get; set; } - - private object? DefaultGetServiceCallback(Type serviceType, object? serviceKey) => - serviceType is not null && serviceKey is null && serviceType.IsInstanceOfType(this) ? this : null; - - public Task GetResponseAsync(IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - => GetResponseAsyncCallback!.Invoke(messages, options, cancellationToken); - - public IAsyncEnumerable GetStreamingResponseAsync(IEnumerable messages, ChatOptions? options = null, CancellationToken cancellationToken = default) - => GetStreamingResponseAsyncCallback!.Invoke(messages, options, cancellationToken); - - public object? GetService(Type serviceType, object? serviceKey = null) - => GetServiceCallback(serviceType, serviceKey); - - void IDisposable.Dispose() - { - // No resources need disposing. - } -} diff --git a/dotnet/tests/OpenAIChatCompletion.IntegrationTests/OpenAIChatCompletionFixture.cs b/dotnet/tests/OpenAIChatCompletion.IntegrationTests/OpenAIChatCompletionFixture.cs index da5324e60e..feaacca6f8 100644 --- a/dotnet/tests/OpenAIChatCompletion.IntegrationTests/OpenAIChatCompletionFixture.cs +++ b/dotnet/tests/OpenAIChatCompletion.IntegrationTests/OpenAIChatCompletionFixture.cs @@ -32,7 +32,7 @@ public class OpenAIChatCompletionFixture : IChatClientAgentFixture public async Task> GetChatHistoryAsync(AgentThread thread) { - return await thread.GetMessagesAsync().ToListAsync(); + return thread.MessageStore is null ? [] : (await thread.MessageStore.GetMessagesAsync()).ToList(); } public Task CreateChatClientAgentAsync( diff --git a/dotnet/tests/OpenAIResponse.IntegrationTests/OpenAIResponseFixture.cs b/dotnet/tests/OpenAIResponse.IntegrationTests/OpenAIResponseFixture.cs index 304a955b68..de094e46a2 100644 --- a/dotnet/tests/OpenAIResponse.IntegrationTests/OpenAIResponseFixture.cs +++ b/dotnet/tests/OpenAIResponse.IntegrationTests/OpenAIResponseFixture.cs @@ -50,7 +50,7 @@ public class OpenAIResponseFixture(bool store) : IChatClientAgentFixture return [.. previousMessages, responseMessage]; } - return await thread.GetMessagesAsync().ToListAsync(); + return thread.MessageStore is null ? [] : (await thread.MessageStore.GetMessagesAsync()).ToList(); } private static ChatMessage ConvertToChatMessage(ResponseItem item) @@ -70,7 +70,7 @@ public class OpenAIResponseFixture(bool store) : IChatClientAgentFixture IList? aiTools = null) { return Task.FromResult(new ChatClientAgent( - this._openAIResponseClient.AsNewIChatClient(), + this._openAIResponseClient.AsIChatClient(), options: new() { Name = name, diff --git a/python/.cspell.json b/python/.cspell.json index ab7106ad7b..1b21f5263d 100644 --- a/python/.cspell.json +++ b/python/.cspell.json @@ -53,6 +53,7 @@ "nopep", "NOSQL", "ollama", + "otlp", "Onnx", "onyourdatatest", "OPENAI", diff --git a/python/.env.example b/python/.env.example index e8de35394a..54cb688999 100644 --- a/python/.env.example +++ b/python/.env.example @@ -1,8 +1,19 @@ +# Foundry FOUNDRY_PROJECT_ENDPOINT="" FOUNDRY_MODEL_DEPLOYMENT_NAME="" +# OpenAI OPENAI_API_KEY="" OPENAI_CHAT_MODEL_ID="" +OPENAI_RESPONSES_MODEL_ID="" +# Azure OpenAI AZURE_OPENAI_ENDPOINT="" AZURE_OPENAI_CHAT_DEPLOYMENT_NAME="" AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="" -OPENAI_RESPONSES_MODEL_ID="" +# Telemetry +AGENT_FRAMEWORK_MONITOR_CONNECTION_STRING="..." +AGENT_FRAMEWORK_OTLP_ENDPOINT="http://localhost:4317/" +AGENT_FRAMEWORK_ENABLE_OTEL=true +AGENT_FRAMEWORK_ENABLE_SENSITIVE_DATA=true +AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL=true +# Mem0 +MEM0_API_KEY="" diff --git a/python/packages/azure/agent_framework_azure/_chat_client.py b/python/packages/azure/agent_framework_azure/_chat_client.py index f140f281b2..11231353bf 100644 --- a/python/packages/azure/agent_framework_azure/_chat_client.py +++ b/python/packages/azure/agent_framework_azure/_chat_client.py @@ -11,9 +11,11 @@ from agent_framework import ( ChatResponseUpdate, CitationAnnotation, TextContent, + use_function_invocation, ) from agent_framework.exceptions import ServiceInitializationError from agent_framework.openai._chat_client import OpenAIBaseChatClient +from agent_framework.telemetry import use_telemetry from azure.core.credentials import TokenCredential from openai.lib.azure import AsyncAzureADTokenProvider, AsyncAzureOpenAI from openai.types.chat.chat_completion import Choice @@ -37,6 +39,8 @@ TChatResponse = TypeVar("TChatResponse", ChatResponse, ChatResponseUpdate) TAzureChatClient = TypeVar("TAzureChatClient", bound="AzureChatClient") +@use_function_invocation +@use_telemetry class AzureChatClient(AzureOpenAIConfigMixin, OpenAIBaseChatClient): """Azure Chat completion class.""" diff --git a/python/packages/azure/agent_framework_azure/_responses_client.py b/python/packages/azure/agent_framework_azure/_responses_client.py index de4d679e37..b1811280a6 100644 --- a/python/packages/azure/agent_framework_azure/_responses_client.py +++ b/python/packages/azure/agent_framework_azure/_responses_client.py @@ -4,7 +4,7 @@ from collections.abc import Mapping from typing import Any, TypeVar from urllib.parse import urljoin -from agent_framework import use_tool_calling +from agent_framework import use_function_invocation from agent_framework.exceptions import ServiceInitializationError from agent_framework.openai._responses_client import OpenAIBaseResponsesClient from agent_framework.telemetry import use_telemetry @@ -22,7 +22,7 @@ TAzureResponsesClient = TypeVar("TAzureResponsesClient", bound="AzureResponsesCl @use_telemetry -@use_tool_calling +@use_function_invocation class AzureResponsesClient(AzureOpenAIConfigMixin, OpenAIBaseResponsesClient): """Azure Responses completion class.""" diff --git a/python/packages/azure/agent_framework_azure/_shared.py b/python/packages/azure/agent_framework_azure/_shared.py index b4beba5da0..4addf194b2 100644 --- a/python/packages/azure/agent_framework_azure/_shared.py +++ b/python/packages/azure/agent_framework_azure/_shared.py @@ -9,7 +9,7 @@ from typing import Any, ClassVar, Final from agent_framework._pydantic import AFBaseSettings, HTTPsUrl from agent_framework.exceptions import ServiceInitializationError from agent_framework.openai._shared import OpenAIBase -from agent_framework.telemetry import USER_AGENT_KEY +from agent_framework.telemetry import APP_INFO, USER_AGENT_KEY, prepend_agent_framework_to_user_agent from azure.core.credentials import TokenCredential from openai.lib.azure import AsyncAzureOpenAI from pydantic import ConfigDict, SecretStr, model_validator, validate_call @@ -168,7 +168,7 @@ class AzureOpenAISettings(AFBaseSettings): class AzureOpenAIConfigMixin(OpenAIBase): """Internal class for configuring a connection to an Azure OpenAI service.""" - MODEL_PROVIDER_NAME: ClassVar[str] = "azure_openai" # type: ignore[reportIncompatibleVariableOverride, misc] + OTEL_PROVIDER_NAME: ClassVar[str] = "azure_openai" # type: ignore[reportIncompatibleVariableOverride, misc] @validate_call(config=ConfigDict(arbitrary_types_allowed=True)) def __init__( @@ -212,7 +212,9 @@ class AzureOpenAIConfigMixin(OpenAIBase): """ # Merge APP_INFO into the headers if it exists merged_headers = dict(copy(default_headers)) if default_headers else {} - + if APP_INFO: + merged_headers.update(APP_INFO) + merged_headers = prepend_agent_framework_to_user_agent(merged_headers) if not client: # If the client is None, the api_key is none, the ad_token is none, and the ad_token_provider is none, # then we will attempt to get the ad_token using the default endpoint specified in the Azure OpenAI diff --git a/python/packages/azure/tests/test_azure_assistants_client.py b/python/packages/azure/tests/test_azure_assistants_client.py index abc128151a..7bd2f6571b 100644 --- a/python/packages/azure/tests/test_azure_assistants_client.py +++ b/python/packages/azure/tests/test_azure_assistants_client.py @@ -16,7 +16,6 @@ from agent_framework import ( ChatResponseUpdate, HostedCodeInterpreterTool, TextContent, - ai_function, ) from agent_framework.exceptions import ServiceInitializationError from azure.identity import AzureCliCredential @@ -543,45 +542,6 @@ async def test_azure_assistants_client_agent_level_tool_persistence(): assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"]) -@skip_if_azure_integration_tests_disabled -async def test_azure_assistants_client_run_level_tool_isolation(): - """Test that run-level tools are isolated to specific runs and don't persist with Azure Assistants Client.""" - # Counter to track how many times the weather tool is called - call_count = 0 - - @ai_function - async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str: - """Get the current weather in a given location.""" - nonlocal call_count - call_count += 1 - return f"The weather in {location} is sunny and 72°F." - - async with ChatAgent( - chat_client=AzureAssistantsClient(credential=AzureCliCredential()), - instructions="You are a helpful assistant.", - ) as agent: - # First run - use run-level tool - first_response = await agent.run( - "What's the weather like in Chicago?", - tools=[get_weather_with_counter], # Run-level tool - ) - - assert isinstance(first_response, AgentRunResponse) - assert first_response.text is not None - # Should use the run-level weather tool (call count should be 1) - assert call_count == 1 - assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"]) - - # Second run - run-level tool should NOT persist (key isolation test) - second_response = await agent.run("What's the weather like in Miami?") - - assert isinstance(second_response, AgentRunResponse) - assert second_response.text is not None - # Should NOT use the weather tool since it was only run-level in previous call - # Call count should still be 1 (no additional calls) - assert call_count == 1 - - def test_azure_assistants_client_entra_id_authentication() -> None: """Test Entra ID authentication path with credential.""" mock_credential = MagicMock() diff --git a/python/packages/azure/tests/test_azure_chat_client.py b/python/packages/azure/tests/test_azure_chat_client.py index 60417581fb..b4669d1ec0 100644 --- a/python/packages/azure/tests/test_azure_chat_client.py +++ b/python/packages/azure/tests/test_azure_chat_client.py @@ -2,7 +2,6 @@ import json import os -from typing import Annotated from unittest.mock import AsyncMock, MagicMock, patch import openai @@ -834,42 +833,3 @@ async def test_azure_chat_client_agent_level_tool_persistence(): assert second_response.text is not None # Should use the agent-level weather tool again assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"]) - - -@skip_if_azure_integration_tests_disabled -async def test_azure_chat_client_run_level_tool_isolation(): - """Test that run-level tools are isolated to specific runs and don't persist with Azure Chat Client.""" - # Counter to track how many times the weather tool is called - call_count = 0 - - @ai_function - async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str: - """Get the current weather in a given location.""" - nonlocal call_count - call_count += 1 - return f"The weather in {location} is sunny and 72°F." - - async with ChatAgent( - chat_client=AzureChatClient(credential=AzureCliCredential()), - instructions="You are a helpful assistant.", - ) as agent: - # First run - use run-level tool - first_response = await agent.run( - "What's the weather like in Chicago?", - tools=[get_weather_with_counter], # Run-level tool - ) - - assert isinstance(first_response, AgentRunResponse) - assert first_response.text is not None - # Should use the run-level weather tool (call count should be 1) - assert call_count == 1 - assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"]) - - # Second run - run-level tool should NOT persist (key isolation test) - second_response = await agent.run("What's the weather like in Miami?") - - assert isinstance(second_response, AgentRunResponse) - assert second_response.text is not None - # Should NOT use the weather tool since it was only run-level in previous call - # Call count should still be 1 (no additional calls) - assert call_count == 1 diff --git a/python/packages/azure/tests/test_azure_responses_client.py b/python/packages/azure/tests/test_azure_responses_client.py index dcbc41e839..2e02989478 100644 --- a/python/packages/azure/tests/test_azure_responses_client.py +++ b/python/packages/azure/tests/test_azure_responses_client.py @@ -459,42 +459,3 @@ async def test_azure_responses_client_agent_level_tool_persistence(): assert second_response.text is not None # Should use the agent-level weather tool again assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"]) - - -@skip_if_azure_integration_tests_disabled -async def test_azure_responses_client_run_level_tool_isolation(): - """Test that run-level tools are isolated to specific runs and don't persist with Azure Responses Client.""" - # Counter to track how many times the weather tool is called - call_count = 0 - - @ai_function - async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str: - """Get the current weather in a given location.""" - nonlocal call_count - call_count += 1 - return f"The weather in {location} is sunny and 72°F." - - async with ChatAgent( - chat_client=AzureResponsesClient(credential=AzureCliCredential()), - instructions="You are a helpful assistant.", - ) as agent: - # First run - use run-level tool - first_response = await agent.run( - "What's the weather like in Chicago?", - tools=[get_weather_with_counter], # Run-level tool - ) - - assert isinstance(first_response, AgentRunResponse) - assert first_response.text is not None - # Should use the run-level weather tool (call count should be 1) - assert call_count == 1 - assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"]) - - # Second run - run-level tool should NOT persist (key isolation test) - second_response = await agent.run("What's the weather like in Miami?") - - assert isinstance(second_response, AgentRunResponse) - assert second_response.text is not None - # Should NOT use the weather tool since it was only run-level in previous call - # Call count should still be 1 (no additional calls) - assert call_count == 1 diff --git a/python/packages/foundry/agent_framework_foundry/_chat_client.py b/python/packages/foundry/agent_framework_foundry/_chat_client.py index 130eeebc47..7f375b885e 100644 --- a/python/packages/foundry/agent_framework_foundry/_chat_client.py +++ b/python/packages/foundry/agent_framework_foundry/_chat_client.py @@ -1,6 +1,5 @@ # Copyright (c) Microsoft. All rights reserved. -import contextlib import json import sys from collections.abc import AsyncIterable, MutableMapping, MutableSequence @@ -24,11 +23,11 @@ from agent_framework import ( UriContent, UsageContent, UsageDetails, - use_tool_calling, + use_function_invocation, ) from agent_framework._pydantic import AFBaseSettings from agent_framework.exceptions import ServiceInitializationError, ServiceResponseException -from agent_framework.telemetry import use_telemetry +from agent_framework.telemetry import prepend_agent_framework_to_user_agent, use_telemetry from azure.ai.agents.models import ( AgentsNamedToolChoice, AgentsNamedToolChoiceType, @@ -95,18 +94,20 @@ class FoundrySettings(AFBaseSettings): TFoundryChatClient = TypeVar("TFoundryChatClient", bound="FoundryChatClient") +HEADERS = prepend_agent_framework_to_user_agent() + +@use_function_invocation @use_telemetry -@use_tool_calling class FoundryChatClient(BaseChatClient): """Azure AI Foundry Chat client.""" - MODEL_PROVIDER_NAME: ClassVar[str] = "azure_ai_foundry" # type: ignore[reportIncompatibleVariableOverride, misc] + OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.foundry" # type: ignore[reportIncompatibleVariableOverride, misc] client: AIProjectClient = Field(...) credential: AsyncTokenCredential | None = Field(...) agent_id: str | None = Field(default=None) agent_name: str | None = Field(default=None) - ai_model_deployment_name: str | None = Field(default=None) + ai_model_id: str | None = Field(default=None) thread_id: str | None = Field(default=None) _should_delete_agent: bool = PrivateAttr(default=False) # Track whether we should delete the agent _should_close_client: bool = PrivateAttr(default=False) # Track whether we should close client connection @@ -138,6 +139,7 @@ class FoundryChatClient(BaseChatClient): project_endpoint: The Azure AI Foundry project endpoint URL. Used if client is not provided. model_deployment_name: The model deployment name to use for agent creation. async_credential: Azure async credential to use for authentication. + setup_tracing: Whether to setup tracing for the client. Defaults to True. env_file_path: Path to environment file for loading settings. env_file_encoding: Encoding of the environment file. **kwargs: Additional keyword arguments passed to the parent class. @@ -180,11 +182,25 @@ class FoundryChatClient(BaseChatClient): agent_id=agent_id, # type: ignore[reportCallIssue] thread_id=thread_id, # type: ignore[reportCallIssue] agent_name=foundry_settings.agent_name, # type: ignore[reportCallIssue] - ai_model_deployment_name=foundry_settings.model_deployment_name, # type: ignore[reportCallIssue] + ai_model_id=foundry_settings.model_deployment_name, # type: ignore[reportCallIssue] **kwargs, ) self._should_close_client = should_close_client + async def setup_foundry_telemetry(self, enable_live_metrics: bool = False) -> None: + """Call this method to setup tracing with Foundry. + + This will take the connection string from the project client. + It will override any connection string that is set in the environment variables. + It will disable any OTLP endpoint that might have been set. + """ + from agent_framework.telemetry import setup_telemetry + + setup_telemetry( + application_insights_connection_string=await self.client.telemetry.get_application_insights_connection_string(), # noqa: E501 + enable_live_metrics=enable_live_metrics, + ) + async def __aenter__(self) -> "Self": """Async context manager entry.""" return self @@ -239,7 +255,9 @@ class FoundryChatClient(BaseChatClient): # Get the thread ID thread_id: str | None = ( - chat_options.conversation_id if chat_options.conversation_id is not None else self.thread_id + chat_options.conversation_id + if chat_options.conversation_id is not None + else run_options.get("conversation_id", self.thread_id) ) if thread_id is None and tool_results is not None: @@ -263,11 +281,15 @@ class FoundryChatClient(BaseChatClient): """ # If no agent_id is provided, create a temporary agent if self.agent_id is None: - if not self.ai_model_deployment_name: + if not self.ai_model_id: raise ServiceInitializationError("Model deployment name is required for agent creation.") agent_name = self.agent_name - args = {"model": self.ai_model_deployment_name, "name": agent_name} + args = { + "model": self.ai_model_id, + "name": agent_name, + "headers": HEADERS, + } if run_options: if "tools" in run_options: args["tools"] = run_options["tools"] @@ -303,7 +325,11 @@ class FoundryChatClient(BaseChatClient): if thread_run is not None and tool_run_id is not None and tool_run_id == thread_run.id and tool_outputs: # There's an active run and we have tool results to submit, so submit the results. await self.client.agents.runs.submit_tool_outputs_stream( # type: ignore[reportUnknownMemberType] - thread_run.thread_id, tool_run_id, tool_outputs=tool_outputs, event_handler=handler + thread_run.thread_id, + tool_run_id, + tool_outputs=tool_outputs, + event_handler=handler, + headers=HEADERS, ) # Pass the handler to the stream to continue processing stream = handler # type: ignore @@ -313,9 +339,11 @@ class FoundryChatClient(BaseChatClient): final_thread_id = await self._prepare_thread(thread_id, thread_run, run_options) # Now create a new run and stream the results. + run_options.pop("conversation_id", None) stream = await self.client.agents.runs.stream( # type: ignore[reportUnknownMemberType] final_thread_id, agent_id=agent_id, + headers=HEADERS, **run_options, ) @@ -326,7 +354,9 @@ class FoundryChatClient(BaseChatClient): if thread_id is None: return None - async for run in self.client.agents.runs.list(thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING): + async for run in self.client.agents.runs.list( + thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING, headers=HEADERS + ): # type: ignore[reportUnknownMemberType] if run.status not in [ RunStatus.COMPLETED, RunStatus.CANCELLED, @@ -340,20 +370,33 @@ class FoundryChatClient(BaseChatClient): self, thread_id: str | None, thread_run: ThreadRun | None, run_options: dict[str, Any] ) -> str: """Prepare the thread for a new run, creating or cleaning up as needed.""" - if thread_id is None: - # No thread ID was provided, so create a new thread. - thread = await self.client.agents.threads.create( - messages=run_options["additional_messages"], - tool_resources=run_options.get("tool_resources"), - metadata=run_options.get("metadata"), + if thread_id is not None: + if thread_run is not None: + # There was an active run; we need to cancel it before starting a new run. + await self.client.agents.runs.cancel(thread_id, thread_run.id, headers=HEADERS) + + return thread_id + + # No thread ID was provided, so create a new thread. + thread = await self.client.agents.threads.create( + tool_resources=run_options.get("tool_resources"), + metadata=run_options.get("metadata"), + headers=HEADERS, + ) + thread_id = thread.id + # workaround for: https://github.com/Azure/azure-sdk-for-python/issues/42805 + # this occurs when otel is enabled + # once fixed, in the function above, readd: + # `messages=run_options.pop("additional_messages")` + for msg in run_options.pop("additional_messages", []): + await self.client.agents.messages.create( + thread_id=thread_id, + role=msg.role, + content=msg.content, + metadata=msg.metadata, + headers=HEADERS, ) - run_options["additional_messages"] = [] - return thread.id - - if thread_run is not None: - # There was an active run; we need to cancel it before starting a new run. - await self.client.agents.runs.cancel(thread_id, thread_run.id) - + # and remove until here. return thread_id async def _process_stream_events( @@ -364,7 +407,7 @@ class FoundryChatClient(BaseChatClient): """Process events from the agent stream and yield ChatResponseUpdate objects.""" # Use 'async with' only if the stream supports async context management (main agent stream). # Tool output handlers only support async iteration, not context management. - if isinstance(stream, contextlib.AbstractAsyncContextManager): + if isinstance(stream, AsyncAgentRunStream): async with stream as response_stream: # type: ignore async for update in self._process_stream_events_from_iterator(response_stream, thread_id): yield update @@ -373,7 +416,7 @@ class FoundryChatClient(BaseChatClient): yield update async def _process_stream_events_from_iterator( - self, stream_iter: Any, thread_id: str + self, stream_iter: AsyncAgentEventHandler[Any], thread_id: str ) -> AsyncIterable[ChatResponseUpdate]: """Process events from the stream iterator and yield ChatResponseUpdate objects.""" response_id: str | None = None @@ -386,6 +429,7 @@ class FoundryChatClient(BaseChatClient): raw_representation=event_data, response_id=response_id, role=Role.ASSISTANT, + ai_model_id=event_data.model, ) elif event_type == AgentStreamEvent.THREAD_RUN_STEP_CREATED and isinstance(event_data, RunStep): response_id = event_data.run_id @@ -415,7 +459,7 @@ class FoundryChatClient(BaseChatClient): response_id=response_id, ) elif ( - event_type == AgentStreamEvent.THREAD_RUN_COMPLETED + event_type in [AgentStreamEvent.THREAD_RUN_COMPLETED, AgentStreamEvent.THREAD_RUN_STEP_COMPLETED] and isinstance(event_data, RunStep) and event_data.usage is not None ): @@ -454,16 +498,16 @@ class FoundryChatClient(BaseChatClient): """Create function call contents from a tool action event.""" contents: list[Contents] = [] - if isinstance(event_data.required_action, SubmitToolOutputsAction): + if isinstance(event_data, ThreadRun) and isinstance(event_data.required_action, SubmitToolOutputsAction): for tool_call in event_data.required_action.submit_tool_outputs.tool_calls: if isinstance(tool_call, RequiredFunctionToolCall): - call_id = json.dumps([response_id, tool_call.id]) - function_name = tool_call.function.name - function_arguments = json.loads(tool_call.function.arguments) contents.append( - FunctionCallContent(call_id=call_id, name=function_name, arguments=function_arguments) + FunctionCallContent( + call_id=f'["{response_id}", "{tool_call.id}"]', + name=tool_call.function.name, + arguments=tool_call.function.arguments, + ) ) - return contents async def _close_client_if_needed(self) -> None: @@ -474,7 +518,7 @@ class FoundryChatClient(BaseChatClient): async def _cleanup_agent_if_needed(self) -> None: """Clean up the agent if we created it.""" if self._should_delete_agent and self.agent_id is not None: - await self.client.agents.delete_agent(self.agent_id) + await self.client.agents.delete_agent(self.agent_id, headers=HEADERS) self.agent_id = None self._should_delete_agent = False @@ -618,3 +662,11 @@ class FoundryChatClient(BaseChatClient): # to update the agent name in the client. if agent_name and not self.agent_name: self.agent_name = agent_name + + def service_url(self) -> str: + """Get the service URL for the chat client. + + Returns: + The service URL for the chat client, or None if not set. + """ + return self.client._config.endpoint diff --git a/python/packages/foundry/pyproject.toml b/python/packages/foundry/pyproject.toml index 2d12831c69..1c1f18605f 100644 --- a/python/packages/foundry/pyproject.toml +++ b/python/packages/foundry/pyproject.toml @@ -26,7 +26,7 @@ dependencies = [ "agent-framework", "azure-ai-projects >= 1.0.0b11", "azure-ai-agents >= 1.1.0b1", - "aiohttp ~= 3.8" + "aiohttp ~= 3.8", ] [tool.uv] diff --git a/python/packages/foundry/tests/conftest.py b/python/packages/foundry/tests/conftest.py index cb204880ee..eb858f7a1b 100644 --- a/python/packages/foundry/tests/conftest.py +++ b/python/packages/foundry/tests/conftest.py @@ -62,6 +62,7 @@ def mock_ai_project_client() -> MagicMock: # Mock threads property mock_client.agents.threads = MagicMock() mock_client.agents.threads.create = AsyncMock() + mock_client.agents.messages.create = AsyncMock() # Mock runs property mock_client.agents.runs = MagicMock() diff --git a/python/packages/foundry/tests/test_foundry_chat_client.py b/python/packages/foundry/tests/test_foundry_chat_client.py index d2bd6e6c3c..8a7eec03b6 100644 --- a/python/packages/foundry/tests/test_foundry_chat_client.py +++ b/python/packages/foundry/tests/test_foundry_chat_client.py @@ -18,12 +18,14 @@ from agent_framework import ( FunctionCallContent, FunctionResultContent, HostedCodeInterpreterTool, + MCPStreamableHTTPTool, Role, TextContent, UriContent, - ai_function, ) +from agent_framework import __version__ as AF_VERSION from agent_framework.exceptions import ServiceInitializationError +from agent_framework.foundry import FoundryChatClient, FoundrySettings from azure.ai.agents.models import ( RequiredFunctionToolCall, SubmitToolOutputsAction, @@ -33,8 +35,6 @@ from azure.core.credentials_async import AsyncTokenCredential from azure.identity.aio import AzureCliCredential from pydantic import Field, ValidationError -from agent_framework_foundry import FoundryChatClient, FoundrySettings - skip_if_foundry_integration_tests_disabled = pytest.mark.skipif( os.getenv("RUN_INTEGRATION_TESTS", "false").lower() != "true" or os.getenv("FOUNDRY_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/"), @@ -61,8 +61,7 @@ def create_test_foundry_chat_client( thread_id=thread_id, _should_delete_agent=should_delete_agent, agent_name=foundry_settings.agent_name, # type: ignore[reportCallIssue] - ai_model_deployment_name=foundry_settings.model_deployment_name, # type: - credential=None, + ai_model_id=foundry_settings.model_deployment_name, ) @@ -315,9 +314,10 @@ async def test_foundry_chat_client_cleanup_agent_if_needed_should_delete( ) await chat_client._cleanup_agent_if_needed() # type: ignore - # Verify agent deletion was called - mock_ai_project_client.agents.delete_agent.assert_called_once_with("agent-to-delete") + mock_ai_project_client.agents.delete_agent.assert_called_once_with( + "agent-to-delete", headers={"User-Agent": f"agent-framework-python/{AF_VERSION}"} + ) assert not chat_client._should_delete_agent # type: ignore @@ -358,7 +358,9 @@ async def test_foundry_chat_client_aclose(mock_ai_project_client: MagicMock) -> await chat_client.close() # Verify agent deletion was called - mock_ai_project_client.agents.delete_agent.assert_called_once_with("agent-to-delete") + mock_ai_project_client.agents.delete_agent.assert_called_once_with( + "agent-to-delete", headers={"User-Agent": f"agent-framework-python/{AF_VERSION}"} + ) async def test_foundry_chat_client_async_context_manager(mock_ai_project_client: MagicMock) -> None: @@ -372,7 +374,9 @@ async def test_foundry_chat_client_async_context_manager(mock_ai_project_client: pass # Just test that we can enter and exit # Verify cleanup was called on exit - mock_ai_project_client.agents.delete_agent.assert_called_once_with("agent-to-delete") + mock_ai_project_client.agents.delete_agent.assert_called_once_with( + "agent-to-delete", headers={"User-Agent": f"agent-framework-python/{AF_VERSION}"} + ) def test_foundry_chat_client_create_run_options_basic(mock_ai_project_client: MagicMock) -> None: @@ -599,7 +603,9 @@ async def test_foundry_chat_client_prepare_thread_cancels_active_run(mock_ai_pro result = await chat_client._prepare_thread("test-thread", mock_thread_run, run_options) # type: ignore assert result == "test-thread" - mock_ai_project_client.agents.runs.cancel.assert_called_once_with("test-thread", "run_123") + mock_ai_project_client.agents.runs.cancel.assert_called_once_with( + "test-thread", "run_123", headers={"User-Agent": f"agent-framework-python/{AF_VERSION}"} + ) def test_foundry_chat_client_create_function_call_contents_basic(mock_ai_project_client: MagicMock) -> None: @@ -880,6 +886,27 @@ async def test_foundry_chat_client_agent_code_interpreter(): assert "120" in response.text or "factorial" in response.text.lower() +@skip_if_foundry_integration_tests_disabled +async def test_foundry_chat_client_agent_with_mcp_tools() -> None: + """Test MCP tools defined at agent creation with FoundryChatClient.""" + async with ChatAgent( + chat_client=FoundryChatClient(async_credential=AzureCliCredential()), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=MCPStreamableHTTPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + ), + ) as agent: + # Test that the agent can use MCP tools to answer questions + response = await agent.run("What is Azure App Service?") + + assert isinstance(response, AgentRunResponse) + assert response.text is not None + # Verify the response contains relevant information about Azure App Service + assert any(term in response.text.lower() for term in ["app service", "azure", "web", "application"]) + + @skip_if_foundry_integration_tests_disabled async def test_foundry_chat_client_agent_level_tool_persistence(): """Test that agent-level tools persist across multiple runs with FoundryChatClient.""" @@ -903,42 +930,3 @@ async def test_foundry_chat_client_agent_level_tool_persistence(): assert second_response.text is not None # Should use the agent-level weather tool again assert any(term in second_response.text.lower() for term in ["miami", "sunny", "25"]) - - -@skip_if_foundry_integration_tests_disabled -async def test_foundry_chat_client_run_level_tool_isolation(): - """Test that run-level tools are isolated to specific runs and don't persist with FoundryChatClient.""" - # Counter to track how many times the weather tool is called - call_count = 0 - - @ai_function - async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str: - """Get the current weather in a given location.""" - nonlocal call_count - call_count += 1 - return f"The weather in {location} is sunny and 25°C." - - async with ChatAgent( - chat_client=FoundryChatClient(async_credential=AzureCliCredential()), - instructions="You are a helpful assistant.", - ) as agent: - # First run - use run-level tool - first_response = await agent.run( - "What's the weather like in Chicago?", - tools=[get_weather_with_counter], # Run-level tool - ) - - assert isinstance(first_response, AgentRunResponse) - assert first_response.text is not None - # Should use the run-level weather tool (call count should be 1) - assert call_count == 1 - assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "25"]) - - # Second run - run-level tool should NOT persist (key isolation test) - second_response = await agent.run("What's the weather like in Miami?") - - assert isinstance(second_response, AgentRunResponse) - assert second_response.text is not None - # Should NOT use the weather tool since it was only run-level in previous call - # Call count should still be 1 (no additional calls) - assert call_count == 1 diff --git a/python/packages/main/agent_framework/__init__.py b/python/packages/main/agent_framework/__init__.py index da8d8ee482..ca82fa412d 100644 --- a/python/packages/main/agent_framework/__init__.py +++ b/python/packages/main/agent_framework/__init__.py @@ -12,6 +12,7 @@ from ._agents import * # noqa: F403 from ._clients import * # noqa: F403 from ._logging import * # noqa: F403 from ._mcp import * # noqa: F403 +from ._memory import * # noqa: F403 from ._threads import * # noqa: F403 from ._tools import * # noqa: F403 from ._types import * # noqa: F403 diff --git a/python/packages/main/agent_framework/_agents.py b/python/packages/main/agent_framework/_agents.py index bc22654079..0981112521 100644 --- a/python/packages/main/agent_framework/_agents.py +++ b/python/packages/main/agent_framework/_agents.py @@ -3,17 +3,18 @@ import sys from collections.abc import AsyncIterable, Callable, MutableMapping, Sequence from contextlib import AbstractAsyncContextManager, AsyncExitStack -from itertools import chain from typing import Any, ClassVar, Literal, Protocol, TypeVar, runtime_checkable from uuid import uuid4 from pydantic import BaseModel, Field, PrivateAttr -from ._clients import ChatClientProtocol +from ._clients import BaseChatClient, ChatClientProtocol +from ._logging import get_logger from ._mcp import MCPTool +from ._memory import AggregateContextProvider, Context, ContextProvider from ._pydantic import AFBaseModel from ._threads import AgentThread, ChatMessageStore, deserialize_thread_state, thread_on_new_messages -from ._tools import ToolProtocol +from ._tools import FUNCTION_INVOKING_CHAT_CLIENT_MARKER, ToolProtocol from ._types import ( AgentRunResponse, AgentRunResponseUpdate, @@ -32,6 +33,8 @@ if sys.version_info >= (3, 11): else: from typing_extensions import Self # pragma: no cover +logger = get_logger("agent_framework") + TThreadType = TypeVar("TThreadType", bound="AgentThread") __all__ = ["AgentProtocol", "BaseAgent", "ChatAgent"] @@ -134,12 +137,13 @@ class BaseAgent(AFBaseModel): name: The name of the agent, can be None. description: The description of the agent. display_name: The display name of the agent, which is either the name or id. - + context_providers: The collection of multiple context providers to include during agent invocation. """ id: str = Field(default_factory=lambda: str(uuid4())) name: str | None = None description: str | None = None + context_providers: AggregateContextProvider | None = None async def _notify_thread_of_new_messages( self, thread: AgentThread, new_messages: ChatMessage | Sequence[ChatMessage] @@ -211,6 +215,7 @@ class ChatAgent(BaseAgent): user: str | None = None, additional_properties: dict[str, Any] | None = None, chat_message_store_factory: Callable[[], ChatMessageStore] | None = None, + context_providers: ContextProvider | list[ContextProvider] | AggregateContextProvider | None = None, **kwargs: Any, ) -> None: """Create a ChatAgent. @@ -245,11 +250,19 @@ class ChatAgent(BaseAgent): additional_properties: additional properties to include in the request. chat_message_store_factory: factory function to create an instance of ChatMessageStore. If not provided, the default in-memory store will be used. + context_providers: The collection of multiple context providers to include during agent invocation. kwargs: any additional keyword arguments. Unused, can be used by subclasses of this Agent. """ + if not hasattr(chat_client, FUNCTION_INVOKING_CHAT_CLIENT_MARKER) and isinstance(chat_client, BaseChatClient): + logger.warning( + "The provided chat client does not support function invoking, this might limit agent capabilities." + ) + kwargs.update(additional_properties or {}) + aggregate_context_providers = self._prepare_context_providers(context_providers) + # We ignore the MCP Servers here and store them separately, # we add their functions to the tools list at runtime normalized_tools = [] if tools is None else tools if isinstance(tools, list) else [tools] @@ -258,6 +271,7 @@ class ChatAgent(BaseAgent): args: dict[str, Any] = { "chat_client": chat_client, "chat_message_store_factory": chat_message_store_factory, + "context_providers": aggregate_context_providers, "chat_options": ChatOptions( ai_model_id=model, frequency_penalty=frequency_penalty, @@ -293,12 +307,16 @@ class ChatAgent(BaseAgent): async def __aenter__(self) -> "Self": """Async context manager entry. - If either the chat_client or the local_mcp_tools are context managers, + If any of the chat_client, local_mcp_tools, or context_providers are context managers, they will be entered into the async exit stack to ensure proper cleanup. This list might be extended in the future. """ - for context_manager in chain([self.chat_client], self._local_mcp_tools): + context_managers = [self.chat_client, *self._local_mcp_tools] + if self.context_providers: + context_managers.append(self.context_providers) + + for context_manager in context_managers: if isinstance(context_manager, AbstractAsyncContextManager): await self._async_exit_stack.enter_async_context(context_manager) return self @@ -317,8 +335,8 @@ class ChatAgent(BaseAgent): should check if there is already a agent name defined, and if not set it to this value. """ - if hasattr(self.chat_client, "_update_agent_name") and callable(self.chat_client._update_agent_name): # type: ignore[reportAttributeAccessIssue] - self.chat_client._update_agent_name(self.name) # type: ignore[reportAttributeAccessIssue] + if hasattr(self.chat_client, "_update_agent_name") and callable(self.chat_client._update_agent_name): # type: ignore[reportAttributeAccessIssue, attr-defined] + self.chat_client._update_agent_name(self.name) # type: ignore[reportAttributeAccessIssue, attr-defined] async def run( self, @@ -380,7 +398,10 @@ class ChatAgent(BaseAgent): will only be passed to functions that are called. """ input_messages = self._normalize_messages(messages) - thread, thread_messages = await self._prepare_thread_and_messages(thread=thread, input_messages=input_messages) + context = await self.context_providers.model_invoking(input_messages) if self.context_providers else None + thread, thread_messages = await self._prepare_thread_and_messages( + thread=thread, context=context, input_messages=input_messages + ) agent_name = self._get_agent_name() # Resolve final tool list (runtime provided tools + local MCP server tools) @@ -433,6 +454,10 @@ class ChatAgent(BaseAgent): await self._notify_thread_of_new_messages(thread, input_messages) await self._notify_thread_of_new_messages(thread, response.messages) + if self.context_providers: + await self.context_providers.thread_created(response.conversation_id) + await self.context_providers.messages_adding(thread.service_thread_id, input_messages + response.messages) + return AgentRunResponse( messages=response.messages, response_id=response.response_id, @@ -501,7 +526,10 @@ class ChatAgent(BaseAgent): """ input_messages = self._normalize_messages(messages) - thread, thread_messages = await self._prepare_thread_and_messages(thread=thread, input_messages=input_messages) + context = await self.context_providers.model_invoking(input_messages) if self.context_providers else None + thread, thread_messages = await self._prepare_thread_and_messages( + thread=thread, context=context, input_messages=input_messages + ) agent_name = self._get_agent_name() response_updates: list[ChatResponseUpdate] = [] @@ -567,6 +595,10 @@ class ChatAgent(BaseAgent): await self._notify_thread_of_new_messages(thread, input_messages) await self._notify_thread_of_new_messages(thread, response.messages) + if self.context_providers: + await self.context_providers.thread_created(response.conversation_id) + await self.context_providers.messages_adding(thread.service_thread_id, input_messages + response.messages) + def get_new_thread(self) -> AgentThread: message_store: ChatMessageStore | None = None @@ -609,12 +641,14 @@ class ChatAgent(BaseAgent): self, *, thread: AgentThread | None, + context: Context | None, input_messages: list[ChatMessage] | None = None, ) -> tuple[AgentThread, list[ChatMessage]]: """Prepare the messages for agent execution. Args: thread: The conversation thread. + context: Context to include in messages. input_messages: Messages to process. Returns: @@ -628,6 +662,8 @@ class ChatAgent(BaseAgent): messages: list[ChatMessage] = [] if self.instructions: messages.append(ChatMessage(role=Role.SYSTEM, text=self.instructions)) + if context and context.contents: + messages.append(ChatMessage(role=Role.SYSTEM, contents=context.contents)) if thread.message_store: messages.extend(await thread.message_store.list_messages() or []) messages.extend(input_messages or []) @@ -650,3 +686,18 @@ class ChatAgent(BaseAgent): def _get_agent_name(self) -> str: return self.name or "UnnamedAgent" + + def _prepare_context_providers( + self, + context_providers: ContextProvider | list[ContextProvider] | AggregateContextProvider | None = None, + ) -> AggregateContextProvider | None: + if not context_providers: + return None + + if isinstance(context_providers, AggregateContextProvider): + return context_providers + + if isinstance(context_providers, ContextProvider): + return AggregateContextProvider([context_providers]) + + return AggregateContextProvider(context_providers) diff --git a/python/packages/main/agent_framework/_clients.py b/python/packages/main/agent_framework/_clients.py index 4ad1119162..4d5775c96b 100644 --- a/python/packages/main/agent_framework/_clients.py +++ b/python/packages/main/agent_framework/_clients.py @@ -2,31 +2,30 @@ import asyncio from abc import ABC, abstractmethod -from collections.abc import AsyncIterable, Awaitable, Callable, MutableMapping, MutableSequence, Sequence -from functools import wraps +from collections.abc import AsyncIterable, Callable, MutableMapping, MutableSequence, Sequence from typing import TYPE_CHECKING, Any, Generic, Literal, Protocol, TypeVar, runtime_checkable -from pydantic import BaseModel +from pydantic import BaseModel, Field from ._logging import get_logger +from ._mcp import MCPTool +from ._memory import AggregateContextProvider, ContextProvider from ._pydantic import AFBaseModel from ._threads import ChatMessageStore -from ._tools import AIFunction, ToolProtocol +from ._tools import ToolProtocol from ._types import ( ChatMessage, ChatOptions, ChatResponse, ChatResponseUpdate, ChatToolMode, - Contents, - FunctionCallContent, - FunctionResultContent, GeneratedEmbeddings, ) if TYPE_CHECKING: from ._agents import ChatAgent + TInput = TypeVar("TInput", contravariant=True) TEmbedding = TypeVar("TEmbedding") TBaseChatClient = TypeVar("TBaseChatClient", bound="BaseChatClient") @@ -37,215 +36,8 @@ __all__ = [ "BaseChatClient", "ChatClientProtocol", "EmbeddingGenerator", - "use_tool_calling", ] -# region Tool Calling Functions and Decorators - - -async def _auto_invoke_function( - function_call_content: FunctionCallContent, - custom_args: dict[str, Any] | None = None, - *, - tool_map: dict[str, AIFunction[BaseModel, Any]], - sequence_index: int | None = None, - request_index: int | None = None, -) -> Contents: - """Invoke a function call requested by the agent, applying filters that are defined in the agent.""" - tool: AIFunction[BaseModel, Any] | None = tool_map.get(function_call_content.name) - if tool is None: - raise KeyError(f"No tool or function named '{function_call_content.name}'") - - parsed_args: dict[str, Any] = dict(function_call_content.parse_arguments() or {}) - - # Merge with user-supplied args; right-hand side dominates, so parsed args win on conflicts. - merged_args: dict[str, Any] = (custom_args or {}) | parsed_args - args = tool.input_model.model_validate(merged_args) - exception = None - try: - function_result = await tool.invoke(arguments=args, tool_call_id=function_call_content.call_id) - except Exception as ex: - exception = ex - function_result = None - return FunctionResultContent( - call_id=function_call_content.call_id, - exception=exception, - result=function_result, - ) - - -def _tool_call_non_streaming( - func: Callable[..., Awaitable["ChatResponse"]], -) -> Callable[..., Awaitable["ChatResponse"]]: - """Decorate the internal _inner_get_response method to enable tool calls.""" - - @wraps(func) - async def wrapper( - self: "BaseChatClient", - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> ChatResponse: - response: ChatResponse | None = None - fcc_messages: list[ChatMessage] = [] - for attempt_idx in range(getattr(self, "__maximum_iterations_per_request", 10)): - response = await func(self, messages=messages, chat_options=chat_options, **kwargs) - # if there are function calls, we will handle them first - function_results = { - it.call_id for it in response.messages[0].contents if isinstance(it, FunctionResultContent) - } - function_calls = [ - it - for it in response.messages[0].contents - if isinstance(it, FunctionCallContent) and it.call_id not in function_results - ] - if function_calls: - # Run all function calls concurrently - results = await asyncio.gather(*[ - _auto_invoke_function( - function_call, - custom_args=kwargs, - tool_map={t.name: t for t in chat_options.tools or [] if isinstance(t, AIFunction)}, # type: ignore[reportPrivateUsage] - sequence_index=seq_idx, - request_index=attempt_idx, - ) - for seq_idx, function_call in enumerate(function_calls) - ]) - # add a single ChatMessage to the response with the results - result_message = ChatMessage(role="tool", contents=results) - response.messages.append(result_message) - # response should contain 2 messages after this, - # one with function call contents - # and one with function result contents - # the amount and call_id's should match - # this runs in every but the first run - # we need to keep track of all function call messages - fcc_messages.extend(response.messages) - # and add them as additional context to the messages - if chat_options.store: - messages.clear() - messages.append(result_message) - else: - messages.extend(response.messages) - continue - # If we reach this point, it means there were no function calls to handle, - # we'll add the previous function call and responses - # to the front of the list, so that the final response is the last one - # TODO (eavanvalkenburg): control this behavior? - if fcc_messages: - for msg in reversed(fcc_messages): - response.messages.insert(0, msg) - return response - - # Failsafe: give up on tools, ask model for plain answer - chat_options.tool_choice = "none" - self._prepare_tool_choice(chat_options=chat_options) # type: ignore[reportPrivateUsage] - response = await func(self, messages=messages, chat_options=chat_options, **kwargs) - if fcc_messages: - for msg in reversed(fcc_messages): - response.messages.insert(0, msg) - return response - - return wrapper - - -def _tool_call_streaming( - func: Callable[..., AsyncIterable["ChatResponseUpdate"]], -) -> Callable[..., AsyncIterable["ChatResponseUpdate"]]: - """Decorate the internal _inner_get_response method to enable tool calls.""" - - @wraps(func) - async def wrapper( - self: "BaseChatClient", - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> AsyncIterable[ChatResponseUpdate]: - """Wrap the inner get streaming response method to handle tool calls.""" - for attempt_idx in range(getattr(self, "__maximum_iterations_per_request", 10)): - function_call_returned = False - all_messages: list[ChatResponseUpdate] = [] - async for update in func(self, messages=messages, chat_options=chat_options, **kwargs): - if update.contents and any(isinstance(item, FunctionCallContent) for item in update.contents): - all_messages.append(update) - function_call_returned = True - yield update - - if not function_call_returned: - return - - # There is one FunctionCallContent response stream in the messages, combining now to create - # the full completion depending on the prompt, the message may contain both function call - # content and others - response: ChatResponse = ChatResponse.from_chat_response_updates(all_messages) - # add the single assistant response message to the history - messages.append(response.messages[0]) - function_calls = [item for item in response.messages[0].contents if isinstance(item, FunctionCallContent)] - - # When conversation id is present, it means that messages are hosted on the server. - # In this case, we need to update ChatOptions with conversation id and also clear messages - if response.conversation_id is not None: - chat_options.conversation_id = response.conversation_id - messages = [] - - if function_calls: - # Run all function calls concurrently - results = await asyncio.gather(*[ - _auto_invoke_function( - function_call, - custom_args=kwargs, - tool_map={t.name: t for t in chat_options.tools or [] if isinstance(t, AIFunction)}, # type: ignore[reportPrivateUsage] - sequence_index=seq_idx, - request_index=attempt_idx, - ) - for seq_idx, function_call in enumerate(function_calls) - ]) - yield ChatResponseUpdate(contents=results, role="tool") - function_result_msg = ChatMessage(role="tool", contents=results) - response.messages.append(function_result_msg) - messages.append(function_result_msg) - continue - - # Failsafe: give up on tools, ask model for plain answer - chat_options.tool_choice = "none" - self._prepare_tool_choice(chat_options=chat_options) # type: ignore[reportPrivateUsage] - async for update in func(self, messages=messages, chat_options=chat_options, **kwargs): - yield update - - return wrapper - - -def use_tool_calling(cls: type[TBaseChatClient]) -> type[TBaseChatClient]: - """Class decorator that enables tool calling for a chat client. - - Remarks: - This only works on classes that derive from BaseChatClient - and the `_inner_get_response` - and `_inner_get_streaming_response` methods. - It also sets a `__maximum_iterations_per_request` attribute on the class. - if you want to expose this to end_users, do a version of this: - - @property - - def maximum_iterations_per_request(self): - return getattr(self, "__maximum_iterations_per_request", 10) - - @maximum_iterations_per_request.setter - - def maximum_iterations_per_request(self, value: int) -> None: - setattr(self, "__maximum_iterations_per_request", value) - - """ - setattr(cls, "__maximum_iterations_per_request", 10) - - if inner_response := getattr(cls, "_inner_get_response", None): - cls._inner_get_response = _tool_call_non_streaming(inner_response) # type: ignore - if inner_streaming_response := getattr(cls, "_inner_get_streaming_response", None): - cls._inner_get_streaming_response = _tool_call_streaming(inner_streaming_response) # type: ignore - return cls - # region ChatClientProtocol Protocol @@ -254,6 +46,11 @@ def use_tool_calling(cls: type[TBaseChatClient]) -> type[TBaseChatClient]: class ChatClientProtocol(Protocol): """A protocol for a chat client that can generate responses.""" + @property + def additional_properties(self) -> dict[str, Any]: + """Get additional properties associated with the client.""" + ... + async def get_response( self, messages: str | ChatMessage | list[str] | list[ChatMessage], @@ -370,26 +167,54 @@ class ChatClientProtocol(Protocol): ... +# region ChatClientBase + + +def prepare_messages(messages: str | ChatMessage | list[str] | list[ChatMessage]) -> list[ChatMessage]: + """Turn the allowed input into a list of chat messages.""" + if isinstance(messages, str): + return [ChatMessage(role="user", text=messages)] + if isinstance(messages, ChatMessage): + return [messages] + return_messages: list[ChatMessage] = [] + for msg in messages: + if isinstance(msg, str): + msg = ChatMessage(role="user", text=msg) + return_messages.append(msg) + return return_messages + + class BaseChatClient(AFBaseModel, ABC): """Base class for chat clients.""" - MODEL_PROVIDER_NAME: str = "unknown" + additional_properties: dict[str, Any] = Field(default_factory=dict) + OTEL_PROVIDER_NAME: str = "unknown" # This is used for OTel setup, should be overridden in subclasses - def _prepare_messages( + def prepare_messages( self, messages: str | ChatMessage | list[str] | list[ChatMessage] ) -> MutableSequence[ChatMessage]: """Turn the allowed input into a list of chat messages.""" - if isinstance(messages, str): - return [ChatMessage(role="user", text=messages)] - if isinstance(messages, ChatMessage): - return [messages] - return_messages: list[ChatMessage] = [] - for msg in messages: - if isinstance(msg, str): - msg = ChatMessage(role="user", text=msg) - return_messages.append(msg) - return return_messages + return prepare_messages(messages) + + @staticmethod + def _normalize_tools( + tools: ToolProtocol + | MutableMapping[str, Any] + | Callable[..., Any] + | list[ToolProtocol | MutableMapping[str, Any] | Callable[..., Any]] + | None = None, + ) -> list[ToolProtocol | dict[str, Any] | Callable[..., Any]]: + """Normalize the tools input to a list of tools.""" + final_tools: list[ToolProtocol | dict[str, Any] | Callable[..., Any]] = [] + if not tools: + return final_tools + for tool in tools if isinstance(tools, list) else [tools]: # type: ignore[reportUnknownType] + if isinstance(tool, MCPTool): + final_tools.extend(tool.functions) # type: ignore + continue + final_tools.append(tool) # type: ignore + return final_tools # region Internal methods to be implemented by the derived classes @@ -513,11 +338,11 @@ class BaseChatClient(AFBaseModel, ABC): temperature=temperature, top_p=top_p, tool_choice=tool_choice, - tools=tools, # type: ignore + tools=self._normalize_tools(tools), # type: ignore user=user, additional_properties=additional_properties or {}, ) - prepped_messages = self._prepare_messages(messages) + prepped_messages = self.prepare_messages(messages) self._prepare_tool_choice(chat_options=chat_options) return await self._inner_get_response(messages=prepped_messages, chat_options=chat_options, **kwargs) @@ -592,12 +417,12 @@ class BaseChatClient(AFBaseModel, ABC): temperature=temperature, top_p=top_p, tool_choice=tool_choice, - tools=tools, # type: ignore + tools=self._normalize_tools(tools), # type: ignore user=user, additional_properties=additional_properties or {}, **kwargs, ) - prepped_messages = self._prepare_messages(messages) + prepped_messages = self.prepare_messages(messages) self._prepare_tool_choice(chat_options=chat_options) async for update in self._inner_get_streaming_response( messages=prepped_messages, chat_options=chat_options, **kwargs @@ -620,13 +445,13 @@ class BaseChatClient(AFBaseModel, ABC): else: chat_options.tool_choice = chat_tool_mode.mode - def service_url(self) -> str | None: + def service_url(self) -> str: """Get the URL of the service. Override this in the subclass to return the proper URL. If the service does not have a URL, return None. """ - return None + return "Unknown" def create_agent( self, @@ -639,6 +464,7 @@ class BaseChatClient(AFBaseModel, ABC): | list[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]] | None = None, chat_message_store_factory: Callable[[], ChatMessageStore] | None = None, + context_providers: ContextProvider | list[ContextProvider] | AggregateContextProvider | None = None, **kwargs: Any, ) -> "ChatAgent": """Create an agent with the given name and instructions. @@ -649,6 +475,7 @@ class BaseChatClient(AFBaseModel, ABC): tools: Optional list of tools to associate with the agent. chat_message_store_factory: Factory function to create an instance of ChatMessageStore. If not provided, the default in-memory store will be used. + context_providers: Context providers to include during agent invocation. **kwargs: Additional keyword arguments to pass to the agent. See ChatAgent for all the available options. @@ -663,6 +490,7 @@ class BaseChatClient(AFBaseModel, ABC): instructions=instructions, tools=tools, chat_message_store_factory=chat_message_store_factory, + context_providers=context_providers, **kwargs, ) diff --git a/python/packages/main/agent_framework/_mcp.py b/python/packages/main/agent_framework/_mcp.py index 27a4c3d5af..180aecfc95 100644 --- a/python/packages/main/agent_framework/_mcp.py +++ b/python/packages/main/agent_framework/_mcp.py @@ -12,7 +12,6 @@ from typing import TYPE_CHECKING, Any from mcp import types from mcp.client.session import ClientSession -from mcp.client.sse import sse_client from mcp.client.stdio import StdioServerParameters, stdio_client from mcp.client.streamable_http import streamablehttp_client from mcp.client.websocket import websocket_client @@ -49,7 +48,6 @@ LOG_LEVEL_MAPPING: dict[types.LoggingLevel, int] = { } __all__ = [ - "MCPSseTools", "MCPStdioTool", "MCPStreamableHTTPTool", "MCPWebsocketTool", @@ -224,7 +222,7 @@ def _normalize_mcp_name(name: str) -> str: class MCPTool: - """Base class with the MCP logic.""" + """Main MCP class, to initialize use one of the subclasses.""" def __init__( self, @@ -567,82 +565,6 @@ class MCPStdioTool(MCPTool): return stdio_client(server=StdioServerParameters(**args)) -class MCPSseTools(MCPTool): - """MCP sse server configuration.""" - - def __init__( - self, - name: str, - url: str, - *, - load_tools: bool = True, - load_prompts: bool = True, - request_timeout: int | None = None, - session: ClientSession | None = None, - description: str | None = None, - additional_properties: dict[str, Any] | None = None, - headers: dict[str, Any] | None = None, - timeout: float | None = None, - sse_read_timeout: float | None = None, - chat_client: "ChatClientProtocol | None" = None, - **kwargs: Any, - ) -> None: - """Initialize the MCP sse plugin. - - The arguments are used to create a sse client. - see mcp.client.sse.sse_client for more details. - - Any extra arguments passed to the constructor will be passed to the - sse client constructor. - - Args: - name: The name of the plugin. - url: The URL of the MCP server. - load_tools: Whether to load tools from the MCP server. - load_prompts: Whether to load prompts from the MCP server. - request_timeout: The default timeout used for all requests. - session: The session to use for the MCP connection. - description: The description of the plugin. - additional_properties: Additional properties. - headers: The headers to send with the request. - timeout: The timeout for the request. - sse_read_timeout: The timeout for reading from the SSE stream. - chat_client: The chat client to use for sampling. - kwargs: Any extra arguments to pass to the sse client. - - """ - super().__init__( - name=name, - description=description, - additional_properties=additional_properties, - session=session, - chat_client=chat_client, - load_tools=load_tools, - load_prompts=load_prompts, - request_timeout=request_timeout, - ) - self.url = url - self.headers = headers or {} - self.timeout = timeout - self.sse_read_timeout = sse_read_timeout - self._client_kwargs = kwargs - - def get_mcp_client(self) -> _AsyncGeneratorContextManager[Any, None]: - """Get an MCP SSE client.""" - args: dict[str, Any] = { - "url": self.url, - } - if self.headers: - args["headers"] = self.headers - if self.timeout is not None: - args["timeout"] = self.timeout - if self.sse_read_timeout is not None: - args["sse_read_timeout"] = self.sse_read_timeout - if self._client_kwargs: - args.update(self._client_kwargs) - return sse_client(**args) - - class MCPStreamableHTTPTool(MCPTool): """MCP streamable http server configuration.""" diff --git a/python/packages/main/agent_framework/_memory.py b/python/packages/main/agent_framework/_memory.py new file mode 100644 index 0000000000..cdb3f2ff61 --- /dev/null +++ b/python/packages/main/agent_framework/_memory.py @@ -0,0 +1,188 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +import sys +from abc import ABC, abstractmethod +from collections.abc import MutableSequence, Sequence +from contextlib import AsyncExitStack +from types import TracebackType + +from ._pydantic import AFBaseModel +from ._types import ChatMessage, Contents + +if sys.version_info >= (3, 11): + from typing import Self # pragma: no cover +else: + from typing_extensions import Self # pragma: no cover + +# region Context + + +class Context(AFBaseModel): + """A class containing any context that should be provided to the AI model as supplied by an ContextProvider. + + Each ContextProvider has the ability to provide its own context for each invocation. + The Context class contains the additional context supplied by the ContextProvider. + This context will be combined with context supplied by other providers before being passed to the AI model. + This context is per invocation, and will not be stored as part of the chat history. + """ + + contents: list[Contents] | None = None + """ + Any content to pass to the AI model in addition to any other prompts + that it may already have (in the case of an agent), or chat history that may already exist. + """ + + +# region ContextProvider + + +class ContextProvider(AFBaseModel, ABC): + """Base class for all context providers. + + A context provider is a component that can be used to enhance the AI's context management. + It can listen to changes in the conversation and provide additional context to the AI model + just before invocation. + """ + + async def thread_created(self, thread_id: str | None) -> None: + """Called just after a new thread is created. + + Implementers can use this method to do any operations required at the creation of a new thread. + For example, checking long term storage for any data that is relevant + to the current session based on the input text. + + Args: + thread_id: The ID of the new thread. + """ + pass + + async def messages_adding(self, thread_id: str | None, new_messages: ChatMessage | Sequence[ChatMessage]) -> None: + """Called just before messages are added to the chat by any participant. + + Inheritors can use this method to update their context based on new messages. + + Args: + thread_id: The ID of the thread for the new message. + new_messages: New messages to add. + """ + pass + + @abstractmethod + async def model_invoking(self, messages: ChatMessage | MutableSequence[ChatMessage]) -> Context: + """Called just before the Model/Agent/etc. is invoked. + + Implementers can load any additional context required at this time, + and they should return any context that should be passed to the agent. + + Args: + messages: The most recent messages that the agent is being invoked with. + """ + pass + + async def __aenter__(self) -> "Self": + """Async context manager entry. + + Override this method to perform any setup operations when the context provider is entered. + + Returns: + Self for chaining. + """ + return self + + async def __aexit__( + self, + exc_type: type[BaseException] | None, + exc_val: BaseException | None, + exc_tb: TracebackType | None, + ) -> None: + """Async context manager exit. + + Override this method to perform any cleanup operations when the context provider is exited. + + Args: + exc_type: Exception type if an exception occurred, None otherwise. + exc_val: Exception value if an exception occurred, None otherwise. + exc_tb: Exception traceback if an exception occurred, None otherwise. + """ + pass + + +# region AggregateContextProvider + + +class AggregateContextProvider(ContextProvider): + """A ContextProvider that contains multiple context providers. + + It delegates events to multiple context providers and aggregates responses from those events before returning. + """ + + providers: list[ContextProvider] + """List of registered context providers.""" + + def __init__(self, context_providers: Sequence[ContextProvider] | None = None) -> None: + """Initialize AggregateContextProvider with context providers. + + Args: + context_providers: Context providers to add. + """ + super().__init__(providers=list(context_providers or [])) # type: ignore + self._exit_stack: AsyncExitStack | None = None + + def add(self, context_provider: ContextProvider) -> None: + """Adds new context provider. + + Args: + context_provider: Context provider to add. + """ + self.providers.append(context_provider) + + async def thread_created(self, thread_id: str | None = None) -> None: + await asyncio.gather(*[x.thread_created(thread_id) for x in self.providers]) + + async def messages_adding(self, thread_id: str | None, new_messages: ChatMessage | Sequence[ChatMessage]) -> None: + await asyncio.gather(*[x.messages_adding(thread_id, new_messages) for x in self.providers]) + + async def model_invoking(self, messages: ChatMessage | MutableSequence[ChatMessage]) -> Context: + sub_contexts = await asyncio.gather(*[x.model_invoking(messages) for x in self.providers]) + combined_context = Context() + # Flatten the list of lists and filter out None values + all_contents = [] + for ctx in sub_contexts: + if ctx.contents: + all_contents.extend(ctx.contents) + + combined_context.contents = all_contents if all_contents else None + return combined_context + + async def __aenter__(self) -> "Self": + """Enter async context manager and set up all providers. + + Returns: + Self for chaining. + """ + self._exit_stack = AsyncExitStack() + await self._exit_stack.__aenter__() + + # Enter all context providers + for provider in self.providers: + await self._exit_stack.enter_async_context(provider) + + return self + + async def __aexit__( + self, + exc_type: type[BaseException] | None, + exc_val: BaseException | None, + exc_tb: TracebackType | None, + ) -> None: + """Exit async context manager and clean up all providers. + + Args: + exc_type: Exception type if an exception occurred, None otherwise. + exc_val: Exception value if an exception occurred, None otherwise. + exc_tb: Exception traceback if an exception occurred, None otherwise. + """ + if self._exit_stack is not None: + await self._exit_stack.__aexit__(exc_type, exc_val, exc_tb) + self._exit_stack = None diff --git a/python/packages/main/agent_framework/_tools.py b/python/packages/main/agent_framework/_tools.py index 5bd9566cb5..b0751b2406 100644 --- a/python/packages/main/agent_framework/_tools.py +++ b/python/packages/main/agent_framework/_tools.py @@ -1,14 +1,18 @@ # Copyright (c) Microsoft. All rights reserved. +import asyncio import inspect -from collections.abc import Awaitable, Callable +import sys +from collections.abc import AsyncIterable, Awaitable, Callable, Collection, MutableMapping, Sequence from functools import wraps -from time import perf_counter +from time import perf_counter, time_ns from typing import ( TYPE_CHECKING, Annotated, Any, + Final, Generic, + Literal, Protocol, TypeVar, get_args, @@ -16,30 +20,58 @@ from typing import ( runtime_checkable, ) -from opentelemetry import metrics, trace -from pydantic import BaseModel, Field, PrivateAttr, create_model +from opentelemetry import metrics +from pydantic import AnyUrl, BaseModel, Field, PrivateAttr, ValidationError, create_model, field_validator from ._logging import get_logger from ._pydantic import AFBaseModel -from .telemetry import GenAIAttributes, start_as_current_span +from .exceptions import ChatClientInitializationError, ToolException +from .telemetry import ( + OPERATION_DURATION_BUCKET_BOUNDARIES, + OtelAttr, + _capture_exception, # type: ignore + get_function_span, + meter, +) if TYPE_CHECKING: - from ._types import Contents + from ._clients import ChatClientProtocol + from ._types import ( + ChatMessage, + ChatResponse, + ChatResponseUpdate, + Contents, + FunctionCallContent, + ) + +if sys.version_info >= (3, 12): + from typing import TypedDict # pragma: no cover +else: + from typing_extensions import TypedDict # pragma: no cover -tracer: trace.Tracer = trace.get_tracer("agent_framework") -meter: metrics.Meter = metrics.get_meter_provider().get_meter("agent_framework") logger = get_logger() __all__ = [ + "FUNCTION_INVOKING_CHAT_CLIENT_MARKER", "AIFunction", "HostedCodeInterpreterTool", "HostedFileSearchTool", + "HostedMCPSpecificApproval", + "HostedMCPTool", "HostedWebSearchTool", "ToolProtocol", "ai_function", + "use_function_invocation", ] +logger = get_logger() +FUNCTION_INVOKING_CHAT_CLIENT_MARKER: Final[str] = "__function_invoking_chat_client__" +DEFAULT_MAX_ITERATIONS: Final[int] = 10 +TChatClient = TypeVar("TChatClient", bound="ChatClientProtocol") +# region Helpers + + def _parse_inputs( inputs: "Contents | dict[str, Any] | str | list[Contents | dict[str, Any] | str] | None", ) -> list["Contents"]: @@ -82,6 +114,7 @@ def _parse_inputs( return parsed_inputs +# region Tools @runtime_checkable class ToolProtocol(Protocol): """Represents a generic tool that can be specified to an AI service. @@ -197,13 +230,88 @@ class HostedWebSearchTool(BaseTool): args: dict[str, Any] = { "name": "web_search", } + super().__init__(**args, **kwargs) + + +class HostedMCPSpecificApproval(TypedDict, total=False): + """Represents the `specific` mode for a hosted tool. + + When using this mode, the user must specify which tools always or never require approval. + This is represented as a dictionary with two optional keys: + - `always_require_approval`: A sequence of tool names that always require approval. + - `never_require_approval`: A sequence of tool names that never require approval. + + """ + + always_require_approval: Collection[str] | None + never_require_approval: Collection[str] | None + + +class HostedMCPTool(BaseTool): + """Represents a MCP tool that is managed and executed by the service.""" + + url: AnyUrl + approval_mode: Literal["always_require", "never_require"] | HostedMCPSpecificApproval | None = None + allowed_tools: set[str] | None = None + headers: dict[str, str] | None = None + + def __init__( + self, + *, + name: str, + description: str | None = None, + url: AnyUrl | str, + approval_mode: Literal["always_require", "never_require"] | HostedMCPSpecificApproval | None = None, + allowed_tools: Collection[str] | None = None, + headers: dict[str, str] | None = None, + additional_properties: dict[str, Any] | None = None, + **kwargs: Any, + ) -> None: + """Create a hosted MCP tool. + + Args: + name: The name of the tool. + description: A description of the tool. + url: The URL of the tool. + approval_mode: The approval mode for the tool. This can be: + - "always_require": The tool always requires approval before use. + - "never_require": The tool never requires approval before use. + - A dict with keys `always_require_approval` or `never_require_approval`, + followed by a sequence of strings with the names of the relevant tools. + allowed_tools: A list of tools that are allowed to use this tool. + headers: Headers to include in requests to the tool. + additional_properties: Additional properties to include in the tool definition. + **kwargs: Additional keyword arguments to pass to the base class. + """ + args: dict[str, Any] = { + "name": name, + "url": url, + } + if allowed_tools is not None: + args["allowed_tools"] = allowed_tools + if approval_mode is not None: + args["approval_mode"] = approval_mode + if headers is not None: + args["headers"] = headers if description is not None: args["description"] = description if additional_properties is not None: args["additional_properties"] = additional_properties - if "name" in kwargs: - raise ValueError("The 'name' argument is reserved for the HostedFileSearchTool and cannot be set.") - super().__init__(**args, **kwargs) + try: + super().__init__(**args, **kwargs) + except ValidationError as err: + raise ToolException(f"Error initializing HostedMCPTool: {err}", inner_exception=err) from err + + @field_validator("approval_mode") + def validate_approval_mode(cls, approval_mode: str | dict[str, Any] | None) -> str | dict[str, Any] | None: + """Validate the approval_mode field to ensure it is one of the accepted values.""" + if approval_mode is None or not isinstance(approval_mode, dict): + return approval_mode + # Validate that the dict has sets + for key, value in approval_mode.items(): + if not isinstance(value, set): + approval_mode[key] = set(value) # Convert to set if it's a list or other collection + return approval_mode class HostedFileSearchTool(BaseTool): @@ -253,7 +361,7 @@ class HostedFileSearchTool(BaseTool): class AIFunction(BaseTool, Generic[ArgsT, ReturnT]): - """A ToolProtocol that is callable as code. + """A AITool that is callable as code. Args: name: The name of the function. @@ -267,9 +375,10 @@ class AIFunction(BaseTool, Generic[ArgsT, ReturnT]): input_model: type[ArgsT] _invocation_duration_histogram: metrics.Histogram = PrivateAttr( default_factory=lambda: meter.create_histogram( - GenAIAttributes.MEASUREMENT_FUNCTION_INVOCATION_DURATION.value, - unit="s", + name=OtelAttr.MEASUREMENT_FUNCTION_INVOCATION_DURATION, + unit=OtelAttr.DURATION_UNIT, description="Measures the duration of a function's execution", + explicit_bucket_boundaries_advisory=OPERATION_DURATION_BUCKET_BOUNDARIES, ) ) @@ -287,40 +396,60 @@ class AIFunction(BaseTool, Generic[ArgsT, ReturnT]): Args: arguments: A Pydantic model instance containing the arguments for the function. - kwargs: keyword arguments to pass to the function, will not be used if `args` is provided. + otel_settings: Optional model diagnostics settings to override the default settings. + kwargs: keyword arguments to pass to the function, will not be used if `arguments` is provided. """ + global OTEL_SETTINGS + from .telemetry import OTEL_SETTINGS, setup_telemetry + tool_call_id = kwargs.pop("tool_call_id", None) if arguments is not None: if not isinstance(arguments, self.input_model): raise TypeError(f"Expected {self.input_model.__name__}, got {type(arguments).__name__}") kwargs = arguments.model_dump(exclude_none=True) - logger.info(f"Function name: {self.name}") - logger.debug(f"Function arguments: {kwargs}") - with start_as_current_span( - tracer, self, metadata={"tool_call_id": tool_call_id, "kwargs": kwargs} - ) as current_span: - attributes: dict[str, Any] = { - GenAIAttributes.MEASUREMENT_FUNCTION_TAG_NAME.value: self.name, - GenAIAttributes.TOOL_CALL_ID.value: tool_call_id, + if not OTEL_SETTINGS.ENABLED: # type: ignore + logger.info(f"Function name: {self.name}") + logger.debug(f"Function arguments: {kwargs}") + res = self.__call__(**kwargs) + result = await res if inspect.isawaitable(res) else res + logger.info(f"Function {self.name} succeeded.") + logger.debug(f"Function result: {result or 'None'}") + return result # type: ignore[reportReturnType] + + setup_telemetry() + with get_function_span( + function=self, + tool_call_id=tool_call_id, + ) as span: + hist_attributes: dict[str, Any] = { + OtelAttr.MEASUREMENT_FUNCTION_TAG_NAME: self.name, + OtelAttr.TOOL_CALL_ID: tool_call_id or "unknown", } - starting_time_stamp = perf_counter() + logger.info(f"Function name: {self.name}") + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED: # type: ignore + logger.debug(f"Function arguments: {kwargs}") + start_time_stamp = perf_counter() + end_time_stamp: float | None = None try: res = self.__call__(**kwargs) result = await res if inspect.isawaitable(res) else res - logger.info(f"Function {self.name} succeeded.") - logger.debug(f"Function result: {result or 'None'}") - return result # type: ignore[reportReturnType] + end_time_stamp = perf_counter() except Exception as exception: - attributes[GenAIAttributes.ERROR_TYPE.value] = type(exception).__name__ - current_span.record_exception(exception) - current_span.set_attribute(GenAIAttributes.ERROR_TYPE.value, type(exception).__name__) - current_span.set_status(trace.StatusCode.ERROR, description=str(exception)) + end_time_stamp = perf_counter() + hist_attributes[OtelAttr.ERROR_TYPE] = type(exception).__name__ + _capture_exception(span=span, exception=exception, timestamp=time_ns()) logger.error(f"Function failed. Error: {exception}") raise + else: + logger.info(f"Function {self.name} succeeded.") + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED: # type: ignore + logger.debug(f"Function result: {result or 'None'}") + return result # type: ignore[reportReturnType] finally: - duration = perf_counter() - starting_time_stamp - self._invocation_duration_histogram.record(duration, attributes=attributes) - logger.info("Function completed. Duration: %fs", duration) + duration = (end_time_stamp or perf_counter()) - start_time_stamp + span.set_attribute(OtelAttr.MEASUREMENT_FUNCTION_INVOCATION_DURATION, duration) + self._invocation_duration_histogram.record(duration, attributes=hist_attributes) + logger.info("Function duration: %fs", duration) def parameters(self) -> dict[str, Any]: """Create the json schema of the parameters.""" @@ -338,6 +467,9 @@ class AIFunction(BaseTool, Generic[ArgsT, ReturnT]): } +# region AI Function Decorator + + def _parse_annotation(annotation: Any) -> Any: """Parse a type annotation and return the corresponding type. @@ -415,3 +547,306 @@ def ai_function( return wrapper(func) return decorator(func) if func else decorator # type: ignore[reportReturnType, return-value] + + +# region Function Invoking Chat Client + + +async def _auto_invoke_function( + function_call_content: "FunctionCallContent", + custom_args: dict[str, Any] | None = None, + *, + tool_map: dict[str, AIFunction[BaseModel, Any]], + sequence_index: int | None = None, + request_index: int | None = None, +) -> "Contents": + """Invoke a function call requested by the agent, applying filters that are defined in the agent.""" + from ._types import FunctionResultContent + + tool: AIFunction[BaseModel, Any] | None = tool_map.get(function_call_content.name) + if tool is None: + raise KeyError(f"No tool or function named '{function_call_content.name}'") + + parsed_args: dict[str, Any] = dict(function_call_content.parse_arguments() or {}) + + # Merge with user-supplied args; right-hand side dominates, so parsed args win on conflicts. + merged_args: dict[str, Any] = (custom_args or {}) | parsed_args + args = tool.input_model.model_validate(merged_args) + exception = None + try: + function_result = await tool.invoke( + arguments=args, + tool_call_id=function_call_content.call_id, + ) # type: ignore[arg-type] + except Exception as ex: + exception = ex + function_result = None + return FunctionResultContent( + call_id=function_call_content.call_id, + exception=exception, + result=function_result, + ) + + +def _get_tool_map( + tools: "ToolProtocol \ + | Callable[..., Any] \ + | MutableMapping[str, Any] \ + | list[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]", +) -> dict[str, AIFunction[Any, Any]]: + ai_function_list: dict[str, AIFunction[Any, Any]] = {} + for tool in tools if isinstance(tools, list) else [tools]: + if isinstance(tool, AIFunction): + ai_function_list[tool.name] = tool + continue + if callable(tool): + # Convert to AITool if it's a function or callable + ai_tool = ai_function(tool) + ai_function_list[ai_tool.name] = ai_tool + return ai_function_list + + +async def execute_function_calls( + custom_args: dict[str, Any], + attempt_idx: int, + function_calls: Sequence["FunctionCallContent"], + tools: "ToolProtocol \ + | Callable[..., Any] \ + | MutableMapping[str, Any] \ + | list[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]", +) -> list["Contents"]: + tool_map = _get_tool_map(tools) + # Run all function calls concurrently + return await asyncio.gather(*[ + _auto_invoke_function( + function_call_content=function_call, + custom_args=custom_args, + tool_map=tool_map, + sequence_index=seq_idx, + request_index=attempt_idx, + ) + for seq_idx, function_call in enumerate(function_calls) + ]) + + +def update_conversation_id(kwargs: dict[str, Any], conversation_id: str | None) -> None: + """Update kwargs with conversation id.""" + if conversation_id is None: + return + if "chat_options" in kwargs: + kwargs["chat_options"].conversation_id = conversation_id + else: + kwargs["conversation_id"] = conversation_id + + +def _handle_function_calls_response( + func: Callable[..., Awaitable["ChatResponse"]], + *, + max_iterations: int = 10, +) -> Callable[..., Awaitable["ChatResponse"]]: + """Decorate the get_response method to enable function calls. + + Args: + func: The get_response method to decorate. + max_iterations: The maximum number of function call iterations to perform. + + """ + + def decorator( + func: Callable[..., Awaitable["ChatResponse"]], + ) -> Callable[..., Awaitable["ChatResponse"]]: + """Inner decorator.""" + + @wraps(func) + async def function_invocation_wrapper( + self: "ChatClientProtocol", + messages: "str | ChatMessage | list[str] | list[ChatMessage]", + **kwargs: Any, + ) -> "ChatResponse": + from ._clients import prepare_messages + from ._types import ChatMessage, ChatOptions, FunctionCallContent, FunctionResultContent + + prepped_messages = prepare_messages(messages) + response: "ChatResponse | None" = None + fcc_messages: "list[ChatMessage]" = [] + for attempt_idx in range(max_iterations): + response = await func(self, messages=prepped_messages, **kwargs) + # if there are function calls, we will handle them first + function_results = { + it.call_id for it in response.messages[0].contents if isinstance(it, FunctionResultContent) + } + function_calls = [ + it + for it in response.messages[0].contents + if isinstance(it, FunctionCallContent) and it.call_id not in function_results + ] + + if response.conversation_id is not None: + update_conversation_id(kwargs, response.conversation_id) + prepped_messages = [] + + tools = kwargs.get("tools") + if not tools and (chat_options := kwargs.get("chat_options")) and isinstance(chat_options, ChatOptions): + tools = chat_options.tools + if function_calls and tools: + function_results = await execute_function_calls( + custom_args=kwargs, + attempt_idx=attempt_idx, + function_calls=function_calls, + tools=tools, # type: ignore + ) + # add a single ChatMessage to the response with the results + result_message = ChatMessage(role="tool", contents=function_results) # type: ignore[call-overload] + response.messages.append(result_message) + # response should contain 2 messages after this, + # one with function call contents + # and one with function result contents + # the amount and call_id's should match + # this runs in every but the first run + # we need to keep track of all function call messages + fcc_messages.extend(response.messages) + # and add them as additional context to the messages + if kwargs.get("store"): + prepped_messages.clear() + prepped_messages.append(result_message) + else: + prepped_messages.extend(response.messages) + continue + # If we reach this point, it means there were no function calls to handle, + # we'll add the previous function call and responses + # to the front of the list, so that the final response is the last one + # TODO (eavanvalkenburg): control this behavior? + if fcc_messages: + for msg in reversed(fcc_messages): + response.messages.insert(0, msg) + return response + + # Failsafe: give up on tools, ask model for plain answer + kwargs["tool_choice"] = "none" + response = await func(self, messages=prepped_messages, **kwargs) + if fcc_messages: + for msg in reversed(fcc_messages): + response.messages.insert(0, msg) + return response + + return function_invocation_wrapper # type: ignore + + return decorator(func) + + +def _handle_function_calls_streaming_response( + func: Callable[..., AsyncIterable["ChatResponseUpdate"]], + *, + max_iterations: int = 10, +) -> Callable[..., AsyncIterable["ChatResponseUpdate"]]: + """Decorate the get_streaming_response method to handle function calls. + + Args: + func: The get_streaming_response method to decorate. + max_iterations: The maximum number of function call iterations to perform. + + """ + + def decorator( + func: Callable[..., AsyncIterable["ChatResponseUpdate"]], + ) -> Callable[..., AsyncIterable["ChatResponseUpdate"]]: + """Inner decorator.""" + + @wraps(func) + async def streaming_function_invocation_wrapper( + self: "ChatClientProtocol", + messages: "str | ChatMessage | list[str] | list[ChatMessage]", + **kwargs: Any, + ) -> AsyncIterable["ChatResponseUpdate"]: + """Wrap the inner get streaming response method to handle tool calls.""" + from ._clients import prepare_messages + from ._types import ChatMessage, ChatOptions, ChatResponse, ChatResponseUpdate, FunctionCallContent + + prepped_messages = prepare_messages(messages) + for attempt_idx in range(max_iterations): + all_updates: list["ChatResponseUpdate"] = [] + async for update in func(self, messages=prepped_messages, **kwargs): + all_updates.append(update) + yield update + + # efficient check for FunctionCallContent in the updates + # if there is at least one, this stops and continuous + # if there are no FCC's then it returns + if not any(isinstance(item, FunctionCallContent) for upd in all_updates for item in upd.contents): + return + + # Now combining the updates to create the full response. + # Depending on the prompt, the message may contain both function call + # content and others + + response: "ChatResponse" = ChatResponse.from_chat_response_updates(all_updates) + # add the response message to the previous messages + prepped_messages.append(response.messages[0]) + # get the fccs + function_calls = [ + item for item in response.messages[0].contents if isinstance(item, FunctionCallContent) + ] + + # When conversation id is present, it means that messages are hosted on the server. + # In this case, we need to update kwargs with conversation id and also clear messages + if response.conversation_id is not None: + update_conversation_id(kwargs, response.conversation_id) + prepped_messages = [] + + tools = kwargs.get("tools") + if not tools and (chat_options := kwargs.get("chat_options")) and isinstance(chat_options, ChatOptions): + tools = chat_options.tools + + if function_calls and tools: + function_results = await execute_function_calls( + custom_args=kwargs, + attempt_idx=attempt_idx, + function_calls=function_calls, + tools=tools, # type: ignore[reportArgumentType] + ) + function_result_msg = ChatMessage(role="tool", contents=function_results) + yield ChatResponseUpdate(contents=function_results, role="tool") + response.messages.append(function_result_msg) + prepped_messages.append(function_result_msg) + continue + + # Failsafe: give up on tools, ask model for plain answer + kwargs["tool_choice"] = "none" + async for update in func(self, messages=prepped_messages, **kwargs): + yield update + + return streaming_function_invocation_wrapper + + return decorator(func) + + +def use_function_invocation( + chat_client: type[TChatClient], +) -> type[TChatClient]: + """Class decorator that enables tool calling for a chat client.""" + if getattr(chat_client, FUNCTION_INVOKING_CHAT_CLIENT_MARKER, False): + return chat_client + + max_iterations = DEFAULT_MAX_ITERATIONS + + try: + chat_client.get_response = _handle_function_calls_response( # type: ignore + func=chat_client.get_response, # type: ignore + max_iterations=max_iterations, + ) + except AttributeError as ex: + raise ChatClientInitializationError( + f"Chat client {chat_client.__name__} does not have a get_response method, cannot apply function invocation." + ) from ex + try: + chat_client.get_streaming_response = _handle_function_calls_streaming_response( # type: ignore + func=chat_client.get_streaming_response, + max_iterations=max_iterations, + ) + except AttributeError as ex: + raise ChatClientInitializationError( + f"Chat client {chat_client.__name__} does not have a get_streaming_response method, " + "cannot apply function invocation." + ) from ex + setattr(chat_client, FUNCTION_INVOKING_CHAT_CLIENT_MARKER, True) + return chat_client diff --git a/python/packages/main/agent_framework/_types.py b/python/packages/main/agent_framework/_types.py index c80d01dc60..1a7e54efef 100644 --- a/python/packages/main/agent_framework/_types.py +++ b/python/packages/main/agent_framework/_types.py @@ -29,7 +29,7 @@ from pydantic import ( from ._logging import get_logger from ._pydantic import AFBaseModel from ._tools import ToolProtocol, ai_function -from .exceptions import AgentFrameworkException +from .exceptions import AdditionItemMismatch if sys.version_info >= (3, 11): from typing import Self # pragma: no cover @@ -55,6 +55,7 @@ KNOWN_MEDIA_TYPES = [ "application/pdf", "application/xml", "audio/mpeg", + "audio/mp3", "audio/ogg", "audio/wav", "image/apng", @@ -93,6 +94,8 @@ __all__ = [ "DataContent", "ErrorContent", "FinishReason", + "FunctionApprovalRequestContent", + "FunctionApprovalResponseContent", "FunctionCallContent", "FunctionResultContent", "GeneratedEmbeddings", @@ -224,7 +227,11 @@ def _process_update( is_new_message = False if ( not response.messages - or (update.message_id and response.messages[-1].message_id != update.message_id) + or ( + update.message_id + and response.messages[-1].message_id + and response.messages[-1].message_id != update.message_id + ) or (update.role and response.messages[-1].role != update.role) ): is_new_message = True @@ -249,7 +256,7 @@ def _process_update( ): try: message.contents[-1] += content - except AgentFrameworkException: + except AdditionItemMismatch: message.contents.append(content) elif isinstance(content, UsageContent): if response.usage_details is None: @@ -718,7 +725,7 @@ class DataContent(BaseContent): raise ValueError(f"Unknown media type: {media_type}") return uri - def has_top_level_media_type(self, top_level_media_type: str) -> bool: + def has_top_level_media_type(self, top_level_media_type: Literal["application", "audio", "image", "text"]) -> bool: return _has_top_level_media_type(self.media_type, top_level_media_type) @@ -776,11 +783,13 @@ class UriContent(BaseContent): **kwargs, ) - def has_top_level_media_type(self, top_level_media_type: str) -> bool: + def has_top_level_media_type(self, top_level_media_type: Literal["application", "audio", "image", "text"]) -> bool: return _has_top_level_media_type(self.media_type, top_level_media_type) -def _has_top_level_media_type(media_type: str | None, top_level_media_type: str) -> bool: +def _has_top_level_media_type( + media_type: str | None, top_level_media_type: Literal["application", "audio", "image", "text"] +) -> bool: if media_type is None: return False @@ -924,7 +933,7 @@ class FunctionCallContent(BaseContent): if not isinstance(other, FunctionCallContent): raise TypeError("Incompatible type") if other.call_id and self.call_id != other.call_id: - raise AgentFrameworkException("Incompatible function call contents") + raise AdditionItemMismatch("", log_level=None) if not self.arguments: arguments = other.arguments elif not other.arguments: @@ -1093,6 +1102,110 @@ class HostedVectorStoreContent(BaseContent): ) +class BaseUserInputRequest(BaseContent): + """Base class for all user requests.""" + + type: Literal["user_input_request"] = "user_input_request" # type: ignore[assignment] + id: Annotated[str, Field(..., min_length=1)] + + +class BaseUserInputResponse(BaseContent): + """Base class for all user responses.""" + + type: Literal["user_input_response"] = "user_input_response" # type: ignore[assignment] + id: Annotated[str, Field(..., min_length=1)] + + +class FunctionApprovalResponseContent(BaseUserInputResponse): + """Represents a response for user approval of a function call.""" + + type: Literal["function_approval_response"] = "function_approval_response" # type: ignore[assignment] + approved: bool + function_call: FunctionCallContent + + def __init__( + self, + approved: bool, + *, + id: str, + function_call: FunctionCallContent, + annotations: list[Annotations] | None = None, + additional_properties: dict[str, Any] | None = None, + raw_representation: Any | None = None, + **kwargs: Any, + ) -> None: + """Initializes a FunctionApprovalResponseContent instance. + + Args: + approved: Whether the function call was approved. + id: The unique identifier for the request. + function_call: The function call content to be approved. + annotations: Optional list of annotations for the request. + additional_properties: Optional additional properties for the request. + raw_representation: Optional raw representation of the request. + **kwargs: Additional keyword arguments. + """ + super().__init__( + approved=approved, # type: ignore[reportCallIssue] + id=id, # type: ignore[reportCallIssue] + function_call=function_call, # type: ignore[reportCallIssue] + annotations=annotations, + additional_properties=additional_properties, + raw_representation=raw_representation, + **kwargs, + ) + + +class FunctionApprovalRequestContent(BaseUserInputRequest): + """Represents a request for user approval of a function call.""" + + type: Literal["function_approval_request"] = "function_approval_request" # type: ignore[assignment] + function_call: FunctionCallContent + + def __init__( + self, + *, + id: str, + function_call: FunctionCallContent, + annotations: list[Annotations] | None = None, + additional_properties: dict[str, Any] | None = None, + raw_representation: Any | None = None, + **kwargs: Any, + ) -> None: + """Initializes a FunctionApprovalRequestContent instance. + + Args: + id: The unique identifier for the request. + function_call: The function call content to be approved. + annotations: Optional list of annotations for the request. + additional_properties: Optional additional properties for the request. + raw_representation: Optional raw representation of the request. + **kwargs: Additional keyword arguments. + """ + super().__init__( + id=id, # type: ignore[reportCallIssue] + function_call=function_call, # type: ignore[reportCallIssue] + annotations=annotations, + additional_properties=additional_properties, + raw_representation=raw_representation, + **kwargs, + ) + + def create_response(self, approved: bool) -> "FunctionApprovalResponseContent": + """Create a response for the function approval request.""" + return FunctionApprovalResponseContent( + approved, + id=self.id, + function_call=self.function_call, + additional_properties=self.additional_properties, + ) + + +UserInputRequestContents = Annotated[ + FunctionApprovalRequestContent, + Field(discriminator="type"), +] + Contents = Annotated[ TextContent | DataContent @@ -1103,7 +1216,9 @@ Contents = Annotated[ | ErrorContent | UsageContent | HostedFileContent - | HostedVectorStoreContent, + | HostedVectorStoreContent + | FunctionApprovalRequestContent + | FunctionApprovalResponseContent, Field(discriminator="type"), ] @@ -1957,6 +2072,13 @@ class AgentRunResponse(AFBaseModel): """Get the concatenated text of all messages.""" return "".join(msg.text for msg in self.messages) if self.messages else "" + @property + def user_input_requests(self) -> list[UserInputRequestContents]: + """Get all BaseUserInputRequest messages from the response.""" + return [ + content for msg in self.messages for content in msg.contents if isinstance(content, BaseUserInputRequest) + ] + @classmethod def from_agent_run_response_updates( cls: type[TAgentRunResponse], updates: Sequence["AgentRunResponseUpdate"] @@ -2007,6 +2129,11 @@ class AgentRunResponseUpdate(AFBaseModel): else "" ) + @property + def user_input_requests(self) -> list[UserInputRequestContents]: + """Get all BaseUserInputRequest messages from the response.""" + return [content for content in self.contents if isinstance(content, BaseUserInputRequest)] + def __str__(self) -> str: return self.text @@ -2082,9 +2209,3 @@ class TextToSpeechOptions(AFBaseModel): for key in merged_exclude: settings.pop(key, None) return settings - - -# endregion - - -# endregion diff --git a/python/packages/main/agent_framework/exceptions.py b/python/packages/main/agent_framework/exceptions.py index 66a2c14033..242b83c995 100644 --- a/python/packages/main/agent_framework/exceptions.py +++ b/python/packages/main/agent_framework/exceptions.py @@ -1,7 +1,7 @@ # Copyright (c) Microsoft. All rights reserved. import logging -from typing import Any +from typing import Any, Literal logger = logging.getLogger("agent_framework") @@ -12,13 +12,23 @@ class AgentFrameworkException(Exception): Automatically logs the message as debug. """ - def __init__(self, message: str, inner_exception: Exception | None = None, *args: Any, **kwargs: Any): + def __init__( + self, + message: str, + inner_exception: Exception | None = None, + log_level: Literal[0] | Literal[10] | Literal[20] | Literal[30] | Literal[40] | Literal[50] | None = 10, + *args: Any, + **kwargs: Any, + ): """Create an AgentFrameworkException. - This emits a debug log, with the inner_exception if provided. + This emits a debug log (by default), with the inner_exception if provided. """ - logger.debug(message, exc_info=inner_exception) - super().__init__(message, *args, **kwargs) # type: ignore + if log_level is not None: + logger.log(log_level, message, exc_info=inner_exception) + if inner_exception: + super().__init__(message, inner_exception, *args) # type: ignore + super().__init__(message, *args) # type: ignore class AgentException(AgentFrameworkException): @@ -33,6 +43,24 @@ class AgentExecutionException(AgentException): pass +class AgentInitializationError(AgentException): + """An error occurred while initializing the agent.""" + + pass + + +class ChatClientException(AgentFrameworkException): + """An error occurred while dealing with a chat client.""" + + pass + + +class ChatClientInitializationError(ChatClientException): + """An error occurred while initializing the chat client.""" + + pass + + # region Service Exceptions @@ -94,3 +122,9 @@ class ToolExecutionException(ToolException): """An error occurred while executing a tool.""" pass + + +class AdditionItemMismatch(AgentFrameworkException): + """An error occurred while adding two types.""" + + pass diff --git a/python/packages/main/agent_framework/mem0/__init__.py b/python/packages/main/agent_framework/mem0/__init__.py new file mode 100644 index 0000000000..e2028a27e5 --- /dev/null +++ b/python/packages/main/agent_framework/mem0/__init__.py @@ -0,0 +1,24 @@ +# Copyright (c) Microsoft. All rights reserved. + +import importlib +from typing import Any + +PACKAGE_NAME = "agent_framework_mem0" +PACKAGE_EXTRA = "mem0" +_IMPORTS = ["__version__", "Mem0Provider"] + + +def __getattr__(name: str) -> Any: + if name in _IMPORTS: + try: + return getattr(importlib.import_module(PACKAGE_NAME), name) + except ModuleNotFoundError as exc: + raise ModuleNotFoundError( + f"The '{PACKAGE_EXTRA}' extra is not installed, " + f"please do `pip install agent-framework[{PACKAGE_EXTRA}]`" + ) from exc + raise AttributeError(f"Module {PACKAGE_NAME} has no attribute {name}.") + + +def __dir__() -> list[str]: + return _IMPORTS diff --git a/python/packages/main/agent_framework/mem0/__init__.pyi b/python/packages/main/agent_framework/mem0/__init__.pyi new file mode 100644 index 0000000000..53fb1720f2 --- /dev/null +++ b/python/packages/main/agent_framework/mem0/__init__.pyi @@ -0,0 +1,5 @@ +# Copyright (c) Microsoft. All rights reserved. + +from agent_framework_mem0 import Mem0Provider, __version__ + +__all__ = ["Mem0Provider", "__version__"] diff --git a/python/packages/main/agent_framework/openai/_assistants_client.py b/python/packages/main/agent_framework/openai/_assistants_client.py index da7a209112..ea81734481 100644 --- a/python/packages/main/agent_framework/openai/_assistants_client.py +++ b/python/packages/main/agent_framework/openai/_assistants_client.py @@ -20,8 +20,8 @@ from openai.types.beta.threads.run_submit_tool_outputs_params import ToolOutput from openai.types.beta.threads.runs import RunStep from pydantic import Field, PrivateAttr, SecretStr, ValidationError -from .._clients import BaseChatClient, use_tool_calling -from .._tools import AIFunction, HostedCodeInterpreterTool, HostedFileSearchTool +from .._clients import BaseChatClient +from .._tools import AIFunction, HostedCodeInterpreterTool, HostedFileSearchTool, use_function_invocation from .._types import ( ChatMessage, ChatOptions, @@ -50,8 +50,8 @@ else: __all__ = ["OpenAIAssistantsClient"] +@use_function_invocation @use_telemetry -@use_tool_calling class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient): """OpenAI Assistants client.""" @@ -166,7 +166,9 @@ class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient): # Get the thread ID thread_id: str | None = ( - chat_options.conversation_id if chat_options.conversation_id is not None else self.thread_id + chat_options.conversation_id + if chat_options.conversation_id is not None + else run_options.get("conversation_id", self.thread_id) ) if thread_id is None and tool_results is not None: diff --git a/python/packages/main/agent_framework/openai/_chat_client.py b/python/packages/main/agent_framework/openai/_chat_client.py index 754e17dbd9..aa98257804 100644 --- a/python/packages/main/agent_framework/openai/_chat_client.py +++ b/python/packages/main/agent_framework/openai/_chat_client.py @@ -1,6 +1,7 @@ # Copyright (c) Microsoft. All rights reserved. import json +import sys from collections.abc import AsyncIterable, Mapping, MutableMapping, MutableSequence, Sequence from datetime import datetime from itertools import chain @@ -15,9 +16,9 @@ from openai.types.chat.chat_completion_chunk import Choice as ChunkChoice from openai.types.chat.chat_completion_message_custom_tool_call import ChatCompletionMessageCustomToolCall from pydantic import BaseModel, SecretStr, ValidationError -from .._clients import BaseChatClient, use_tool_calling +from .._clients import BaseChatClient from .._logging import get_logger -from .._tools import AIFunction, HostedWebSearchTool, ToolProtocol +from .._tools import AIFunction, HostedWebSearchTool, ToolProtocol, use_function_invocation from .._types import ( ChatMessage, ChatOptions, @@ -41,14 +42,17 @@ from ..telemetry import use_telemetry from ._exceptions import OpenAIContentFilterException from ._shared import OpenAIBase, OpenAIConfigMixin, OpenAISettings, prepare_function_call_results +if sys.version_info >= (3, 12): + from typing import override # type: ignore # pragma: no cover +else: + from typing_extensions import override # type: ignore[import] # pragma: no cover + __all__ = ["OpenAIChatClient"] logger = get_logger("agent_framework.openai") # region Base Client -@use_telemetry -@use_tool_calling class OpenAIBaseChatClient(OpenAIBase, BaseChatClient): """OpenAI Chat completion class.""" @@ -233,11 +237,26 @@ class OpenAIBaseChatClient(OpenAIBase, BaseChatClient): ) def _usage_details_from_openai(self, usage: CompletionUsage) -> UsageDetails: - return UsageDetails( - prompt_tokens=usage.prompt_tokens, - completion_tokens=usage.completion_tokens, - total_tokens=usage.total_tokens, + details = UsageDetails( + input_token_count=usage.prompt_tokens, + output_token_count=usage.completion_tokens, + total_token_count=usage.total_tokens, ) + if usage.completion_tokens_details: + if tokens := usage.completion_tokens_details.accepted_prediction_tokens: + details["completion/accepted_prediction_tokens"] = tokens + if tokens := usage.completion_tokens_details.audio_tokens: + details["completion/audio_tokens"] = tokens + if tokens := usage.completion_tokens_details.reasoning_tokens: + details["completion/reasoning_tokens"] = tokens + if tokens := usage.completion_tokens_details.rejected_prediction_tokens: + details["completion/rejected_prediction_tokens"] = tokens + if usage.prompt_tokens_details: + if tokens := usage.prompt_tokens_details.audio_tokens: + details["prompt/audio_tokens"] = tokens + if tokens := usage.prompt_tokens_details.cached_tokens: + details["prompt/cached_tokens"] = tokens + return details def _parse_text_from_choice(self, choice: Choice | ChunkChoice) -> TextContent | None: """Parse the choice into a TextContent object.""" @@ -362,13 +381,14 @@ class OpenAIBaseChatClient(OpenAIBase, BaseChatClient): case _: return content.model_dump(exclude_none=True) - def service_url(self) -> str | None: + @override + def service_url(self) -> str: """Get the URL of the service. Override this in the subclass to return the proper URL. If the service does not have a URL, return None. """ - return str(self.client.base_url) if self.client else None + return str(self.client.base_url) if self.client else "Unknown" # region Public client @@ -376,6 +396,8 @@ class OpenAIBaseChatClient(OpenAIBase, BaseChatClient): TOpenAIChatClient = TypeVar("TOpenAIChatClient", bound="OpenAIChatClient") +@use_function_invocation +@use_telemetry class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient): """OpenAI Chat completion class.""" @@ -387,6 +409,7 @@ class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient): default_headers: Mapping[str, str] | None = None, async_client: AsyncOpenAI | None = None, instruction_role: str | None = None, + base_url: str | None = None, env_file_path: str | None = None, env_file_encoding: str | None = None, ) -> None: @@ -404,6 +427,7 @@ class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient): async_client: An existing client to use. (Optional) instruction_role: The role to use for 'instruction' messages, for example, "system" or "developer". If not provided, the default is "system". + base_url: The optional base URL to use. If provided will override the standard value for a OpenAI connector. env_file_path: Use the environment settings file as a fallback to environment variables. (Optional) env_file_encoding: The encoding of the environment settings file. (Optional) @@ -436,6 +460,7 @@ class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient): default_headers=default_headers, client=async_client, instruction_role=instruction_role, + base_url=base_url, ) @classmethod diff --git a/python/packages/main/agent_framework/openai/_responses_client.py b/python/packages/main/agent_framework/openai/_responses_client.py index 9abfc5772b..9bc646c5f5 100644 --- a/python/packages/main/agent_framework/openai/_responses_client.py +++ b/python/packages/main/agent_framework/openai/_responses_client.py @@ -13,27 +13,29 @@ from openai.types.responses.parsed_response import ( ParsedResponse, ) from openai.types.responses.response import Response as OpenAIResponse -from openai.types.responses.response_completed_event import ResponseCompletedEvent -from openai.types.responses.response_content_part_added_event import ResponseContentPartAddedEvent -from openai.types.responses.response_function_call_arguments_delta_event import ResponseFunctionCallArgumentsDeltaEvent -from openai.types.responses.response_output_item_added_event import ResponseOutputItemAddedEvent -from openai.types.responses.response_output_refusal import ResponseOutputRefusal -from openai.types.responses.response_output_text import ResponseOutputText from openai.types.responses.response_stream_event import ResponseStreamEvent as OpenAIResponseStreamEvent -from openai.types.responses.response_text_delta_event import ResponseTextDeltaEvent from openai.types.responses.response_usage import ResponseUsage from openai.types.responses.tool_param import ( CodeInterpreter, CodeInterpreterContainerCodeInterpreterToolAuto, + Mcp, ToolParam, ) from openai.types.responses.web_search_tool_param import UserLocation as WebSearchUserLocation from openai.types.responses.web_search_tool_param import WebSearchToolParam from pydantic import BaseModel, SecretStr, ValidationError -from .._clients import BaseChatClient, use_tool_calling +from .._clients import BaseChatClient from .._logging import get_logger -from .._tools import AIFunction, HostedCodeInterpreterTool, HostedFileSearchTool, HostedWebSearchTool, ToolProtocol +from .._tools import ( + AIFunction, + HostedCodeInterpreterTool, + HostedFileSearchTool, + HostedMCPTool, + HostedWebSearchTool, + ToolProtocol, + use_function_invocation, +) from .._types import ( ChatMessage, ChatOptions, @@ -42,6 +44,8 @@ from .._types import ( CitationAnnotation, Contents, DataContent, + FunctionApprovalRequestContent, + FunctionApprovalResponseContent, FunctionCallContent, FunctionResultContent, HostedFileContent, @@ -364,26 +368,52 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): # region Prep methods - def _chat_to_response_tool_spec( + def _tools_to_response_tools( self, tools: list[ToolProtocol | MutableMapping[str, Any]] ) -> list[ToolParam | dict[str, Any]]: response_tools: list[ToolParam | dict[str, Any]] = [] for tool in tools: if isinstance(tool, ToolProtocol): match tool: + case HostedMCPTool(): + mcp: Mcp = { + "type": "mcp", + "server_label": tool.name.replace(" ", "_"), + "server_url": str(tool.url), + "server_description": tool.description, + "headers": tool.headers, + } + if tool.allowed_tools: + mcp["allowed_tools"] = list(tool.allowed_tools) + if tool.approval_mode: + match tool.approval_mode: + case str(): + mcp["require_approval"] = ( + "always" if tool.approval_mode == "always_require" else "never" + ) + case _: + if always_require_approvals := tool.approval_mode.get("always_require_approval"): + mcp["require_approval"] = { + "always": {"tool_names": list(always_require_approvals)} + } + if never_require_approvals := tool.approval_mode.get("never_require_approval"): + mcp["require_approval"] = { + "never": {"tool_names": list(never_require_approvals)} + } + response_tools.append(mcp) case HostedCodeInterpreterTool(): - tool_args: dict[str, Any] = {"type": "auto"} + tool_args: CodeInterpreterContainerCodeInterpreterToolAuto = {"type": "auto"} if tool.inputs: tool_args["file_ids"] = [] for tool_input in tool.inputs: if isinstance(tool_input, HostedFileContent): - tool_args["file_ids"].append(tool_input.file_id) + tool_args["file_ids"].append(tool_input.file_id) # type: ignore[attr-defined] if not tool_args["file_ids"]: tool_args.pop("file_ids") response_tools.append( CodeInterpreter( type="code_interpreter", - container=CodeInterpreterContainerCodeInterpreterToolAuto(**tool_args), # type: ignore[typeddict-item] + container=tool_args, ) ) case AIFunction(): @@ -425,7 +455,7 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): ) response_tools.append( WebSearchToolParam( - type="web_search", + type="web_search_preview", user_location=WebSearchUserLocation( type="approximate", city=location.get("city", None), @@ -455,7 +485,7 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): if chat_options.tools is None: options_dict.pop("parallel_tool_calls", None) else: - options_dict["tools"] = self._chat_to_response_tool_spec(chat_options.tools) + options_dict["tools"] = self._tools_to_response_tools(chat_options.tools) # other settings if "store" not in options_dict: options_dict["store"] = False @@ -496,6 +526,137 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): # Flatten the list of lists into a single list return list(chain.from_iterable(list_of_list)) + def _openai_chat_message_parser( + self, + message: ChatMessage, + call_id_to_id: dict[str, str], + ) -> list[dict[str, Any]]: + """Parse a chat message into the openai format.""" + all_messages: list[dict[str, Any]] = [] + args: dict[str, Any] = { + "role": message.role.value if isinstance(message.role, Role) else message.role, + } + if message.additional_properties: + args["metadata"] = message.additional_properties + for content in message.contents: + match content: + case FunctionResultContent(): + new_args: dict[str, Any] = {} + new_args.update(self._openai_content_parser(message.role, content, call_id_to_id)) + all_messages.append(new_args) + case FunctionCallContent(): + function_call = self._openai_content_parser(message.role, content, call_id_to_id) + all_messages.append(function_call) # type: ignore + case FunctionApprovalResponseContent() | FunctionApprovalRequestContent(): + all_messages.append(self._openai_content_parser(message.role, content, call_id_to_id)) # type: ignore + case _: + if "content" not in args: + args["content"] = [] + args["content"].append(self._openai_content_parser(message.role, content, call_id_to_id)) # type: ignore + if "content" in args or "tool_calls" in args: + all_messages.append(args) + return all_messages + + def _openai_content_parser( + self, + role: Role, + content: Contents, + call_id_to_id: dict[str, str], + ) -> dict[str, Any]: + """Parse contents into the openai format.""" + match content: + case TextContent(): + return { + "type": "output_text" if role == Role.ASSISTANT else "input_text", + "text": content.text, + } + case TextReasoningContent(): + ret: dict[str, Any] = { + "type": "reasoning", + "summary": { + "type": "summary_text", + "text": content.text, + }, + } + if content.additional_properties is not None: + if status := content.additional_properties.get("status"): + ret["status"] = status + if reasoning_text := content.additional_properties.get("reasoning_text"): + ret["content"] = {"type": "reasoning_text", "text": reasoning_text} + if encrypted_content := content.additional_properties.get("encrypted_content"): + ret["encrypted_content"] = encrypted_content + return ret + case DataContent() | UriContent(): + if content.has_top_level_media_type("image"): + return { + "type": "input_image", + "image_url": content.uri, + "detail": content.additional_properties.get("detail", "auto") + if content.additional_properties + else "auto", + "file_id": content.additional_properties.get("file_id", None) + if content.additional_properties + else None, + } + if content.has_top_level_media_type("audio"): + if content.media_type and "wav" in content.media_type: + format = "wav" + elif content.media_type and "mp3" in content.media_type: + format = "mp3" + else: + logger.warning("Unsupported audio media type: %s", content.media_type) + return {} + return { + "type": "input_audio", + "input_audio": { + "data": content.uri, + "format": format, + }, + } + return {} + case FunctionCallContent(): + return { + "call_id": content.call_id, + "id": call_id_to_id[content.call_id], + "type": "function_call", + "name": content.name, + "arguments": content.arguments, + } + case FunctionResultContent(): + # call_id for the result needs to be the same as the call_id for the function call + args: dict[str, Any] = { + "call_id": content.call_id, + "id": call_id_to_id.get(content.call_id), + "type": "function_call_output", + } + if content.result: + args["output"] = prepare_function_call_results(content.result) + return args + case FunctionApprovalRequestContent(): + return { + "type": "mcp_approval_request", + "id": content.id, + "arguments": content.function_call.arguments, + "name": content.function_call.name, + "server_label": content.function_call.additional_properties.get("server_label") + if content.function_call.additional_properties + else None, + } + case FunctionApprovalResponseContent(): + return { + "type": "mcp_approval_response", + "approval_request_id": content.id, + "approve": content.approved, + } + case HostedFileContent(): + return { + "type": "input_file", + "file_id": content.file_id, + } + case _: # should catch UsageDetails and ErrorContent and HostedVectorStoreContent + logger.debug("Unsupported content type passed (type: %s)", type(content)) + return {} + # region Response creation methods def _create_response_content( @@ -533,7 +694,8 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): match message_content.type: case "output_text": text_content = TextContent( - text=message_content.text, raw_representation=message_content + text=message_content.text, + raw_representation=message_content, # type: ignore[reportUnknownArgumentType] ) metadata.update(self._get_metadata_from_response(message_content)) if message_content.annotations: @@ -639,6 +801,19 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): raw_representation=item, ) ) + case "mcp_approval_request": # ResponseOutputMcpApprovalRequest + contents.append( + FunctionApprovalRequestContent( + id=item.id, + function_call=FunctionCallContent( + call_id=item.id, + name=item.name, + arguments=item.arguments, + additional_properties={"server_label": item.server_label}, + raw_representation=item, + ), + ) + ) case "image_generation_call": # ResponseOutputImageGenerationCall if item.result: contents.append( @@ -649,7 +824,7 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): ) # TODO(peterychang): Add support for other content types case _: - logger.debug("Unparsed content of type: %s: %s", item.type, item) + logger.debug("Unparsed output of type: %s: %s", item.type, item) response_message = ChatMessage(role="assistant", contents=contents) args: dict[str, Any] = { "response_id": response.id, @@ -677,35 +852,151 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): ) -> ChatResponseUpdate: """Create a streaming chat message content object from a choice.""" metadata: dict[str, Any] = {} - items: list[Contents] = [] + contents: list[Contents] = [] conversation_id: str | None = None model = self.ai_model_id # TODO(peterychang): Add support for other content types - match event: - case ResponseContentPartAddedEvent(): - match event.part: - case ResponseOutputText(): - items.append(TextContent(text=event.part.text, raw_representation=event)) - metadata.update(self._get_metadata_from_response(event.part)) - case ResponseOutputRefusal(): - items.append(TextContent(text=event.part.refusal, raw_representation=event)) - case ResponseTextDeltaEvent(): - items.append(TextContent(text=event.delta, raw_representation=event)) + match event.type: + # types: + # ResponseAudioDeltaEvent, + # ResponseAudioDoneEvent, + # ResponseAudioTranscriptDeltaEvent, + # ResponseAudioTranscriptDoneEvent, + # ResponseCodeInterpreterCallCodeDeltaEvent, + # ResponseCodeInterpreterCallCodeDoneEvent, + # ResponseCodeInterpreterCallCompletedEvent, + # ResponseCodeInterpreterCallInProgressEvent, + # ResponseCodeInterpreterCallInterpretingEvent, + # ResponseCompletedEvent, + # ResponseContentPartAddedEvent, + # ResponseContentPartDoneEvent, + # ResponseCreatedEvent, + # ResponseErrorEvent, + # ResponseFileSearchCallCompletedEvent, + # ResponseFileSearchCallInProgressEvent, + # ResponseFileSearchCallSearchingEvent, + # ResponseFunctionCallArgumentsDeltaEvent, + # ResponseFunctionCallArgumentsDoneEvent, + # ResponseInProgressEvent, + # ResponseFailedEvent, + # ResponseIncompleteEvent, + # ResponseOutputItemAddedEvent, + # ResponseOutputItemDoneEvent, + # ResponseReasoningSummaryPartAddedEvent, + # ResponseReasoningSummaryPartDoneEvent, + # ResponseReasoningSummaryTextDeltaEvent, + # ResponseReasoningSummaryTextDoneEvent, + # ResponseReasoningTextDeltaEvent, + # ResponseReasoningTextDoneEvent, + # ResponseRefusalDeltaEvent, + # ResponseRefusalDoneEvent, + # ResponseTextDeltaEvent, + # ResponseTextDoneEvent, + # ResponseWebSearchCallCompletedEvent, + # ResponseWebSearchCallInProgressEvent, + # ResponseWebSearchCallSearchingEvent, + # ResponseImageGenCallCompletedEvent, + # ResponseImageGenCallGeneratingEvent, + # ResponseImageGenCallInProgressEvent, + # ResponseImageGenCallPartialImageEvent, + # ResponseMcpCallArgumentsDeltaEvent, + # ResponseMcpCallArgumentsDoneEvent, + # ResponseMcpCallCompletedEvent, + # ResponseMcpCallFailedEvent, + # ResponseMcpCallInProgressEvent, + # ResponseMcpListToolsCompletedEvent, + # ResponseMcpListToolsFailedEvent, + # ResponseMcpListToolsInProgressEvent, + # ResponseOutputTextAnnotationAddedEvent, + # ResponseQueuedEvent, + # ResponseCustomToolCallInputDeltaEvent, + # ResponseCustomToolCallInputDoneEvent, + case "response.content_part.added": + event_part = event.part + match event_part.type: + case "output_text": + contents.append(TextContent(text=event_part.text, raw_representation=event)) + metadata.update(self._get_metadata_from_response(event_part)) + case "refusal": + contents.append(TextContent(text=event_part.refusal, raw_representation=event)) + case "response.output_text.delta": + contents.append(TextContent(text=event.delta, raw_representation=event)) metadata.update(self._get_metadata_from_response(event)) - case ResponseCompletedEvent(): + case "response.completed": conversation_id = event.response.id if chat_options.store is True else None model = event.response.model if event.response.usage: usage = self._usage_details_from_openai(event.response.usage) if usage: - items.append(UsageContent(details=usage, raw_representation=event)) - case ResponseOutputItemAddedEvent(): - if event.item.type == "function_call": - function_call_ids[event.output_index] = (event.item.call_id, event.item.name) - case ResponseFunctionCallArgumentsDeltaEvent(): + contents.append(UsageContent(details=usage, raw_representation=event)) + case "response.output_item.added": + event_item = event.item + match event_item.type: + # types: + # ResponseOutputMessage, + # ResponseFileSearchToolCall, + # ResponseFunctionToolCall, + # ResponseFunctionWebSearch, + # ResponseComputerToolCall, + # ResponseReasoningItem, + # ImageGenerationCall, + # ResponseCodeInterpreterToolCall, + # LocalShellCall, + # McpCall, + # McpListTools, + # McpApprovalRequest, + # ResponseCustomToolCall, + case "function_call": + function_call_ids[event.output_index] = (event_item.call_id, event_item.name) + case "mcp_approval_request": + contents.append( + FunctionApprovalRequestContent( + id=event_item.id, + function_call=FunctionCallContent( + call_id=event_item.id, + name=event_item.name, + arguments=event_item.arguments, + additional_properties={"server_label": event_item.server_label}, + raw_representation=event_item, + ), + ) + ) + case "code_interpreter_call": # ResponseOutputCodeInterpreterCall + if event_item.outputs: + for code_output in event_item.outputs: + if code_output.type == "logs": + contents.append(TextContent(text=code_output.logs, raw_representation=event_item)) + if code_output.type == "image": + contents.append( + UriContent( + uri=code_output.url, + raw_representation=event_item, + # no more specific media type then this can be inferred + media_type="image", + ) + ) + elif event_item.code: + # fallback if no output was returned is the code: + contents.append(TextContent(text=event_item.code, raw_representation=event_item)) + case "reasoning": # ResponseOutputReasoning + if event_item.content: + for index, reasoning_content in enumerate(event_item.content): + additional_properties = None + if event_item.summary and index < len(event_item.summary): + additional_properties = {"summary": event_item.summary[index]} + contents.append( + TextReasoningContent( + text=reasoning_content.text, + raw_representation=reasoning_content, + additional_properties=additional_properties, + ) + ) + case _: + logger.debug("Unparsed event of type: %s: %s", event.type, event) + case "response.function_call_arguments.delta": call_id, name = function_call_ids.get(event.output_index, (None, None)) if call_id and name: - items.append( + contents.append( FunctionCallContent( call_id=call_id, name=name, @@ -715,10 +1006,10 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): ) ) case _: - logger.debug("Unparsed event: %s", event) + logger.debug("Unparsed event of type: %s: %s", event.type, event) return ChatResponseUpdate( - contents=items, + contents=contents, conversation_id=conversation_id, role=Role.ASSISTANT, ai_model_id=model, @@ -738,69 +1029,6 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): details["openai.reasoning_tokens"] = usage.output_tokens_details.reasoning_tokens return details - def _openai_chat_message_parser( - self, - message: ChatMessage, - call_id_to_id: dict[str, str], - ) -> list[dict[str, Any]]: - """Parse a chat message into the openai format.""" - all_messages: list[dict[str, Any]] = [] - args: dict[str, Any] = { - "role": message.role.value if isinstance(message.role, Role) else message.role, - } - if message.additional_properties: - args["metadata"] = message.additional_properties - for content in message.contents: - match content: - case FunctionResultContent(): - new_args: dict[str, Any] = {} - new_args.update(self._openai_content_parser(message.role, content, call_id_to_id)) - all_messages.append(new_args) - case FunctionCallContent(): - function_call = self._openai_content_parser(message.role, content, call_id_to_id) - all_messages.append(function_call) # type: ignore - case _: - if "content" not in args: - args["content"] = [] - args["content"].append(self._openai_content_parser(message.role, content, call_id_to_id)) # type: ignore - if "content" in args or "tool_calls" in args: - all_messages.append(args) - return all_messages - - def _openai_content_parser( - self, - role: Role, - content: Contents, - call_id_to_id: dict[str, str], - ) -> dict[str, Any]: - """Parse contents into the openai format.""" - match content: - case FunctionCallContent(): - return { - "call_id": content.call_id, - "id": call_id_to_id[content.call_id], - "type": "function_call", - "name": content.name, - "arguments": content.arguments, - } - case FunctionResultContent(): - # call_id for the result needs to be the same as the call_id for the function call - args: dict[str, Any] = { - "call_id": content.call_id, - "type": "function_call_output", - } - if content.result: - args["output"] = prepare_function_call_results(content.result) - return args - case TextContent(): - return { - "type": "output_text" if role == Role.ASSISTANT else "input_text", - "text": content.text, - } - # TODO(peterychang): We'll probably need to specialize the other content types as well - case _: - return content.model_dump(exclude_none=True) - def _get_metadata_from_response(self, output: Any) -> dict[str, Any]: """Get metadata from a chat choice.""" if logprobs := getattr(output, "logprobs", None): @@ -813,8 +1041,8 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient): TOpenAIResponsesClient = TypeVar("TOpenAIResponsesClient", bound="OpenAIResponsesClient") +@use_function_invocation @use_telemetry -@use_tool_calling class OpenAIResponsesClient(OpenAIConfigMixin, OpenAIBaseResponsesClient): """OpenAI Responses client class.""" diff --git a/python/packages/main/agent_framework/openai/_shared.py b/python/packages/main/agent_framework/openai/_shared.py index 1e7c29ec8d..de8ada2ca4 100644 --- a/python/packages/main/agent_framework/openai/_shared.py +++ b/python/packages/main/agent_framework/openai/_shared.py @@ -60,7 +60,7 @@ def prepare_function_call_results(content: Contents | Any | list[Contents | Any] results.extend(res) else: results.append(res) - return results[0] if len(results) == 1 else results + return results[0] if len(results) == 1 else json.dumps(results) if isinstance(content, BaseModel): return content.model_dump_json(exclude_none=True, exclude={"raw_representation", "additional_properties"}) # fallback @@ -127,7 +127,7 @@ class OpenAIBase(AFBaseModel): class OpenAIConfigMixin(OpenAIBase): """Internal class for configuring a connection to an OpenAI service.""" - MODEL_PROVIDER_NAME: ClassVar[str] = "openai" # type: ignore[reportIncompatibleVariableOverride, misc] + OTEL_PROVIDER_NAME: ClassVar[str] = "openai" # type: ignore[reportIncompatibleVariableOverride, misc] @validate_call(config=ConfigDict(arbitrary_types_allowed=True)) def __init__( @@ -138,6 +138,7 @@ class OpenAIConfigMixin(OpenAIBase): default_headers: Mapping[str, str] | None = None, client: AsyncOpenAI | None = None, instruction_role: str | None = None, + base_url: str | None = None, **kwargs: Any, ) -> None: """Initialize a client for OpenAI services. @@ -146,17 +147,19 @@ class OpenAIConfigMixin(OpenAIBase): different types of AI model interactions, like chat or text completion. Args: - ai_model_id (str): OpenAI model identifier. Must be non-empty. + ai_model_id: OpenAI model identifier. Must be non-empty. Default to a preset value. - api_key (str): OpenAI API key for authentication. + api_key: OpenAI API key for authentication. Must be non-empty. (Optional) - org_id (str): OpenAI organization ID. This is optional + org_id: OpenAI organization ID. This is optional unless the account belongs to multiple organizations. - default_headers (Mapping[str, str]): Default headers + default_headers: Default headers for HTTP requests. (Optional) - client (AsyncOpenAI): An existing OpenAI client, optional. - instruction_role (str): The role to use for 'instruction' + client: An existing OpenAI client, optional. + instruction_role: The role to use for 'instruction' messages, for example, summarization prompts could use `developer` or `system`. (Optional) + base_url: The optional base URL to use. If provided will override the standard value for a OpenAI connector. + Will not be used when supplying a custom client. kwargs: Additional keyword arguments. """ @@ -169,11 +172,12 @@ class OpenAIConfigMixin(OpenAIBase): if not client: if not api_key: raise ServiceInitializationError("Please provide an api_key") - client = AsyncOpenAI( - api_key=api_key, - organization=org_id, - default_headers=merged_headers, - ) + args: dict[str, Any] = {"api_key": api_key, "default_headers": merged_headers} + if org_id: + args["organization"] = org_id + if base_url: + args["base_url"] = base_url + client = AsyncOpenAI(**args) args = { "ai_model_id": ai_model_id, "client": client, diff --git a/python/packages/main/agent_framework/telemetry.py b/python/packages/main/agent_framework/telemetry.py index dd909837a2..604bed1388 100644 --- a/python/packages/main/agent_framework/telemetry.py +++ b/python/packages/main/agent_framework/telemetry.py @@ -1,51 +1,148 @@ # Copyright (c) Microsoft. All rights reserved. -import functools import json import logging import os -from collections.abc import AsyncIterable, Awaitable, Callable, MutableSequence +from collections.abc import AsyncIterable, Awaitable, Callable, Generator +from contextlib import contextmanager from enum import Enum +from functools import wraps +from time import perf_counter, time_ns from typing import TYPE_CHECKING, Any, ClassVar, Final, TypeVar -from opentelemetry import trace +from opentelemetry import metrics +from opentelemetry.semconv_ai import GenAISystem, Meters, SpanAttributes from opentelemetry.trace import Span, StatusCode, get_tracer, use_span +from opentelemetry.version import __version__ as otel_version +from pydantic import PrivateAttr from . import __version__ as version_info from ._logging import get_logger from ._pydantic import AFBaseSettings +from .exceptions import AgentInitializationError, ChatClientInitializationError if TYPE_CHECKING: # pragma: no cover + from opentelemetry.metrics import Histogram + from opentelemetry.sdk.resources import Resource from opentelemetry.util._decorator import _AgnosticContextManager # type: ignore[reportPrivateUsage] - from ._agents import AgentProtocol, ChatAgent - from ._clients import BaseChatClient + from ._agents import AgentProtocol + from ._clients import ChatClientProtocol from ._threads import AgentThread from ._tools import AIFunction from ._types import ( AgentRunResponse, AgentRunResponseUpdate, ChatMessage, - ChatOptions, ChatResponse, ChatResponseUpdate, + Contents, + FinishReason, ) -TBaseChatClient = TypeVar("TBaseChatClient", bound="BaseChatClient") -TChatClientAgent = TypeVar("TChatClientAgent", bound="ChatAgent") +TAgent = TypeVar("TAgent", bound="AgentProtocol") +TChatClient = TypeVar("TChatClient", bound="ChatClientProtocol") -tracer = get_tracer("agent_framework") logger = get_logger() __all__ = [ "AGENT_FRAMEWORK_USER_AGENT", "APP_INFO", + "OPEN_TELEMETRY_AGENT_MARKER", + "OPEN_TELEMETRY_CHAT_CLIENT_MARKER", + "OTEL_SETTINGS", "USER_AGENT_KEY", "prepend_agent_framework_to_user_agent", + "setup_telemetry", "use_agent_telemetry", "use_telemetry", ] +# region User Agents +# Note that if this environment variable does not exist, user agent telemetry is enabled. +USER_AGENT_TELEMETRY_DISABLED_ENV_VAR = "AGENT_FRAMEWORK_USER_AGENT_DISABLED" +IS_TELEMETRY_ENABLED = os.environ.get(USER_AGENT_TELEMETRY_DISABLED_ENV_VAR, "false").lower() not in ["true", "1"] + +APP_INFO = ( + { + "agent-framework-version": f"python/{version_info}", # type: ignore[has-type] + } + if IS_TELEMETRY_ENABLED + else None +) +USER_AGENT_KEY: Final[str] = "User-Agent" +HTTP_USER_AGENT: Final[str] = "agent-framework-python" +AGENT_FRAMEWORK_USER_AGENT = f"{HTTP_USER_AGENT}/{version_info}" # type: ignore[has-type] + + +def prepend_agent_framework_to_user_agent(headers: dict[str, Any] | None = None) -> dict[str, Any]: + """Prepend "agent-framework" to the User-Agent in the headers. + + When user agent telemetry is disabled, through the AZURE_TELEMETRY_DISABLED environment variable, + the User-Agent header will not include the agent-framework information, it will be sent back as is, + or as a empty dict when None is passed. + + Args: + headers: The existing headers dictionary. + + Returns: + A new dict with "User-Agent" set to "agent-framework-python/{version}" if headers is None. + The modified headers dictionary with "agent-framework-python/{version}" prepended to the User-Agent. + """ + if not IS_TELEMETRY_ENABLED: + return headers or {} + if not headers: + return {USER_AGENT_KEY: AGENT_FRAMEWORK_USER_AGENT} + headers[USER_AGENT_KEY] = ( + f"{AGENT_FRAMEWORK_USER_AGENT} {headers[USER_AGENT_KEY]}" + if USER_AGENT_KEY in headers + else AGENT_FRAMEWORK_USER_AGENT + ) + + return headers + + +# region Otel + +tracer = get_tracer("agent_framework", otel_version) +meter = metrics.get_meter_provider().get_meter("agent_framework", otel_version) + +OTEL_METRICS: Final[str] = "__otel_metrics__" +OPEN_TELEMETRY_CHAT_CLIENT_MARKER: Final[str] = "__open_telemetry_chat_client__" +OPEN_TELEMETRY_AGENT_MARKER: Final[str] = "__open_telemetry_agent__" +TOKEN_USAGE_BUCKET_BOUNDARIES: Final[tuple[float, ...]] = ( + 1, + 4, + 16, + 64, + 256, + 1024, + 4096, + 16384, + 65536, + 262144, + 1048576, + 4194304, + 16777216, + 67108864, +) +OPERATION_DURATION_BUCKET_BOUNDARIES: Final[tuple[float, ...]] = ( + 0.01, + 0.02, + 0.04, + 0.08, + 0.16, + 0.32, + 0.64, + 1.28, + 2.56, + 5.12, + 10.24, + 20.48, + 40.96, + 81.92, +) + # We're recording multiple events for the chat history, some of them are emitted within (hundreds of) # nanoseconds of each other. The default timestamp resolution is not high enough to guarantee unique @@ -60,7 +157,7 @@ __all__ = [ class ChatMessageListTimestampFilter(logging.Filter): """A filter to increment the timestamp of INFO logs by 1 microsecond.""" - INDEX_KEY: ClassVar[str] = "CHAT_MESSAGE_INDEX" + INDEX_KEY: ClassVar[str] = "chat_message_index" def filter(self, record: logging.LogRecord) -> bool: """Increment the timestamp of INFO logs by 1 microsecond.""" @@ -70,42 +167,34 @@ class ChatMessageListTimestampFilter(logging.Filter): return True -# Creates a tracer from the global tracer provider logger.addFilter(ChatMessageListTimestampFilter()) -class GenAIAttributes(str, Enum): +class OtelAttr(str, Enum): """Enum to capture the attributes used in OpenTelemetry for Generative AI. Based on: https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/ and https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-agent-spans/ - - Should always be used, with `.value` to get the string representation. """ OPERATION = "gen_ai.operation.name" - SYSTEM = "gen_ai.system" + PROVIDER_NAME = "gen_ai.provider.name" ERROR_TYPE = "error.type" PORT = "server.port" ADDRESS = "server.address" SPAN_ID = "SpanId" TRACE_ID = "TraceId" # Request attributes - MODEL = "gen_ai.request.model" SEED = "gen_ai.request.seed" ENCODING_FORMATS = "gen_ai.request.encoding_formats" FREQUENCY_PENALTY = "gen_ai.request.frequency_penalty" - MAX_TOKENS = "gen_ai.request.max_tokens" PRESENCE_PENALTY = "gen_ai.request.presence_penalty" STOP_SEQUENCES = "gen_ai.request.stop_sequences" - TEMPERATURE = "gen_ai.request.temperature" TOP_K = "gen_ai.request.top_k" - TOP_P = "gen_ai.request.top_p" CHOICE_COUNT = "gen_ai.request.choice.count" # Response attributes FINISH_REASONS = "gen_ai.response.finish_reasons" RESPONSE_ID = "gen_ai.response.id" - RESPONSE_MODEL = "gen_ai.response.model" # Usage attributes INPUT_TOKENS = "gen_ai.usage.input_tokens" OUTPUT_TOKENS = "gen_ai.usage.output_tokens" @@ -113,13 +202,26 @@ class GenAIAttributes(str, Enum): TOOL_CALL_ID = "gen_ai.tool.call.id" TOOL_DESCRIPTION = "gen_ai.tool.description" TOOL_NAME = "gen_ai.tool.name" + TOOL_TYPE = "gen_ai.tool.type" + # Agent attributes AGENT_ID = "gen_ai.agent.id" + # Client attributes + # replaced TOKEN with T, because both ruff and bandit, + # complain about TOKEN being a potential secret + T_UNIT = "tokens" + T_TYPE = "gen_ai.token.type" + T_TYPE_INPUT = "input" + T_TYPE_OUTPUT = "output" + DURATION_UNIT = "s" # Agent attributes AGENT_NAME = "gen_ai.agent.name" AGENT_DESCRIPTION = "gen_ai.agent.description" CONVERSATION_ID = "gen_ai.conversation.id" DATA_SOURCE_ID = "gen_ai.data_source.id" OUTPUT_TYPE = "gen_ai.output.type" + INPUT_MESSAGES = "gen_ai.input.messages" + OUTPUT_MESSAGES = "gen_ai.output.messages" + SYSTEM_INSTRUCTIONS = "gen_ai.system_instructions" # Activity events EVENT_NAME = "event.name" @@ -128,7 +230,6 @@ class GenAIAttributes(str, Enum): ASSISTANT_MESSAGE = "gen_ai.assistant.message" TOOL_MESSAGE = "gen_ai.tool.message" CHOICE = "gen_ai.choice" - PROMPT = "gen_ai.prompt" # Operation names CHAT_COMPLETION_OPERATION = "chat" @@ -142,52 +243,119 @@ class GenAIAttributes(str, Enum): MEASUREMENT_FUNCTION_INVOCATION_DURATION = "agent_framework.function.invocation.duration" AGENT_FRAMEWORK_GEN_AI_SYSTEM = "microsoft.agent_framework" + def __repr__(self) -> str: + return self.value + + def __str__(self) -> str: + return self.value + ROLE_EVENT_MAP = { - "system": GenAIAttributes.SYSTEM_MESSAGE.value, - "user": GenAIAttributes.USER_MESSAGE.value, - "assistant": GenAIAttributes.ASSISTANT_MESSAGE.value, - "tool": GenAIAttributes.TOOL_MESSAGE.value, + "system": OtelAttr.SYSTEM_MESSAGE, + "user": OtelAttr.USER_MESSAGE, + "assistant": OtelAttr.ASSISTANT_MESSAGE, + "tool": OtelAttr.TOOL_MESSAGE, +} +FINISH_REASON_MAP = { + "stop": "stop", + "content_filter": "content_filter", + "tool_calls": "tool_call", + "length": "length", } -# Note that if this environment variable does not exist, telemetry is enabled. -TELEMETRY_DISABLED_ENV_VAR = "AZURE_TELEMETRY_DISABLED" -IS_TELEMETRY_ENABLED = os.environ.get(TELEMETRY_DISABLED_ENV_VAR, "false").lower() not in ["true", "1"] - -APP_INFO = ( - { - "agent-framework-version": f"python/{version_info}", # type: ignore[has-type] - } - if IS_TELEMETRY_ENABLED - else None -) -USER_AGENT_KEY: Final[str] = "User-Agent" -HTTP_USER_AGENT: Final[str] = "agent-framework-python" -AGENT_FRAMEWORK_USER_AGENT = f"{HTTP_USER_AGENT}/{version_info}" # type: ignore[has-type] - - -def prepend_agent_framework_to_user_agent(headers: dict[str, Any]) -> dict[str, Any]: - """Prepend "agent-framework" to the User-Agent in the headers. - - Args: - headers: The existing headers dictionary. - - Returns: - The modified headers dictionary with "agent-framework-python/{version}" prepended to the User-Agent. - """ - headers[USER_AGENT_KEY] = ( - f"{AGENT_FRAMEWORK_USER_AGENT} {headers[USER_AGENT_KEY]}" - if USER_AGENT_KEY in headers - else AGENT_FRAMEWORK_USER_AGENT - ) - - return headers # region Telemetry utils -class ModelDiagnosticSettings(AFBaseSettings): - """Settings for model diagnostics. +def _get_exporters(endpoint: str | None = None, connection_string: str | None = None) -> dict[str, list[Any]]: + """Create the different exporters based on the connection string and endpoint.""" + from azure.monitor.opentelemetry.exporter import ( # pylint: disable=import-error,no-name-in-module + AzureMonitorLogExporter, + AzureMonitorMetricExporter, + AzureMonitorTraceExporter, + ) + from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter + from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter + from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter + + exporters: dict[str, Any] = {} + exporters.setdefault("log", []) + exporters.setdefault("trace", []) + exporters.setdefault("metric", []) + if endpoint: + exporters["log"].append(OTLPLogExporter(endpoint=endpoint)) + exporters["trace"].append(OTLPSpanExporter(endpoint=endpoint)) + exporters["metric"].append(OTLPMetricExporter(endpoint=endpoint)) + if connection_string: + exporters["log"].append(AzureMonitorLogExporter(connection_string=connection_string)) + exporters["trace"].append(AzureMonitorTraceExporter(connection_string=connection_string)) + exporters["metric"].append(AzureMonitorMetricExporter(connection_string=connection_string)) + return exporters + + +def _configure_tracing(exporters: dict[str, list[Any]], resource: "Resource") -> None: + from opentelemetry._events import set_event_logger_provider + from opentelemetry._logs import set_logger_provider + from opentelemetry.metrics import set_meter_provider + from opentelemetry.sdk._events import EventLoggerProvider + from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler + from opentelemetry.sdk._logs.export import BatchLogRecordProcessor + from opentelemetry.sdk.metrics import MeterProvider + from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader + from opentelemetry.sdk.metrics.view import DropAggregation, View + from opentelemetry.sdk.trace import TracerProvider + from opentelemetry.sdk.trace.export import BatchSpanProcessor + from opentelemetry.trace import set_tracer_provider + + # Tracing + tracer_provider = TracerProvider(resource=resource) + for exporter in exporters.get("trace", []): + tracer_provider.add_span_processor(BatchSpanProcessor(exporter)) + set_tracer_provider(tracer_provider) + + # Logging + logger_provider = LoggerProvider(resource=resource) + for exporter in exporters.get("log", []): + logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter)) + set_logger_provider(logger_provider) + logger = get_logger() + if not any(isinstance(handler, LoggingHandler) for handler in logger.handlers): + handler = LoggingHandler(logger_provider=logger_provider) + logger.addHandler(handler) + logger.setLevel(logging.NOTSET) + + # Events + event_logger_provider = EventLoggerProvider(logger_provider) + set_event_logger_provider(event_logger_provider) + + # metrics + + metric_readers = [ + PeriodicExportingMetricReader(exporter, export_interval_millis=5000) for exporter in exporters.get("metric", []) + ] + meter_provider = MeterProvider( + metric_readers=metric_readers, + resource=resource, + views=[ + # Dropping all instrument names except for those starting with "agent_framework" + View(instrument_name="*", aggregation=DropAggregation()), + View(instrument_name="agent_framework*"), + View(instrument_name="gen_ai*"), + ], + ) + # Sets the global default meter provider + set_meter_provider(meter_provider) + + +OTEL_ENABLED_ENV_VAR = "ENABLE_OTEL" +SENSITIVE_DATA_ENV_VAR = "ENABLE_SENSITIVE_DATA" +MONITOR_CONNECTION_STRING_ENV_VAR = "MONITOR_CONNECTION_STRING" +MONITOR_LIVE_METRICS_ENV_VAR = "MONITOR_LIVE_METRICS" +OTLP_ENDPOINT_ENV_VAR = "OTLP_ENDPOINT" + + +class OtelSettings(AFBaseSettings): + """Settings for Open Telemetry. The settings are first loaded from environment variables with the prefix 'AGENT_FRAMEWORK_GENAI_'. @@ -200,17 +368,27 @@ class ModelDiagnosticSettings(AFBaseSettings): Warning: Sensitive events should only be enabled on test and development environments. - Required settings for prefix 'AGENT_FRAMEWORK_GENAI_' are: - - enable_otel_diagnostics: bool - Enable OpenTelemetry diagnostics. Default is False. - (Env var AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS) - - enable_otel_diagnostics_sensitive: bool - Enable OpenTelemetry sensitive events. Default is False. - (Env var AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE) + Args: + enable_otel: Enable OpenTelemetry diagnostics. Default is False. + (Env var ENABLE_OTEL) + enable_sensitive_data: Enable OpenTelemetry sensitive events. Default is False. + (Env var ENABLE_SENSITIVE_DATA) + application_insights_connection_string: The Azure Monitor connection string. Default is None. + (Env var APPLICATION_INSIGHTS_CONNECTION_STRING) + application_insights_live_metrics: Enable Azure Monitor live metrics. Default is False. + (Env var APPLICATION_INSIGHTS_LIVE_METRICS) + otlp_endpoint: The OpenTelemetry Protocol (OTLP) endpoint. Default is None. + (Env var OTLP_ENDPOINT) """ - env_prefix: ClassVar[str] = "AGENT_FRAMEWORK_GENAI_" + env_prefix: ClassVar[str] = "" - enable_otel_diagnostics: bool = False - enable_otel_diagnostics_sensitive: bool = False + enable_otel: bool = False + enable_sensitive_data: bool = False + application_insights_connection_string: str | None = None + application_insights_live_metrics: bool = False + otlp_endpoint: str | None = None + _executed_setup: bool = PrivateAttr(default=False) @property def ENABLED(self) -> bool: @@ -218,292 +396,336 @@ class ModelDiagnosticSettings(AFBaseSettings): Model diagnostics are enabled if either diagnostic is enabled or diagnostic with sensitive events is enabled. """ - return self.enable_otel_diagnostics or self.enable_otel_diagnostics_sensitive + return self.enable_otel or self.enable_sensitive_data @property - def SENSITIVE_EVENTS_ENABLED(self) -> bool: + def SENSITIVE_DATA_ENABLED(self) -> bool: """Check if sensitive events are enabled. Sensitive events are enabled if the diagnostic with sensitive events is enabled. """ - return self.enable_otel_diagnostics_sensitive + return self.enable_sensitive_data + + @property + def is_setup(self) -> bool: + """Check if the setup has been executed.""" + return self._executed_setup + + def setup_telemetry(self) -> None: + """Setup telemetry based on the settings. + + If both connection_string and otlp_endpoint both will be used. + """ + if not self.ENABLED or self._executed_setup: + return + + if not self.application_insights_connection_string and not self.otlp_endpoint: + logger.warning("Telemetry is enabled but no connection string or OTLP endpoint is provided.") + return + if self.application_insights_connection_string and self.otlp_endpoint: + logger.warning("Both connection string and OTLP endpoint are provided. Azure Monitor will be used.") + + from opentelemetry.sdk.resources import Resource + from opentelemetry.semconv.attributes import service_attributes + + resource = Resource.create({service_attributes.SERVICE_NAME: "agent_framework"}) + global_logger = logging.getLogger() + global_logger.setLevel(logging.NOTSET) + if self.application_insights_connection_string: + from azure.monitor.opentelemetry import configure_azure_monitor + + configure_azure_monitor( + connection_string=self.application_insights_connection_string, + logger_name="agent_framework", + resource=resource, + enable_live_metrics=self.application_insights_live_metrics, + ) + if self.otlp_endpoint: + exporters = _get_exporters(endpoint=self.otlp_endpoint) + _configure_tracing(exporters, resource) + + self._executed_setup = True -MODEL_DIAGNOSTICS_SETTINGS = ModelDiagnosticSettings() +global OTEL_SETTINGS +OTEL_SETTINGS: OtelSettings = OtelSettings() -def start_as_current_span( - tracer: trace.Tracer, - function: "AIFunction[Any, Any]", - metadata: dict[str, Any] | None = None, -) -> "_AgnosticContextManager[Span]": - """Starts a span for the given function using the provided tracer. +def setup_telemetry( + enable_otel: bool | None = None, + enable_sensitive_data: bool | None = None, + otlp_endpoint: str | None = None, + application_insights_connection_string: str | None = None, + enable_live_metrics: bool | None = None, +) -> None: + """Setup telemetry with optionally provided settings. + + All of these values can be set through environment variables or you can pass them here, + in the case where both are present, the provided value takes precedence. + + If you have both connection_string and otlp_endpoint, the connection_string will be used. Args: - tracer: The OpenTelemetry tracer to use. - function: The function for which to start the span. - metadata: Optional metadata to include in the span attributes. + enable_otel: Enable OpenTelemetry diagnostics. Default is False. + enable_sensitive_data: Enable OpenTelemetry sensitive events. Default is False. + otlp_endpoint: The OpenTelemetry Protocol (OTLP) endpoint. Default is None. + application_insights_connection_string: The Azure Monitor connection string. Default is None. + enable_live_metrics: Enable Azure Monitor live metrics. Default is False. - Returns: - trace.Span: The started span as a context manager. """ - attributes = { - GenAIAttributes.OPERATION.value: GenAIAttributes.TOOL_EXECUTION_OPERATION.value, - GenAIAttributes.TOOL_NAME.value: function.name, - } + global OTEL_SETTINGS + if enable_otel is not None: + OTEL_SETTINGS.enable_otel = enable_otel + if enable_sensitive_data is not None: + OTEL_SETTINGS.enable_sensitive_data = enable_sensitive_data + if otlp_endpoint is not None: + OTEL_SETTINGS.otlp_endpoint = otlp_endpoint + if application_insights_connection_string is not None: + OTEL_SETTINGS.application_insights_connection_string = application_insights_connection_string + if enable_live_metrics is not None: + OTEL_SETTINGS.application_insights_live_metrics = enable_live_metrics + OTEL_SETTINGS.setup_telemetry() - tool_call_id = metadata.get("tool_call_id", None) if metadata else None - if tool_call_id: - attributes[GenAIAttributes.TOOL_CALL_ID.value] = tool_call_id - if function.description: - attributes[GenAIAttributes.TOOL_DESCRIPTION.value] = function.description - return tracer.start_as_current_span( - f"{GenAIAttributes.TOOL_EXECUTION_OPERATION.value} {function.name}", attributes=attributes +# region Chat Client Telemetry + + +def _get_duration_histogram() -> "Histogram": + return meter.create_histogram( + name=Meters.LLM_OPERATION_DURATION, + unit=OtelAttr.DURATION_UNIT, + description="Captures the duration of operations of function-invoking chat clients", + explicit_bucket_boundaries_advisory=OPERATION_DURATION_BUCKET_BOUNDARIES, ) -def _set_error(span: Span, error: Exception) -> None: - """Set an error for spans.""" - span.set_attribute(GenAIAttributes.ERROR_TYPE.value, str(type(error))) - span.set_status(StatusCode.ERROR, repr(error)) +def _get_token_usage_histogram() -> "Histogram": + return meter.create_histogram( + name=Meters.LLM_TOKEN_USAGE, + unit=OtelAttr.T_UNIT, + description="Captures the token usage of chat clients", + explicit_bucket_boundaries_advisory=TOKEN_USAGE_BUCKET_BOUNDARIES, + ) # region ChatClientProtocol -def _trace_chat_get_response( - completion_func: Callable[..., Awaitable["ChatResponse"]], +def _trace_get_response( + func: Callable[..., Awaitable["ChatResponse"]], + *, + provider_name: str = "unknown", ) -> Callable[..., Awaitable["ChatResponse"]]: """Decorator to trace chat completion activities. Args: - completion_func: The function to trace. + func: The function to trace. + provider_name: The model provider name. """ - @functools.wraps(completion_func) - async def wrap_inner_get_response( - self: "BaseChatClient", - *, - messages: MutableSequence["ChatMessage"], - chat_options: "ChatOptions", - **kwargs: Any, - ) -> "ChatResponse": - if not MODEL_DIAGNOSTICS_SETTINGS.ENABLED: - # If model diagnostics are not enabled, just return the completion - return await completion_func( - self, - messages=messages, - chat_options=chat_options, + def decorator(func: Callable[..., Awaitable["ChatResponse"]]) -> Callable[..., Awaitable["ChatResponse"]]: + """Inner decorator.""" + + @wraps(func) + async def trace_get_response( + self: "ChatClientProtocol", + messages: "str | ChatMessage | list[str] | list[ChatMessage]", + **kwargs: Any, + ) -> "ChatResponse": + global OTEL_SETTINGS + if not OTEL_SETTINGS.ENABLED: + # If model diagnostics are not enabled, just return the completion + return await func( + self, + messages=messages, + **kwargs, + ) + setup_telemetry() + if "token_usage_histogram" not in self.additional_properties: + self.additional_properties["token_usage_histogram"] = _get_token_usage_histogram() + if "operation_duration_histogram" not in self.additional_properties: + self.additional_properties["operation_duration_histogram"] = _get_duration_histogram() + model_id = str(kwargs.get("ai_model_id") or getattr(self, "ai_model_id", "unknown")) + service_url = str( + service_url_func() + if (service_url_func := getattr(self, "service_url", None)) and callable(service_url_func) + else "unknown" + ) + attributes = _get_span_attributes( + operation_name=OtelAttr.CHAT_COMPLETION_OPERATION, + provider_name=provider_name, + model_id=model_id, + service_url=service_url, **kwargs, ) + with _get_span(attributes=attributes, span_name_attribute=SpanAttributes.LLM_REQUEST_MODEL) as span: + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and messages: + _capture_messages(span=span, provider_name=provider_name, messages=messages) + start_time_stamp = perf_counter() + end_time_stamp: float | None = None + try: + response = await func(self, messages=messages, **kwargs) + end_time_stamp = perf_counter() + except Exception as exception: + end_time_stamp = perf_counter() + _capture_exception(span=span, exception=exception, timestamp=time_ns()) + raise + else: + duration = (end_time_stamp or perf_counter()) - start_time_stamp + attributes = _get_response_attributes(attributes, response, duration=duration) + _capture_response( + span=span, + attributes=attributes, + token_usage_histogram=self.additional_properties["token_usage_histogram"], + operation_duration_histogram=self.additional_properties["operation_duration_histogram"], + ) + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and response.messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=response.messages, + finish_reason=response.finish_reason, + output=True, + ) + return response - with use_span( - _get_chat_response_span( - GenAIAttributes.CHAT_COMPLETION_OPERATION.value, - getattr(self, "ai_model_id", chat_options.ai_model_id or "unknown"), - self.MODEL_PROVIDER_NAME, - self.service_url() if hasattr(self, "service_url") else None, - chat_options, - ), - end_on_exit=True, - ) as current_span: - _set_chat_response_input(self.MODEL_PROVIDER_NAME, messages) - try: - response = await completion_func(self, messages=messages, chat_options=chat_options, **kwargs) - _set_chat_response_output(current_span, response, self.MODEL_PROVIDER_NAME) - return response - except Exception as exception: - _set_error(current_span, exception) - raise + return trace_get_response - # Mark the wrapper decorator as a chat completion decorator - wrap_inner_get_response.__model_diagnostics_chat_client__ = True # type: ignore - - return wrap_inner_get_response + return decorator(func) -def _trace_chat_get_streaming_response( - completion_func: Callable[..., AsyncIterable["ChatResponseUpdate"]], +def _trace_get_streaming_response( + func: Callable[..., AsyncIterable["ChatResponseUpdate"]], + *, + provider_name: str = "unknown", ) -> Callable[..., AsyncIterable["ChatResponseUpdate"]]: """Decorator to trace streaming chat completion activities. Args: - completion_func: The function to trace. + func: The function to trace. + provider_name: The model provider name. """ - @functools.wraps(completion_func) - async def wrap_inner_get_streaming_response( - self: "BaseChatClient", *, messages: MutableSequence["ChatMessage"], chat_options: "ChatOptions", **kwargs: Any - ) -> AsyncIterable["ChatResponseUpdate"]: - if not MODEL_DIAGNOSTICS_SETTINGS.ENABLED: - # If model diagnostics are not enabled, just return the completion - async for streaming_chat_message_contents in completion_func( - self, messages=messages, chat_options=chat_options, **kwargs - ): - yield streaming_chat_message_contents - return + def decorator( + func: Callable[..., AsyncIterable["ChatResponseUpdate"]], + ) -> Callable[..., AsyncIterable["ChatResponseUpdate"]]: + """Inner decorator.""" - from ._types import ChatResponse + @wraps(func) + async def trace_get_streaming_response( + self: "ChatClientProtocol", messages: "str | ChatMessage | list[str] | list[ChatMessage]", **kwargs: Any + ) -> AsyncIterable["ChatResponseUpdate"]: + global OTEL_SETTINGS + if not OTEL_SETTINGS.ENABLED: + # If model diagnostics are not enabled, just return the completion + async for update in func(self, messages=messages, **kwargs): + yield update + return + setup_telemetry() + if "token_usage_histogram" not in self.additional_properties: + self.additional_properties["token_usage_histogram"] = _get_token_usage_histogram() + if "operation_duration_histogram" not in self.additional_properties: + self.additional_properties["operation_duration_histogram"] = _get_duration_histogram() - all_updates: list["ChatResponseUpdate"] = [] + model_id = kwargs.get("ai_model_id") or getattr(self, "ai_model_id", None) + service_url = str( + service_url_func() + if (service_url_func := getattr(self, "service_url", None)) and callable(service_url_func) + else "unknown" + ) + attributes = _get_span_attributes( + operation_name=OtelAttr.CHAT_COMPLETION_OPERATION, + provider_name=provider_name, + model_id=model_id, + service_url=service_url, + **kwargs, + ) + all_updates: list["ChatResponseUpdate"] = [] + with _get_span(attributes=attributes, span_name_attribute=SpanAttributes.LLM_REQUEST_MODEL) as span: + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=messages, + ) + start_time_stamp = perf_counter() + end_time_stamp: float | None = None + try: + async for update in func(self, messages=messages, **kwargs): + all_updates.append(update) + yield update + end_time_stamp = perf_counter() + except Exception as exception: + end_time_stamp = perf_counter() + _capture_exception(span=span, exception=exception, timestamp=time_ns()) + raise + else: + duration = (end_time_stamp or perf_counter()) - start_time_stamp + from ._types import ChatResponse - with use_span( - _get_chat_response_span( - GenAIAttributes.CHAT_COMPLETION_OPERATION.value, - getattr(self, "ai_model_id", chat_options.ai_model_id or "unknown"), - self.MODEL_PROVIDER_NAME, - self.service_url() if hasattr(self, "service_url") else None, - chat_options, - ), - end_on_exit=True, - ) as current_span: - _set_chat_response_input(self.MODEL_PROVIDER_NAME, messages) - try: - async for response in completion_func(self, messages=messages, chat_options=chat_options, **kwargs): - all_updates.append(response) - yield response + response = ChatResponse.from_chat_response_updates(all_updates) + attributes = _get_response_attributes(attributes, response, duration=duration) + _capture_response( + span=span, + attributes=attributes, + token_usage_histogram=self.additional_properties["token_usage_histogram"], + operation_duration_histogram=self.additional_properties["operation_duration_histogram"], + ) - all_messages_flattened = ChatResponse.from_chat_response_updates(all_updates) - _set_chat_response_output(current_span, all_messages_flattened, self.MODEL_PROVIDER_NAME) - except Exception as exception: - _set_error(current_span, exception) - raise + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and response.messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=response.messages, + finish_reason=response.finish_reason, + output=True, + ) - # Mark the wrapper decorator as a streaming chat completion decorator - wrap_inner_get_streaming_response.__model_diagnostics_streaming_chat_completion__ = True # type: ignore - return wrap_inner_get_streaming_response + return trace_get_streaming_response + + return decorator(func) -def use_telemetry(cls: type[TBaseChatClient]) -> type[TBaseChatClient]: +def use_telemetry( + chat_client: type[TChatClient], +) -> type[TChatClient]: """Class decorator that enables telemetry for a chat client. - Remarks: - This only works on classes that derive from BaseChatClient - and the _inner_get_response - and _inner_get_streaming_response methods. - It also relies on the presence of the MODEL_PROVIDER_NAME class variable. - ``` + This needs to be applied on the class itself, not a instance of it. + + To set the proper provider name, the chat client class should have a class variable + OTEL_PROVIDER_NAME. """ - if inner_response := getattr(cls, "_inner_get_response", None): - cls._inner_get_response = _trace_chat_get_response(inner_response) # type: ignore - if inner_streaming_response := getattr(cls, "_inner_get_streaming_response", None): - cls._inner_get_streaming_response = _trace_chat_get_streaming_response(inner_streaming_response) # type: ignore - return cls + if getattr(chat_client, OPEN_TELEMETRY_CHAT_CLIENT_MARKER, False): + # Already decorated + return chat_client + provider_name = str(getattr(chat_client, "OTEL_PROVIDER_NAME", "unknown")) -def _get_chat_response_span( - operation_name: str, - model_name: str, - model_provider: str, - service_url: str | None, - chat_options: "ChatOptions", -) -> Span: - """Start a text or chat completion span for a given model. - - Note that `start_span` doesn't make the span the current span. - Use `use_span` to make it the current span as a context manager. - """ - span = tracer.start_span(f"{operation_name} {model_name}") - - # Set attributes on the span - span.set_attributes({ - GenAIAttributes.OPERATION.value: operation_name, - GenAIAttributes.SYSTEM.value: model_provider, - GenAIAttributes.MODEL.value: model_name, - GenAIAttributes.CHOICE_COUNT.value: 1, - }) - - if service_url: - span.set_attribute(GenAIAttributes.ADDRESS.value, service_url) - - if chat_options.seed is not None: - span.set_attribute(GenAIAttributes.SEED.value, chat_options.seed) - if chat_options.frequency_penalty is not None: - span.set_attribute(GenAIAttributes.FREQUENCY_PENALTY.value, chat_options.frequency_penalty) - if chat_options.max_tokens is not None: - span.set_attribute(GenAIAttributes.MAX_TOKENS.value, chat_options.max_tokens) - if chat_options.stop is not None: - span.set_attribute(GenAIAttributes.STOP_SEQUENCES.value, chat_options.stop) - if chat_options.temperature is not None: - span.set_attribute(GenAIAttributes.TEMPERATURE.value, chat_options.temperature) - if chat_options.top_p is not None: - span.set_attribute(GenAIAttributes.TOP_P.value, chat_options.top_p) - if chat_options.presence_penalty is not None: - span.set_attribute(GenAIAttributes.PRESENCE_PENALTY.value, chat_options.presence_penalty) - if "top_k" in chat_options.additional_properties: - span.set_attribute(GenAIAttributes.TOP_K.value, chat_options.additional_properties["top_k"]) - if "encoding_formats" in chat_options.additional_properties: - span.set_attribute( - GenAIAttributes.ENCODING_FORMATS.value, chat_options.additional_properties["encoding_formats"] + if provider_name not in GenAISystem.__members__: + # that list is not complete, so just logging, no consequences. + logger.debug( + f"The provider name '{provider_name}' is not recognized. " + f"Consider using one of the following: {', '.join(GenAISystem.__members__.keys())}" ) - return span + try: + chat_client.get_response = _trace_get_response(chat_client.get_response, provider_name=provider_name) # type: ignore + except AttributeError as exc: + raise ChatClientInitializationError( + f"The chat client {chat_client.__name__} does not have a get_response method.", exc + ) from exc + try: + chat_client.get_streaming_response = _trace_get_streaming_response( # type: ignore + chat_client.get_streaming_response, provider_name=provider_name + ) + except AttributeError as exc: + raise ChatClientInitializationError( + f"The chat client {chat_client.__name__} does not have a get_streaming_response method.", exc + ) from exc + setattr(chat_client, OPEN_TELEMETRY_CHAT_CLIENT_MARKER, True) -def _set_chat_response_input( - model_provider: str, - messages: MutableSequence["ChatMessage"], -) -> None: - """Set the input for a chat response. - - The logs will be associated to the current span. - """ - if MODEL_DIAGNOSTICS_SETTINGS.SENSITIVE_EVENTS_ENABLED: - for idx, message in enumerate(messages): - event_name = ROLE_EVENT_MAP.get(message.role.value) - logger.info( - message.model_dump_json(exclude_none=True), - extra={ - GenAIAttributes.EVENT_NAME.value: event_name, - GenAIAttributes.SYSTEM.value: model_provider, - ChatMessageListTimestampFilter.INDEX_KEY: idx, - }, - ) - - -def _set_chat_response_output( - current_span: Span, - response: "ChatResponse", - model_provider: str, -) -> None: - """Set the response for a given span.""" - first_completion = response.messages[0] - - # Set the response ID - response_id = ( - first_completion.additional_properties.get("id") if first_completion.additional_properties is not None else None - ) - if response_id: - current_span.set_attribute(GenAIAttributes.RESPONSE_ID.value, response_id) - - # Set the finish reason - finish_reason = response.finish_reason - if finish_reason: - current_span.set_attribute(GenAIAttributes.FINISH_REASONS.value, [finish_reason.value]) - - # Set usage attributes - - usage = response.usage_details - if usage: - if usage.input_token_count: - current_span.set_attribute(GenAIAttributes.INPUT_TOKENS.value, usage.input_token_count) - if usage.output_token_count: - current_span.set_attribute(GenAIAttributes.OUTPUT_TOKENS.value, usage.output_token_count) - - # Set the completion event - if MODEL_DIAGNOSTICS_SETTINGS.SENSITIVE_EVENTS_ENABLED: - for completion in response.messages: - full_response: dict[str, Any] = { - "message": completion.model_dump(exclude_none=True), - } - full_response["index"] = response.response_id - logger.info( - json.dumps(full_response), - extra={ - GenAIAttributes.EVENT_NAME.value: GenAIAttributes.CHOICE.value, - GenAIAttributes.SYSTEM.value: model_provider, - }, - ) + return chat_client # region Agent @@ -511,75 +733,91 @@ def _set_chat_response_output( def _trace_agent_run( run_func: Callable[..., Awaitable["AgentRunResponse"]], + provider_name: str, ) -> Callable[..., Awaitable["AgentRunResponse"]]: """Decorator to trace chat completion activities. Args: run_func: The function to trace. + provider_name: The system name used for Open Telemetry. """ - @functools.wraps(run_func) - async def wrap_run( - self: "ChatAgent", + @wraps(run_func) + async def trace_run( + self: "AgentProtocol", messages: "str | ChatMessage | list[str] | list[ChatMessage] | None" = None, *, thread: "AgentThread | None" = None, **kwargs: Any, ) -> "AgentRunResponse": - if not MODEL_DIAGNOSTICS_SETTINGS.ENABLED: - # If model diagnostics are not enabled, just return the completion - return await run_func( - self, - messages=messages, - thread=thread, - **kwargs, - ) + global OTEL_SETTINGS - with use_span( - _get_agent_run_span( - operation_name=GenAIAttributes.AGENT_INVOKE_OPERATION.value, - agent=self, - system=self.AGENT_SYSTEM_NAME, - thread=thread, - **kwargs, - ), - end_on_exit=True, - ) as current_span: - _set_agent_run_input(self.AGENT_SYSTEM_NAME, messages) + if not OTEL_SETTINGS.ENABLED: + # If model diagnostics are not enabled, just return the completion + return await run_func(self, messages=messages, thread=thread, **kwargs) + setup_telemetry() + attributes = _get_span_attributes( + operation_name=OtelAttr.AGENT_INVOKE_OPERATION, + provider_name=provider_name, + agent_id=self.id, + agent_name=self.display_name, + agent_description=self.description, + thread_id=thread.service_thread_id if thread else None, + **kwargs, + ) + with _get_span(attributes=attributes, span_name_attribute=OtelAttr.AGENT_NAME) as span: + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=messages, + system_instructions=getattr(self, "instructions", None), + ) try: response = await run_func(self, messages=messages, thread=thread, **kwargs) - _set_agent_run_output(current_span, response, self.AGENT_SYSTEM_NAME) - return response except Exception as exception: - _set_error(current_span, exception) + _capture_exception(span=span, exception=exception, timestamp=time_ns()) raise + else: + attributes = _get_response_attributes(attributes, response) + _capture_response(span=span, attributes=attributes) + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and response.messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=response.messages, + output=True, + ) + return response - # Mark the wrapper decorator as a agent run decorator - wrap_run.__model_diagnostics_agent_run__ = True # type: ignore - - return wrap_run + return trace_run def _trace_agent_run_stream( - run_func: Callable[..., AsyncIterable["AgentRunResponseUpdate"]], + run_streaming_func: Callable[..., AsyncIterable["AgentRunResponseUpdate"]], + provider_name: str, ) -> Callable[..., AsyncIterable["AgentRunResponseUpdate"]]: """Decorator to trace streaming agent run activities. Args: - run_func: The function to trace. + agent: The agent that is wrapped. + run_streaming_func: The function to trace. + provider_name: The system name used for Open Telemetry. """ - @functools.wraps(run_func) - async def wrap_run_stream( - self: "ChatAgent", + @wraps(run_streaming_func) + async def trace_run_streaming( + self: "AgentProtocol", messages: "str | ChatMessage | list[str] | list[ChatMessage] | None" = None, *, thread: "AgentThread | None" = None, **kwargs: Any, ) -> AsyncIterable["AgentRunResponseUpdate"]: - if not MODEL_DIAGNOSTICS_SETTINGS.ENABLED: + global OTEL_SETTINGS + + if not OTEL_SETTINGS.ENABLED: # If model diagnostics are not enabled, just return the completion - async for streaming_agent_response in run_func(self, messages=messages, thread=thread, **kwargs): + async for streaming_agent_response in run_streaming_func(self, messages=messages, thread=thread, **kwargs): yield streaming_agent_response return @@ -587,167 +825,280 @@ def _trace_agent_run_stream( all_updates: list["AgentRunResponseUpdate"] = [] - with use_span( - _get_agent_run_span( - operation_name=GenAIAttributes.AGENT_INVOKE_OPERATION.value, - agent=self, - system=self.AGENT_SYSTEM_NAME, - thread=thread, - **kwargs, - ), - end_on_exit=True, - ) as current_span: - _set_agent_run_input(self.AGENT_SYSTEM_NAME, messages) + setup_telemetry() + attributes = _get_span_attributes( + operation_name=OtelAttr.AGENT_INVOKE_OPERATION, + provider_name=provider_name, + agent_id=self.id, + agent_name=self.display_name, + agent_description=self.description, + thread_id=thread.service_thread_id if thread else None, + **kwargs, + ) + with _get_span(attributes=attributes, span_name_attribute=OtelAttr.AGENT_NAME) as span: + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=messages, + system_instructions=getattr(self, "instructions", None), + ) try: - async for response in run_func(self, messages=messages, thread=thread, **kwargs): - all_updates.append(response) - yield response - - all_messages_flattened = AgentRunResponse.from_agent_run_response_updates(all_updates) - _set_agent_run_output(current_span, all_messages_flattened, self.AGENT_SYSTEM_NAME) + async for update in run_streaming_func(self, messages=messages, thread=thread, **kwargs): + all_updates.append(update) + yield update except Exception as exception: - _set_error(current_span, exception) + _capture_exception(span=span, exception=exception, timestamp=time_ns()) raise - - # Mark the wrapper decorator as a streaming agent run decorator - wrap_run_stream.__model_diagnostics_streaming_agent_run__ = True # type: ignore - return wrap_run_stream - - -def use_agent_telemetry(cls: type[TChatClientAgent]) -> type[TChatClientAgent]: - """Class decorator that enables telemetry for an agent.""" - if run := getattr(cls, "run", None): - cls.run = _trace_agent_run(run) # type: ignore - if run_stream := getattr(cls, "run_stream", None): - cls.run_stream = _trace_agent_run_stream(run_stream) # type: ignore - return cls - - -def _get_agent_run_span( - *, - operation_name: str, - agent: "AgentProtocol", - system: str, - thread: "AgentThread | None", - **kwargs: Any, -) -> Span: - """Start a text or chat completion span for a given model. - - Note that `start_span` doesn't make the span the current span. - Use `use_span` to make it the current span as a context manager. - - Should follow: https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-agent-spans/#invoke-agent-span - """ - span = tracer.start_span(f"{operation_name} {agent.display_name}") - - # Set attributes on the span - span.set_attributes({ - GenAIAttributes.OPERATION.value: operation_name, - GenAIAttributes.SYSTEM.value: system, - GenAIAttributes.CHOICE_COUNT.value: 1, - GenAIAttributes.AGENT_ID.value: agent.id, - }) - if agent.name: - span.set_attribute(GenAIAttributes.AGENT_NAME.value, agent.name) - if agent.description: - span.set_attribute(GenAIAttributes.AGENT_DESCRIPTION.value, agent.description) - if thread and thread.service_thread_id: - span.set_attribute(GenAIAttributes.CONVERSATION_ID.value, thread.service_thread_id) - if "model" in kwargs: - span.set_attribute(GenAIAttributes.MODEL.value, kwargs["model"]) - if "seed" in kwargs: - span.set_attribute(GenAIAttributes.SEED.value, kwargs["seed"]) - if "frequency_penalty" in kwargs: - span.set_attribute(GenAIAttributes.FREQUENCY_PENALTY.value, kwargs["frequency_penalty"]) - if "presence_penalty" in kwargs: - span.set_attribute(GenAIAttributes.PRESENCE_PENALTY.value, kwargs["presence_penalty"]) - if "max_tokens" in kwargs: - span.set_attribute(GenAIAttributes.MAX_TOKENS.value, kwargs["max_tokens"]) - if "stop" in kwargs: - span.set_attribute(GenAIAttributes.STOP_SEQUENCES.value, kwargs["stop"]) - if "temperature" in kwargs: - span.set_attribute(GenAIAttributes.TEMPERATURE.value, kwargs["temperature"]) - if "top_p" in kwargs: - span.set_attribute(GenAIAttributes.TOP_P.value, kwargs["top_p"]) - if "top_k" in kwargs: - span.set_attribute(GenAIAttributes.TOP_K.value, kwargs["top_k"]) - if "encoding_formats" in kwargs: - span.set_attribute(GenAIAttributes.ENCODING_FORMATS.value, kwargs["encoding_formats"]) - return span - - -def _set_agent_run_input( - system: str, - messages: "str | ChatMessage | list[str] | list[ChatMessage] | list[str | ChatMessage] | None" = None, -) -> None: - """Set the input for a chat response. - - The logs will be associated to the current span. - """ - if messages and MODEL_DIAGNOSTICS_SETTINGS.SENSITIVE_EVENTS_ENABLED: - if not isinstance(messages, list): - messages = [messages] - for idx, message in enumerate(messages): - if isinstance(message, str): - logger.info( - message, - extra={ - # assume user message - GenAIAttributes.EVENT_NAME.value: GenAIAttributes.USER_MESSAGE.value, - GenAIAttributes.SYSTEM.value: system, - ChatMessageListTimestampFilter.INDEX_KEY: idx, - }, - ) else: - logger.info( - message.model_dump_json(exclude_none=True), - extra={ - GenAIAttributes.EVENT_NAME.value: ROLE_EVENT_MAP.get(message.role.value), - GenAIAttributes.SYSTEM.value: system, - ChatMessageListTimestampFilter.INDEX_KEY: idx, - }, - ) + response = AgentRunResponse.from_agent_run_response_updates(all_updates) + attributes = _get_response_attributes(attributes, response) + _capture_response(span=span, attributes=attributes) + if OTEL_SETTINGS.SENSITIVE_DATA_ENABLED and response.messages: + _capture_messages( + span=span, + provider_name=provider_name, + messages=response.messages, + output=True, + ) + + return trace_run_streaming -def _set_agent_run_output( - current_span: Span, - response: "AgentRunResponse", - model_provider: str, -) -> None: - """Set the agent response for a given span.""" - first_completion = response.messages[0] +def use_agent_telemetry( + agent: type[TAgent], +) -> type[TAgent]: + """Class decorator that enables telemetry for an agent.""" + provider_name = str(getattr(agent, "AGENT_SYSTEM_NAME", "Unknown")) + try: + agent.run = _trace_agent_run(agent.run, provider_name) # type: ignore + except AttributeError as exc: + raise AgentInitializationError(f"The agent {agent.__name__} does not have a run method.", exc) from exc + try: + agent.run_stream = _trace_agent_run_stream(agent.run_stream, provider_name) # type: ignore + except AttributeError as exc: + raise AgentInitializationError(f"The agent {agent.__name__} does not have a run_stream method.", exc) from exc + setattr(agent, OPEN_TELEMETRY_AGENT_MARKER, True) + return agent - # Set the response ID - response_id = ( - first_completion.additional_properties.get("id") if first_completion.additional_properties is not None else None + +# region Otel Helpers + + +def get_function_span( + function: "AIFunction[Any, Any]", + tool_call_id: str | None = None, +) -> "_AgnosticContextManager[Span]": + """Starts a span for the given function. + + Args: + function: The function for which to start the span. + tool_call_id: The id of the tool_call that was requested. + + Returns: + trace.Span: The started span as a context manager. + """ + attributes: dict[str, str] = { + OtelAttr.OPERATION: OtelAttr.TOOL_EXECUTION_OPERATION, + OtelAttr.TOOL_NAME: function.name, + OtelAttr.TOOL_CALL_ID: tool_call_id or "unknown", + OtelAttr.TOOL_TYPE: "function", + } + if function.description: + attributes[OtelAttr.TOOL_DESCRIPTION] = function.description + + return tracer.start_as_current_span( + name=f"{OtelAttr.TOOL_EXECUTION_OPERATION} {function.name}", + attributes=attributes, + set_status_on_exception=False, + end_on_exit=True, + record_exception=False, ) - if response_id: - current_span.set_attribute(GenAIAttributes.RESPONSE_ID.value, response_id) - # Set the finish reason - finish_reason = getattr(response.raw_representation, "finish_reason", None) if response.raw_representation else None + +@contextmanager +def _get_span( + attributes: dict[str, Any], + span_name_attribute: str, +) -> Generator[Span, Any, Any]: + """Start a span for a agent run.""" + span = tracer.start_span(f"{attributes[OtelAttr.OPERATION]} {attributes[span_name_attribute]}") + span.set_attributes(attributes) + with use_span( + span=span, + end_on_exit=True, + record_exception=False, + set_status_on_exception=False, + ) as current_span: + yield current_span + + +def _get_span_attributes(**kwargs: Any) -> dict[str, Any]: + """Get the span attributes from a kwargs dictionary.""" + attributes: dict[str, Any] = {} + if operation_name := kwargs.get("operation_name"): + attributes[OtelAttr.OPERATION] = operation_name + if choice_count := kwargs.get("choice_count", 1): + attributes[OtelAttr.CHOICE_COUNT] = choice_count + if operation_name := kwargs.get("operation_name"): + attributes[OtelAttr.OPERATION] = operation_name + if system_name := kwargs.get("system_name"): + attributes[SpanAttributes.LLM_SYSTEM] = system_name + if provider_name := kwargs.get("provider_name"): + attributes[OtelAttr.PROVIDER_NAME] = provider_name + attributes[SpanAttributes.LLM_REQUEST_MODEL] = kwargs.get("model_id", "unknown") + if service_url := kwargs.get("service_url"): + attributes[OtelAttr.ADDRESS] = service_url + if conversation_id := kwargs.get("conversation_id"): + attributes[OtelAttr.CONVERSATION_ID] = conversation_id + if seed := kwargs.get("seed"): + attributes[OtelAttr.SEED] = seed + if frequency_penalty := kwargs.get("frequency_penalty"): + attributes[OtelAttr.FREQUENCY_PENALTY] = frequency_penalty + if max_tokens := kwargs.get("max_tokens"): + attributes[SpanAttributes.LLM_REQUEST_MAX_TOKENS] = max_tokens + if stop := kwargs.get("stop"): + attributes[OtelAttr.STOP_SEQUENCES] = stop + if temperature := kwargs.get("temperature"): + attributes[SpanAttributes.LLM_REQUEST_TEMPERATURE] = temperature + if top_p := kwargs.get("top_p"): + attributes[SpanAttributes.LLM_REQUEST_TOP_P] = top_p + if presence_penalty := kwargs.get("presence_penalty"): + attributes[OtelAttr.PRESENCE_PENALTY] = presence_penalty + if top_k := kwargs.get("top_k"): + attributes[OtelAttr.TOP_K] = top_k + if encoding_formats := kwargs.get("encoding_formats"): + attributes[OtelAttr.ENCODING_FORMATS] = json.dumps( + encoding_formats if isinstance(encoding_formats, list) else [encoding_formats] + ) + if error := kwargs.get("error"): + attributes[OtelAttr.ERROR_TYPE] = type(error).__name__ + # agent attributes + if agent_id := kwargs.get("agent_id"): + attributes[OtelAttr.AGENT_ID] = agent_id + if agent_name := kwargs.get("agent_name"): + attributes[OtelAttr.AGENT_NAME] = agent_name + if agent_description := kwargs.get("agent_description"): + attributes[OtelAttr.AGENT_DESCRIPTION] = agent_description + if thread_id := kwargs.get("thread_id"): + # override if thread is set + attributes[OtelAttr.CONVERSATION_ID] = thread_id + return attributes + + +def _capture_exception(span: Span, exception: Exception, timestamp: int | None = None) -> None: + """Set an error for spans.""" + span.set_attribute(OtelAttr.ERROR_TYPE, type(exception).__name__) + span.record_exception(exception=exception, timestamp=timestamp) + span.set_status(status=StatusCode.ERROR, description=repr(exception)) + + +def _capture_messages( + span: Span, + provider_name: str, + messages: "str | ChatMessage | list[str] | list[ChatMessage]", + system_instructions: str | list[str] | None = None, + output: bool = False, + finish_reason: "FinishReason | None" = None, +) -> None: + """Log messages with extra information.""" + from ._clients import prepare_messages + + prepped = prepare_messages(messages) + for index, message in enumerate(prepped): + logger.info( + message.model_dump_json(exclude_none=True), + extra={ + OtelAttr.EVENT_NAME: OtelAttr.CHOICE if output else ROLE_EVENT_MAP.get(message.role.value), + OtelAttr.PROVIDER_NAME: provider_name, + ChatMessageListTimestampFilter.INDEX_KEY: index, + }, + ) + otel_messages = [_to_otel_message(message) for message in prepped] if finish_reason: - current_span.set_attribute(GenAIAttributes.FINISH_REASONS.value, [finish_reason.value]) + otel_messages[-1]["finish_reason"] = FINISH_REASON_MAP[finish_reason.value] + span.set_attribute(OtelAttr.OUTPUT_MESSAGES if output else OtelAttr.INPUT_MESSAGES, json.dumps(otel_messages)) + if system_instructions: + if not isinstance(system_instructions, list): + system_instructions = [system_instructions] + otel_sys_instructions = [{"type": "text", "content": instruction} for instruction in system_instructions] + span.set_attribute(OtelAttr.SYSTEM_INSTRUCTIONS, json.dumps(otel_sys_instructions)) - # Set usage attributes - usage = response.usage_details - if usage: + +def _to_otel_message(message: "ChatMessage") -> dict[str, Any]: + """Create a otel representation of a message.""" + return {"role": message.role.value, "parts": [_to_otel_part(content) for content in message.contents]} + + +def _to_otel_part(content: "Contents") -> dict[str, Any] | None: + """Create a otel representation of a Content.""" + match content.type: + case "text": + return {"type": "text", "content": content.text} + case "function_call": + return {"type": "tool_call", "id": content.call_id, "name": content.name, "arguments": content.arguments} + case "function_result": + return {"type": "tool_call_response", "id": content.call_id, "response": content.result} + case _: + # GenericPart in otel output messages json spec. + # just required type, and arbitrary other fields. + return content.model_dump(exclude_none=True) + return None + + +def _get_response_attributes( + attributes: dict[str, Any], + response: "ChatResponse | AgentRunResponse", + duration: float | None = None, +) -> dict[str, Any]: + """Get the response attributes from a response.""" + if response.response_id: + attributes[OtelAttr.RESPONSE_ID] = response.response_id + finish_reason = getattr(response, "finish_reason", None) + if not finish_reason: + finish_reason = ( + getattr(response.raw_representation, "finish_reason", None) if response.raw_representation else None + ) + if finish_reason: + attributes[OtelAttr.FINISH_REASONS] = json.dumps([finish_reason.value]) + if ai_model_id := getattr(response, "ai_model_id", None): + attributes[SpanAttributes.LLM_RESPONSE_MODEL] = ai_model_id + if usage := response.usage_details: if usage.input_token_count: - current_span.set_attribute(GenAIAttributes.INPUT_TOKENS.value, usage.input_token_count) + attributes[OtelAttr.INPUT_TOKENS] = usage.input_token_count if usage.output_token_count: - current_span.set_attribute(GenAIAttributes.OUTPUT_TOKENS.value, usage.output_token_count) + attributes[OtelAttr.OUTPUT_TOKENS] = usage.output_token_count + if duration: + attributes[Meters.LLM_OPERATION_DURATION] = duration + return attributes - # Set the completion event - if MODEL_DIAGNOSTICS_SETTINGS.SENSITIVE_EVENTS_ENABLED: - for msg in response.messages: - full_response: dict[str, Any] = { - "message": msg.model_dump(exclude_none=True), - } - full_response["index"] = response.response_id - logger.info( - json.dumps(full_response), - extra={ - GenAIAttributes.EVENT_NAME.value: GenAIAttributes.CHOICE.value, - GenAIAttributes.SYSTEM.value: model_provider, - }, - ) + +GEN_AI_METRIC_ATTRIBUTES = ( + OtelAttr.OPERATION, + OtelAttr.PROVIDER_NAME, + SpanAttributes.LLM_REQUEST_MODEL, + SpanAttributes.LLM_RESPONSE_MODEL, + OtelAttr.ADDRESS, + OtelAttr.PORT, +) + + +def _capture_response( + span: Span, + attributes: dict[str, Any], + operation_duration_histogram: "Histogram | None" = None, + token_usage_histogram: "Histogram | None" = None, +) -> None: + """Set the response for a given span.""" + span.set_attributes(attributes) + attrs: dict[str, Any] = {k: v for k, v in attributes.items() if k in GEN_AI_METRIC_ATTRIBUTES} + if token_usage_histogram and (input_tokens := attributes.get(OtelAttr.INPUT_TOKENS)): + token_usage_histogram.record( + input_tokens, attributes={**attrs, SpanAttributes.LLM_TOKEN_TYPE: OtelAttr.T_TYPE_INPUT} + ) + if token_usage_histogram and (output_tokens := attributes.get(OtelAttr.OUTPUT_TOKENS)): + token_usage_histogram.record(output_tokens, {**attrs, SpanAttributes.LLM_TOKEN_TYPE: OtelAttr.T_TYPE_OUTPUT}) + if operation_duration_histogram and (duration := attributes.get(Meters.LLM_OPERATION_DURATION)): + if OtelAttr.ERROR_TYPE in attributes: + attrs[OtelAttr.ERROR_TYPE] = attributes[OtelAttr.ERROR_TYPE] + operation_duration_histogram.record(duration, attributes=attrs) diff --git a/python/packages/main/pyproject.toml b/python/packages/main/pyproject.toml index b8fcf2f966..64b34bd0ef 100644 --- a/python/packages/main/pyproject.toml +++ b/python/packages/main/pyproject.toml @@ -23,13 +23,16 @@ classifiers = [ "Typing :: Typed", ] dependencies = [ - "openai>=1.103.0", + "openai>=1.99.0", "pydantic>=2.11.7", "pydantic-settings>=2.10.1", "typing-extensions>=4.14.0", "opentelemetry-api ~= 1.24", "opentelemetry-sdk ~= 1.24", - "mcp>=1.12", + "mcp[ws]>=1.13", + "azure-monitor-opentelemetry>=1.7.0", + "azure-monitor-opentelemetry-exporter>=1.0.0b41", + "opentelemetry-exporter-otlp-proto-grpc>=1.36.0", ] [project.optional-dependencies] diff --git a/python/packages/main/tests/main/conftest.py b/python/packages/main/tests/main/conftest.py index 7801989167..001510f877 100644 --- a/python/packages/main/tests/main/conftest.py +++ b/python/packages/main/tests/main/conftest.py @@ -1,11 +1,64 @@ # Copyright (c) Microsoft. All rights reserved. -from typing import Any -from pydantic import BaseModel +import asyncio +import logging +import sys +from collections.abc import AsyncIterable, MutableSequence +from typing import Any +from unittest.mock import patch +from uuid import uuid4 + +from pydantic import BaseModel, Field from pytest import fixture -from agent_framework import ChatMessage, ToolProtocol, ai_function -from agent_framework.telemetry import ModelDiagnosticSettings +from agent_framework import ( + AgentProtocol, + AgentRunResponse, + AgentRunResponseUpdate, + AgentThread, + BaseChatClient, + ChatMessage, + ChatOptions, + ChatResponse, + ChatResponseUpdate, + Role, + TextContent, + ToolProtocol, + ai_function, + use_function_invocation, +) +from agent_framework.telemetry import OtelSettings, setup_telemetry + +if sys.version_info >= (3, 12): + from typing import override # type: ignore +else: + from typing_extensions import override # type: ignore[import] +# region Chat History + +logger = logging.getLogger(__name__) + + +@fixture +def enable_otel(request: Any) -> bool: + """Fixture that returns a boolean indicating if Otel is enabled.""" + return request.param if hasattr(request, "param") else True + + +@fixture +def enable_sensitive_data(request: Any) -> bool: + """Fixture that returns a boolean indicating if sensitive data is enabled.""" + return request.param if hasattr(request, "param") else False + + +@fixture +def otel_settings(enable_otel: bool, enable_sensitive_data: bool) -> OtelSettings: + """Fixture to set environment variables for OtelSettings.""" + + from agent_framework.telemetry import OTEL_SETTINGS + + setup_telemetry(enable_otel=enable_otel, enable_sensitive_data=enable_sensitive_data) + + return OTEL_SETTINGS @fixture(scope="function") @@ -13,13 +66,16 @@ def chat_history() -> list[ChatMessage]: return [] +# region Tools + + @fixture def ai_tool() -> ToolProtocol: """Returns a generic ToolProtocol.""" class GenericTool(BaseModel): name: str - description: str | None = None + description: str additional_properties: dict[str, Any] | None = None def parameters(self) -> dict[str, Any]: @@ -43,17 +99,173 @@ def ai_function_tool() -> ToolProtocol: return simple_function +# region Chat Clients +class MockChatClient: + """Simple implementation of a chat client.""" + + def __init__(self) -> None: + self.additional_properties: dict[str, Any] = {} + + async def get_response( + self, + messages: str | ChatMessage | list[str] | list[ChatMessage], + **kwargs: Any, + ) -> ChatResponse: + logger.debug(f"Running custom chat client, with: {messages=}, {kwargs=}") + return ChatResponse(messages=ChatMessage(role="assistant", text="test response")) + + async def get_streaming_response( + self, + messages: str | ChatMessage | list[str] | list[ChatMessage], + **kwargs: Any, + ) -> AsyncIterable[ChatResponseUpdate]: + logger.debug(f"Running custom chat client stream, with: {messages=}, {kwargs=}") + yield ChatResponseUpdate(text=TextContent(text="test streaming response "), role="assistant") + yield ChatResponseUpdate(contents=[TextContent(text="another update")], role="assistant") + + +class MockBaseChatClient(BaseChatClient): + """Mock implementation of the BaseChatClient.""" + + run_responses: list[ChatResponse] = Field(default_factory=list) + streaming_responses: list[list[ChatResponseUpdate]] = Field(default_factory=list) + + @override + async def _inner_get_response( + self, + *, + messages: MutableSequence[ChatMessage], + chat_options: ChatOptions, + **kwargs: Any, + ) -> ChatResponse: + """Send a chat request to the AI service. + + Args: + messages: The chat messages to send. + chat_options: The options for the request. + kwargs: Any additional keyword arguments. + + Returns: + The chat response contents representing the response(s). + """ + logger.debug(f"Running base chat client inner, with: {messages=}, {chat_options=}, {kwargs=}") + if not self.run_responses: + return ChatResponse(messages=ChatMessage(role="assistant", text=f"test response - {messages[0].text}")) + + response = self.run_responses.pop(0) + + if chat_options.tool_choice == "none": + return ChatResponse( + messages=ChatMessage( + role="assistant", + text="I broke out of the function invocation loop...", + ), + conversation_id=response.conversation_id, + ) + + return response + + @override + async def _inner_get_streaming_response( + self, + *, + messages: MutableSequence[ChatMessage], + chat_options: ChatOptions, + **kwargs: Any, + ) -> AsyncIterable[ChatResponseUpdate]: + logger.debug(f"Running base chat client inner stream, with: {messages=}, {chat_options=}, {kwargs=}") + if not self.streaming_responses: + yield ChatResponseUpdate(text=f"update - {messages[0].text}", role="assistant") + return + if chat_options.tool_choice == "none": + yield ChatResponseUpdate(text="I broke out of the function invocation loop...", role="assistant") + return + response = self.streaming_responses.pop(0) + for update in response: + yield update + await asyncio.sleep(0) + + @fixture -def model_diagnostic_settings(monkeypatch, request) -> ModelDiagnosticSettings: - """Fixture to set environment variables for ModelDiagnosticSettings.""" - enabled = getattr(request, "param", (None, None))[0] - sensitive = getattr(request, "param", (None, None))[1] - if enabled is None: - monkeypatch.delenv("AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS", raising=False) - else: - monkeypatch.setenv("AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS", str(enabled).lower()) - if sensitive is None: - monkeypatch.delenv("AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE", raising=False) - else: - monkeypatch.setenv("AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE", str(sensitive).lower()) - return ModelDiagnosticSettings(env_file_path="test.env") +def enable_function_calling(request: Any) -> bool: + return request.param if hasattr(request, "param") else True + + +@fixture +def max_iterations(request: Any) -> int: + return request.param if hasattr(request, "param") else 2 + + +@fixture +def chat_client(enable_function_calling: bool, max_iterations: int) -> MockChatClient: + if enable_function_calling: + with patch("agent_framework._tools.DEFAULT_MAX_ITERATIONS", max_iterations): + return use_function_invocation(MockChatClient)() + return MockChatClient() + + +@fixture +def chat_client_base(enable_function_calling: bool, max_iterations: int) -> MockBaseChatClient: + if enable_function_calling: + with patch("agent_framework._tools.DEFAULT_MAX_ITERATIONS", max_iterations): + return use_function_invocation(MockBaseChatClient)() + return MockBaseChatClient() + + +# region Agents +class MockAgentThread(AgentThread): + pass + + +# Mock Agent implementation for testing +class MockAgent(AgentProtocol): + @property + def id(self) -> str: + return str(uuid4()) + + @property + def name(self) -> str | None: + """Returns the name of the agent.""" + return "Name" + + @property + def display_name(self) -> str: + """Returns the name of the agent.""" + return "Display Name" + + @property + def description(self) -> str | None: + return "Description" + + async def run( + self, + messages: str | ChatMessage | list[str] | list[ChatMessage] | None = None, + *, + thread: AgentThread | None = None, + **kwargs: Any, + ) -> AgentRunResponse: + logger.debug(f"Running mock agent, with: {messages=}, {thread=}, {kwargs=}") + return AgentRunResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("Response")])]) + + async def run_stream( + self, + messages: str | ChatMessage | list[str] | list[ChatMessage] | None = None, + *, + thread: AgentThread | None = None, + **kwargs: Any, + ) -> AsyncIterable[AgentRunResponseUpdate]: + logger.debug(f"Running mock agent stream, with: {messages=}, {thread=}, {kwargs=}") + yield AgentRunResponseUpdate(contents=[TextContent("Response")]) + + def get_new_thread(self) -> AgentThread: + return MockAgentThread() + + +@fixture +def agent_thread() -> AgentThread: + return MockAgentThread() + + +@fixture +def agent() -> AgentProtocol: + return MockAgent() diff --git a/python/packages/main/tests/main/test_agents.py b/python/packages/main/tests/main/test_agents.py index ab48a8ad45..9737810b60 100644 --- a/python/packages/main/tests/main/test_agents.py +++ b/python/packages/main/tests/main/test_agents.py @@ -1,122 +1,29 @@ # Copyright (c) Microsoft. All rights reserved. -from collections.abc import AsyncIterable, MutableSequence -from typing import Any +from collections.abc import AsyncIterable, MutableSequence, Sequence from uuid import uuid4 -from pytest import fixture, raises +from pytest import raises from agent_framework import ( AgentProtocol, AgentRunResponse, AgentRunResponseUpdate, AgentThread, - BaseChatClient, ChatAgent, ChatClientProtocol, ChatMessage, ChatMessageList, - ChatOptions, ChatResponse, - ChatResponseUpdate, + Contents, + HostedCodeInterpreterTool, Role, TextContent, ) +from agent_framework._memory import AggregateContextProvider, Context, ContextProvider from agent_framework.exceptions import AgentExecutionException -# Mock AgentThread implementation for testing -class MockAgentThread(AgentThread): - pass - - -# Mock Agent implementation for testing -class MockAgent(AgentProtocol): - @property - def id(self) -> str: - return str(uuid4()) - - @property - def name(self) -> str | None: - """Returns the name of the agent.""" - return "Name" - - @property - def display_name(self) -> str: - """Returns the name of the agent.""" - return "Display Name" - - @property - def description(self) -> str | None: - return "Description" - - async def run( - self, - messages: str | ChatMessage | list[str] | list[ChatMessage] | None = None, - *, - thread: AgentThread | None = None, - **kwargs: Any, - ) -> AgentRunResponse: - return AgentRunResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("Response")])]) - - async def run_stream( - self, - messages: str | ChatMessage | list[str] | list[ChatMessage] | None = None, - *, - thread: AgentThread | None = None, - **kwargs: Any, - ) -> AsyncIterable[AgentRunResponseUpdate]: - yield AgentRunResponseUpdate(contents=[TextContent("Response")]) - - def get_new_thread(self) -> AgentThread: - return MockAgentThread() - - -# Mock ChatClientProtocol implementation for testing -class MockChatClient(BaseChatClient): - _mock_response: ChatResponse | None = None - - def __init__(self, mock_response: ChatResponse | None = None) -> None: - self._mock_response = mock_response - - async def _inner_get_response( - self, - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> ChatResponse: - return ( - self._mock_response - if self._mock_response - else ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="test response")) - ) - - async def _inner_get_streaming_response( - self, - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(role=Role.ASSISTANT, text=TextContent(text="test streaming response")) - - -@fixture -def agent_thread() -> AgentThread: - return MockAgentThread() - - -@fixture -def agent() -> AgentProtocol: - return MockAgent() - - -@fixture -def chat_client() -> BaseChatClient: - return MockChatClient() - - def test_agent_thread_type(agent_thread: AgentThread) -> None: assert isinstance(agent_thread, AgentThread) @@ -178,7 +85,7 @@ async def test_chat_client_agent_run_streaming(chat_client: ChatClientProtocol) result = await AgentRunResponse.from_agent_response_generator(agent.run_stream("Hello")) - assert result.text == "test streaming response" + assert result.text == "test streaming response another update" async def test_chat_client_agent_get_new_thread(chat_client: ChatClientProtocol) -> None: @@ -195,6 +102,7 @@ async def test_chat_client_agent_prepare_thread_and_messages(chat_client: ChatCl _, result_messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] thread=thread, + context=Context(), input_messages=[ChatMessage(role=Role.USER, text="Test")], ) @@ -203,14 +111,16 @@ async def test_chat_client_agent_prepare_thread_and_messages(chat_client: ChatCl assert result_messages[1].text == "Test" -async def test_chat_client_agent_update_thread_id() -> None: - chat_client = MockChatClient( - mock_response=ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("test response")])], - conversation_id="123", - ) +async def test_chat_client_agent_update_thread_id(chat_client_base: ChatClientProtocol) -> None: + mock_response = ChatResponse( + messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("test response")])], + conversation_id="123", + ) + chat_client_base.run_responses = [mock_response] + agent = ChatAgent( + chat_client=chat_client_base, + tools=HostedCodeInterpreterTool(), ) - agent = ChatAgent(chat_client=chat_client) thread = agent.get_new_thread() result = await agent.run("Hello", thread=thread) @@ -263,16 +173,224 @@ async def test_chat_client_agent_author_name_as_agent_name(chat_client: ChatClie assert result.messages[0].author_name == "TestAgent" -async def test_chat_client_agent_author_name_is_used_from_response() -> None: - chat_client = MockChatClient( - mock_response=ChatResponse( +async def test_chat_client_agent_author_name_is_used_from_response(chat_client_base: ChatClientProtocol) -> None: + chat_client_base.run_responses = [ + ChatResponse( messages=[ ChatMessage(role=Role.ASSISTANT, contents=[TextContent("test response")], author_name="TestAuthor") ] ) - ) - agent = ChatAgent(chat_client=chat_client) + ] + + agent = ChatAgent(chat_client=chat_client_base, tools=HostedCodeInterpreterTool()) result = await agent.run("Hello") assert result.text == "test response" assert result.messages[0].author_name == "TestAuthor" + + +# Mock context provider for testing +class MockContextProvider(ContextProvider): + context_contents: list[Contents] | None = None + thread_created_called: bool = False + messages_adding_called: bool = False + model_invoking_called: bool = False + thread_created_thread_id: str | None = None + messages_adding_thread_id: str | None = None + new_messages: list[ChatMessage] = [] + + def __init__(self, contents: list[Contents] | None = None) -> None: + super().__init__() + self.context_contents = contents + self.thread_created_called = False + self.messages_adding_called = False + self.model_invoking_called = False + self.thread_created_thread_id = None + self.messages_adding_thread_id = None + self.new_messages = [] + + async def thread_created(self, thread_id: str | None) -> None: + self.thread_created_called = True + self.thread_created_thread_id = thread_id + + async def messages_adding(self, thread_id: str | None, new_messages: ChatMessage | Sequence[ChatMessage]) -> None: + self.messages_adding_called = True + self.messages_adding_thread_id = thread_id + if isinstance(new_messages, ChatMessage): + self.new_messages.append(new_messages) + else: + self.new_messages.extend(new_messages) + + async def model_invoking(self, messages: ChatMessage | MutableSequence[ChatMessage]) -> Context: + self.model_invoking_called = True + return Context(contents=self.context_contents) + + +async def test_chat_agent_context_providers_model_invoking(chat_client: ChatClientProtocol) -> None: + """Test that context providers' model_invoking is called during agent run.""" + mock_provider = MockContextProvider(contents=[TextContent("Test context instructions")]) + agent = ChatAgent(chat_client=chat_client, context_providers=mock_provider) + + await agent.run("Hello") + + assert mock_provider.model_invoking_called + + +async def test_chat_agent_context_providers_thread_created(chat_client_base: ChatClientProtocol) -> None: + """Test that context providers' thread_created is called during agent run.""" + mock_provider = MockContextProvider() + chat_client_base.run_responses = [ + ChatResponse( + messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("test response")])], + conversation_id="test-thread-id", + ) + ] + + agent = ChatAgent(chat_client=chat_client_base, context_providers=mock_provider) + + await agent.run("Hello") + + assert mock_provider.thread_created_called + assert mock_provider.thread_created_thread_id == "test-thread-id" + + +async def test_chat_agent_context_providers_messages_adding(chat_client: ChatClientProtocol) -> None: + """Test that context providers' messages_adding is called during agent run.""" + mock_provider = MockContextProvider() + agent = ChatAgent(chat_client=chat_client, context_providers=mock_provider) + + await agent.run("Hello") + + assert mock_provider.messages_adding_called + # Should be called with both input and response messages + assert len(mock_provider.new_messages) >= 2 + + +async def test_chat_agent_context_instructions_in_messages(chat_client: ChatClientProtocol) -> None: + """Test that AI context instructions are included in messages.""" + mock_provider = MockContextProvider(contents=[TextContent("Context-specific instructions")]) + agent = ChatAgent(chat_client=chat_client, instructions="Agent instructions", context_providers=mock_provider) + + # We need to test the _prepare_thread_and_messages method directly + context = Context(contents=[TextContent("Context-specific instructions")]) + _, messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] + thread=None, context=context, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + ) + + # Should have agent instructions, context instructions, and user message + assert len(messages) == 3 + assert messages[0].role == Role.SYSTEM + assert messages[0].text == "Agent instructions" + assert messages[1].role == Role.SYSTEM + assert messages[1].text == "Context-specific instructions" + assert messages[2].role == Role.USER + assert messages[2].text == "Hello" + + +async def test_chat_agent_context_instructions_without_agent_instructions(chat_client: ChatClientProtocol) -> None: + """Test that AI context instructions work when agent has no instructions.""" + agent = ChatAgent(chat_client=chat_client) # No instructions + context = Context(contents=[TextContent("Context-only instructions")]) + + _, messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] + thread=None, context=context, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + ) + + # Should have context instructions and user message only + assert len(messages) == 2 + assert messages[0].role == Role.SYSTEM + assert messages[0].text == "Context-only instructions" + assert messages[1].role == Role.USER + assert messages[1].text == "Hello" + + +async def test_chat_agent_no_context_instructions(chat_client: ChatClientProtocol) -> None: + """Test behavior when AI context has no instructions.""" + agent = ChatAgent(chat_client=chat_client, instructions="Agent instructions") + context = Context() # No instructions + + _, messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] + thread=None, context=context, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + ) + + # Should have agent instructions and user message only + assert len(messages) == 2 + assert messages[0].role == Role.SYSTEM + assert messages[0].text == "Agent instructions" + assert messages[1].role == Role.USER + assert messages[1].text == "Hello" + + +async def test_chat_agent_run_stream_context_providers(chat_client: ChatClientProtocol) -> None: + """Test that context providers work with run_stream method.""" + mock_provider = MockContextProvider(contents=[TextContent("Stream context instructions")]) + agent = ChatAgent(chat_client=chat_client, context_providers=mock_provider) + + # Collect all stream updates + updates: list[AgentRunResponseUpdate] = [] + async for update in agent.run_stream("Hello"): + updates.append(update) + + # Verify context provider was called + assert mock_provider.model_invoking_called + assert mock_provider.thread_created_called + assert mock_provider.messages_adding_called + + +async def test_chat_agent_multiple_context_providers(chat_client: ChatClientProtocol) -> None: + """Test that multiple context providers work together.""" + provider1 = MockContextProvider(contents=[TextContent("First provider instructions")]) + provider2 = MockContextProvider(contents=[TextContent("Second provider instructions")]) + + agent = ChatAgent(chat_client=chat_client, context_providers=[provider1, provider2]) + + await agent.run("Hello") + + # Both providers should be called + assert provider1.model_invoking_called + assert provider1.thread_created_called + assert provider1.messages_adding_called + + assert provider2.model_invoking_called + assert provider2.thread_created_called + assert provider2.messages_adding_called + + +async def test_chat_agent_aggregate_context_provider_combines_instructions() -> None: + """Test that AggregateContextProvider combines instructions from multiple providers.""" + provider1 = MockContextProvider(contents=[TextContent("First instruction")]) + provider2 = MockContextProvider(contents=[TextContent("Second instruction")]) + + aggregate = AggregateContextProvider() + aggregate.providers.append(provider1) + aggregate.providers.append(provider2) + + # Test model_invoking combines instructions + result = await aggregate.model_invoking([ChatMessage(role=Role.USER, text="Test")]) + + assert result.contents + assert isinstance(result.contents[0], TextContent) + assert isinstance(result.contents[1], TextContent) + assert result.contents[0].text == "First instruction" + assert result.contents[1].text == "Second instruction" + + +async def test_chat_agent_context_providers_with_thread_service_id(chat_client_base: ChatClientProtocol) -> None: + """Test context providers with service-managed thread.""" + mock_provider = MockContextProvider() + chat_client_base.run_responses = [ + ChatResponse( + messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent("test response")])], + conversation_id="service-thread-123", + ) + ] + + agent = ChatAgent(chat_client=chat_client_base, context_providers=mock_provider) + + # Use existing service-managed thread + thread = AgentThread(service_thread_id="existing-thread-id") + await agent.run("Hello", thread=thread) + + # messages_adding should be called with the service thread ID from response + assert mock_provider.messages_adding_called + assert mock_provider.messages_adding_thread_id == "service-thread-123" # Updated thread ID from response diff --git a/python/packages/main/tests/main/test_clients.py b/python/packages/main/tests/main/test_clients.py index 5d415bec91..d733362bc9 100644 --- a/python/packages/main/tests/main/test_clients.py +++ b/python/packages/main/tests/main/test_clients.py @@ -1,18 +1,15 @@ # Copyright (c) Microsoft. All rights reserved. -import asyncio import sys -from collections.abc import AsyncIterable, MutableSequence, Sequence +from collections.abc import Sequence from typing import Any -from pydantic import Field from pytest import fixture from agent_framework import ( BaseChatClient, ChatClientProtocol, ChatMessage, - ChatOptions, ChatResponse, ChatResponseUpdate, EmbeddingGenerator, @@ -22,81 +19,12 @@ from agent_framework import ( Role, TextContent, ai_function, - use_tool_calling, ) if sys.version_info >= (3, 12): - from typing import override # type: ignore + pass # type: ignore else: - from typing_extensions import override # type: ignore[import] - - -class MockChatClient: - """Simple implementation of a chat client.""" - - async def get_response( - self, - messages: ChatMessage | Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponse: - # Implement the method - - return ChatResponse(messages=ChatMessage(role="assistant", text="test response")) - - async def get_streaming_response( - self, - messages: ChatMessage | Sequence[ChatMessage], - **kwargs: Any, - ) -> AsyncIterable[ChatResponseUpdate]: - # Implement the method - yield ChatResponseUpdate(text=TextContent(text="test streaming response"), role="assistant") - yield ChatResponseUpdate(contents=[TextContent(text="another update")], role="assistant") - - -@use_tool_calling -class MockBaseChatClient(BaseChatClient): - """Mock implementation of the BaseChatClient.""" - - run_responses: list[ChatResponse] = Field(default_factory=list) - streaming_responses: list[list[ChatResponseUpdate]] = Field(default_factory=list) - - @override - async def _inner_get_response( - self, - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> ChatResponse: - """Send a chat request to the AI service. - - Args: - messages: The chat messages to send. - chat_options: The options for the request. - kwargs: Any additional keyword arguments. - - Returns: - The chat response contents representing the response(s). - """ - if not self.run_responses or chat_options.tool_choice == "none": - return ChatResponse(messages=ChatMessage(role="assistant", text=f"test response - {messages[0].text}")) - return self.run_responses.pop(0) - - @override - async def _inner_get_streaming_response( - self, - *, - messages: MutableSequence[ChatMessage], - chat_options: ChatOptions, - **kwargs: Any, - ) -> AsyncIterable[ChatResponseUpdate]: - if not self.streaming_responses or chat_options.tool_choice == "none": - yield ChatResponseUpdate(text=f"update - {messages[0].text}", role="assistant") - return - response = self.streaming_responses.pop(0) - for update in response: - yield update - await asyncio.sleep(0) + pass # type: ignore[import] class MockEmbeddingGenerator: @@ -114,35 +42,25 @@ class MockEmbeddingGenerator: return embeddings -@fixture -def chat_client() -> MockChatClient: - return MockChatClient() - - -@fixture -def chat_client_base() -> MockBaseChatClient: - return MockBaseChatClient() - - @fixture def embedding_generator() -> MockEmbeddingGenerator: gen: EmbeddingGenerator[str, list[float]] = MockEmbeddingGenerator() return gen -def test_chat_client_type(chat_client: MockChatClient): +def test_chat_client_type(chat_client: ChatClientProtocol): assert isinstance(chat_client, ChatClientProtocol) -async def test_chat_client_get_response(chat_client: MockChatClient): +async def test_chat_client_get_response(chat_client: ChatClientProtocol): response = await chat_client.get_response(ChatMessage(role="user", text="Hello")) assert response.text == "test response" assert response.messages[0].role == Role.ASSISTANT -async def test_chat_client_get_streaming_response(chat_client: MockChatClient): +async def test_chat_client_get_streaming_response(chat_client: ChatClientProtocol): async for update in chat_client.get_streaming_response(ChatMessage(role="user", text="Hello")): - assert update.text == "test streaming response" or update.text == "another update" + assert update.text == "test streaming response " or update.text == "another update" assert update.role == Role.ASSISTANT @@ -158,23 +76,23 @@ async def test_embedding_generator_generate(embedding_generator: MockEmbeddingGe assert len(emb) == 5 -def test_base_client(chat_client_base: MockBaseChatClient): +def test_base_client(chat_client_base: ChatClientProtocol): assert isinstance(chat_client_base, BaseChatClient) assert isinstance(chat_client_base, ChatClientProtocol) -async def test_base_client_get_response(chat_client_base: MockBaseChatClient): +async def test_base_client_get_response(chat_client_base: ChatClientProtocol): response = await chat_client_base.get_response(ChatMessage(role="user", text="Hello")) assert response.messages[0].role == Role.ASSISTANT assert response.messages[0].text == "test response - Hello" -async def test_base_client_get_streaming_response(chat_client_base: MockBaseChatClient): +async def test_base_client_get_streaming_response(chat_client_base: ChatClientProtocol): async for update in chat_client_base.get_streaming_response(ChatMessage(role="user", text="Hello")): assert update.text == "update - Hello" or update.text == "another update" -async def test_base_client_with_function_calling(chat_client_base: MockBaseChatClient): +async def test_base_client_with_function_calling(chat_client_base: ChatClientProtocol): exec_counter = 0 @ai_function(name="test_function") @@ -208,8 +126,7 @@ async def test_base_client_with_function_calling(chat_client_base: MockBaseChatC assert response.messages[2].text == "done" -async def test_base_client_with_function_calling_disabled(chat_client_base: MockBaseChatClient): - chat_client_base.__maximum_iterations_per_request = 0 +async def test_base_client_with_function_calling_resets(chat_client_base: ChatClientProtocol): exec_counter = 0 @ai_function(name="test_function") @@ -225,16 +142,32 @@ async def test_base_client_with_function_calling_disabled(chat_client_base: Mock contents=[FunctionCallContent(call_id="1", name="test_function", arguments='{"arg1": "value1"}')], ) ), + ChatResponse( + messages=ChatMessage( + role="assistant", + contents=[FunctionCallContent(call_id="2", name="test_function", arguments='{"arg1": "value1"}')], + ) + ), ChatResponse(messages=ChatMessage(role="assistant", text="done")), ] response = await chat_client_base.get_response("hello", tool_choice="auto", tools=[ai_func]) - assert exec_counter == 0 - assert len(response.messages) == 1 + assert exec_counter == 2 + assert len(response.messages) == 5 assert response.messages[0].role == Role.ASSISTANT - assert response.messages[0].text == "test response - hello" + assert response.messages[1].role == Role.TOOL + assert response.messages[2].role == Role.ASSISTANT + assert response.messages[3].role == Role.TOOL + assert response.messages[4].role == Role.ASSISTANT + assert isinstance(response.messages[0].contents[0], FunctionCallContent) + assert isinstance(response.messages[1].contents[0], FunctionResultContent) + assert isinstance(response.messages[2].contents[0], FunctionCallContent) + assert isinstance(response.messages[3].contents[0], FunctionResultContent) + # after these two responses, it would try another regular call, but since max_iterations is 1, it stops and calls + assert isinstance(response.messages[4].contents[0], TextContent) + assert response.text == "I broke out of the function invocation loop..." -async def test_base_client_with_streaming_function_calling(chat_client_base: MockBaseChatClient): +async def test_base_client_with_streaming_function_calling(chat_client_base: ChatClientProtocol): exec_counter = 0 @ai_function(name="test_function") @@ -270,38 +203,3 @@ async def test_base_client_with_streaming_function_calling(chat_client_base: Moc assert updates[2].contents[0].call_id == "1" assert updates[3].text == "Processed value1" assert exec_counter == 1 - - -async def test_base_client_with_streaming_function_calling_disabled(chat_client_base: MockBaseChatClient): - chat_client_base.__maximum_iterations_per_request = 0 - exec_counter = 0 - - @ai_function(name="test_function") - def ai_func(arg1: str) -> str: - nonlocal exec_counter - exec_counter += 1 - return f"Processed {arg1}" - - chat_client_base.streaming_responses = [ - [ - ChatResponseUpdate( - contents=[FunctionCallContent(call_id="1", name="test_function", arguments='{"arg1":')], - role="assistant", - ), - ChatResponseUpdate( - contents=[FunctionCallContent(call_id="1", name="test_function", arguments='"value1"}')], - role="assistant", - ), - ], - [ - ChatResponseUpdate( - contents=[TextContent(text="Processed value1")], - role="assistant", - ) - ], - ] - updates = [] - async for update in chat_client_base.get_streaming_response("hello", tool_choice="auto", tools=[ai_func]): - updates.append(update) - assert len(updates) == 1 - assert exec_counter == 0 diff --git a/python/packages/main/tests/main/test_logging.py b/python/packages/main/tests/main/test_logging.py index 2f7e40f17a..6565834596 100644 --- a/python/packages/main/tests/main/test_logging.py +++ b/python/packages/main/tests/main/test_logging.py @@ -22,7 +22,7 @@ def test_get_logger_custom_name(): def test_get_logger_invalid_name(): """Test that an exception is raised for an invalid logger name.""" - with pytest.raises(AgentFrameworkException, match="Logger name must start with 'agent_framework'."): + with pytest.raises(AgentFrameworkException): get_logger("invalid_name") diff --git a/python/packages/main/tests/main/test_memory.py b/python/packages/main/tests/main/test_memory.py new file mode 100644 index 0000000000..5c823066a2 --- /dev/null +++ b/python/packages/main/tests/main/test_memory.py @@ -0,0 +1,302 @@ +# Copyright (c) Microsoft. All rights reserved. + +from collections.abc import MutableSequence, Sequence +from unittest.mock import AsyncMock, Mock + +from agent_framework import ChatMessage, Contents, Role, TextContent +from agent_framework._memory import AggregateContextProvider, Context, ContextProvider + + +class MockContextProvider(ContextProvider): + """Mock ContextProvider for testing.""" + + context_contents: list[Contents] | None = None + thread_created_called: bool = False + messages_adding_called: bool = False + model_invoking_called: bool = False + thread_created_thread_id: str | None = None + messages_adding_thread_id: str | None = None + messages_adding_new_messages: ChatMessage | Sequence[ChatMessage] | None = None + model_invoking_messages: ChatMessage | MutableSequence[ChatMessage] | None = None + + def __init__(self, context_contents: list[Contents] | None = None) -> None: + super().__init__() + self.context_contents = context_contents + self.thread_created_called = False + self.messages_adding_called = False + self.model_invoking_called = False + self.thread_created_thread_id = None + self.messages_adding_thread_id = None + self.messages_adding_new_messages = None + self.model_invoking_messages = None + + async def thread_created(self, thread_id: str | None) -> None: + """Track thread_created calls.""" + self.thread_created_called = True + self.thread_created_thread_id = thread_id + + async def messages_adding(self, thread_id: str | None, new_messages: ChatMessage | Sequence[ChatMessage]) -> None: + """Track messages_adding calls.""" + self.messages_adding_called = True + self.messages_adding_thread_id = thread_id + self.messages_adding_new_messages = new_messages + + async def model_invoking(self, messages: ChatMessage | MutableSequence[ChatMessage]) -> Context: + """Track model_invoking calls and return context.""" + self.model_invoking_called = True + self.model_invoking_messages = messages + context = Context() + context.contents = self.context_contents + return context + + +class TestAggregateContextProvider: + """Tests for AggregateContextProvider class.""" + + def test_init_with_no_providers(self) -> None: + """Test initialization with no providers.""" + aggregate = AggregateContextProvider() + assert aggregate.providers == [] + + def test_init_with_none_providers(self) -> None: + """Test initialization with None providers.""" + aggregate = AggregateContextProvider(None) + assert aggregate.providers == [] + + def test_init_with_providers(self) -> None: + """Test initialization with providers.""" + provider1 = MockContextProvider([TextContent("instructions1")]) + provider2 = MockContextProvider([TextContent("instructions1")]) + providers = [provider1, provider2] + + aggregate = AggregateContextProvider(providers) + assert len(aggregate.providers) == 2 + assert aggregate.providers[0] is provider1 + assert aggregate.providers[1] is provider2 + + def test_add_provider(self) -> None: + """Test adding a provider.""" + aggregate = AggregateContextProvider() + provider = MockContextProvider([TextContent("instructions")]) + + aggregate.add(provider) + assert len(aggregate.providers) == 1 + assert aggregate.providers[0] is provider + + def test_add_multiple_providers(self) -> None: + """Test adding multiple providers.""" + aggregate = AggregateContextProvider() + provider1 = MockContextProvider([TextContent("instructions1")]) + provider2 = MockContextProvider([TextContent("instructions2")]) + + aggregate.add(provider1) + aggregate.add(provider2) + + assert len(aggregate.providers) == 2 + assert aggregate.providers[0] is provider1 + assert aggregate.providers[1] is provider2 + + async def test_thread_created_with_no_providers(self) -> None: + """Test thread_created with no providers.""" + aggregate = AggregateContextProvider() + + # Should not raise an exception + await aggregate.thread_created("thread-123") + + async def test_thread_created_with_providers(self) -> None: + """Test thread_created calls all providers.""" + provider1 = MockContextProvider([TextContent("instructions1")]) + provider2 = MockContextProvider([TextContent("instructions2")]) + aggregate = AggregateContextProvider([provider1, provider2]) + + thread_id = "thread-123" + await aggregate.thread_created(thread_id) + + assert provider1.thread_created_called + assert provider1.thread_created_thread_id == thread_id + assert provider2.thread_created_called + assert provider2.thread_created_thread_id == thread_id + + async def test_thread_created_with_none_thread_id(self) -> None: + """Test thread_created with None thread_id.""" + provider = MockContextProvider([TextContent("instructions")]) + aggregate = AggregateContextProvider([provider]) + + await aggregate.thread_created(None) + + assert provider.thread_created_called + assert provider.thread_created_thread_id is None + + async def test_messages_adding_with_no_providers(self) -> None: + """Test messages_adding with no providers.""" + aggregate = AggregateContextProvider() + message = ChatMessage(text="Hello", role=Role.USER) + + # Should not raise an exception + await aggregate.messages_adding("thread-123", message) + + async def test_messages_adding_with_single_message(self) -> None: + """Test messages_adding with a single message.""" + provider1 = MockContextProvider([TextContent("instructions1")]) + provider2 = MockContextProvider([TextContent("instructions2")]) + aggregate = AggregateContextProvider([provider1, provider2]) + + thread_id = "thread-123" + message = ChatMessage(text="Hello", role=Role.USER) + await aggregate.messages_adding(thread_id, message) + + assert provider1.messages_adding_called + assert provider1.messages_adding_thread_id == thread_id + assert provider1.messages_adding_new_messages == message + assert provider2.messages_adding_called + assert provider2.messages_adding_thread_id == thread_id + assert provider2.messages_adding_new_messages == message + + async def test_messages_adding_with_message_sequence(self) -> None: + """Test messages_adding with a sequence of messages.""" + provider = MockContextProvider([TextContent("instructions")]) + aggregate = AggregateContextProvider([provider]) + + thread_id = "thread-123" + messages = [ + ChatMessage(text="Hello", role=Role.USER), + ChatMessage(text="Hi there", role=Role.ASSISTANT), + ] + await aggregate.messages_adding(thread_id, messages) + + assert provider.messages_adding_called + assert provider.messages_adding_thread_id == thread_id + assert provider.messages_adding_new_messages == messages + + async def test_model_invoking_with_no_providers(self) -> None: + """Test model_invoking with no providers.""" + aggregate = AggregateContextProvider() + message = ChatMessage(text="Hello", role=Role.USER) + + context = await aggregate.model_invoking(message) + + assert isinstance(context, Context) + assert not context.contents + + async def test_model_invoking_with_single_provider(self) -> None: + """Test model_invoking with a single provider.""" + provider = MockContextProvider([TextContent("Test instructions")]) + aggregate = AggregateContextProvider([provider]) + + message = ChatMessage(text="Hello", role=Role.USER) + context = await aggregate.model_invoking(message) + + assert provider.model_invoking_called + assert provider.model_invoking_messages == message + assert isinstance(context, Context) + + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert context.contents[0].text == "Test instructions" + + async def test_model_invoking_with_multiple_providers(self) -> None: + """Test model_invoking combines contexts from multiple providers.""" + provider1 = MockContextProvider([TextContent("Instructions 1")]) + provider2 = MockContextProvider([TextContent("Instructions 2")]) + provider3 = MockContextProvider([TextContent("Instructions 3")]) + aggregate = AggregateContextProvider([provider1, provider2, provider3]) + + messages = [ChatMessage(text="Hello", role=Role.USER)] + context = await aggregate.model_invoking(messages) + + assert provider1.model_invoking_called + assert provider1.model_invoking_messages == messages + assert provider2.model_invoking_called + assert provider2.model_invoking_messages == messages + assert provider3.model_invoking_called + assert provider3.model_invoking_messages == messages + + assert isinstance(context, Context) + + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert isinstance(context.contents[1], TextContent) + assert isinstance(context.contents[2], TextContent) + assert context.contents[0].text == "Instructions 1" + assert context.contents[1].text == "Instructions 2" + assert context.contents[2].text == "Instructions 3" + + async def test_model_invoking_with_none_instructions(self) -> None: + """Test model_invoking filters out None instructions.""" + provider1 = MockContextProvider([TextContent("Instructions 1")]) + provider2 = MockContextProvider(None) # None instructions + provider3 = MockContextProvider([TextContent("Instructions 3")]) + aggregate = AggregateContextProvider([provider1, provider2, provider3]) + + message = ChatMessage(text="Hello", role=Role.USER) + context = await aggregate.model_invoking(message) + + assert isinstance(context, Context) + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert isinstance(context.contents[1], TextContent) + assert context.contents[0].text == "Instructions 1" + assert context.contents[1].text == "Instructions 3" + + async def test_model_invoking_with_all_none_instructions(self) -> None: + """Test model_invoking when all providers return None instructions.""" + provider1 = MockContextProvider(None) + provider2 = MockContextProvider(None) + aggregate = AggregateContextProvider([provider1, provider2]) + + message = ChatMessage(text="Hello", role=Role.USER) + context = await aggregate.model_invoking(message) + + assert isinstance(context, Context) + assert not context.contents + + async def test_model_invoking_with_mutable_sequence(self) -> None: + """Test model_invoking with MutableSequence of messages.""" + provider = MockContextProvider([TextContent("Test instructions")]) + aggregate = AggregateContextProvider([provider]) + + messages = [ChatMessage(text="Hello", role=Role.USER)] + context = await aggregate.model_invoking(messages) + + assert provider.model_invoking_called + assert provider.model_invoking_messages == messages + assert isinstance(context, Context) + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert context.contents[0].text == "Test instructions" + + async def test_async_methods_concurrent_execution(self) -> None: + """Test that async methods execute providers concurrently.""" + # Use AsyncMock to verify concurrent execution + provider1 = Mock(spec=ContextProvider) + provider1.thread_created = AsyncMock() + provider1.messages_adding = AsyncMock() + provider1.model_invoking = AsyncMock(return_value=Context(contents=[TextContent("Test 1")])) + + provider2 = Mock(spec=ContextProvider) + provider2.thread_created = AsyncMock() + provider2.messages_adding = AsyncMock() + provider2.model_invoking = AsyncMock(return_value=Context(contents=[TextContent("Test 2")])) + + aggregate = AggregateContextProvider([provider1, provider2]) + + # Test thread_created + await aggregate.thread_created("thread-123") + provider1.thread_created.assert_called_once_with("thread-123") + provider2.thread_created.assert_called_once_with("thread-123") + + # Test messages_adding + message = ChatMessage(text="Hello", role=Role.USER) + await aggregate.messages_adding("thread-123", message) + provider1.messages_adding.assert_called_once_with("thread-123", message) + provider2.messages_adding.assert_called_once_with("thread-123", message) + + # Test model_invoking + context = await aggregate.model_invoking(message) + provider1.model_invoking.assert_called_once_with(message) + provider2.model_invoking.assert_called_once_with(message) + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert isinstance(context.contents[1], TextContent) + assert context.contents[0].text == "Test 1" + assert context.contents[1].text == "Test 2" diff --git a/python/packages/main/tests/main/test_telemetry.py b/python/packages/main/tests/main/test_telemetry.py index 8936decfcc..597961488e 100644 --- a/python/packages/main/tests/main/test_telemetry.py +++ b/python/packages/main/tests/main/test_telemetry.py @@ -1,14 +1,19 @@ # Copyright (c) Microsoft. All rights reserved. import logging -from collections.abc import AsyncIterable, MutableSequence +from collections.abc import MutableSequence from typing import Any -from unittest.mock import Mock, patch +from unittest.mock import MagicMock, Mock, patch import pytest +from opentelemetry.semconv_ai import SpanAttributes from opentelemetry.trace import StatusCode from agent_framework import ( + AgentProtocol, + AgentRunResponse, + AgentThread, + BaseChatClient, ChatMessage, ChatOptions, ChatResponse, @@ -16,15 +21,19 @@ from agent_framework import ( Role, UsageDetails, ) +from agent_framework.exceptions import AgentInitializationError, ChatClientInitializationError from agent_framework.telemetry import ( AGENT_FRAMEWORK_USER_AGENT, + OPEN_TELEMETRY_AGENT_MARKER, + OPEN_TELEMETRY_CHAT_CLIENT_MARKER, ROLE_EVENT_MAP, - TELEMETRY_DISABLED_ENV_VAR, USER_AGENT_KEY, + USER_AGENT_TELEMETRY_DISABLED_ENV_VAR, ChatMessageListTimestampFilter, - GenAIAttributes, + OtelAttr, + get_function_span, prepend_agent_framework_to_user_agent, - start_as_current_span, + use_agent_telemetry, use_telemetry, ) @@ -33,7 +42,7 @@ from agent_framework.telemetry import ( def test_telemetry_disabled_env_var(): """Test that the telemetry disabled environment variable is correctly defined.""" - assert TELEMETRY_DISABLED_ENV_VAR == "AZURE_TELEMETRY_DISABLED" + assert USER_AGENT_TELEMETRY_DISABLED_ENV_VAR == "AGENT_FRAMEWORK_USER_AGENT_DISABLED" def test_user_agent_key(): @@ -78,20 +87,20 @@ def test_app_info_when_telemetry_disabled(): def test_role_event_map(): """Test that ROLE_EVENT_MAP contains expected mappings.""" - assert ROLE_EVENT_MAP["system"] == GenAIAttributes.SYSTEM_MESSAGE.value - assert ROLE_EVENT_MAP["user"] == GenAIAttributes.USER_MESSAGE.value - assert ROLE_EVENT_MAP["assistant"] == GenAIAttributes.ASSISTANT_MESSAGE.value - assert ROLE_EVENT_MAP["tool"] == GenAIAttributes.TOOL_MESSAGE.value + assert ROLE_EVENT_MAP["system"] == OtelAttr.SYSTEM_MESSAGE + assert ROLE_EVENT_MAP["user"] == OtelAttr.USER_MESSAGE + assert ROLE_EVENT_MAP["assistant"] == OtelAttr.ASSISTANT_MESSAGE + assert ROLE_EVENT_MAP["tool"] == OtelAttr.TOOL_MESSAGE def test_enum_values(): - """Test that GenAIAttributes enum has expected values.""" - assert GenAIAttributes.OPERATION.value == "gen_ai.operation.name" - assert GenAIAttributes.SYSTEM.value == "gen_ai.system" - assert GenAIAttributes.MODEL.value == "gen_ai.request.model" - assert GenAIAttributes.CHAT_COMPLETION_OPERATION.value == "chat" - assert GenAIAttributes.TOOL_EXECUTION_OPERATION.value == "execute_tool" - assert GenAIAttributes.AGENT_INVOKE_OPERATION.value == "invoke_agent" + """Test that OtelAttr enum has expected values.""" + assert OtelAttr.OPERATION == "gen_ai.operation.name" + assert SpanAttributes.LLM_SYSTEM == "gen_ai.system" + assert SpanAttributes.LLM_REQUEST_MODEL == "gen_ai.request.model" + assert OtelAttr.CHAT_COMPLETION_OPERATION == "chat" + assert OtelAttr.TOOL_EXECUTION_OPERATION == "execute_tool" + assert OtelAttr.AGENT_INVOKE_OPERATION == "invoke_agent" # region Test prepend_agent_framework_to_user_agent @@ -135,47 +144,6 @@ def test_modifies_original_dict(): assert "User-Agent" in headers -# region ModelDiagnosticSettings tests - - -@pytest.mark.parametrize("model_diagnostic_settings", [(None, None)], indirect=True) -def test_default_values(model_diagnostic_settings): - """Test default values for ModelDiagnosticSettings.""" - assert not model_diagnostic_settings.ENABLED - assert not model_diagnostic_settings.SENSITIVE_EVENTS_ENABLED - - -@pytest.mark.parametrize("model_diagnostic_settings", [(False, False)], indirect=True) -def test_disabled(model_diagnostic_settings): - """Test default values for ModelDiagnosticSettings.""" - assert not model_diagnostic_settings.ENABLED - assert not model_diagnostic_settings.SENSITIVE_EVENTS_ENABLED - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -def test_non_sensitive_events_enabled(model_diagnostic_settings): - """Test loading model_diagnostic_settings from environment variables.""" - assert model_diagnostic_settings.ENABLED - assert not model_diagnostic_settings.SENSITIVE_EVENTS_ENABLED - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, True)], indirect=True) -def test_sensitive_events_enabled(model_diagnostic_settings): - """Test loading model_diagnostic_settings from environment variables.""" - assert model_diagnostic_settings.ENABLED - assert model_diagnostic_settings.SENSITIVE_EVENTS_ENABLED - - -@pytest.mark.parametrize("model_diagnostic_settings", [(False, True)], indirect=True) -def test_sensitive_events_enabled_only(model_diagnostic_settings): - """Test loading sensitive events setting from environment. - - But when sensitive events are enabled, diagnostics are also enabled. - """ - assert model_diagnostic_settings.ENABLED - assert model_diagnostic_settings.SENSITIVE_EVENTS_ENABLED - - # region Test ChatMessageListTimestampFilter @@ -213,88 +181,74 @@ def test_filter_with_index_key(): def test_index_key_constant(): """Test that INDEX_KEY constant is correctly defined.""" - assert ChatMessageListTimestampFilter.INDEX_KEY == "CHAT_MESSAGE_INDEX" + assert ChatMessageListTimestampFilter.INDEX_KEY == "chat_message_index" -# region Test start_as_current_span +# region Test get_function_span def test_start_span_basic(): """Test starting a span with basic function info.""" mock_tracer = Mock() - mock_span = Mock() - mock_tracer.start_as_current_span.return_value = mock_span + with patch("agent_framework.telemetry.tracer", mock_tracer): + mock_span = Mock() + mock_tracer.start_as_current_span.return_value = mock_span - # Create a mock function - mock_function = Mock() - mock_function.name = "test_function" - mock_function.description = "Test function description" + # Create a mock function + mock_function = Mock() + mock_function.name = "test_function" + mock_function.description = "Test function description" - result = start_as_current_span(mock_tracer, mock_function) + result = get_function_span(mock_function) - assert result == mock_span - mock_tracer.start_as_current_span.assert_called_once() + assert result == mock_span + mock_tracer.start_as_current_span.assert_called_once() - call_args = mock_tracer.start_as_current_span.call_args - assert call_args[0][0] == "execute_tool test_function" + call_args = mock_tracer.start_as_current_span.call_args + assert call_args[1]["name"] == "execute_tool test_function" - attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.OPERATION.value] == GenAIAttributes.TOOL_EXECUTION_OPERATION.value - assert attributes[GenAIAttributes.TOOL_NAME.value] == "test_function" - assert attributes[GenAIAttributes.TOOL_DESCRIPTION.value] == "Test function description" + attributes = call_args[1]["attributes"] + assert attributes[OtelAttr.OPERATION.value] == OtelAttr.TOOL_EXECUTION_OPERATION + assert attributes[OtelAttr.TOOL_NAME] == "test_function" + assert attributes[OtelAttr.TOOL_DESCRIPTION] == "Test function description" -def test_start_span_with_metadata(): - """Test starting a span with metadata containing tool_call_id.""" +def test_start_span_with_tool_call_id(): + """Test starting a span with tool_call_id.""" mock_tracer = Mock() - mock_span = Mock() - mock_tracer.start_as_current_span.return_value = mock_span + with patch("agent_framework.telemetry.tracer", mock_tracer): + mock_span = Mock() + mock_tracer.start_as_current_span.return_value = mock_span - mock_function = Mock() - mock_function.name = "test_function" - mock_function.description = "Test function" + mock_function = Mock() + mock_function.name = "test_function" + mock_function.description = "Test function" - metadata = {"tool_call_id": "test_call_123"} + tool_call_id = "test_call_123" - _ = start_as_current_span(mock_tracer, mock_function, metadata) + _ = get_function_span(mock_function, tool_call_id) - call_args = mock_tracer.start_as_current_span.call_args - attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.TOOL_CALL_ID.value] == "test_call_123" + call_args = mock_tracer.start_as_current_span.call_args + attributes = call_args[1]["attributes"] + assert attributes[OtelAttr.TOOL_CALL_ID] == "test_call_123" def test_start_span_without_description(): """Test starting a span when function has no description.""" mock_tracer = Mock() - mock_span = Mock() - mock_tracer.start_as_current_span.return_value = mock_span + with patch("agent_framework.telemetry.tracer", mock_tracer): + mock_span = Mock() + mock_tracer.start_as_current_span.return_value = mock_span - mock_function = Mock() - mock_function.name = "test_function" - mock_function.description = None + mock_function = Mock() + mock_function.name = "test_function" + mock_function.description = None - start_as_current_span(mock_tracer, mock_function) + get_function_span(mock_function) - call_args = mock_tracer.start_as_current_span.call_args - attributes = call_args[1]["attributes"] - assert GenAIAttributes.TOOL_DESCRIPTION.value not in attributes - - -def test_start_span_empty_metadata(): - """Test starting a span with empty metadata.""" - mock_tracer = Mock() - mock_span = Mock() - mock_tracer.start_as_current_span.return_value = mock_span - - mock_function = Mock() - mock_function.name = "test_function" - mock_function.description = "Test function" - - start_as_current_span(mock_tracer, mock_function, {}) - - call_args = mock_tracer.start_as_current_span.call_args - attributes = call_args[1]["attributes"] - assert GenAIAttributes.TOOL_CALL_ID.value not in attributes + call_args = mock_tracer.start_as_current_span.call_args + attributes = call_args[1]["attributes"] + assert OtelAttr.TOOL_DESCRIPTION not in attributes # region Test use_telemetry decorator @@ -305,12 +259,10 @@ def test_decorator_with_valid_class(): # Create a mock class with the required methods class MockChatClient: - MODEL_PROVIDER_NAME = "test_provider" - - async def _inner_get_response(self, *, messages, chat_options, **kwargs): + async def get_response(self, messages, **kwargs): return Mock() - async def _inner_get_streaming_response(self, *, messages, chat_options, **kwargs): + async def get_streaming_response(self, messages, **kwargs): async def gen(): yield Mock() @@ -318,39 +270,31 @@ def test_decorator_with_valid_class(): # Apply the decorator decorated_class = use_telemetry(MockChatClient) - - # Check that the methods were wrapped - assert hasattr(decorated_class._inner_get_response, "__model_diagnostics_chat_client__") - assert hasattr(decorated_class._inner_get_streaming_response, "__model_diagnostics_streaming_chat_completion__") + assert hasattr(decorated_class, OPEN_TELEMETRY_CHAT_CLIENT_MARKER) def test_decorator_with_missing_methods(): """Test that decorator handles classes missing required methods gracefully.""" class MockChatClient: - MODEL_PROVIDER_NAME = "test_provider" + OTEL_PROVIDER_NAME = "test_provider" # Apply the decorator - should not raise an error - decorated_class = use_telemetry(MockChatClient) - - # Class should be returned unchanged - assert decorated_class is MockChatClient + with pytest.raises(ChatClientInitializationError): + use_telemetry(MockChatClient) def test_decorator_with_partial_methods(): """Test decorator when only one method is present.""" class MockChatClient: - MODEL_PROVIDER_NAME = "test_provider" + OTEL_PROVIDER_NAME = "test_provider" - async def _inner_get_response(self, *, messages, chat_options, **kwargs): + async def get_response(self, messages, **kwargs): return Mock() - decorated_class = use_telemetry(MockChatClient) - - # Only the present method should be wrapped - assert hasattr(decorated_class._inner_get_response, "__model_diagnostics_chat_client__") - assert not hasattr(decorated_class, "_inner_get_streaming_response") + with pytest.raises(ChatClientInitializationError): + use_telemetry(MockChatClient) # region Test telemetry decorator with mock client @@ -360,12 +304,7 @@ def test_decorator_with_partial_methods(): def mock_chat_client(): """Create a mock chat client for testing.""" - class MockChatClient: - MODEL_PROVIDER_NAME = "test_provider" - - def __init__(self): - self.ai_model_id = "test-model" - + class MockChatClient(BaseChatClient): def service_url(self): return "https://test.example.com" @@ -384,223 +323,77 @@ def mock_chat_client(): yield ChatResponseUpdate(text="Hello", role=Role.ASSISTANT) yield ChatResponseUpdate(text=" world", role=Role.ASSISTANT) - return MockChatClient() + return MockChatClient -@pytest.mark.parametrize("model_diagnostic_settings", [(False, False)], indirect=True) -async def test_telemetry_disabled_bypasses_instrumentation(mock_chat_client, model_diagnostic_settings): - """Test that when diagnostics are disabled, telemetry is bypassed.""" - decorated_class = use_telemetry(type(mock_chat_client)) - client = decorated_class() - - messages = [ChatMessage(role=Role.USER, text="Test message")] - chat_options = ChatOptions() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - ): - # This should not create any spans - response = await client._inner_get_response(messages=messages, chat_options=chat_options) - assert response is not None - mock_use_span.assert_not_called() - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, True)], indirect=True) -async def test_instrumentation_enabled(mock_chat_client, model_diagnostic_settings): +@pytest.mark.parametrize("enable_sensitive_data", [True, False], indirect=True) +async def test_instrumentation_enabled(mock_chat_client, otel_settings): """Test that when diagnostics are enabled, telemetry is applied.""" - decorated_class = use_telemetry(type(mock_chat_client)) - client = decorated_class() + client = use_telemetry(mock_chat_client)() messages = [ChatMessage(role=Role.USER, text="Test message")] chat_options = ChatOptions() with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry.logger") as mock_logger, + patch("agent_framework.telemetry._get_span") as mock_response_span, + patch("agent_framework.telemetry._capture_messages") as mock_log_messages, ): - response = await client._inner_get_response(messages=messages, chat_options=chat_options) + response = await client.get_response(messages=messages, chat_options=chat_options) assert response is not None - mock_use_span.assert_called_once() - # Check that logger.info was called (telemetry logs input/output) - assert mock_logger.info.call_count == 2 + mock_response_span.assert_called_once() + + # Check that log messages was called only if sensitive events are enabled + assert mock_log_messages.call_count == (2 if otel_settings.enable_sensitive_data else 0) -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_streaming_response_with_diagnostics_enabled_via_decorator(mock_chat_client, model_diagnostic_settings): +@pytest.mark.parametrize("enable_sensitive_data", [True, False], indirect=True) +async def test_streaming_response_with_otel(mock_chat_client, otel_settings): """Test streaming telemetry through the use_telemetry decorator.""" - decorated_class = use_telemetry(type(mock_chat_client)) - client = decorated_class() + client = use_telemetry(mock_chat_client)() messages = [ChatMessage(role=Role.USER, text="Test")] chat_options = ChatOptions() with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_chat_response_span") as mock_get_span, - patch("agent_framework.telemetry._set_chat_response_input") as mock_set_input, - patch("agent_framework.telemetry._set_chat_response_output") as mock_set_output, + patch("agent_framework.telemetry._get_span") as mock_response_span, + patch("agent_framework.telemetry._capture_messages") as mock_log_messages, + patch("agent_framework.telemetry._capture_response") as mock_set_output, ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # We can't easily mock ChatResponse.from_chat_response_updates since it's imported locally, - # but we can verify telemetry calls were made - # Collect all yielded updates updates = [] - async for update in client._inner_get_streaming_response(messages=messages, chat_options=chat_options): + async for update in client.get_streaming_response(messages=messages, chat_options=chat_options): updates.append(update) - # Verify we got the expected updates + # Verify we got the expected updates, this shouldn't be dependent on otel assert len(updates) == 2 # Verify telemetry calls were made - mock_get_span.assert_called_once() - mock_set_input.assert_called_once_with("test_provider", messages) - mock_set_output.assert_called_once() + mock_response_span.assert_called_once() + if otel_settings.enable_sensitive_data: + mock_log_messages.assert_called() + assert mock_log_messages.call_count == 2 # One for input, one for output + else: + mock_log_messages.assert_not_called() - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_streaming_response_with_exception_via_decorator(mock_chat_client, model_diagnostic_settings): - """Test streaming telemetry exception handling through decorator.""" - - async def _inner_get_streaming_response( - self, *, messages: MutableSequence[ChatMessage], chat_options: ChatOptions, **kwargs: Any - ) -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(text="Partial", role=Role.ASSISTANT) - raise ValueError("Test streaming error") - - type(mock_chat_client)._inner_get_streaming_response = _inner_get_streaming_response - - decorated_class = use_telemetry(type(mock_chat_client)) - client = decorated_class() - - messages = [ChatMessage(role=Role.USER, text="Test")] - chat_options = ChatOptions() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_chat_response_span"), - patch("agent_framework.telemetry._set_chat_response_input"), - patch("agent_framework.telemetry._set_error") as mock_set_error, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # Should raise the exception and call error handler - with pytest.raises(ValueError, match="Test streaming error"): - async for _ in client._inner_get_streaming_response(messages=messages, chat_options=chat_options): - pass - - # Verify error was recorded - mock_set_error.assert_called_once() - assert isinstance(mock_set_error.call_args[0][1], ValueError) - - -@pytest.mark.parametrize("model_diagnostic_settings", [(False, False)], indirect=True) -async def test_streaming_response_diagnostics_disabled_via_decorator(model_diagnostic_settings): - """Test streaming response when diagnostics are disabled.""" - from agent_framework import ChatResponseUpdate - - class MockStreamingClientNoDiagnostics: - MODEL_PROVIDER_NAME = "test_provider" - - async def _inner_get_streaming_response( - self, *, messages: MutableSequence[ChatMessage], chat_options: ChatOptions, **kwargs: Any - ) -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(text="Test", role=Role.ASSISTANT) - - decorated_class = use_telemetry(MockStreamingClientNoDiagnostics) - client = decorated_class() - - messages = [ChatMessage(role=Role.USER, text="Test")] - chat_options = ChatOptions() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry._get_chat_response_span") as mock_get_span, - ): - # Should not create spans when diagnostics are disabled - updates = [] - async for update in client._inner_get_streaming_response(messages=messages, chat_options=chat_options): - updates.append(update) - - assert len(updates) == 1 - # Should not have called telemetry functions - mock_get_span.assert_not_called() - - -# region Test empty streaming response handling - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_empty_streaming_response_via_decorator(model_diagnostic_settings): - """Test streaming wrapper with empty response.""" - - class MockEmptyStreamingClient: - MODEL_PROVIDER_NAME = "test_provider" - - def __init__(self): - self.ai_model_id = "test_model" - - def service_url(self) -> str: - return "https://test.com" - - async def _inner_get_streaming_response( - self, *, messages: MutableSequence[ChatMessage], chat_options: ChatOptions, **kwargs: Any - ) -> AsyncIterable[ChatResponseUpdate]: - # Return empty stream - return - yield # This will never be reached - - decorated_class = use_telemetry(MockEmptyStreamingClient) - client = decorated_class() - - messages = [ChatMessage(role=Role.USER, text="Test")] - chat_options = ChatOptions() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_chat_response_span"), - patch("agent_framework.telemetry._set_chat_response_input"), - patch("agent_framework.telemetry._set_chat_response_output") as mock_set_output, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # Should handle empty stream gracefully - updates = [] - async for update in client._inner_get_streaming_response(messages=messages, chat_options=chat_options): - updates.append(update) - - assert len(updates) == 0 - # Should still call telemetry mock_set_output.assert_called_once() def test_start_as_current_span_with_none_metadata(): - """Test start_as_current_span with None metadata.""" + """Test get_function_span with None metadata.""" mock_tracer = Mock() - mock_span = Mock() - mock_tracer.start_as_current_span.return_value = mock_span + with patch("agent_framework.telemetry.tracer", mock_tracer): + mock_span = Mock() + mock_tracer.start_as_current_span.return_value = mock_span - mock_function = Mock() - mock_function.name = "test_function" - mock_function.description = "Test description" + mock_function = Mock() + mock_function.name = "test_function" + mock_function.description = "Test description" - result = start_as_current_span(mock_tracer, mock_function, None) + result = get_function_span(mock_function, None) - assert result == mock_span - call_args = mock_tracer.start_as_current_span.call_args - attributes = call_args[1]["attributes"] - assert GenAIAttributes.TOOL_CALL_ID.value not in attributes + assert result == mock_span + call_args = mock_tracer.start_as_current_span.call_args + attributes = call_args[1]["attributes"] + assert attributes[OtelAttr.TOOL_CALL_ID] == "unknown" def test_prepend_user_agent_with_none_value(): @@ -618,7 +411,6 @@ def test_prepend_user_agent_with_none_value(): def test_agent_decorator_with_valid_class(): """Test that agent decorator works with a valid ChatAgent-like class.""" - from agent_framework.telemetry import use_agent_telemetry # Create a mock class with the required methods class MockChatClientAgent: @@ -639,33 +431,31 @@ def test_agent_decorator_with_valid_class(): return gen() + def get_new_thread(self) -> AgentThread: + return AgentThread() + # Apply the decorator decorated_class = use_agent_telemetry(MockChatClientAgent) - # Check that the methods were wrapped - assert hasattr(decorated_class.run, "__model_diagnostics_agent_run__") - assert hasattr(decorated_class.run_stream, "__model_diagnostics_streaming_agent_run__") + assert hasattr(decorated_class, OPEN_TELEMETRY_AGENT_MARKER) def test_agent_decorator_with_missing_methods(): """Test that agent decorator handles classes missing required methods gracefully.""" - from agent_framework.telemetry import use_agent_telemetry - class MockChatClientAgent: + class MockAgent: AGENT_SYSTEM_NAME = "test_agent_system" # Apply the decorator - should not raise an error - decorated_class = use_agent_telemetry(MockChatClientAgent) - - # Class should be returned unchanged - assert decorated_class is MockChatClientAgent + with pytest.raises(AgentInitializationError): + use_agent_telemetry(MockAgent) def test_agent_decorator_with_partial_methods(): """Test agent decorator when only one method is present.""" from agent_framework.telemetry import use_agent_telemetry - class MockChatClientAgent: + class MockAgent: AGENT_SYSTEM_NAME = "test_agent_system" def __init__(self): @@ -676,11 +466,8 @@ def test_agent_decorator_with_partial_methods(): async def run(self, messages=None, *, thread=None, **kwargs): return Mock() - decorated_class = use_agent_telemetry(MockChatClientAgent) - - # Only the present method should be wrapped - assert hasattr(decorated_class.run, "__model_diagnostics_agent_run__") - assert not hasattr(decorated_class, "run_stream") + with pytest.raises(AgentInitializationError): + use_agent_telemetry(MockAgent) # region Test agent telemetry decorator with mock agent @@ -689,7 +476,6 @@ def test_agent_decorator_with_partial_methods(): @pytest.fixture def mock_chat_client_agent(): """Create a mock chat client agent for testing.""" - from agent_framework import AgentRunResponse, ChatMessage, Role, UsageDetails class MockChatClientAgent: AGENT_SYSTEM_NAME = "test_agent_system" @@ -714,37 +500,16 @@ def mock_chat_client_agent(): yield AgentRunResponseUpdate(text="Hello", role=Role.ASSISTANT) yield AgentRunResponseUpdate(text=" from agent", role=Role.ASSISTANT) - return MockChatClientAgent() + return MockChatClientAgent -@pytest.mark.parametrize("model_diagnostic_settings", [(False, False)], indirect=True) -async def test_agent_telemetry_disabled_bypasses_instrumentation(mock_chat_client_agent, model_diagnostic_settings): - """Test that when agent diagnostics are disabled, telemetry is bypassed.""" - from agent_framework.telemetry import use_agent_telemetry - - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - ): - # This should not create any spans - response = await agent.run("Test message") - assert response is not None - mock_use_span.assert_not_called() - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, True)], indirect=True) -async def test_agent_instrumentation_enabled(mock_chat_client_agent, model_diagnostic_settings): +@pytest.mark.parametrize("enable_sensitive_data", [True, False], indirect=True) +async def test_agent_instrumentation_enabled(mock_chat_client_agent: AgentProtocol, otel_settings): """Test that when agent diagnostics are enabled, telemetry is applied.""" - from agent_framework.telemetry import use_agent_telemetry - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() + agent = use_agent_telemetry(mock_chat_client_agent)() with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), patch("agent_framework.telemetry.use_span") as mock_use_span, patch("agent_framework.telemetry.logger") as mock_logger, ): @@ -752,30 +517,21 @@ async def test_agent_instrumentation_enabled(mock_chat_client_agent, model_diagn assert response is not None mock_use_span.assert_called_once() # Check that logger.info was called (telemetry logs input/output) - assert mock_logger.info.call_count == 2 + assert mock_logger.info.call_count == (2 if otel_settings.enable_sensitive_data else 0) -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) +@pytest.mark.parametrize("enable_sensitive_data", [True, False], indirect=True) async def test_agent_streaming_response_with_diagnostics_enabled_via_decorator( - mock_chat_client_agent, model_diagnostic_settings + mock_chat_client_agent: AgentProtocol, otel_settings ): """Test agent streaming telemetry through the use_agent_telemetry decorator.""" - from agent_framework.telemetry import use_agent_telemetry - - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() + agent = use_agent_telemetry(mock_chat_client_agent)() with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_agent_run_span") as mock_get_span, - patch("agent_framework.telemetry._set_agent_run_input") as mock_set_input, - patch("agent_framework.telemetry._set_agent_run_output") as mock_set_output, + patch("agent_framework.telemetry._get_span") as mock_get_span, + patch("agent_framework.telemetry._capture_messages") as mock_capture_messages, + patch("agent_framework.telemetry._capture_response") as mock_capture_response, ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - # Collect all yielded updates updates = [] async for update in agent.run_stream("Test message"): @@ -786,219 +542,39 @@ async def test_agent_streaming_response_with_diagnostics_enabled_via_decorator( # Verify telemetry calls were made mock_get_span.assert_called_once() - mock_set_input.assert_called_once_with("test_agent_system", "Test message") - mock_set_output.assert_called_once() + mock_capture_response.assert_called_once() + if otel_settings.enable_sensitive_data: + mock_capture_messages.assert_called() + else: + mock_capture_messages.assert_not_called() -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_agent_streaming_response_with_exception_via_decorator(mock_chat_client_agent, model_diagnostic_settings): - """Test agent streaming telemetry exception handling through decorator.""" - from agent_framework.telemetry import use_agent_telemetry - - async def run_stream(self, messages=None, *, thread=None, **kwargs): - from agent_framework import AgentRunResponseUpdate, Role - - yield AgentRunResponseUpdate(text="Partial", role=Role.ASSISTANT) - raise ValueError("Test agent streaming error") - - type(mock_chat_client_agent).run_stream = run_stream - - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_agent_run_span"), - patch("agent_framework.telemetry._set_agent_run_input"), - patch("agent_framework.telemetry._set_error") as mock_set_error, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # Should raise the exception and call error handler - with pytest.raises(ValueError, match="Test agent streaming error"): - async for _ in agent.run_stream("Test message"): - pass - - # Verify error was recorded - mock_set_error.assert_called_once() - assert isinstance(mock_set_error.call_args[0][1], ValueError) - - -@pytest.mark.parametrize("model_diagnostic_settings", [(False, False)], indirect=True) -async def test_agent_streaming_response_diagnostics_disabled_via_decorator(model_diagnostic_settings): - """Test agent streaming response when diagnostics are disabled.""" - from agent_framework import AgentRunResponseUpdate, Role - from agent_framework.telemetry import use_agent_telemetry - - class MockStreamingAgentNoDiagnostics: - AGENT_SYSTEM_NAME = "test_agent_system" - - def __init__(self): - self.id = "test_agent_id" - self.name = "test_agent" - self.display_name = "Test Agent" - - async def run_stream(self, messages=None, *, thread=None, **kwargs): - yield AgentRunResponseUpdate(text="Test", role=Role.ASSISTANT) - - decorated_class = use_agent_telemetry(MockStreamingAgentNoDiagnostics) - agent = decorated_class() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry._get_agent_run_span") as mock_get_span, - ): - # Should not create spans when diagnostics are disabled - updates = [] - async for update in agent.run_stream("Test message"): - updates.append(update) - - assert len(updates) == 1 - # Should not have called telemetry functions - mock_get_span.assert_not_called() - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_agent_empty_streaming_response_via_decorator(model_diagnostic_settings): - """Test agent streaming wrapper with empty response.""" - from agent_framework.telemetry import use_agent_telemetry - - class MockEmptyStreamingAgent: - AGENT_SYSTEM_NAME = "test_agent_system" - - def __init__(self): - self.id = "test_agent_id" - self.name = "test_agent" - self.display_name = "Test Agent" - - async def run_stream(self, messages=None, *, thread=None, **kwargs): - # Return empty stream - return - yield # This will never be reached - - decorated_class = use_agent_telemetry(MockEmptyStreamingAgent) - agent = decorated_class() - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_agent_run_span"), - patch("agent_framework.telemetry._set_agent_run_input"), - patch("agent_framework.telemetry._set_agent_run_output") as mock_set_output, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # Should handle empty stream gracefully - updates = [] - async for update in agent.run_stream("Test message"): - updates.append(update) - - assert len(updates) == 0 - # Should still call telemetry - mock_set_output.assert_called_once() - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, True)], indirect=True) -async def test_agent_run_with_thread_and_kwargs(mock_chat_client_agent, model_diagnostic_settings): - """Test agent run with thread and additional kwargs.""" - from agent_framework.telemetry import use_agent_telemetry - - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() - - # Mock thread - mock_thread = Mock() - mock_thread.id = "test_thread_id" - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._get_agent_run_span") as mock_get_span, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - # Test with thread and additional kwargs - response = await agent.run( - "Test message", thread=mock_thread, temperature=0.7, max_tokens=100, model="test-model" - ) - assert response is not None - - # Verify the span was created with the correct parameters - mock_get_span.assert_called_once() - call_kwargs = mock_get_span.call_args[1] - assert call_kwargs["agent"] == agent - assert call_kwargs["thread"] == mock_thread - assert call_kwargs["temperature"] == 0.7 - assert call_kwargs["max_tokens"] == 100 - assert call_kwargs["model"] == "test-model" - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_agent_run_with_list_messages(mock_chat_client_agent, model_diagnostic_settings): - """Test agent run with list of messages.""" - from agent_framework import ChatMessage, Role - from agent_framework.telemetry import use_agent_telemetry - - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() - - messages = [ - ChatMessage(role=Role.USER, text="First message"), - ChatMessage(role=Role.ASSISTANT, text="Response"), - ChatMessage(role=Role.USER, text="Second message"), - ] - - with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, - patch("agent_framework.telemetry._set_agent_run_input") as mock_set_input, - ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - - response = await agent.run(messages) - assert response is not None - - # Verify input was set with the list of messages - mock_set_input.assert_called_once_with("test_agent_system", messages) - - -@pytest.mark.parametrize("model_diagnostic_settings", [(True, False)], indirect=True) -async def test_agent_run_with_exception_handling(mock_chat_client_agent, model_diagnostic_settings): +async def test_agent_run_with_exception_handling(mock_chat_client_agent: AgentProtocol): """Test agent run with exception handling.""" - from agent_framework.telemetry import use_agent_telemetry async def run_with_error(self, messages=None, *, thread=None, **kwargs): raise RuntimeError("Agent run error") - type(mock_chat_client_agent).run = run_with_error + mock_chat_client_agent.run = run_with_error - decorated_class = use_agent_telemetry(type(mock_chat_client_agent)) - agent = decorated_class() + agent = use_agent_telemetry(mock_chat_client_agent)() + + from opentelemetry.trace import Span with ( - patch("agent_framework.telemetry.MODEL_DIAGNOSTICS_SETTINGS", model_diagnostic_settings), - patch("agent_framework.telemetry.use_span") as mock_use_span, + patch("agent_framework.telemetry._get_span") as mock_get_span, ): - mock_span = Mock() - mock_use_span.return_value.__enter__.return_value = mock_span - mock_use_span.return_value.__exit__.return_value = None - + mock_span = MagicMock(spec=Span) + # Ensure the patched context manager returns mock_span when entered + mock_get_span.return_value.__enter__.return_value = mock_span # Should raise the exception and call error handler with pytest.raises(RuntimeError, match="Agent run error"): await agent.run("Test message") # Verify error was recorded # Check that both error attributes were set on the span - mock_span.set_attribute.assert_called_once_with( - GenAIAttributes.ERROR_TYPE.value, str(type(RuntimeError("Agent run error"))) + mock_span.set_attribute.assert_called_with(OtelAttr.ERROR_TYPE, "RuntimeError") + mock_span.record_exception.assert_called_once() + mock_span.set_status.assert_called_once_with( + status=StatusCode.ERROR, description=repr(RuntimeError("Agent run error")) ) - mock_span.set_status.assert_called_once_with(StatusCode.ERROR, repr(RuntimeError("Agent run error"))) diff --git a/python/packages/main/tests/main/test_tools.py b/python/packages/main/tests/main/test_tools.py index a3a39b9613..11daff6716 100644 --- a/python/packages/main/tests/main/test_tools.py +++ b/python/packages/main/tests/main/test_tools.py @@ -1,13 +1,23 @@ # Copyright (c) Microsoft. All rights reserved. +from typing import Any from unittest.mock import Mock, patch import pytest from pydantic import BaseModel -from agent_framework import AIFunction, HostedCodeInterpreterTool, ToolProtocol, ai_function +from agent_framework import ( + AIFunction, + HostedCodeInterpreterTool, + HostedMCPTool, + ToolProtocol, + ai_function, +) from agent_framework._tools import _parse_inputs -from agent_framework.telemetry import GenAIAttributes +from agent_framework.exceptions import ToolException +from agent_framework.telemetry import OtelAttr + +# region AIFunction and ai_function decorator tests def test_ai_function_decorator(): @@ -73,19 +83,23 @@ async def test_ai_function_decorator_with_async(): assert (await async_test_tool(1, 2)) == 3 -# Telemetry tests for AIFunction -async def test_ai_function_invoke_telemetry_enabled(): +@pytest.mark.parametrize("otel_settings", [(True, True)], indirect=True) +async def test_ai_function_invoke_telemetry_enabled(otel_settings): """Test the ai_function invoke method with telemetry enabled.""" - @ai_function(name="telemetry_test_tool", description="A test tool for telemetry") + @ai_function( + name="telemetry_test_tool", + description="A test tool for telemetry", + additional_properties={"otel_settings": otel_settings}, + ) def telemetry_test_tool(x: int, y: int) -> int: """A function that adds two numbers for telemetry testing.""" return x + y # Mock the tracer and span with ( - patch("agent_framework._tools.tracer") as mock_tracer, - patch("agent_framework._tools.start_as_current_span") as mock_start_span, + patch("agent_framework.telemetry.tracer"), + patch("agent_framework._tools.get_function_span") as mock_start_span, ): mock_span = Mock() mock_context_manager = Mock() @@ -104,23 +118,26 @@ async def test_ai_function_invoke_telemetry_enabled(): assert result == 3 # Verify telemetry calls - mock_start_span.assert_called_once_with( - mock_tracer, telemetry_test_tool, metadata={"tool_call_id": "test_call_id", "kwargs": {"x": 1, "y": 2}} - ) + mock_start_span.assert_called_once_with(function=telemetry_test_tool, tool_call_id="test_call_id") # Verify histogram was called with correct attributes mock_histogram.record.assert_called_once() call_args = mock_histogram.record.call_args assert call_args[0][0] > 0 # duration should be positive attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.MEASUREMENT_FUNCTION_TAG_NAME.value] == "telemetry_test_tool" - assert attributes[GenAIAttributes.TOOL_CALL_ID.value] == "test_call_id" + assert attributes[OtelAttr.MEASUREMENT_FUNCTION_TAG_NAME] == "telemetry_test_tool" + assert attributes[OtelAttr.TOOL_CALL_ID] == "test_call_id" -async def test_ai_function_invoke_telemetry_with_pydantic_args(): +@pytest.mark.parametrize("otel_settings", [(True, True)], indirect=True) +async def test_ai_function_invoke_telemetry_with_pydantic_args(otel_settings): """Test the ai_function invoke method with Pydantic model arguments.""" - @ai_function(name="pydantic_test_tool", description="A test tool with Pydantic args") + @ai_function( + name="pydantic_test_tool", + description="A test tool with Pydantic args", + additional_properties={"otel_settings": otel_settings}, + ) def pydantic_test_tool(x: int, y: int) -> int: """A function that adds two numbers using Pydantic args.""" return x + y @@ -129,8 +146,8 @@ async def test_ai_function_invoke_telemetry_with_pydantic_args(): args_model = pydantic_test_tool.input_model(x=5, y=10) with ( - patch("agent_framework._tools.tracer") as mock_tracer, - patch("agent_framework._tools.start_as_current_span") as mock_start_span, + patch("agent_framework.telemetry.tracer"), + patch("agent_framework._tools.get_function_span") as mock_start_span, ): mock_span = Mock() mock_context_manager = Mock() @@ -149,21 +166,27 @@ async def test_ai_function_invoke_telemetry_with_pydantic_args(): # Verify telemetry calls mock_start_span.assert_called_once_with( - mock_tracer, pydantic_test_tool, metadata={"tool_call_id": "pydantic_call", "kwargs": {"x": 5, "y": 10}} + function=pydantic_test_tool, + tool_call_id="pydantic_call", ) -async def test_ai_function_invoke_telemetry_with_exception(): +@pytest.mark.parametrize("otel_settings", [(True, True)], indirect=True) +async def test_ai_function_invoke_telemetry_with_exception(otel_settings): """Test the ai_function invoke method with telemetry when an exception occurs.""" - @ai_function(name="exception_test_tool", description="A test tool that raises an exception") + @ai_function( + name="exception_test_tool", + description="A test tool that raises an exception", + additional_properties={"otel_settings": otel_settings}, + ) def exception_test_tool(x: int, y: int) -> int: """A function that raises an exception for telemetry testing.""" raise ValueError("Test exception for telemetry") with ( - patch("agent_framework._tools.tracer"), - patch("agent_framework._tools.start_as_current_span") as mock_start_span, + patch("agent_framework.telemetry.tracer"), + patch("agent_framework._tools.get_function_span") as mock_start_span, ): mock_span = Mock() mock_context_manager = Mock() @@ -190,20 +213,25 @@ async def test_ai_function_invoke_telemetry_with_exception(): mock_histogram.record.assert_called_once() call_args = mock_histogram.record.call_args attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.ERROR_TYPE.value] == "ValueError" + assert attributes[OtelAttr.ERROR_TYPE] == ValueError.__name__ -async def test_ai_function_invoke_telemetry_async_function(): +@pytest.mark.parametrize("otel_settings", [(True, True)], indirect=True) +async def test_ai_function_invoke_telemetry_async_function(otel_settings): """Test the ai_function invoke method with telemetry on async function.""" - @ai_function(name="async_telemetry_test", description="An async test tool for telemetry") + @ai_function( + name="async_telemetry_test", + description="An async test tool for telemetry", + additional_properties={"otel_settings": otel_settings}, + ) async def async_telemetry_test(x: int, y: int) -> int: """An async function for telemetry testing.""" return x * y with ( - patch("agent_framework._tools.tracer") as mock_tracer, - patch("agent_framework._tools.start_as_current_span") as mock_start_span, + patch("agent_framework.telemetry.tracer"), + patch("agent_framework._tools.get_function_span") as mock_start_span, ): mock_span = Mock() mock_context_manager = Mock() @@ -221,54 +249,13 @@ async def test_ai_function_invoke_telemetry_async_function(): assert result == 12 # Verify telemetry calls - mock_start_span.assert_called_once_with( - mock_tracer, async_telemetry_test, metadata={"tool_call_id": "async_call", "kwargs": {"x": 3, "y": 4}} - ) + mock_start_span.assert_called_once_with(function=async_telemetry_test, tool_call_id="async_call") # Verify histogram recording mock_histogram.record.assert_called_once() call_args = mock_histogram.record.call_args attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.MEASUREMENT_FUNCTION_TAG_NAME.value] == "async_telemetry_test" - - -async def test_ai_function_invoke_telemetry_no_tool_call_id(): - """Test the ai_function invoke method with telemetry when no tool_call_id is provided.""" - - @ai_function(name="no_id_test_tool", description="A test tool without tool_call_id") - def no_id_test_tool(x: int) -> int: - """A function for testing without tool_call_id.""" - return x * 2 - - with ( - patch("agent_framework._tools.tracer") as mock_tracer, - patch("agent_framework._tools.start_as_current_span") as mock_start_span, - ): - mock_span = Mock() - mock_context_manager = Mock() - mock_context_manager.__enter__ = Mock(return_value=mock_span) - mock_context_manager.__exit__ = Mock(return_value=None) - mock_start_span.return_value = mock_context_manager - - mock_histogram = Mock() - no_id_test_tool._invocation_duration_histogram = mock_histogram - - # Call invoke without tool_call_id - result = await no_id_test_tool.invoke(x=5) - - # Verify result - assert result == 10 - - # Verify telemetry calls - mock_start_span.assert_called_once_with( - mock_tracer, no_id_test_tool, metadata={"tool_call_id": None, "kwargs": {"x": 5}} - ) - - # Verify histogram attributes - mock_histogram.record.assert_called_once() - call_args = mock_histogram.record.call_args - attributes = call_args[1]["attributes"] - assert attributes[GenAIAttributes.TOOL_CALL_ID.value] is None + assert attributes[OtelAttr.MEASUREMENT_FUNCTION_TAG_NAME] == "async_telemetry_test" async def test_ai_function_invoke_invalid_pydantic_args(): @@ -291,7 +278,7 @@ async def test_ai_function_invoke_invalid_pydantic_args(): await invalid_args_test.invoke(arguments=wrong_args) -# Tests for HostedCodeInterpreterTool and _parse_inputs +# region HostedCodeInterpreterTool and _parse_inputs def test_hosted_code_interpreter_tool_default(): @@ -507,3 +494,104 @@ def test_hosted_code_interpreter_tool_with_unknown_input(): """Test HostedCodeInterpreterTool with single unknown input.""" with pytest.raises(ValueError, match="Unsupported input type"): HostedCodeInterpreterTool(inputs={"hosted_file": "file-single"}) + + +# region HostedMCPTool tests + + +def test_hosted_mcp_tool_with_other_fields(): + """Test creating a HostedMCPTool with a specific approval dict, headers and additional properties.""" + tool = HostedMCPTool( + name="mcp-tool", + url="https://mcp.example", + description="A test MCP tool", + headers={"x": "y"}, + additional_properties={"p": 1}, + ) + + assert tool.name == "mcp-tool" + # pydantic AnyUrl preserves as string-like + assert str(tool.url).startswith("https://") + assert tool.headers == {"x": "y"} + assert tool.additional_properties == {"p": 1} + assert tool.description == "A test MCP tool" + + +@pytest.mark.parametrize( + "approval_mode", + [ + "always_require", + "never_require", + { + "always_require_approval": {"toolA"}, + "never_require_approval": {"toolB"}, + }, + { + "always_require_approval": ["toolA"], + "never_require_approval": ("toolB",), + }, + ], + ids=["always_require", "never_require", "specific", "specific_with_parsing"], +) +def test_hosted_mcp_tool_with_approval_mode(approval_mode: str | dict[str, Any]): + """Test creating a HostedMCPTool with a specific approval dict, headers and additional properties.""" + tool = HostedMCPTool(name="mcp-tool", url="https://mcp.example", approval_mode=approval_mode) + + assert tool.name == "mcp-tool" + # pydantic AnyUrl preserves as string-like + assert str(tool.url).startswith("https://") + if not isinstance(approval_mode, dict): + assert tool.approval_mode == approval_mode + else: + # approval_mode parsed to sets + assert isinstance(tool.approval_mode["always_require_approval"], set) + assert isinstance(tool.approval_mode["never_require_approval"], set) + assert "toolA" in tool.approval_mode["always_require_approval"] + assert "toolB" in tool.approval_mode["never_require_approval"] + + +def test_hosted_mcp_tool_invalid_approval_mode_raises(): + """Invalid approval_mode string should raise ServiceInitializationError.""" + with pytest.raises(ToolException): + HostedMCPTool(name="bad", url="https://x", approval_mode="invalid_mode") + + +@pytest.mark.parametrize( + "tools", + [ + {"toolA", "toolB"}, + ("toolA", "toolB"), + ["toolA", "toolB"], + ["toolA", "toolB", "toolA"], + ], + ids=[ + "set", + "tuple", + "list", + "list_with_duplicates", + ], +) +def test_hosted_mcp_tool_with_allowed_tools(tools: list[str] | tuple[str, ...] | set[str]): + """Test creating a HostedMCPTool with a list of allowed tools.""" + tool = HostedMCPTool( + name="mcp-tool", + url="https://mcp.example", + allowed_tools=tools, + ) + + assert tool.name == "mcp-tool" + # pydantic AnyUrl preserves as string-like + assert str(tool.url).startswith("https://") + # approval_mode parsed to set + assert isinstance(tool.allowed_tools, set) + assert tool.allowed_tools == {"toolA", "toolB"} + + +def test_hosted_mcp_tool_with_dict_of_allowed_tools(): + """Test creating a HostedMCPTool with a dict of allowed tools.""" + with pytest.raises(ToolException): + HostedMCPTool( + name="mcp-tool", + url="https://mcp.example", + allowed_tools={"toolA": "Tool A", "toolC": "Tool C"}, + ) diff --git a/python/packages/main/tests/main/test_types.py b/python/packages/main/tests/main/test_types.py index 40fd8e9f0e..094d4ea494 100644 --- a/python/packages/main/tests/main/test_types.py +++ b/python/packages/main/tests/main/test_types.py @@ -21,6 +21,8 @@ from agent_framework import ( DataContent, ErrorContent, FinishReason, + FunctionApprovalRequestContent, + FunctionApprovalResponseContent, FunctionCallContent, FunctionResultContent, GeneratedEmbeddings, @@ -38,6 +40,7 @@ from agent_framework import ( UsageDetails, ai_function, ) +from agent_framework.exceptions import AdditionItemMismatch @fixture @@ -296,9 +299,8 @@ def test_function_call_content_add_merging_and_errors(): # incompatible call ids a = FunctionCallContent(call_id="1", name="f", arguments="abc") b = FunctionCallContent(call_id="2", name="f", arguments="def") - from agent_framework.exceptions import AgentFrameworkException - with raises(AgentFrameworkException): + with raises(AdditionItemMismatch): _ = a + b @@ -379,6 +381,42 @@ def test_usage_details_add_with_none_and_type_errors(): u += 42 # type: ignore[arg-type] +# region UserInputRequest and Response + + +def test_function_approval_request_and_response_creation(): + """Test creating a FunctionApprovalRequestContent and producing a response.""" + fc = FunctionCallContent(call_id="call-1", name="do_something", arguments={"a": 1}) + req = FunctionApprovalRequestContent(id="req-1", function_call=fc) + + assert req.type == "function_approval_request" + assert req.function_call == fc + assert req.id == "req-1" + assert isinstance(req, BaseContent) + + resp = req.create_response(True) + + assert isinstance(resp, FunctionApprovalResponseContent) + assert resp.approved is True + assert resp.function_call == fc + assert resp.id == "req-1" + + +def test_function_approval_serialization_roundtrip(): + fc = FunctionCallContent(call_id="c2", name="f", arguments='{"x":1}') + req = FunctionApprovalRequestContent(id="id-2", function_call=fc, additional_properties={"meta": 1}) + + dumped = req.model_dump() + loaded = FunctionApprovalRequestContent.model_validate(dumped) + assert loaded == req + + class TestModel(BaseModel): + content: Contents + + test_item = TestModel.model_validate({"content": dumped}) + assert isinstance(test_item.content, FunctionApprovalRequestContent) + + # region BaseContent Serialization diff --git a/python/packages/main/tests/openai/conftest.py b/python/packages/main/tests/openai/conftest.py index beb20ead82..7bedccd52d 100644 --- a/python/packages/main/tests/openai/conftest.py +++ b/python/packages/main/tests/openai/conftest.py @@ -3,6 +3,8 @@ from typing import Any from pytest import fixture +from agent_framework.telemetry import OtelSettings, setup_telemetry + # region Connector Settings fixtures @fixture @@ -49,3 +51,26 @@ def openai_unit_test_env(monkeypatch, exclude_list, override_env_param_dict): # monkeypatch.setenv(key, value) # type: ignore return env_vars + + +@fixture +def enable_otel(request: Any) -> bool: + """Fixture that returns a boolean indicating if Otel is enabled.""" + return request.param if hasattr(request, "param") else True + + +@fixture +def enable_sensitive_data(request: Any) -> bool: + """Fixture that returns a boolean indicating if sensitive data is enabled.""" + return request.param if hasattr(request, "param") else False + + +@fixture +def otel_settings(enable_otel: bool, enable_sensitive_data: bool) -> OtelSettings: + """Fixture to set environment variables for OtelSettings.""" + + from agent_framework.telemetry import OTEL_SETTINGS + + setup_telemetry(enable_otel=enable_otel, enable_sensitive_data=enable_sensitive_data) + + return OTEL_SETTINGS diff --git a/python/packages/main/tests/openai/test_openai_assistants_client.py b/python/packages/main/tests/openai/test_openai_assistants_client.py index 7e3b455bc9..76ce1ce87e 100644 --- a/python/packages/main/tests/openai/test_openai_assistants_client.py +++ b/python/packages/main/tests/openai/test_openai_assistants_client.py @@ -1049,6 +1049,7 @@ async def test_openai_assistants_client_with_existing_assistant() -> None: @skip_if_openai_integration_tests_disabled +@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue") async def test_openai_assistants_client_file_search() -> None: """Test OpenAI Assistants Client response.""" async with OpenAIAssistantsClient() as openai_assistants_client: @@ -1071,6 +1072,7 @@ async def test_openai_assistants_client_file_search() -> None: @skip_if_openai_integration_tests_disabled +@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue") async def test_openai_assistants_client_file_search_streaming() -> None: """Test OpenAI Assistants Client response.""" async with OpenAIAssistantsClient() as openai_assistants_client: @@ -1249,42 +1251,3 @@ async def test_openai_assistants_client_agent_level_tool_persistence(): assert second_response.text is not None # Should use the agent-level weather tool again assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"]) - - -@skip_if_openai_integration_tests_disabled -async def test_openai_assistants_client_run_level_tool_isolation(): - """Test that run-level tools are isolated to specific runs and don't persist with OpenAI Assistants Client.""" - # Counter to track how many times the weather tool is called - call_count = 0 - - @ai_function - async def get_weather_with_counter(location: Annotated[str, "The location as a city name"]) -> str: - """Get the current weather in a given location.""" - nonlocal call_count - call_count += 1 - return f"The weather in {location} is sunny and 72°F." - - async with ChatAgent( - chat_client=OpenAIAssistantsClient(), - instructions="You are a helpful assistant.", - ) as agent: - # First run - use run-level tool - first_response = await agent.run( - "What's the weather like in Chicago?", - tools=[get_weather_with_counter], # Run-level tool - ) - - assert isinstance(first_response, AgentRunResponse) - assert first_response.text is not None - # Should use the run-level weather tool (call count should be 1) - assert call_count == 1 - assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"]) - - # Second run - run-level tool should NOT persist (key isolation test) - second_response = await agent.run("What's the weather like in Miami?") - - assert isinstance(second_response, AgentRunResponse) - assert second_response.text is not None - # Should NOT use the weather tool since it was only run-level in previous call - # Call count should still be 1 (no additional calls) - assert call_count == 1 diff --git a/python/packages/main/tests/openai/test_openai_chat_client.py b/python/packages/main/tests/openai/test_openai_chat_client.py index cd0baf5629..f57af48207 100644 --- a/python/packages/main/tests/openai/test_openai_chat_client.py +++ b/python/packages/main/tests/openai/test_openai_chat_client.py @@ -74,6 +74,12 @@ def test_init_with_default_header(openai_unit_test_env: dict[str, str]) -> None: assert open_ai_chat_completion.client.default_headers[key] == value +def test_init_base_url(openai_unit_test_env: dict[str, str]) -> None: + # Test successful initialization + open_ai_chat_completion = OpenAIChatClient(base_url="http://localhost:1234/v1") + assert str(open_ai_chat_completion.client.base_url) == "http://localhost:1234/v1/" + + @pytest.mark.parametrize("exclude_list", [["OPENAI_CHAT_MODEL_ID"]], indirect=True) def test_init_with_empty_model_id(openai_unit_test_env: dict[str, str]) -> None: with pytest.raises(ServiceInitializationError): @@ -333,7 +339,7 @@ async def test_openai_chat_client_web_search() -> None: tools=[HostedWebSearchTool(additional_properties=additional_properties)], tool_choice="auto", ) - assert "Seattle" in response.text + assert response.text is not None @skip_if_openai_integration_tests_disabled @@ -386,7 +392,7 @@ async def test_openai_chat_client_web_search_streaming() -> None: for content in chunk.contents: if isinstance(content, TextContent) and content.text: full_message += content.text - assert "Seattle" in full_message + assert full_message is not None @skip_if_openai_integration_tests_disabled diff --git a/python/packages/main/tests/openai/test_openai_responses_client.py b/python/packages/main/tests/openai/test_openai_responses_client.py index 51d8633b79..4f2846a981 100644 --- a/python/packages/main/tests/openai/test_openai_responses_client.py +++ b/python/packages/main/tests/openai/test_openai_responses_client.py @@ -18,11 +18,14 @@ from agent_framework import ( ChatMessage, ChatResponse, ChatResponseUpdate, + FunctionApprovalRequestContent, + FunctionApprovalResponseContent, FunctionCallContent, FunctionResultContent, HostedCodeInterpreterTool, HostedFileContent, HostedFileSearchTool, + HostedMCPTool, HostedVectorStoreContent, HostedWebSearchTool, Role, @@ -49,7 +52,7 @@ class OutputStruct(BaseModel): """A structured output for testing purposes.""" location: str - weather: str + weather: str | None = None async def create_vector_store(client: OpenAIResponsesClient) -> tuple[str, HostedVectorStoreContent]: @@ -370,7 +373,7 @@ def test_chat_message_parsing_with_function_calls() -> None: asyncio.run(client.get_response(messages=messages)) -def test_response_format_parse_path() -> None: +async def test_response_format_parse_path() -> None: """Test get_response response_format parsing path.""" client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") @@ -383,19 +386,18 @@ def test_response_format_parse_path() -> None: mock_parsed_response.metadata = {} mock_parsed_response.output_parsed = None mock_parsed_response.usage = None + mock_parsed_response.finish_reason = None with patch.object(client.client.responses, "parse", return_value=mock_parsed_response): - response = asyncio.run( - client.get_response( - messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct, store=True - ) + response = await client.get_response( + messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct, store=True ) assert response.conversation_id == "parsed_response_123" assert response.ai_model_id == "test-model" -def test_bad_request_error_non_content_filter() -> None: +async def test_bad_request_error_non_content_filter() -> None: """Test get_response BadRequestError without content_filter.""" client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") @@ -409,10 +411,8 @@ def test_bad_request_error_non_content_filter() -> None: with patch.object(client.client.responses, "parse", side_effect=mock_error): with pytest.raises(ServiceResponseException) as exc_info: - asyncio.run( - client.get_response( - messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct - ) + await client.get_response( + messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct ) assert "failed to complete the prompt" in str(exc_info.value) @@ -437,11 +437,13 @@ async def test_streaming_content_filter_exception_handling() -> None: break -def test_get_streaming_response_with_all_parameters() -> None: +@skip_if_openai_integration_tests_disabled +async def test_get_streaming_response_with_all_parameters() -> None: """Test get_streaming_response with all possible parameters.""" client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") - async def run_streaming_test(): + # Should fail due to invalid API key + with pytest.raises(ServiceResponseException): response = client.get_streaming_response( messages=[ChatMessage(role="user", text="Test streaming")], include=["file_search_call.results"], @@ -468,10 +470,6 @@ def test_get_streaming_response_with_all_parameters() -> None: async for _ in response: break - # Should fail due to invalid API key - with pytest.raises(ServiceResponseException): - asyncio.run(run_streaming_test()) - def test_response_content_creation_with_annotations() -> None: """Test _create_response_content with different annotation types.""" @@ -644,6 +642,158 @@ def test_response_content_creation_with_function_call() -> None: assert function_call.arguments == '{"location": "Seattle"}' +def test_tools_to_response_tools_with_hosted_mcp() -> None: + """Test that HostedMCPTool is converted to the correct response tool dict.""" + client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") + + tool = HostedMCPTool( + name="My MCP", + url="https://mcp.example", + description="An MCP server", + approval_mode={"always_require_approval": ["tool_a", "tool_b"]}, + allowed_tools={"tool_a", "tool_b"}, + headers={"X-Test": "yes"}, + additional_properties={"custom": "value"}, + ) + + resp_tools = client._tools_to_response_tools([tool]) + assert isinstance(resp_tools, list) + assert len(resp_tools) == 1 + mcp = resp_tools[0] + assert isinstance(mcp, dict) + assert mcp["type"] == "mcp" + assert mcp["server_label"] == "My_MCP" + # server_url may be normalized to include a trailing slash by the client + assert str(mcp["server_url"]).rstrip("/") == "https://mcp.example" + assert mcp["server_description"] == "An MCP server" + assert mcp["headers"]["X-Test"] == "yes" + assert set(mcp["allowed_tools"]) == {"tool_a", "tool_b"} + # approval mapping created from approval_mode dict + assert "require_approval" in mcp + + +def test_create_response_content_with_mcp_approval_request() -> None: + """Test that a non-streaming mcp_approval_request is parsed into FunctionApprovalRequestContent.""" + client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") + + mock_response = MagicMock() + mock_response.output_parsed = None + mock_response.metadata = {} + mock_response.usage = None + mock_response.id = "resp-id" + mock_response.model = "test-model" + mock_response.created_at = 1000000000 + + mock_item = MagicMock() + mock_item.type = "mcp_approval_request" + mock_item.id = "approval-1" + mock_item.name = "do_sensitive_action" + mock_item.arguments = {"arg": 1} + mock_item.server_label = "My_MCP" + + mock_response.output = [mock_item] + + response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore + + assert isinstance(response.messages[0].contents[0], FunctionApprovalRequestContent) + req = response.messages[0].contents[0] + assert req.id == "approval-1" + assert req.function_call.name == "do_sensitive_action" + assert req.function_call.arguments == {"arg": 1} + assert req.function_call.additional_properties["server_label"] == "My_MCP" + + +def test_create_streaming_response_content_with_mcp_approval_request() -> None: + """Test that a streaming mcp_approval_request event is parsed into FunctionApprovalRequestContent.""" + client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") + chat_options = ChatOptions() + function_call_ids: dict[int, tuple[str, str]] = {} + + mock_event = MagicMock() + mock_event.type = "response.output_item.added" + mock_item = MagicMock() + mock_item.type = "mcp_approval_request" + mock_item.id = "approval-stream-1" + mock_item.name = "do_stream_action" + mock_item.arguments = {"x": 2} + mock_item.server_label = "My_MCP" + mock_event.item = mock_item + + update = client._create_streaming_response_content(mock_event, chat_options, function_call_ids) + assert any(isinstance(c, FunctionApprovalRequestContent) for c in update.contents) + fa = next(c for c in update.contents if isinstance(c, FunctionApprovalRequestContent)) + assert fa.id == "approval-stream-1" + assert fa.function_call.name == "do_stream_action" + + +@pytest.mark.parametrize("enable_otel", [False], indirect=True) +@pytest.mark.parametrize("enable_sensitive_data", [False], indirect=True) +def test_end_to_end_mcp_approval_flow(otel_settings) -> None: + """End-to-end mocked test: + model issues an mcp_approval_request, user approves, client sends mcp_approval_response. + """ + client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") + + # First mocked response: model issues an mcp_approval_request + mock_response1 = MagicMock() + mock_response1.output_parsed = None + mock_response1.metadata = {} + mock_response1.usage = None + mock_response1.id = "resp-1" + mock_response1.model = "test-model" + mock_response1.created_at = 1000000000 + + mock_item = MagicMock() + mock_item.type = "mcp_approval_request" + mock_item.id = "approval-1" + mock_item.name = "do_sensitive_action" + mock_item.arguments = {"arg": "value"} + mock_item.server_label = "My_MCP" + mock_response1.output = [mock_item] + + # Second mocked response: simple assistant acknowledgement after approval + mock_response2 = MagicMock() + mock_response2.output_parsed = None + mock_response2.metadata = {} + mock_response2.usage = None + mock_response2.id = "resp-2" + mock_response2.model = "test-model" + mock_response2.created_at = 1000000001 + mock_text_item = MagicMock() + mock_text_item.type = "message" + mock_text_content = MagicMock() + mock_text_content.type = "output_text" + mock_text_content.text = "Approved." + mock_text_item.content = [mock_text_content] + mock_response2.output = [mock_text_item] + + # Patch the create call to return the two mocked responses in sequence + with patch.object(client.client.responses, "create", side_effect=[mock_response1, mock_response2]) as mock_create: + # First call: get the approval request + response = asyncio.run(client.get_response(messages=[ChatMessage(role="user", text="Trigger approval")])) + assert isinstance(response.messages[0].contents[0], FunctionApprovalRequestContent) + req = response.messages[0].contents[0] + assert req.id == "approval-1" + + # Build a user approval and send it (include required function_call) + approval = FunctionApprovalResponseContent(approved=True, id=req.id, function_call=req.function_call) + approval_message = ChatMessage(role="user", contents=[approval]) + _ = asyncio.run(client.get_response(messages=[approval_message])) + + # Ensure two calls were made and the second includes the mcp_approval_response + assert mock_create.call_count == 2 + _, kwargs = mock_create.call_args_list[1] + sent_input = kwargs.get("input") + assert isinstance(sent_input, list) + found = False + for item in sent_input: + if isinstance(item, dict) and item.get("type") == "mcp_approval_response": + assert item["approval_request_id"] == "approval-1" + assert item["approve"] is True + found = True + assert found + + def test_usage_details_basic() -> None: """Test _usage_details_from_openai without cached or reasoning tokens.""" client = OpenAIResponsesClient(ai_model_id="test-model", api_key="test-key") @@ -775,9 +925,10 @@ async def test_openai_responses_client_response() -> None: assert response is not None assert isinstance(response, ChatResponse) - output = OutputStruct.model_validate_json(response.text) + output = response.value + assert output is not None, "Response value is None" assert "seattle" in output.location.lower() - assert "sunny" in output.weather.lower() + assert output.weather is not None @skip_if_openai_integration_tests_disabled @@ -839,17 +990,11 @@ async def test_openai_responses_client_streaming() -> None: messages.append(ChatMessage(role="user", text="who are Emily and David?")) # Test that the client can be used to get a response - response = openai_responses_client.get_streaming_response(messages=messages) + response = await ChatResponse.from_chat_response_generator( + openai_responses_client.get_streaming_response(messages=messages) + ) - full_message: str = "" - async for chunk in response: - assert chunk is not None - assert isinstance(chunk, ChatResponseUpdate) - for content in chunk.contents: - if isinstance(content, TextContent) and content.text: - full_message += content.text - - assert "scientists" in full_message + assert "scientists" in response.text messages.clear() messages.append(ChatMessage(role="user", text="The weather in Seattle is sunny")) @@ -859,17 +1004,16 @@ async def test_openai_responses_client_streaming() -> None: messages=messages, response_format=OutputStruct, ) - full_message = "" + chunks = [] async for chunk in response: assert chunk is not None assert isinstance(chunk, ChatResponseUpdate) - for content in chunk.contents: - if isinstance(content, TextContent) and content.text: - full_message += content.text - - output = OutputStruct.model_validate_json(full_message) + chunks.append(chunk) + full_message = ChatResponse.from_chat_response_updates(chunks, output_format_type=OutputStruct) + output = full_message.value + assert output is not None, "Response value is None" assert "seattle" in output.location.lower() - assert "sunny" in output.weather.lower() + assert output.weather is not None @skip_if_openai_integration_tests_disabled @@ -906,15 +1050,15 @@ async def test_openai_responses_client_streaming_tools() -> None: tool_choice="auto", response_format=OutputStruct, ) - full_message = "" + chunks = [] async for chunk in response: assert chunk is not None assert isinstance(chunk, ChatResponseUpdate) - for content in chunk.contents: - if isinstance(content, TextContent) and content.text: - full_message += content.text + chunks.append(chunk) - output = OutputStruct.model_validate_json(full_message) + full_message = ChatResponse.from_chat_response_updates(chunks, output_format_type=OutputStruct) + output = full_message.value + assert output is not None, "Response value is None" assert "seattle" in output.location.lower() assert "sunny" in output.weather.lower() @@ -955,7 +1099,7 @@ async def test_openai_responses_client_web_search() -> None: tools=[HostedWebSearchTool(additional_properties=additional_properties)], tool_choice="auto", ) - assert "Seattle" in response.text + assert response.text is not None @skip_if_openai_integration_tests_disabled @@ -1008,10 +1152,11 @@ async def test_openai_responses_client_web_search_streaming() -> None: for content in chunk.contents: if isinstance(content, TextContent) and content.text: full_message += content.text - assert "Seattle" in full_message + assert full_message is not None @skip_if_openai_integration_tests_disabled +@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue") async def test_openai_responses_client_file_search() -> None: openai_responses_client = OpenAIResponsesClient() @@ -1036,6 +1181,7 @@ async def test_openai_responses_client_file_search() -> None: @skip_if_openai_integration_tests_disabled +@pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue") async def test_openai_responses_client_streaming_file_search() -> None: openai_responses_client = OpenAIResponsesClient() diff --git a/python/packages/mem0/LICENSE b/python/packages/mem0/LICENSE new file mode 100644 index 0000000000..9e841e7a26 --- /dev/null +++ b/python/packages/mem0/LICENSE @@ -0,0 +1,21 @@ + MIT License + + Copyright (c) Microsoft Corporation. + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to deal + in the Software without restriction, including without limitation the rights + to use, copy, modify, merge, publish, distribute, sublicense, and/or sell + copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + The above copyright notice and this permission notice shall be included in all + copies or substantial portions of the Software. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + SOFTWARE diff --git a/python/packages/mem0/README.md b/python/packages/mem0/README.md new file mode 100644 index 0000000000..10784d337f --- /dev/null +++ b/python/packages/mem0/README.md @@ -0,0 +1,21 @@ +# Get Started with Microsoft Agent Framework Mem0 + +Please install this package as the extra for `agent-framework`: + +```bash +pip install agent-framework[mem0] +``` + +## Memory Context Provider + +The Mem0 context provider enables persistent memory capabilities for your agents, allowing them to remember user preferences and conversation context across different sessions and threads. + +### Basic Usage Example + +See the [Mem0 basic example](https://github.com/microsoft/agent-framework/tree/main/python/samples/getting_started/context_providers/mem0/mem0_basic.py) which demonstrates: + +- Setting up an agent with Mem0 context provider +- Teaching the agent user preferences +- Retrieving information using remembered context across new threads +- Persistent memory + diff --git a/python/packages/mem0/agent_framework_mem0/__init__.py b/python/packages/mem0/agent_framework_mem0/__init__.py new file mode 100644 index 0000000000..256e15356c --- /dev/null +++ b/python/packages/mem0/agent_framework_mem0/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) Microsoft. All rights reserved. + +import importlib.metadata + +from ._provider import Mem0Provider + +try: + __version__ = importlib.metadata.version(__name__) +except importlib.metadata.PackageNotFoundError: + __version__ = "0.0.0" # Fallback for development mode + +__all__ = [ + "Mem0Provider", + "__version__", +] diff --git a/python/packages/mem0/agent_framework_mem0/_provider.py b/python/packages/mem0/agent_framework_mem0/_provider.py new file mode 100644 index 0000000000..7fb2bbbf65 --- /dev/null +++ b/python/packages/mem0/agent_framework_mem0/_provider.py @@ -0,0 +1,180 @@ +# Copyright (c) Microsoft. All rights reserved. + +import sys +from collections.abc import MutableSequence, Sequence +from typing import Any, Final + +from agent_framework import ChatMessage, Context, ContextProvider, TextContent +from agent_framework.exceptions import ServiceInitializationError +from pydantic import PrivateAttr + +if sys.version_info >= (3, 11): + from typing import Self # pragma: no cover +else: + from typing_extensions import Self # pragma: no cover + + +DEFAULT_CONTEXT_PROMPT: Final[str] = "## Memories\nConsider the following memories when answering user questions:" + + +class Mem0Provider(ContextProvider): + api_key: str | None = None + application_id: str | None = None + agent_id: str | None = None + thread_id: str | None = None + user_id: str | None = None + scope_to_per_operation_thread_id: bool = False + context_prompt: str = DEFAULT_CONTEXT_PROMPT + # Use Any to avoid forward reference issues with AsyncMemoryClient + mem0_client: Any = None + + _should_close_client: bool = PrivateAttr(default=False) # Track whether we should close client connection + + def __init__( + self, + api_key: str | None = None, + application_id: str | None = None, + agent_id: str | None = None, + thread_id: str | None = None, + user_id: str | None = None, + scope_to_per_operation_thread_id: bool = False, + context_prompt: str = DEFAULT_CONTEXT_PROMPT, + mem0_client: Any = None, + ) -> None: + """Initializes a new instance of the Mem0Provider class. + + Args: + api_key: The API key for authenticating with the Mem0 API. If not + provided, it will attempt to use the MEM0_API_KEY environment variable. + application_id: The application ID for scoping memories or None. + agent_id: The agent ID for scoping memories or None. + thread_id: The thread ID for scoping memories or None. + user_id: The user ID for scoping memories or None. + scope_to_per_operation_thread_id: Whether to scope memories to per-operation thread ID. + context_prompt: The prompt to prepend to retrieved memories. + mem0_client: A pre-created Mem0 MemoryClient or None to create a default client. + """ + should_close_client = False + if mem0_client is None: + from mem0 import AsyncMemoryClient + + mem0_client = AsyncMemoryClient(api_key=api_key) + should_close_client = True + + super().__init__( + api_key=api_key, # type: ignore[reportCallIssue] + application_id=application_id, # type: ignore[reportCallIssue] + agent_id=agent_id, # type: ignore[reportCallIssue] + thread_id=thread_id, # type: ignore[reportCallIssue] + user_id=user_id, # type: ignore[reportCallIssue] + scope_to_per_operation_thread_id=scope_to_per_operation_thread_id, # type: ignore[reportCallIssue] + context_prompt=context_prompt, # type: ignore[reportCallIssue] + mem0_client=mem0_client, # type: ignore[reportCallIssue] + ) + + self._per_operation_thread_id: str | None = None + self._should_close_client = should_close_client + + async def __aenter__(self) -> "Self": + """Async context manager entry.""" + if self.mem0_client: + await self.mem0_client.__aenter__() + return self + + async def __aexit__(self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: Any) -> None: + """Async context manager exit.""" + if self._should_close_client and self.mem0_client: + await self.mem0_client.__aexit__(exc_type, exc_val, exc_tb) + + async def thread_created(self, thread_id: str | None = None) -> None: + """Called when a new thread is created. + + Args: + thread_id: The ID of the thread or None. + """ + self._validate_per_operation_thread_id(thread_id) + self._per_operation_thread_id = self._per_operation_thread_id or thread_id + + async def messages_adding(self, thread_id: str | None, new_messages: ChatMessage | Sequence[ChatMessage]) -> None: + """Called when a new message is being added to the thread. + + Args: + thread_id: The ID of the thread or None. + new_messages: New messages to add. + """ + self._validate_filters() + self._validate_per_operation_thread_id(thread_id) + self._per_operation_thread_id = self._per_operation_thread_id or thread_id + + messages_list = [new_messages] if isinstance(new_messages, ChatMessage) else list(new_messages) + + messages: list[dict[str, str]] = [ + {"role": message.role.value, "content": message.text} + for message in messages_list + if message.role.value in {"user", "assistant", "system"} and message.text and message.text.strip() + ] + + if messages: + await self.mem0_client.add( # type: ignore[misc] + messages=messages, + user_id=self.user_id, + agent_id=self.agent_id, + run_id=self._per_operation_thread_id if self.scope_to_per_operation_thread_id else self.thread_id, + metadata={"application_id": self.application_id}, + ) + + async def model_invoking(self, messages: ChatMessage | MutableSequence[ChatMessage]) -> Context: + """Called before invoking the AI model to provide context. + + Args: + messages: List of new messages in the thread. + + Returns: + Context: Context object containing instructions with memories. + """ + self._validate_filters() + messages_list = [messages] if isinstance(messages, ChatMessage) else list(messages) + input_text = "\n".join(msg.text for msg in messages_list if msg and msg.text and msg.text.strip()) + + memories = await self.mem0_client.search( # type: ignore[misc] + query=input_text, + user_id=self.user_id, + agent_id=self.agent_id, + run_id=self._per_operation_thread_id if self.scope_to_per_operation_thread_id else self.thread_id, + ) + + line_separated_memories = "\n".join(memory.get("memory", "") for memory in memories) + + content = TextContent(f"{self.context_prompt}\n{line_separated_memories}") if line_separated_memories else None + + return Context(contents=[content] if content else None) + + def _validate_filters(self) -> None: + """Validates that at least one filter is provided. + + Raises: + ServiceInitializationError: If no filters are provided. + """ + if not self.agent_id and not self.user_id and not self.application_id and not self.thread_id: + raise ServiceInitializationError( + "At least one of the filters: agent_id, user_id, application_id, or thread_id is required." + ) + + def _validate_per_operation_thread_id(self, thread_id: str | None) -> None: + """Validates that a new thread ID doesn't conflict with an existing one when scoped. + + Args: + thread_id: The new thread ID or None. + + Raises: + ValueError: If a new thread ID is provided when one already exists. + """ + if ( + self.scope_to_per_operation_thread_id + and thread_id + and self._per_operation_thread_id + and thread_id != self._per_operation_thread_id + ): + raise ValueError( + "Mem0Provider can only be used with one thread at a time when scope_to_per_operation_thread_id is True." + ) diff --git a/python/packages/mem0/pyproject.toml b/python/packages/mem0/pyproject.toml new file mode 100644 index 0000000000..64619181b5 --- /dev/null +++ b/python/packages/mem0/pyproject.toml @@ -0,0 +1,94 @@ +[project] +name = "agent-framework-mem0" +description = "Mem0 integration for Microsoft Agent Framework." +authors = [{ name = "Microsoft", email = "SK-Support@microsoft.com"}] +readme = "README.md" +requires-python = ">=3.10" +version = "0.1.0b1" +license-files = ["LICENSE"] +urls.homepage = "https://learn.microsoft.com/en-us/semantic-kernel/overview/" +urls.source = "https://github.com/microsoft/agent-framework/tree/main/python" +urls.release_notes = "https://github.com/microsoft/agent-framework/releases?q=tag%3Apython-1&expanded=true" +urls.issues = "https://github.com/microsoft/agent-framework/issues" +classifiers = [ + "License :: OSI Approved :: MIT License", + "Development Status :: 5 - Production/Stable", + "Intended Audience :: Developers", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Framework :: Pydantic :: 2", + "Typing :: Typed", +] +dependencies = [ + "agent-framework", + "mem0ai>=0.1.117", +] + +[tool.uv] +prerelease = "if-necessary-or-explicit" +environments = [ + "sys_platform == 'darwin'", + "sys_platform == 'linux'", + "sys_platform == 'win32'" +] + +[tool.uv-dynamic-versioning] +fallback-version = "0.0.0" +[tool.pytest.ini_options] +testpaths = 'tests' +addopts = "-ra -q -r fEX" +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" +filterwarnings = [ + "ignore:Support for class-based `config` is deprecated:DeprecationWarning:pydantic.*" +] +timeout = 120 + +[tool.ruff] +extend = "../../pyproject.toml" + +[tool.coverage.run] +omit = [ + "**/__init__.py" +] + +[tool.pyright] +extend = "../../pyproject.toml" +exclude = ['tests'] + +[tool.mypy] +plugins = ['pydantic.mypy'] +strict = true +python_version = "3.10" +ignore_missing_imports = true +disallow_untyped_defs = true +no_implicit_optional = true +check_untyped_defs = true +warn_return_any = true +show_error_codes = true +warn_unused_ignores = false +disallow_incomplete_defs = true +disallow_untyped_decorators = true +disallow_any_unimported = true + +[tool.bandit] +targets = ["agent_framework_mem0"] +exclude_dirs = ["tests"] + +[tool.poe] +executor.type = "uv" +include = "../../shared_tasks.toml" +[tool.poe.tasks] +mypy = "mypy --config-file $POE_ROOT/pyproject.toml agent_framework_mem0" +test = "pytest --cov=agent_framework_mem0 --cov-report=term-missing:skip-covered tests" + +[tool.uv.build-backend] +module-name = "agent_framework_mem0" +module-root = "" + +[build-system] +requires = ["uv_build>=0.8.2,<0.9.0"] +build-backend = "uv_build" diff --git a/python/packages/mem0/tests/__init__.py b/python/packages/mem0/tests/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/python/packages/mem0/tests/test_cross_package.py b/python/packages/mem0/tests/test_cross_package.py new file mode 100644 index 0000000000..7d6e156702 --- /dev/null +++ b/python/packages/mem0/tests/test_cross_package.py @@ -0,0 +1,28 @@ +# Copyright (c) Microsoft. All rights reserved. + + +def test_self_through_main() -> None: + try: + from agent_framework.mem0 import __version__ + except ImportError: + __version__ = None + + assert __version__ is not None + + +def test_self() -> None: + try: + from agent_framework_mem0 import __version__ + except ImportError: + __version__ = None + + assert __version__ is not None + + +def test_agent_framework() -> None: + try: + from agent_framework import __version__ + except ImportError: + __version__ = None + + assert __version__ is not None diff --git a/python/packages/mem0/tests/test_provider.py b/python/packages/mem0/tests/test_provider.py new file mode 100644 index 0000000000..812eb8ac2a --- /dev/null +++ b/python/packages/mem0/tests/test_provider.py @@ -0,0 +1,481 @@ +# Copyright (c) Microsoft. All rights reserved. +# pyright: reportPrivateUsage=false + +from unittest.mock import AsyncMock, patch + +import pytest +from agent_framework import ChatMessage, Context, Role, TextContent +from agent_framework.exceptions import ServiceInitializationError +from agent_framework.mem0 import Mem0Provider + + +def test_mem0_provider_import(): + """Test that Mem0Provider can be imported.""" + assert Mem0Provider is not None + + +@pytest.fixture +def mock_mem0_client() -> AsyncMock: + """Create a mock Mem0 AsyncMemoryClient.""" + mock_client = AsyncMock() + mock_client.add = AsyncMock() + mock_client.search = AsyncMock() + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock() + mock_client.async_client = AsyncMock() + mock_client.async_client.aclose = AsyncMock() + return mock_client + + +@pytest.fixture +def sample_messages() -> list[ChatMessage]: + """Create sample chat messages for testing.""" + return [ + ChatMessage(role=Role.USER, text="Hello, how are you?"), + ChatMessage(role=Role.ASSISTANT, text="I'm doing well, thank you!"), + ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant"), + ] + + +class TestMem0ProviderInitialization: + """Test initialization and configuration of Mem0Provider.""" + + def test_init_with_all_ids(self, mock_mem0_client: AsyncMock): + """Test initialization with all IDs provided.""" + provider = Mem0Provider( + user_id="user123", + agent_id="agent123", + application_id="app123", + thread_id="thread123", + mem0_client=mock_mem0_client, + ) + assert provider.user_id == "user123" + assert provider.agent_id == "agent123" + assert provider.application_id == "app123" + assert provider.thread_id == "thread123" + + def test_init_without_filters_succeeds(self, mock_mem0_client: AsyncMock): + """Test that initialization succeeds even without filters (validation happens during invocation).""" + provider = Mem0Provider(mem0_client=mock_mem0_client) + assert provider.user_id is None + assert provider.agent_id is None + assert provider.application_id is None + assert provider.thread_id is None + + def test_init_with_custom_context_prompt(self, mock_mem0_client: AsyncMock): + """Test initialization with custom context prompt.""" + custom_prompt = "## Custom Memories\nConsider these memories:" + provider = Mem0Provider(user_id="user123", context_prompt=custom_prompt, mem0_client=mock_mem0_client) + assert provider.context_prompt == custom_prompt + + def test_init_with_scope_to_per_operation_thread_id(self, mock_mem0_client: AsyncMock): + """Test initialization with scope_to_per_operation_thread_id enabled.""" + provider = Mem0Provider( + user_id="user123", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + assert provider.scope_to_per_operation_thread_id is True + + @patch("mem0.AsyncMemoryClient") + def test_init_creates_default_client_when_none_provided(self, mock_memory_client_class: AsyncMock): + """Test that a default client is created when none is provided.""" + mock_client = AsyncMock() + mock_memory_client_class.return_value = mock_client + + provider = Mem0Provider(user_id="user123", api_key="test_api_key") + + mock_memory_client_class.assert_called_once_with(api_key="test_api_key") + assert provider.mem0_client == mock_client + assert provider._should_close_client is True + + def test_init_with_provided_client_should_not_close(self, mock_mem0_client: AsyncMock): + """Test that provided client should not be closed by provider.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + assert provider._should_close_client is False + + +class TestMem0ProviderAsyncContextManager: + """Test async context manager behavior.""" + + async def test_async_context_manager_entry(self, mock_mem0_client: AsyncMock): + """Test async context manager entry returns self.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + async with provider as ctx: + assert ctx is provider + + async def test_async_context_manager_exit_closes_client_when_should_close(self): + """Test that async context manager closes client when it should.""" + mock_client = AsyncMock() + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock() + mock_client.async_client = AsyncMock() + mock_client.async_client.aclose = AsyncMock() + + with patch("mem0.AsyncMemoryClient", return_value=mock_client): + provider = Mem0Provider(user_id="user123", api_key="test_key") + assert provider._should_close_client is True + + async with provider: + pass + + mock_client.__aexit__.assert_called_once() + + async def test_async_context_manager_exit_does_not_close_provided_client(self, mock_mem0_client: AsyncMock): + """Test that async context manager does not close provided client.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + assert provider._should_close_client is False + + async with provider: + pass + + mock_mem0_client.__aexit__.assert_not_called() + + +class TestMem0ProviderThreadMethods: + """Test thread lifecycle methods.""" + + async def test_thread_created_sets_per_operation_thread_id(self, mock_mem0_client: AsyncMock): + """Test that thread_created sets per-operation thread ID.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + + await provider.thread_created("thread123") + + assert provider._per_operation_thread_id == "thread123" + + async def test_thread_created_with_existing_thread_id(self, mock_mem0_client: AsyncMock): + """Test thread_created when thread ID already exists.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + provider._per_operation_thread_id = "existing_thread" + + await provider.thread_created("thread123") + + # Should not overwrite existing thread ID + assert provider._per_operation_thread_id == "existing_thread" + + async def test_thread_created_validation_with_scope_enabled(self, mock_mem0_client: AsyncMock): + """Test thread_created validation when scope_to_per_operation_thread_id is enabled.""" + provider = Mem0Provider( + user_id="user123", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "existing_thread" + + with pytest.raises(ValueError) as exc_info: + await provider.thread_created("different_thread") + + assert "can only be used with one thread at a time" in str(exc_info.value) + + async def test_messages_adding_sets_per_operation_thread_id( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test that messages_adding sets per-operation thread ID.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + + await provider.messages_adding("thread123", sample_messages) + + assert provider._per_operation_thread_id == "thread123" + + +class TestMem0ProviderMessagesAdding: + """Test messages_adding method.""" + + async def test_messages_adding_fails_without_filters(self, mock_mem0_client: AsyncMock): + """Test that messages_adding fails when no filters are provided.""" + provider = Mem0Provider(mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="Hello!") + + with pytest.raises(ServiceInitializationError) as exc_info: + await provider.messages_adding("thread123", message) + + assert "At least one of the filters" in str(exc_info.value) + + async def test_messages_adding_single_message(self, mock_mem0_client: AsyncMock): + """Test adding a single message.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="Hello!") + + await provider.messages_adding("thread123", message) + + mock_mem0_client.add.assert_called_once() + call_args = mock_mem0_client.add.call_args + assert call_args.kwargs["messages"] == [{"role": "user", "content": "Hello!"}] + assert call_args.kwargs["user_id"] == "user123" + + async def test_messages_adding_multiple_messages( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test adding multiple messages.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + + await provider.messages_adding("thread123", sample_messages) + + mock_mem0_client.add.assert_called_once() + call_args = mock_mem0_client.add.call_args + expected_messages = [ + {"role": "user", "content": "Hello, how are you?"}, + {"role": "assistant", "content": "I'm doing well, thank you!"}, + {"role": "system", "content": "You are a helpful assistant"}, + ] + assert call_args.kwargs["messages"] == expected_messages + + async def test_messages_adding_with_agent_id(self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage]): + """Test adding messages with agent_id.""" + provider = Mem0Provider(agent_id="agent123", mem0_client=mock_mem0_client) + + await provider.messages_adding("thread123", sample_messages) + + call_args = mock_mem0_client.add.call_args + assert call_args.kwargs["agent_id"] == "agent123" + assert call_args.kwargs["user_id"] is None + + async def test_messages_adding_with_application_id( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test adding messages with application_id in metadata.""" + provider = Mem0Provider(user_id="user123", application_id="app123", mem0_client=mock_mem0_client) + + await provider.messages_adding("thread123", sample_messages) + + call_args = mock_mem0_client.add.call_args + assert call_args.kwargs["metadata"] == {"application_id": "app123"} + + async def test_messages_adding_with_scope_to_per_operation_thread_id( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test adding messages with scope_to_per_operation_thread_id enabled.""" + provider = Mem0Provider( + user_id="user123", + thread_id="base_thread", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "operation_thread" + + await provider.messages_adding("operation_thread", sample_messages) + + call_args = mock_mem0_client.add.call_args + assert call_args.kwargs["run_id"] == "operation_thread" + + async def test_messages_adding_without_scope_uses_base_thread_id( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test adding messages without scope uses base thread_id.""" + provider = Mem0Provider( + user_id="user123", + thread_id="base_thread", + scope_to_per_operation_thread_id=False, + mem0_client=mock_mem0_client, + ) + + await provider.messages_adding("operation_thread", sample_messages) + + call_args = mock_mem0_client.add.call_args + assert call_args.kwargs["run_id"] == "base_thread" + + async def test_messages_adding_filters_empty_messages(self, mock_mem0_client: AsyncMock): + """Test that empty or invalid messages are filtered out.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + messages = [ + ChatMessage(role=Role.USER, text=""), # Empty text + ChatMessage(role=Role.USER, text=" "), # Whitespace only + ChatMessage(role=Role.USER, text="Valid message"), + ] + + await provider.messages_adding("thread123", messages) + + call_args = mock_mem0_client.add.call_args + # Should only include the valid message + assert call_args.kwargs["messages"] == [{"role": "user", "content": "Valid message"}] + + async def test_messages_adding_skips_when_no_valid_messages(self, mock_mem0_client: AsyncMock): + """Test that mem0 client is not called when no valid messages exist.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + messages = [ + ChatMessage(role=Role.USER, text=""), + ChatMessage(role=Role.USER, text=" "), + ] + + await provider.messages_adding("thread123", messages) + + mock_mem0_client.add.assert_not_called() + + +class TestMem0ProviderModelInvoking: + """Test model_invoking method.""" + + async def test_model_invoking_fails_without_filters(self, mock_mem0_client: AsyncMock): + """Test that model_invoking fails when no filters are provided.""" + provider = Mem0Provider(mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="What's the weather?") + + with pytest.raises(ServiceInitializationError) as exc_info: + await provider.model_invoking(message) + + assert "At least one of the filters" in str(exc_info.value) + + async def test_model_invoking_single_message(self, mock_mem0_client: AsyncMock): + """Test model_invoking with a single message.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="What's the weather?") + + # Mock search results + mock_mem0_client.search.return_value = [ + {"memory": "User likes outdoor activities"}, + {"memory": "User lives in Seattle"}, + ] + + context = await provider.model_invoking(message) + + mock_mem0_client.search.assert_called_once() + call_args = mock_mem0_client.search.call_args + assert call_args.kwargs["query"] == "What's the weather?" + assert call_args.kwargs["user_id"] == "user123" + + assert isinstance(context, Context) + expected_instructions = ( + "## Memories\nConsider the following memories when answering user questions:\n" + "User likes outdoor activities\nUser lives in Seattle" + ) + + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert context.contents[0].text == expected_instructions + + async def test_model_invoking_multiple_messages( + self, mock_mem0_client: AsyncMock, sample_messages: list[ChatMessage] + ): + """Test model_invoking with multiple messages.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + + mock_mem0_client.search.return_value = [{"memory": "Previous conversation context"}] + + await provider.model_invoking(sample_messages) + + call_args = mock_mem0_client.search.call_args + expected_query = "Hello, how are you?\nI'm doing well, thank you!\nYou are a helpful assistant" + assert call_args.kwargs["query"] == expected_query + + async def test_model_invoking_with_agent_id(self, mock_mem0_client: AsyncMock): + """Test model_invoking with agent_id.""" + provider = Mem0Provider(agent_id="agent123", mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="Hello") + + mock_mem0_client.search.return_value = [] + + await provider.model_invoking(message) + + call_args = mock_mem0_client.search.call_args + assert call_args.kwargs["agent_id"] == "agent123" + assert call_args.kwargs["user_id"] is None + + async def test_model_invoking_with_scope_to_per_operation_thread_id(self, mock_mem0_client: AsyncMock): + """Test model_invoking with scope_to_per_operation_thread_id enabled.""" + provider = Mem0Provider( + user_id="user123", + thread_id="base_thread", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "operation_thread" + message = ChatMessage(role=Role.USER, text="Hello") + + mock_mem0_client.search.return_value = [] + + await provider.model_invoking(message) + + call_args = mock_mem0_client.search.call_args + assert call_args.kwargs["run_id"] == "operation_thread" + + async def test_model_invoking_no_memories_returns_none_instructions(self, mock_mem0_client: AsyncMock): + """Test that no memories returns context with None instructions.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + message = ChatMessage(role=Role.USER, text="Hello") + + mock_mem0_client.search.return_value = [] + + context = await provider.model_invoking(message) + + assert isinstance(context, Context) + assert not context.contents + + async def test_model_invoking_filters_empty_message_text(self, mock_mem0_client: AsyncMock): + """Test that empty message text is filtered out from query.""" + provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) + messages = [ + ChatMessage(role=Role.USER, text=""), + ChatMessage(role=Role.USER, text="Valid message"), + ChatMessage(role=Role.USER, text=" "), + ] + + mock_mem0_client.search.return_value = [] + + await provider.model_invoking(messages) + + call_args = mock_mem0_client.search.call_args + assert call_args.kwargs["query"] == "Valid message" + + async def test_model_invoking_custom_context_prompt(self, mock_mem0_client: AsyncMock): + """Test model_invoking with custom context prompt.""" + custom_prompt = "## Custom Context\nRemember these details:" + provider = Mem0Provider( + user_id="user123", + context_prompt=custom_prompt, + mem0_client=mock_mem0_client, + ) + message = ChatMessage(role=Role.USER, text="Hello") + + mock_mem0_client.search.return_value = [{"memory": "Test memory"}] + + context = await provider.model_invoking(message) + + expected_instructions = "## Custom Context\nRemember these details:\nTest memory" + assert context.contents + assert isinstance(context.contents[0], TextContent) + assert context.contents[0].text == expected_instructions + + +class TestMem0ProviderValidation: + """Test validation methods.""" + + def test_validate_per_operation_thread_id_success(self, mock_mem0_client: AsyncMock): + """Test successful validation of per-operation thread ID.""" + provider = Mem0Provider( + user_id="user123", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "thread123" + + # Should not raise exception for same thread ID + provider._validate_per_operation_thread_id("thread123") + + # Should not raise exception for None + provider._validate_per_operation_thread_id(None) + + def test_validate_per_operation_thread_id_failure(self, mock_mem0_client: AsyncMock): + """Test validation failure for conflicting thread IDs.""" + provider = Mem0Provider( + user_id="user123", + scope_to_per_operation_thread_id=True, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "thread123" + + with pytest.raises(ValueError) as exc_info: + provider._validate_per_operation_thread_id("different_thread") + + assert "can only be used with one thread at a time" in str(exc_info.value) + + def test_validate_per_operation_thread_id_disabled_scope(self, mock_mem0_client: AsyncMock): + """Test that validation is skipped when scope is disabled.""" + provider = Mem0Provider( + user_id="user123", + scope_to_per_operation_thread_id=False, + mem0_client=mock_mem0_client, + ) + provider._per_operation_thread_id = "thread123" + + # Should not raise exception even with different thread ID + provider._validate_per_operation_thread_id("different_thread") diff --git a/python/packages/workflow/agent_framework_workflow/_executor.py b/python/packages/workflow/agent_framework_workflow/_executor.py index 2cd1b1623a..0a7135047f 100644 --- a/python/packages/workflow/agent_framework_workflow/_executor.py +++ b/python/packages/workflow/agent_framework_workflow/_executor.py @@ -902,6 +902,14 @@ class AgentExecutor(Executor): ) await ctx.add_event(AgentRunEvent(self.id, response)) + full_conversation: list[ChatMessage] | None = None + if self._cache: + full_conversation = list(self._cache) + list(response.messages) + + agent_response = AgentExecutorResponse(self.id, response, full_conversation=full_conversation) + await ctx.send_message(agent_response) + self._cache.clear() + @handler async def from_response(self, prior: AgentExecutorResponse, ctx: WorkflowContext[AgentExecutorResponse]) -> None: """Enable seamless chaining: accept a prior AgentExecutorResponse as input. diff --git a/python/packages/workflow/agent_framework_workflow/_telemetry.py b/python/packages/workflow/agent_framework_workflow/_telemetry.py index 625e81aa67..682a90b040 100644 --- a/python/packages/workflow/agent_framework_workflow/_telemetry.py +++ b/python/packages/workflow/agent_framework_workflow/_telemetry.py @@ -35,11 +35,11 @@ class WorkflowDiagnosticSettings(AFBaseSettings): """Settings for workflow tracing diagnostics.""" env_prefix: ClassVar[str] = "AGENT_FRAMEWORK_WORKFLOW_" - enable_otel_diagnostics: bool = False + enable_otel: bool = False @property def ENABLED(self) -> bool: - return self.enable_otel_diagnostics + return self.enable_otel class WorkflowTracer: diff --git a/python/packages/workflow/tests/test_tracing.py b/python/packages/workflow/tests/test_tracing.py index 021012f6fd..d42132402a 100644 --- a/python/packages/workflow/tests/test_tracing.py +++ b/python/packages/workflow/tests/test_tracing.py @@ -22,8 +22,8 @@ from agent_framework_workflow._workflow_context import WorkflowContext @pytest.fixture def tracing_enabled() -> Generator[None, None, None]: """Enable tracing for tests.""" - original_value = os.environ.get("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS") - os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS"] = "true" + original_value = os.environ.get("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL") + os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL"] = "true" # Force reload the settings to pick up the environment variable from agent_framework_workflow._telemetry import WorkflowDiagnosticSettings @@ -34,9 +34,9 @@ def tracing_enabled() -> Generator[None, None, None]: # Restore original value if original_value is None: - os.environ.pop("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS", None) + os.environ.pop("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL", None) else: - os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS"] = original_value + os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL"] = original_value # Reload settings again workflow_tracer.settings = WorkflowDiagnosticSettings() @@ -142,7 +142,6 @@ class FanInAggregator(Executor): return self._processed_messages -@pytest.mark.asyncio async def test_workflow_tracer_configuration() -> None: """Test that workflow tracer can be enabled and disabled.""" # Test disabled by default @@ -150,8 +149,8 @@ async def test_workflow_tracer_configuration() -> None: assert not tracer.enabled # Test enabled with environment variable - original_value = os.environ.get("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS") - os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS"] = "true" + original_value = os.environ.get("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL") + os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL"] = "true" # Force reload the settings to pick up the environment variable from agent_framework_workflow._telemetry import WorkflowDiagnosticSettings @@ -162,15 +161,14 @@ async def test_workflow_tracer_configuration() -> None: # Restore original value if original_value is None: - os.environ.pop("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS", None) + os.environ.pop("AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL", None) else: - os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS"] = original_value + os.environ["AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL"] = original_value # Reload settings again tracer.settings = WorkflowDiagnosticSettings() -@pytest.mark.asyncio async def test_span_creation_and_attributes(tracing_enabled: Any, span_exporter: InMemorySpanExporter) -> None: """Test creation and attributes of all span types (workflow, processing, sending).""" # Create a mock workflow object @@ -228,7 +226,6 @@ async def test_span_creation_and_attributes(tracing_enabled: Any, span_exporter: assert sending_span.attributes.get("message.destination_executor_id") == "target-789" -@pytest.mark.asyncio async def test_trace_context_handling(tracing_enabled: Any, span_exporter: InMemorySpanExporter) -> None: """Test trace context propagation and handling in messages and executors.""" shared_state = SharedState() diff --git a/python/pyproject.toml b/python/pyproject.toml index 0b04f3dd21..a8b1d7f979 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -7,6 +7,7 @@ dependencies = [ "agent-framework", "agent-framework-azure", "agent-framework-foundry", + "agent-framework-mem0", "agent-framework-workflow", ] @@ -63,8 +64,9 @@ exclude = [ "packages/agent_framework_project.egg-info" ] agent-framework = { workspace = true } agent-framework-azure = { workspace = true } agent-framework-foundry = { workspace = true } -agent-framework-workflow = { workspace = true } +agent-framework-mem0 = { workspace = true } agent-framework-runtime = { workspace = true } +agent-framework-workflow = { workspace = true } [tool.ruff] line-length = 120 @@ -125,12 +127,17 @@ notice-rgx = "^# Copyright \\(c\\) Microsoft\\. All rights reserved\\." min-file-size = 1 [tool.pytest.ini_options] -testpaths = 'tests' +testpaths = '**/tests' addopts = "-ra -q -r fEX" asyncio_mode = "auto" asyncio_default_fixture_loop_scope = "function" filterwarnings = [] timeout = 120 +markers = [ + "azure: marks tests as Azure provider specific", + "foundry: marks tests as Foundry provider specific", + "openai: marks tests as OpenAI provider specific", +] [tool.coverage.run] omit = [ @@ -186,7 +193,7 @@ build = "python run_tasks_in_packages_if_exists.py build" # combined checks check = ["fmt", "lint", "pyright", "mypy", "test", "markdown-code-lint", "samples-code-check"] pre-commit-check = ["fmt", "lint", "pyright", "markdown-code-lint", "samples-code-check"] -all-tests = "pytest --cov=agent_framework --cov=agent_framework_azure --cov=agent_framework_foundry --cov=agent_framework_workflow --cov-report=term-missing:skip-covered packages/**/tests" +all-tests = "pytest --import-mode=importlib --cov=agent_framework --cov=agent_framework_azure --cov=agent_framework_foundry --cov=agent_framework_mem0 --cov=agent_framework_workflow --cov-report=term-missing:skip-covered packages/azure/tests packages/foundry/tests packages/main/tests packages/mem0/tests packages/workflow/tests" [tool.poe.tasks.venv] cmd = "uv venv --clear --python $python" diff --git a/python/samples/getting_started/agents/foundry/README.md b/python/samples/getting_started/agents/foundry/README.md index 2a2981f2b8..39d8c9aa6e 100644 --- a/python/samples/getting_started/agents/foundry/README.md +++ b/python/samples/getting_started/agents/foundry/README.md @@ -11,6 +11,7 @@ This folder contains examples demonstrating different ways to create and use age | [`foundry_with_existing_agent.py`](foundry_with_existing_agent.py) | Shows how to work with a pre-existing agent by providing the agent ID to the Foundry chat client. This example also demonstrates proper cleanup of manually created agents. | | [`foundry_with_function_tools.py`](foundry_with_function_tools.py) | Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries). | | [`foundry_with_code_interpreter.py`](foundry_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with Foundry agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. | +| [`foundry_with_local_mcp.py`](foundry_with_local_mcp.py) | Shows how to integrate Foundry agents with Model Context Protocol (MCP) servers for enhanced functionality and tool integration. Demonstrates both agent-level and run-level tool configuration. | | [`foundry_with_thread.py`](foundry_with_thread.py) | Demonstrates thread management with Foundry agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions. | ## Environment Variables diff --git a/python/samples/getting_started/agents/foundry/foundry_with_local_mcp.py b/python/samples/getting_started/agents/foundry/foundry_with_local_mcp.py new file mode 100644 index 0000000000..401a62f2a7 --- /dev/null +++ b/python/samples/getting_started/agents/foundry/foundry_with_local_mcp.py @@ -0,0 +1,81 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio + +from agent_framework import ChatAgent, MCPStreamableHTTPTool +from agent_framework.foundry import FoundryChatClient +from azure.identity.aio import AzureCliCredential + + +async def mcp_tools_on_run_level() -> None: + """Example showing MCP tools defined when running the agent.""" + print("=== Tools Defined on Run Level ===") + + # Tools are provided when running the agent + # This means we have to ensure we connect to the MCP server before running the agent + # and pass the tools to the run method. + async with ( + AzureCliCredential() as credential, + MCPStreamableHTTPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + ) as mcp_server, + ChatAgent( + chat_client=FoundryChatClient(async_credential=credential), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + ) as agent, + ): + # First query + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + result1 = await agent.run(query1, tools=mcp_server) + print(f"{agent.name}: {result1}\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + result2 = await agent.run(query2, tools=mcp_server) + print(f"{agent.name}: {result2}\n") + + +async def mcp_tools_on_agent_level() -> None: + """Example showing tools defined when creating the agent.""" + print("=== Tools Defined on Agent Level ===") + + # Tools are provided when creating the agent + # The agent can use these tools for any query during its lifetime + # The agent will connect to the MCP server through its context manager. + async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=MCPStreamableHTTPTool( # Tools defined at agent creation + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + ), + ) as agent, + ): + # First query + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + result1 = await agent.run(query1) + print(f"{agent.name}: {result1}\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + result2 = await agent.run(query2) + print(f"{agent.name}: {result2}\n") + + +async def main() -> None: + print("=== Foundry Chat Client Agent with MCP Tools Examples ===\n") + + await mcp_tools_on_agent_level() + await mcp_tools_on_run_level() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_hosted_mcp.py b/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_hosted_mcp.py new file mode 100644 index 0000000000..ee2140a72f --- /dev/null +++ b/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_hosted_mcp.py @@ -0,0 +1,224 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +from typing import TYPE_CHECKING, Any + +from agent_framework import ChatAgent, HostedMCPTool +from agent_framework.openai import OpenAIResponsesClient + +if TYPE_CHECKING: + from agent_framework import AgentProtocol, AgentThread + + +async def handle_approvals_without_thread(query: str, agent: "AgentProtocol"): + """When we don't have a thread, we need to ensure we return with the input, approval request and approval.""" + from agent_framework import ChatMessage + + result = await agent.run(query) + while len(result.user_input_requests) > 0: + new_inputs: list[Any] = [query] + for user_input_needed in result.user_input_requests: + print( + f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" + f" with arguments: {user_input_needed.function_call.arguments}" + ) + new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + user_approval = input("Approve function call? (y/n): ") + new_inputs.append( + ChatMessage(role="user", contents=[user_input_needed.create_response(user_approval.lower() == "y")]) + ) + + result = await agent.run(new_inputs) + return result + + +async def handle_approvals_with_thread(query: str, agent: "AgentProtocol", thread: "AgentThread"): + """Here we let the thread deal with the previous responses, and we just rerun with the approval.""" + from agent_framework import ChatMessage + + result = await agent.run(query, thread=thread, store=True) + while len(result.user_input_requests) > 0: + new_input: list[Any] = [] + for user_input_needed in result.user_input_requests: + print( + f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" + f" with arguments: {user_input_needed.function_call.arguments}" + ) + user_approval = input("Approve function call? (y/n): ") + new_input.append( + ChatMessage( + role="user", + contents=[user_input_needed.create_response(user_approval.lower() == "y")], + ) + ) + result = await agent.run(new_input, thread=thread, store=True) + return result + + +async def handle_approvals_with_thread_streaming(query: str, agent: "AgentProtocol", thread: "AgentThread"): + """Here we let the thread deal with the previous responses, and we just rerun with the approval.""" + from agent_framework import ChatMessage + + new_input: list[ChatMessage] = [] + new_input_added = True + while new_input_added: + new_input_added = False + new_input.append(ChatMessage(role="user", text=query)) + async for update in agent.run_stream(new_input, thread=thread, store=True): + if update.user_input_requests: + for user_input_needed in update.user_input_requests: + print( + f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" + f" with arguments: {user_input_needed.function_call.arguments}" + ) + user_approval = input("Approve function call? (y/n): ") + new_input.append( + ChatMessage( + role="user", contents=[user_input_needed.create_response(user_approval.lower() == "y")] + ) + ) + new_input_added = True + else: + yield update + + +async def run_hosted_mcp_without_thread_and_specific_approval() -> None: + """Example showing Mcp Tools with approvals without using a thread.""" + print("=== Mcp with approvals and without thread ===") + + # Tools are provided when creating the agent + # The agent can use these tools for any query during its lifetime + async with ChatAgent( + chat_client=OpenAIResponsesClient(), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=HostedMCPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + # we don't require approval for microsoft_docs_search tool calls + # but we do for any other tool + approval_mode={"never_require_approval": ["microsoft_docs_search"]}, + ), + ) as agent: + # First query + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + result1 = await handle_approvals_without_thread(query1, agent) + print(f"{agent.name}: {result1}\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + result2 = await handle_approvals_without_thread(query2, agent) + print(f"{agent.name}: {result2}\n") + + +async def run_hosted_mcp_without_approval() -> None: + """Example showing Mcp Tools without approvals.""" + print("=== Mcp without approvals ===") + + # Tools are provided when creating the agent + # The agent can use these tools for any query during its lifetime + async with ChatAgent( + chat_client=OpenAIResponsesClient(), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=HostedMCPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + # we don't require approval for any function calls + # this means we will not see the approval messages, + # it is fully handled by the service and a final response is returned. + approval_mode="never_require", + ), + ) as agent: + # First query + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + result1 = await handle_approvals_without_thread(query1, agent) + print(f"{agent.name}: {result1}\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + result2 = await handle_approvals_without_thread(query2, agent) + print(f"{agent.name}: {result2}\n") + + +async def run_hosted_mcp_with_thread() -> None: + """Example showing Mcp Tools with approvals using a thread.""" + print("=== Mcp with approvals and with thread ===") + + # Tools are provided when creating the agent + # The agent can use these tools for any query during its lifetime + async with ChatAgent( + chat_client=OpenAIResponsesClient(), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=HostedMCPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + # we require approval for all function calls + approval_mode="always_require", + ), + ) as agent: + # First query + thread = agent.get_new_thread() + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + result1 = await handle_approvals_with_thread(query1, agent, thread) + print(f"{agent.name}: {result1}\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + result2 = await handle_approvals_with_thread(query2, agent, thread) + print(f"{agent.name}: {result2}\n") + + +async def run_hosted_mcp_with_thread_streaming() -> None: + """Example showing Mcp Tools with approvals using a thread.""" + print("=== Mcp with approvals and with thread ===") + + # Tools are provided when creating the agent + # The agent can use these tools for any query during its lifetime + async with ChatAgent( + chat_client=OpenAIResponsesClient(), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=HostedMCPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + # we require approval for all function calls + approval_mode="always_require", + ), + ) as agent: + # First query + thread = agent.get_new_thread() + query1 = "How to create an Azure storage account using az cli?" + print(f"User: {query1}") + print(f"{agent.name}: ", end="") + async for update in handle_approvals_with_thread_streaming(query1, agent, thread): + print(update, end="") + print("\n") + print("\n=======================================\n") + # Second query + query2 = "What is Microsoft Semantic Kernel?" + print(f"User: {query2}") + print(f"{agent.name}: ", end="") + async for update in handle_approvals_with_thread_streaming(query2, agent, thread): + print(update, end="") + print("\n") + + +async def main() -> None: + print("=== OpenAI Responses Client Agent with Hosted Mcp Tools Examples ===\n") + + await run_hosted_mcp_without_approval() + await run_hosted_mcp_without_thread_and_specific_approval() + await run_hosted_mcp_with_thread() + await run_hosted_mcp_with_thread_streaming() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_local_mcp.py b/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_local_mcp.py index 11302318de..a3935b87a5 100644 --- a/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_local_mcp.py +++ b/python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_local_mcp.py @@ -13,7 +13,6 @@ async def streaming_with_mcp(show_raw_stream: bool = False) -> None: through the raw_representation. You can view this, by setting the show_raw_stream parameter to True. """ print("=== Tools Defined on Agent Level ===") - # Tools are provided when creating the agent # The agent can use these tools for any query during its lifetime async with ChatAgent( diff --git a/python/samples/getting_started/context_providers/mem0/README.md b/python/samples/getting_started/context_providers/mem0/README.md new file mode 100644 index 0000000000..dcf68e1527 --- /dev/null +++ b/python/samples/getting_started/context_providers/mem0/README.md @@ -0,0 +1,51 @@ +# Mem0 Context Provider Examples + +[Mem0](https://mem0.ai/) is a self-improving memory layer for Large Language Models that enables applications to have long-term memory capabilities. The Agent Framework's Mem0 context provider integrates with Mem0's API to provide persistent memory across conversation sessions. + +This folder contains examples demonstrating how to use the Mem0 context provider with the Agent Framework for persistent memory and context management across conversations. + +## Examples + +| File | Description | +|------|-------------| +| [`mem0_basic.py`](mem0_basic.py) | Basic example of using Mem0 context provider to store and retrieve user preferences across different conversation threads. | +| [`mem0_threads.py`](mem0_threads.py) | Advanced example demonstrating different thread scoping strategies with Mem0. Covers global thread scope (memories shared across all operations), per-operation thread scope (memories isolated per thread), and multiple agents with different memory configurations for personal vs. work contexts. | + +## Prerequisites + +### Required Resources + +1. [Mem0 API Key](https://app.mem0.ai/) - Sign up for a Mem0 account and get your API key +2. Azure AI Foundry project endpoint (used in these examples) +3. Azure CLI authentication (run `az login`) + +## Configuration + +### Environment Variables + +Set the following environment variables: + +**For Mem0:** +- `MEM0_API_KEY`: Your Mem0 API key (alternatively, pass it as `api_key` parameter to `Mem0Provider`) + +**For Azure AI Foundry:** +- `FOUNDRY_PROJECT_ENDPOINT`: Your Azure AI Foundry project endpoint +- `FOUNDRY_MODEL_DEPLOYMENT_NAME`: The name of your model deployment + +## Key Concepts + +### Memory Scoping + +The Mem0 context provider supports different scoping strategies: + +- **Global Scope** (`scope_to_per_operation_thread_id=False`): Memories are shared across all conversation threads +- **Thread Scope** (`scope_to_per_operation_thread_id=True`): Memories are isolated per conversation thread + +### Memory Association + +Mem0 records can be associated with different identifiers: + +- `user_id`: Associate memories with a specific user +- `agent_id`: Associate memories with a specific agent +- `thread_id`: Associate memories with a specific conversation thread +- `application_id`: Associate memories with an application context diff --git a/python/samples/getting_started/context_providers/mem0/mem0_basic.py b/python/samples/getting_started/context_providers/mem0/mem0_basic.py new file mode 100644 index 0000000000..008542c7b4 --- /dev/null +++ b/python/samples/getting_started/context_providers/mem0/mem0_basic.py @@ -0,0 +1,72 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +import uuid + +from agent_framework.foundry import FoundryChatClient +from agent_framework.mem0 import Mem0Provider +from azure.identity.aio import AzureCliCredential + + +def retrieve_company_report(company_code: str, detailed: bool) -> str: + if company_code != "CNTS": + raise ValueError("Company code not found") + if not detailed: + return "CNTS is a company that specializes in technology." + return ( + "CNTS is a company that specializes in technology. " + "It had a revenue of $10 million in 2022. It has 100 employees." + ) + + +async def main() -> None: + """Example of memory usage with Mem0 context provider.""" + print("=== Mem0 Context Provider Example ===") + + # Each record in Mem0 should be associated with agent_id or user_id or application_id or thread_id. + # In this example, we associate Mem0 records with user_id. + user_id = str(uuid.uuid4()) + + # For Azure authentication, run `az login` command in terminal or replace AzureCliCredential with preferred + # authentication option. + # For Mem0 authentication, set Mem0 API key via "api_key" parameter or MEM0_API_KEY environment variable. + async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="FriendlyAssistant", + instructions="You are a friendly assistant.", + tools=retrieve_company_report, + context_providers=Mem0Provider(user_id=user_id), + ) as agent, + ): + # First ask the agent to retrieve a company report with no previous context. + # The agent will not be able to invoke the tool, since it doesn't know + # the company code or the report format, so it should ask for clarification. + query = "Please retrieve my company report" + print(f"User: {query}") + result = await agent.run(query) + print(f"Agent: {result}\n") + + # Now tell the agent the company code and the report format that you want to use + # and it should be able to invoke the tool and return the report. + query = "I always work with CNTS and I always want a detailed report format. Please remember and retrieve it." + print(f"User: {query}") + result = await agent.run(query) + print(f"Agent: {result}\n") + + print("\nRequest within a new thread:") + # Create a new thread for the agent. + # The new thread has no context of the previous conversation. + thread = agent.get_new_thread() + + # Since we have the mem0 component in the thread, the agent should be able to + # retrieve the company report without asking for clarification, as it will + # be able to remember the user preferences from Mem0 component. + query = "Please retrieve my company report" + print(f"User: {query}") + result = await agent.run(query, thread=thread) + print(f"Agent: {result}\n") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/context_providers/mem0/mem0_threads.py b/python/samples/getting_started/context_providers/mem0/mem0_threads.py new file mode 100644 index 0000000000..7c7c87c1a8 --- /dev/null +++ b/python/samples/getting_started/context_providers/mem0/mem0_threads.py @@ -0,0 +1,164 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +import uuid + +from agent_framework.foundry import FoundryChatClient +from agent_framework.mem0 import Mem0Provider +from azure.identity.aio import AzureCliCredential + + +def get_user_preferences(user_id: str) -> str: + """Mock function to get user preferences.""" + preferences = { + "user123": "Prefers concise responses and technical details", + "user456": "Likes detailed explanations with examples", + } + return preferences.get(user_id, "No specific preferences found") + + +async def example_global_thread_scope() -> None: + """Example 1: Global thread_id scope (memories shared across all operations).""" + print("1. Global Thread Scope Example:") + print("-" * 40) + + global_thread_id = str(uuid.uuid4()) + user_id = "user123" + + async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="GlobalMemoryAssistant", + instructions="You are an assistant that remembers user preferences across conversations.", + tools=get_user_preferences, + context_providers=Mem0Provider( + user_id=user_id, + thread_id=global_thread_id, + scope_to_per_operation_thread_id=False, # Share memories across all threads + ), + ) as global_agent, + ): + # Store some preferences in the global scope + query = "Remember that I prefer technical responses with code examples when discussing programming." + print(f"User: {query}") + result = await global_agent.run(query) + print(f"Agent: {result}\n") + + # Create a new thread - but memories should still be accessible due to global scope + new_thread = global_agent.get_new_thread() + query = "What do you know about my preferences?" + print(f"User (new thread): {query}") + result = await global_agent.run(query, thread=new_thread) + print(f"Agent: {result}\n") + + +async def example_per_operation_thread_scope() -> None: + """Example 2: Per-operation thread scope (memories isolated per thread). + + Note: When scope_to_per_operation_thread_id=True, the provider is bound to a single thread + throughout its lifetime. Use the same thread object for all operations with that provider. + """ + print("2. Per-Operation Thread Scope Example:") + print("-" * 40) + + user_id = "user123" + + async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="ScopedMemoryAssistant", + instructions="You are an assistant with thread-scoped memory.", + tools=get_user_preferences, + context_providers=Mem0Provider( + user_id=user_id, + scope_to_per_operation_thread_id=True, # Isolate memories per thread + ), + ) as scoped_agent, + ): + # Create a specific thread for this scoped provider + dedicated_thread = scoped_agent.get_new_thread() + + # Store some information in the dedicated thread + query = "Remember that for this conversation, I'm working on a Python project about data analysis." + print(f"User (dedicated thread): {query}") + result = await scoped_agent.run(query, thread=dedicated_thread) + print(f"Agent: {result}\n") + + # Test memory retrieval in the same dedicated thread + query = "What project am I working on?" + print(f"User (same dedicated thread): {query}") + result = await scoped_agent.run(query, thread=dedicated_thread) + print(f"Agent: {result}\n") + + # Store more information in the same thread + query = "Also remember that I prefer using pandas and matplotlib for this project." + print(f"User (same dedicated thread): {query}") + result = await scoped_agent.run(query, thread=dedicated_thread) + print(f"Agent: {result}\n") + + # Test comprehensive memory retrieval + query = "What do you know about my current project and preferences?" + print(f"User (same dedicated thread): {query}") + result = await scoped_agent.run(query, thread=dedicated_thread) + print(f"Agent: {result}\n") + + +async def example_multiple_agents() -> None: + """Example 3: Multiple agents with different thread configurations.""" + print("3. Multiple Agents with Different Thread Configurations:") + print("-" * 40) + + agent_id_1 = "agent_personal" + agent_id_2 = "agent_work" + + async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="PersonalAssistant", + instructions="You are a personal assistant that helps with personal tasks.", + context_providers=Mem0Provider( + agent_id=agent_id_1, + ), + ) as personal_agent, + FoundryChatClient(async_credential=credential).create_agent( + name="WorkAssistant", + instructions="You are a work assistant that helps with professional tasks.", + context_providers=Mem0Provider( + agent_id=agent_id_2, + ), + ) as work_agent, + ): + # Store personal information + query = "Remember that I like to exercise at 6 AM and prefer outdoor activities." + print(f"User to Personal Agent: {query}") + result = await personal_agent.run(query) + print(f"Personal Agent: {result}\n") + + # Store work information + query = "Remember that I have team meetings every Tuesday at 2 PM." + print(f"User to Work Agent: {query}") + result = await work_agent.run(query) + print(f"Work Agent: {result}\n") + + # Test memory isolation + query = "What do you know about my schedule?" + print(f"User to Personal Agent: {query}") + result = await personal_agent.run(query) + print(f"Personal Agent: {result}\n") + + print(f"User to Work Agent: {query}") + result = await work_agent.run(query) + print(f"Work Agent: {result}\n") + + +async def main() -> None: + """Run all Mem0 thread management examples.""" + print("=== Mem0 Thread Management Example ===\n") + + await example_global_thread_scope() + await example_per_operation_thread_scope() + await example_multiple_agents() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/.env.example b/python/samples/getting_started/telemetry/.env.example index 5e8bced445..3c1632a83a 100644 --- a/python/samples/getting_started/telemetry/.env.example +++ b/python/samples/getting_started/telemetry/.env.example @@ -1,5 +1,13 @@ -CONNECTION_STRING="..." +# Connector environment variables +# Foundry +# see ../../../env.example for details +# OpenAI +# see ../../../env.example for details + +# Otel specific variables +APPLICATION_INSIGHTS_CONNECTION_STRING="..." +APPLICATION_INSIGHTS_LIVE_METRICS=true OTLP_ENDPOINT="http://localhost:4317/" -AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS=true -AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE=true -AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS=true +ENABLE_OTEL=true +ENABLE_SENSITIVE_DATA=true +WORKFLOW_ENABLE_OTEL=true diff --git a/python/samples/getting_started/telemetry/01-zero_code.py b/python/samples/getting_started/telemetry/01-zero_code.py new file mode 100644 index 0000000000..6fd6e06e79 --- /dev/null +++ b/python/samples/getting_started/telemetry/01-zero_code.py @@ -0,0 +1,86 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +import os +from random import randint +from typing import TYPE_CHECKING, Annotated + +from agent_framework.openai import OpenAIResponsesClient +from pydantic import Field + +if TYPE_CHECKING: + from agent_framework import ChatClientProtocol + + +""" +This is the simplest sample of using the Agent Framework with telemetry. +Since it does not create a tracer or span in the script's code, we can let the Agent Framework SDK handle everything. +If the environment variables are set correctly, +the SDK will automatically initialize telemetry and collect traces and logs. +""" + + +if "AGENT_FRAMEWORK_ENABLE_OTEL" not in os.environ: + print("Set AGENT_FRAMEWORK_ENABLE_OTEL to enable telemetry with a OTLP endpoint.") +if "AGENT_FRAMEWORK_OTLP_ENDPOINT" not in os.environ and "AGENT_FRAMEWORK_MONITOR_CONNECTION_STRING" not in os.environ: + print("Set AGENT_FRAMEWORK_OTLP_ENDPOINT or AGENT_FRAMEWORK_MONITOR_CONNECTION_STRING to enable telemetry.") + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def run_chat_client(client: "ChatClientProtocol", stream: bool = False) -> None: + """Run an AI service. + + This function runs an AI service and prints the output. + Telemetry will be collected for the service execution behind the scenes, + and the traces will be sent to the configured telemetry backend. + + The telemetry will include information about the AI service execution. + + Args: + stream: Whether to use streaming for the plugin + + Remarks: + When function calling is outside the open telemetry loop + each of the call to the model is handled as a seperate span, + while when the open telemetry is put last, a single span + is shown, which might include one or more rounds of function calling. + + So for the scenario below, you should see the following: + + 2 spans with gen_ai.operation.name=chat + The first has finish_reason "tool_calls" + The second has finish_reason "stop" + 2 spans with gen_ai.operation.name=execute_tool + + """ + message = "What's the weather in Amsterdam and in Paris?" + print(f"User: {message}") + if stream: + print("Assistant: ", end="") + async for chunk in client.get_streaming_response(message, tools=get_weather): + if str(chunk): + print(str(chunk), end="") + print("") + else: + response = await client.get_response(message, tools=get_weather) + print(f"Assistant: {response}") + + +async def main() -> None: + client = OpenAIResponsesClient() + + # Scenarios where telemetry is collected in the SDK, from the most basic to the most complex. + await run_chat_client(client, stream=True) + await run_chat_client(client, stream=False) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/02a-generic_chat_client.py b/python/samples/getting_started/telemetry/02a-generic_chat_client.py new file mode 100644 index 0000000000..6fb85a440a --- /dev/null +++ b/python/samples/getting_started/telemetry/02a-generic_chat_client.py @@ -0,0 +1,134 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import argparse +import asyncio +from contextlib import suppress +from random import randint +from typing import TYPE_CHECKING, Annotated, Literal + +from agent_framework import __version__, ai_function +from agent_framework.openai import OpenAIResponsesClient +from agent_framework.telemetry import setup_telemetry +from opentelemetry import trace +from opentelemetry.trace import SpanKind +from opentelemetry.trace.span import format_trace_id +from pydantic import Field + +if TYPE_CHECKING: + from agent_framework import ChatClientProtocol + +""" +This sample, show how you can get telemetry from a chat client and tool. +it explicitly calls the `setup_telemetry` function to set up telemetry in order to include the overall spans, +those are defined in the main and run_* functions. +""" + + +# Define the scenarios that can be run +SCENARIOS = ["chat_client", "chat_client_stream", "ai_function", "all"] + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def run_chat_client(client: "ChatClientProtocol", stream: bool = False) -> None: + """Run an AI service. + + This function runs an AI service and prints the output. + Telemetry will be collected for the service execution behind the scenes, + and the traces will be sent to the configured telemetry backend. + + The telemetry will include information about the AI service execution. + + Args: + client: The chat client to use. + stream: Whether to use streaming for the response + + Remarks: + For the scenario below, you should see the following: + 1 Client span, with 4 children: + 2 Internal span with gen_ai.operation.name=chat + The first has finish_reason "tool_calls" + The second has finish_reason "stop" + 2 Internal span with gen_ai.operation.name=execute_tool + + """ + scenario_name = "Chat Client Stream" if stream else "Chat Client" + + tracer = trace.get_tracer("agent_framework", __version__) + with tracer.start_as_current_span(name=f"Scenario: {scenario_name}", kind=SpanKind.CLIENT): + print("Running scenario:", scenario_name) + message = "What's the weather in Amsterdam and in Paris?" + print(f"User: {message}") + if stream: + print("Assistant: ", end="") + async for chunk in client.get_streaming_response(message, tools=get_weather): + if str(chunk): + print(str(chunk), end="") + print("") + else: + response = await client.get_response(message, tools=get_weather) + print(f"Assistant: {response}") + + +async def run_ai_function() -> None: + """Run a AI function. + + This function runs a AI function and prints the output. + Telemetry will be collected for the function execution behind the scenes, + and the traces will be sent to the configured telemetry backend. + + The telemetry will include information about the AI function execution + and the AI service execution. + """ + + tracer = trace.get_tracer("agent_framework", __version__) + with tracer.start_as_current_span("Scenario: AI Function", kind=SpanKind.CLIENT): + print("Running scenario: AI Function") + func = ai_function(get_weather) + weather = await func.invoke(location="Amsterdam") + print(f"Weather in Amsterdam:\n{weather}") + + +async def main(scenario: Literal["chat_client", "chat_client_stream", "ai_function", "all"] = "all"): + """Run the selected scenario(s).""" + + setup_telemetry() + + tracer = trace.get_tracer("My application", __version__) + with tracer.start_as_current_span("Sample Scenario's", kind=SpanKind.CLIENT) as current_span: + print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}") + + client = OpenAIResponsesClient() + + # Scenarios where telemetry is collected in the SDK, from the most basic to the most complex. + if scenario == "chat_client_stream" or scenario == "all": + with suppress(Exception): + await run_chat_client(client, stream=True) + if scenario == "chat_client" or scenario == "all": + with suppress(Exception): + await run_chat_client(client, stream=False) + if scenario == "ai_function" or scenario == "all": + with suppress(Exception): + await run_ai_function() + + +if __name__ == "__main__": + arg_parser = argparse.ArgumentParser() + + arg_parser.add_argument( + "--scenario", + type=str, + choices=SCENARIOS, + default="all", + help="The scenario to run. Default is all.", + ) + + args = arg_parser.parse_args() + asyncio.run(main(args.scenario)) diff --git a/python/samples/getting_started/telemetry/02b-foundry_chat_client.py b/python/samples/getting_started/telemetry/02b-foundry_chat_client.py new file mode 100644 index 0000000000..fa4706a016 --- /dev/null +++ b/python/samples/getting_started/telemetry/02b-foundry_chat_client.py @@ -0,0 +1,88 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +import os +from random import randint +from typing import Annotated + +from agent_framework import HostedCodeInterpreterTool +from agent_framework.telemetry import setup_telemetry +from agent_framework_foundry import FoundryChatClient +from azure.ai.projects.aio import AIProjectClient +from azure.identity.aio import AzureCliCredential +from opentelemetry import trace +from opentelemetry.trace import SpanKind +from opentelemetry.trace.span import format_trace_id +from pydantic import Field + +""" +This sample, shows you can leverage the built-in telemetry in Foundry. +It uses the Foundry client to setup the telemetry, this calls +out to Foundry for a telemetry connection strings, +and then call the setup_telemetry function in the agent framework. +If you want to compare with the trace sent to a generic OTLP endpoint, +switch the `use_foundry_telemetry` variable to False. +""" + + +# ANSI color codes for printing in blue and resetting after each print +BLUE = "\x1b[34m" +RESET = "\x1b[0m" + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def main() -> None: + """Run an AI service. + + This function runs an AI service and prints the output. + Telemetry will be collected for the service execution behind the scenes, + and the traces will be sent to the configured telemetry backend. + + The telemetry will include information about the AI service execution. + + In foundry you will also see specific operations happening that are called by the Foundry implementation, + such as `create_agent`. + """ + use_foundry_telemetry = True + questions = [ + "What's the weather in Amsterdam and in Paris?", + "Why is the sky blue?", + "Tell me about AI.", + "Can you write a python function that adds two numbers? and use it to add 8483 and 5692?", + ] + async with ( + AzureCliCredential() as credential, + AIProjectClient(endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"], credential=credential) as project, + FoundryChatClient(client=project, setup_tracing=False) as client, + ): + if use_foundry_telemetry: + await client.setup_foundry_telemetry(enable_live_metrics=True) + else: + setup_telemetry() + + tracer = trace.get_tracer("agent_framework") + with tracer.start_as_current_span(name="Foundry Telemetry from Agent Framework", kind=SpanKind.CLIENT) as span: + for question in questions: + print(f"{BLUE}User: {question}{RESET}") + print(f"{BLUE}Assistant: {RESET}", end="") + async for chunk in client.get_streaming_response( + question, tools=[get_weather, HostedCodeInterpreterTool()] + ): + if str(chunk): + print(f"{BLUE}{str(chunk)}{RESET}", end="") + print(f"{BLUE}{RESET}") + + print(f"{BLUE}Done{RESET}") + print(f"{BLUE}Operation ID: {format_trace_id(span.get_span_context().trace_id)}{RESET}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/03a-agent.py b/python/samples/getting_started/telemetry/03a-agent.py new file mode 100644 index 0000000000..4bdb111321 --- /dev/null +++ b/python/samples/getting_started/telemetry/03a-agent.py @@ -0,0 +1,59 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +from random import randint +from typing import Annotated + +from agent_framework import ChatAgent +from agent_framework.openai import OpenAIChatClient +from agent_framework.telemetry import setup_telemetry +from opentelemetry import trace +from opentelemetry.trace import SpanKind +from pydantic import Field + +""" +This sample shows you can can setup telemetry with a agent. +The agent invoke is a additional Semantic Convention that now +will wrap the calls made by the underlying chat client and tools. +""" + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def main(): + # Set up the telemetry + setup_telemetry() + + questions = ["What's the weather in Amsterdam?", "and in Paris, and which is better?", "Why is the sky blue?"] + + tracer = trace.get_tracer("agent_framework") + with tracer.start_as_current_span("Scenario: Agent Chat", kind=SpanKind.CLIENT): + print("Running scenario: Agent Chat") + print("Welcome to the chat, type 'exit' to quit.") + agent = ChatAgent( + chat_client=OpenAIChatClient(), + tools=get_weather, + name="WeatherAgent", + instructions="You are a weather assistant.", + ) + thread = agent.get_new_thread() + for question in questions: + print(f"User: {question}") + print(f"{agent.display_name}: ", end="") + async for update in agent.run_stream( + question, + thread=thread, + ): + if update.text: + print(update.text, end="") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/03b-foundry_agent.py b/python/samples/getting_started/telemetry/03b-foundry_agent.py new file mode 100644 index 0000000000..4c5bc414a3 --- /dev/null +++ b/python/samples/getting_started/telemetry/03b-foundry_agent.py @@ -0,0 +1,65 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +import os +from random import randint +from typing import Annotated + +from agent_framework import ChatAgent +from agent_framework_foundry import FoundryChatClient +from azure.ai.projects.aio import AIProjectClient +from azure.identity.aio import AzureCliCredential +from opentelemetry import trace +from opentelemetry.trace import SpanKind +from pydantic import Field + +""" +This sample shows you can can setup telemetry with a agent from Foundry. +We once again call the `setup_foundry_telemetry` method to set up telemetry in order to include the overall spans. +""" + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def main(): + # Set up the providers + # This must be done before any other telemetry calls + questions = ["What's the weather in Amsterdam?", "and in Paris, and which is better?", "Why is the sky blue?"] + async with ( + AzureCliCredential() as credential, + AIProjectClient(endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"], credential=credential) as project, + # this calls `setup_foundry_telemetry` through the context manager + FoundryChatClient(client=project) as client, + ): + await client.setup_foundry_telemetry(enable_live_metrics=True) + tracer = trace.get_tracer("agent_framework") + with tracer.start_as_current_span("Single Agent Chat", kind=SpanKind.CLIENT): + print("Running Single Agent Chat") + print("Welcome to the chat, type 'exit' to quit.") + agent = ChatAgent( + chat_client=client, + tools=get_weather, + name="WeatherAgent", + instructions="You are a weather assistant.", + ) + thread = agent.get_new_thread() + for question in questions: + print(f"User: {question}") + print(f"{agent.display_name}: ", end="") + async for update in agent.run_stream( + question, + thread=thread, + ): + if update.text: + print(update.text, end="") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/04-workflow.py b/python/samples/getting_started/telemetry/04-workflow.py new file mode 100644 index 0000000000..e07df885e2 --- /dev/null +++ b/python/samples/getting_started/telemetry/04-workflow.py @@ -0,0 +1,120 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +from typing import Any + +from agent_framework.telemetry import setup_telemetry +from agent_framework.workflow import ( + Executor, + WorkflowBuilder, + WorkflowCompletedEvent, + WorkflowContext, + handler, +) +from opentelemetry import trace +from opentelemetry.trace import SpanKind +from opentelemetry.trace.span import format_trace_id + +"""Telemetry sample demonstrating OpenTelemetry integration with Agent Framework workflows. + +This sample runs a simple sequential workflow with telemetry collection, +showing telemetry collection for workflow execution, executor processing, +and message publishing between executors. +""" + + +# Executors for sequential workflow +class UpperCaseExecutor(Executor): + """An executor that converts text to uppercase.""" + + @handler + async def to_upper_case(self, text: str, ctx: WorkflowContext[str]) -> None: + """Execute the task by converting the input string to uppercase.""" + print(f"UpperCaseExecutor: Processing '{text}'") + result = text.upper() + print(f"UpperCaseExecutor: Result '{result}'") + + # Send the result to the next executor in the workflow. + await ctx.send_message(result) + + +class ReverseTextExecutor(Executor): + """An executor that reverses text.""" + + @handler + async def reverse_text(self, text: str, ctx: WorkflowContext[Any]) -> None: + """Execute the task by reversing the input string.""" + print(f"ReverseTextExecutor: Processing '{text}'") + result = text[::-1] + print(f"ReverseTextExecutor: Result '{result}'") + + # Send the result with a workflow completion event. + await ctx.add_event(WorkflowCompletedEvent(result)) + + +async def run_sequential_workflow() -> None: + """Run a simple sequential workflow demonstrating telemetry collection. + + This workflow processes a string through two executors in sequence: + 1. UpperCaseExecutor converts the input to uppercase + 2. ReverseTextExecutor reverses the string and completes the workflow + + Telemetry data collected includes: + - Overall workflow execution spans + - Individual executor processing spans + - Message publishing between executors + - Workflow completion events + """ + + tracer = trace.get_tracer(__name__) + with tracer.start_as_current_span("Scenario: Sequential Workflow", kind=SpanKind.CLIENT) as current_span: + print("Running scenario: Sequential Workflow") + try: + # Step 1: Create the executors. + upper_case_executor = UpperCaseExecutor(id="upper_case_executor") + reverse_text_executor = ReverseTextExecutor(id="reverse_text_executor") + + # Step 2: Build the workflow with the defined edges. + workflow = ( + WorkflowBuilder() + .add_edge(upper_case_executor, reverse_text_executor) + .set_start_executor(upper_case_executor) + .build() + ) + + # Step 3: Run the workflow with an initial message. + input_text = "hello world" + print(f"Starting workflow with input: '{input_text}'") + + completion_event = None + async for event in workflow.run_stream(input_text): + print(f"Event: {event}") + if isinstance(event, WorkflowCompletedEvent): + # The WorkflowCompletedEvent contains the final result. + completion_event = event + + if completion_event: + print(f"Workflow completed with result: '{completion_event.data}'") + else: + print("Workflow completed without a completion event") + + except Exception as e: + current_span.record_exception(e) + print(f"Error running workflow: {e}") + + +async def main(): + """Run the telemetry sample with a simple sequential workflow.""" + + setup_telemetry() + + tracer = trace.get_tracer("agent_framework") + with tracer.start_as_current_span("Sequential Workflow Scenario", kind=SpanKind.CLIENT) as current_span: + print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}") + + # Run the sequential workflow scenario + await run_sequential_workflow() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/README.md b/python/samples/getting_started/telemetry/README.md index 5d947cda17..b574aa4251 100644 --- a/python/samples/getting_started/telemetry/README.md +++ b/python/samples/getting_started/telemetry/README.md @@ -1,8 +1,8 @@ # Agent Framework Python Telemetry -This sample project shows how a Python application can be configured to send Agent Framework telemetry to the Application Performance Management (APM) vendors of your choice. +This sample folder shows how a Python application can be configured to send Agent Framework telemetry to the Application Performance Management (APM) vendors of your choice. -In this sample, we provide options to send telemetry to [Application Insights](https://learn.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview), [Aspire Dashboard](https://learn.microsoft.com/en-us/dotnet/aspire/fundamentals/dashboard/overview?tabs=bash), and console output. +In this sample, we provide options to send telemetry to [Application Insights](https://learn.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview) and [Aspire Dashboard](https://learn.microsoft.com/en-us/dotnet/aspire/fundamentals/dashboard/overview?tabs=bash). > **Quick Start**: For local development without Azure setup, you can use the [Aspire Dashboard](https://learn.microsoft.com/en-us/dotnet/aspire/fundamentals/dashboard/standalone) which runs locally via Docker and provides an excellent telemetry viewing experience for OpenTelemetry data. @@ -24,6 +24,7 @@ The Agent Framework Python SDK is designed to efficiently generate comprehensive ### Required resources 2. OpenAI or [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) +2. [Foundry project](https://ai.azure.com/doc/azure/ai-foundry/what-is-azure-ai-foundry) ### Optional resources @@ -31,61 +32,51 @@ The Agent Framework Python SDK is designed to efficiently generate comprehensive 2. [Aspire Dashboard](https://learn.microsoft.com/en-us/dotnet/aspire/fundamentals/dashboard/standalone-for-python?tabs=flask%2Cwindows#start-the-aspire-dashboard) ### Dependencies +No additional dependencies are required to enable telemetry. The necessary packages are included as part of the `agent-framework` package. Unless you want to use a different APM vendor, in which case you will need to install the appropriate OpenTelemetry exporter package. -You will also need to install the following dependencies to your virtual environment to run this sample: +### Environment variables +The following environment variables can be set to configure telemetry, the first two set the basic configuration: -```bash -# For Azure ApplicationInsights/AzureMonitor -uv pip install azure-monitor-opentelemetry azure-monitor-opentelemetry-exporter -# For OTLP endpoint -uv pip install opentelemetry-exporter-otlp-proto-grpc -``` +- AGENT_FRAMEWORK_ENABLE_OTEL=true +- AGENT_FRAMEWORK_ENABLE_SENSITIVE_DATA=true -## Running the sample +Next we need to know where to send the telemetry, for that you can use either a OTLP endpoint or a connection string for Application Insights: +- AGENT_FRAMEWORK_OTLP_ENDPOINT="" +or +- AGENT_FRAMEWORK_MONITOR_CONNECTION_STRING="" +Finally, you can enable live metrics streaming to Application Insights: +- AGENT_FRAMEWORK_MONITOR_LIVE_METRICS=true + +> IMPORTANT - If both OTLP endpoint and connection string are set, the connection string will take precedence and there will be no trace to the OTLP endpoint. + +## Samples +This folder contains different samples demonstrating how to use telemetry in various scenarios. + +### [01 - zero_code](./01-zero_code.py): +A simple example showing how to enable telemetry in a zero-touch scenario. When the above environment variables are set, telemetry will be automatically enabled, however since you do not define any overarching tracer, you will only see the spans for the specific calls to the chat client and tools. + +### [02a](./02a-generic_chat_client.py) and [02b](./02b-foundry_chat_client.py) Chat Clients: +These two samples show how to first setup the telemetry by manually importing the `setup_telemetry` function from the `agent_framework.telemetry` module and calling it. After this is done, the trace that get's created will live in the same context as the chat client calls, allowing you to see the end-to-end flow of your application. For Foundry, there is a method in the Foundry project client to get the telemetry url for your project, the `.setup_foundry_telemetry()` method in the `FoundryChatClient` class will use this url to configure telemetry and you then do not have to import and call `setup_telemetry()` manually. +Because of the way OpenTelemetry works, you can only call `setup_telemetry()` once per application run, so make sure you do that in the right place. + +### [03a](./03a-generic_agent.py) and [03b](./03b-foundry_agent.py) Agents: +These two samples show how to setup telemetry when using the Agent Framework's agent abstraction layer. They are similar to the chat client samples, but also show how to create an agent and invoke it. The same rules apply for setting up telemetry, you can either call `setup_telemetry()` manually, or use the `setup_foundry_telemetry()` method in the `FoundryChatClient` class. + +### [04 - workflow](./04-workflow.py) Workflow: +This sample shows how to setup telemetry when using the Agent Framework's workflow execution engine. It demonstrates a simple workflow scenario with telemetry. + + +## Running the samples 1. Open a terminal and navigate to this folder: `python/samples/getting_started/telemetry/`. This is necessary for the `.env` file to be read correctly. 2. Create a `.env` file if one doesn't already exist in this folder. Please refer to the [example file](./.env.example). > Note that `CONNECTION_STRING` and `SAMPLE_OTLP_ENDPOINT` are optional. If you don't configure them, everything will get outputted to the console. - > Set `AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS=true` to enable basic telemetry and `AGENT_FRAMEWORK_GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE=true` to include sensitive information like prompts and responses. - > Set `AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL_DIAGNOSTICS=true` to enable workflow telemetry for the workflow samples. + > Set `AGENT_FRAMEWORK_ENABLE_OTEL=true` to enable basic telemetry and `AGENT_FRAMEWORK_ENABLE_SENSITIVE_DATA=true` to include sensitive information like prompts and responses. > Sensitive information should only be enabled in a development or test environment. It is not recommended to enable this in production environments as it may expose sensitive data. -3. Activate your python virtual environment, and then run `python scenarios.py`, `python interactive.py`, `python agent.py`, or `python workflow.py`. - + > Set `AGENT_FRAMEWORK_WORKFLOW_ENABLE_OTEL=true` to enable workflow telemetry for the workflow samples. +3. Activate your python virtual environment, and then run `python 01-zero_code.py` or others. > This will output the Operation/Trace ID, which can be used later for filtering. -### Scenarios - -This sample includes multiple applications demonstrating Agent Framework telemetry: - -#### scenarios.py - -Organized into specific scenarios where the framework will generate useful telemetry data: - -- `chat_client`: This is when a chat client is invoked directly (i.e. not streaming) with a weather tool function. **Information about the call to the underlying model and tool usage will be recorded**. -- `chat_client_stream`: This is when a chat client is invoked with streaming enabled and a weather tool function. **Information about the streaming call to the underlying model and tool usage will be recorded**. -- `ai_function`: This is when an AI function (`get_weather`) is invoked directly. **Information about the AI function and the call to the underlying model will be recorded**. - -By default, running `python scenarios.py` will run all three scenarios. To run individual scenarios, use the `--scenario` command line argument. For example, `python scenarios.py --scenario chat_client`. For more information, please run `python scenarios.py -h`. - -#### interactive.py - -An interactive chat application that demonstrates telemetry collection in a conversational context. This sample includes the same `get_weather` tool function and allows for multi-turn conversations. Run `python interactive.py` and start chatting. Type 'exit' to quit the application. This sample only logs at the `WARNING` level, so you will not see as much telemetry data as in the `scenarios.py` sample. - -#### agent.py - -A sample demonstrating Agent Framework telemetry collection for agent-based workflows. This shows how telemetry is captured when using the Agent Framework's agent abstraction layer, including agent initialization, message processing, and tool execution within an agent context. - -By default, running `python agent.py` will run all agent scenarios. To run individual scenarios, use the `--scenario` command line argument. For example, `python agent.py --scenario basic`. For more information, please run `python agent.py -h`. - -#### workflow.py - -A sample demonstrating workflow telemetry collection for the Agent Framework's workflow execution engine. This includes two scenarios: - -- `sequential`: A simple sequential workflow that processes text through two connected executors (uppercase conversion followed by text reversal). **Information about workflow execution, executor processing, and message passing between executors will be recorded**. -- `sub_workflow`: A more complex scenario demonstrating sub-workflow patterns with a parent workflow orchestrating multiple text processing tasks via sub-workflows. **Information about parent workflow execution, sub-workflow invocation, and cross-workflow communication will be recorded**. - -By default, running `python workflow.py` will run all workflow scenarios. To run individual scenarios, use the `--scenario` command line argument. For example, `python workflow.py --scenario sequential`. For more information, please run `python workflow.py -h`. - ## Application Insights/Azure Monitor ### Logs and traces @@ -151,13 +142,13 @@ This will start the dashboard with: Make sure your `.env` file includes the OTLP endpoint: ```bash -OTLP_ENDPOINT=http://localhost:4317 +AGENT_FRAMEWORK_OTLP_ENDPOINT=http://localhost:4317 ``` Or set it as an environment variable when running your samples: ```bash -OTLP_ENDPOINT=http://localhost:4317 python scenarios.py +AGENT_FRAMEWORK_ENABLE_OTEL=true AGENT_FRAMEWORK_OTLP_ENDPOINT=http://localhost:4317 python 01-zero_code.py ``` ### Viewing telemetry data @@ -170,138 +161,4 @@ Once your sample finishes running, navigate to in a web You won't have to deploy an Application Insights resource or install Docker to run Aspire Dashboard if you choose to inspect telemetry data in a console. However, it is difficult to navigate through all the spans and logs produced, so **this method is only recommended when you are just getting started**. -We recommend you to get started with the `chat_client` scenario as this generates the least amount of telemetry data. Below is similar to what you will see when you run `python scenarios.py --scenario chat_client`: - -```Json -{ - "name": "chat.completions gpt-4o", - "context": { - "trace_id": "0xbda1d9efcd65435653d18fa37aef7dd3", - "span_id": "0xcd443e1917510385", - "trace_state": "[]" - }, - "kind": "SpanKind.INTERNAL", - "parent_id": "0xeca0a2ca7b7a8191", - "start_time": "2024-09-09T23:13:14.625156Z", - "end_time": "2024-09-09T23:13:17.311909Z", - "status": { - "status_code": "UNSET" - }, - "attributes": { - "gen_ai.operation.name": "chat.completions", - "gen_ai.system": "openai", - "gen_ai.request.model": "gpt-4o", - "gen_ai.response.id": "chatcmpl-A5hrG13nhtFsOgx4ziuoskjNscHtT", - "gen_ai.response.finish_reason": "FinishReason.STOP", - "gen_ai.response.prompt_tokens": 16, - "gen_ai.response.completion_tokens": 28 - }, - "events": [ - { - "name": "gen_ai.content.prompt", - "timestamp": "2024-09-09T23:13:14.625156Z", - "attributes": { - "gen_ai.prompt": "[{\"role\": \"user\", \"content\": \"Why is the sky blue in one sentence?\"}]" - } - }, - { - "name": "gen_ai.content.completion", - "timestamp": "2024-09-09T23:13:17.311909Z", - "attributes": { - "gen_ai.completion": "[{\"role\": \"assistant\", \"content\": \"The sky appears blue because molecules in the Earth's atmosphere scatter shorter wavelengths of sunlight, such as blue, more effectively than longer wavelengths like red.\"}]" - } - } - ], - "links": [], - "resource": { - "attributes": { - "telemetry.sdk.language": "python", - "telemetry.sdk.name": "opentelemetry", - "telemetry.sdk.version": "1.26.0", - "service.name": "TelemetryExample" - }, - "schema_url": "" - } -} -{ - "name": "Scenario: Chat Client", - "context": { - "trace_id": "0xbda1d9efcd65435653d18fa37aef7dd3", - "span_id": "0xeca0a2ca7b7a8191", - "trace_state": "[]" - }, - "kind": "SpanKind.INTERNAL", - "parent_id": "0x48af7ad55f2f64b5", - "start_time": "2024-09-09T23:13:14.625156Z", - "end_time": "2024-09-09T23:13:17.312910Z", - "status": { - "status_code": "UNSET" - }, - "attributes": {}, - "events": [], - "links": [], - "resource": { - "attributes": { - "telemetry.sdk.language": "python", - "telemetry.sdk.name": "opentelemetry", - "telemetry.sdk.version": "1.26.0", - "service.name": "TelemetryExample" - }, - "schema_url": "" - } -} -{ - "name": "Scenario's", - "context": { - "trace_id": "0xbda1d9efcd65435653d18fa37aef7dd3", - "span_id": "0x48af7ad55f2f64b5", - "trace_state": "[]" - }, - "kind": "SpanKind.INTERNAL", - "parent_id": null, - "start_time": "2024-09-09T23:13:13.840481Z", - "end_time": "2024-09-09T23:13:17.312910Z", - "status": { - "status_code": "UNSET" - }, - "attributes": {}, - "events": [], - "links": [], - "resource": { - "attributes": { - "telemetry.sdk.language": "python", - "telemetry.sdk.name": "opentelemetry", - "telemetry.sdk.version": "1.26.0", - "service.name": "TelemetryExample" - }, - "schema_url": "" - } -} -{ - "body": "Agent Framework usage: CompletionUsage(completion_tokens=28, prompt_tokens=16, total_tokens=44)", - "severity_number": "", - "severity_text": "INFO", - "attributes": { - "code.filepath": "/path/to/agent_framework/openai/chat_client.py", - "code.function": "store_usage", - "code.lineno": 81 - }, - "dropped_attributes": 0, - "timestamp": "2024-09-09T23:13:17.311909Z", - "observed_timestamp": "2024-09-09T23:13:17.311909Z", - "trace_id": "0xbda1d9efcd65435653d18fa37aef7dd3", - "span_id": "0xcd443e1917510385", - "trace_flags": 1, - "resource": { - "attributes": { - "telemetry.sdk.language": "python", - "telemetry.sdk.name": "opentelemetry", - "telemetry.sdk.version": "1.26.0", - "service.name": "TelemetryExample" - }, - "schema_url": "" - } -} -``` - -In the output, you will find three spans: `Scenario's`, `Scenario: Chat Client`, and `chat.completions gpt-4o`, each representing a different layer in the sample. In particular, `chat.completions gpt-4o` is generated by the chat client. Inside it, you will find information about the call, such as the timestamp of the operation, the response id and the finish reason. You will also find sensitive information such as the prompt and response to and from the model (only if you have `AGENT_FRAMEWORK__GENAI_ENABLE_OTEL_DIAGNOSTICS_SENSITIVE` set to true). If you use Application Insights or Aspire Dashboard, these information will be available to you in an interactive UI. +Use the guides from OpenTelemetry to setup exporters for [the console](https://opentelemetry.io/docs/languages/python/getting-started/), or use [manual_setup_console_output](./manual_setup_console_output.py) as a reference, just know that there are a lot of options you can setup and this is not a comprehensive example. diff --git a/python/samples/getting_started/telemetry/agent.py b/python/samples/getting_started/telemetry/agent.py deleted file mode 100644 index 6f9d59b8dd..0000000000 --- a/python/samples/getting_started/telemetry/agent.py +++ /dev/null @@ -1,190 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. -# type: ignore -import asyncio -import logging -from random import randint -from typing import Annotated - -from agent_framework import ChatAgent -from agent_framework.openai import OpenAIChatClient -from azure.monitor.opentelemetry import configure_azure_monitor -from opentelemetry import trace -from opentelemetry._logs import set_logger_provider -from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter -from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter -from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter -from opentelemetry.metrics import set_meter_provider -from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler -from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter -from opentelemetry.sdk.metrics import MeterProvider -from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader -from opentelemetry.sdk.metrics.view import DropAggregation, View -from opentelemetry.sdk.resources import Resource -from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter -from opentelemetry.semconv.attributes import service_attributes -from opentelemetry.trace import SpanKind, set_tracer_provider -from pydantic import Field -from pydantic_settings import BaseSettings - - -class TelemetrySampleSettings(BaseSettings): - """Settings for the telemetry sample application. - - Optional settings are: - - connection_string: str - The connection string for the Application Insights resource. - This value can be found in the Overview section when examining - your resource from the Azure portal. - (Env var CONNECTION_STRING) - - otlp_endpoint: str - The OTLP endpoint to send telemetry data to. - Depending on the exporter used, you may find this value in different places. - (Env var OTLP_ENDPOINT) - - If no connection string or OTLP endpoint is provided, the telemetry data will be - exported to the console. - """ - - connection_string: str | None = None - otlp_endpoint: str | None = None - - -# Load settings -settings = TelemetrySampleSettings() - -# Create a resource to represent the service/sample -resource = Resource.create({service_attributes.SERVICE_NAME: "TelemetryExample"}) - -# Define the scenarios that can be run -SCENARIOS = ["ai_service", "kernel_function", "auto_function_invocation", "all"] - -if settings.connection_string: - configure_azure_monitor( - connection_string=settings.connection_string, enable_live_metrics=True, logger_name="agent_framework" - ) - - -def set_up_logging(): - class LogFilter(logging.Filter): - """A filter to not process records from several subpackages.""" - - # These are the namespaces that we want to exclude from logging for the purposes of this demo. - namespaces_to_exclude: list[str] = [ - "httpx", - "openai", - ] - - def filter(self, record): - return not any([record.name.startswith(namespace) for namespace in self.namespaces_to_exclude]) - - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPLogExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleLogExporter()) - - # Create and set a global logger provider for the application. - logger_provider = LoggerProvider(resource=resource) - # Log processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for log_exporter in exporters: - logger_provider.add_log_record_processor(BatchLogRecordProcessor(log_exporter)) - # Sets the global default logger provider - set_logger_provider(logger_provider) - - # Create a logging handler to write logging records, in OTLP format, to the exporter. - handler = LoggingHandler() - handler.addFilter(LogFilter()) - # Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger. - # Events from all child loggers will be processed by this handler. - logger = logging.getLogger() - logger.addHandler(handler) - # Set the logging level to INFO. - logger.setLevel(logging.INFO) - - -def set_up_tracing(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPSpanExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleSpanExporter()) - - # Initialize a trace provider for the application. This is a factory for creating tracers. - tracer_provider = TracerProvider(resource=resource) - # Span processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for exporter in exporters: - tracer_provider.add_span_processor(BatchSpanProcessor(exporter)) - # Sets the global default tracer provider - set_tracer_provider(tracer_provider) - - -def set_up_metrics(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPMetricExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleMetricExporter()) - - # Initialize a metric provider for the application. This is a factory for creating meters. - metric_readers = [ - PeriodicExportingMetricReader(metric_exporter, export_interval_millis=5000) for metric_exporter in exporters - ] - meter_provider = MeterProvider( - metric_readers=metric_readers, - resource=resource, - views=[ - # Dropping all instrument names except for those starting with "agent_framework" - View(instrument_name="*", aggregation=DropAggregation()), - View(instrument_name="agent_framework*"), - ], - ) - # Sets the global default meter provider - set_meter_provider(meter_provider) - - -async def get_weather( - location: Annotated[str, Field(description="The location to get the weather for.")], -) -> str: - """Get the weather for a given location.""" - await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call - conditions = ["sunny", "cloudy", "rainy", "stormy"] - return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." - - -async def main(): - # Set up the providers - # This must be done before any other telemetry calls - set_up_logging() - set_up_tracing() - set_up_metrics() - - tracer = trace.get_tracer("agent_framework") - with tracer.start_as_current_span("Scenario: Agent Chat", kind=SpanKind.CLIENT) as current_span: - print("Running scenario: Agent Chat") - print("Welcome to the chat, type 'exit' to quit.") - agent = ChatAgent( - chat_client=OpenAIChatClient(), - tools=get_weather, - name="WeatherAgent", - instructions="You are a weather assistant.", - ) - thread = agent.get_new_thread() - message = input("User: ") - try: - while message.lower() != "exit": - print(f"{agent.display_name}: ", end="") - async for update in agent.run_stream( - message, - thread=thread, - ): - if update.text: - print(update.text, end="") - message = input("\nUser: ") - except Exception as e: - current_span.record_exception(e) - print(f"\nError running interactive chat: {e}") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/interactive.py b/python/samples/getting_started/telemetry/interactive.py deleted file mode 100644 index 88dd294cde..0000000000 --- a/python/samples/getting_started/telemetry/interactive.py +++ /dev/null @@ -1,186 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. -# type: ignore -import asyncio -import logging -from random import randint -from typing import Annotated - -from agent_framework import ChatMessage, ChatResponse, ChatResponseUpdate -from agent_framework.openai import OpenAIChatClient -from azure.monitor.opentelemetry import configure_azure_monitor -from opentelemetry import trace -from opentelemetry._logs import set_logger_provider -from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter -from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter -from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter -from opentelemetry.metrics import set_meter_provider -from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler -from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter -from opentelemetry.sdk.metrics import MeterProvider -from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader -from opentelemetry.sdk.metrics.view import DropAggregation, View -from opentelemetry.sdk.resources import Resource -from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter -from opentelemetry.semconv.attributes import service_attributes -from opentelemetry.trace import SpanKind, set_tracer_provider -from pydantic import Field -from pydantic_settings import BaseSettings - - -class TelemetrySampleSettings(BaseSettings): - """Settings for the telemetry sample application. - - Optional settings are: - - connection_string: str - The connection string for the Application Insights resource. - This value can be found in the Overview section when examining - your resource from the Azure portal. - (Env var CONNECTION_STRING) - - otlp_endpoint: str - The OTLP endpoint to send telemetry data to. - Depending on the exporter used, you may find this value in different places. - (Env var OTLP_ENDPOINT) - - If no connection string or OTLP endpoint is provided, the telemetry data will be - exported to the console. - """ - - connection_string: str | None = None - otlp_endpoint: str | None = None - - -# Load settings -settings = TelemetrySampleSettings() - -# Create a resource to represent the service/sample -resource = Resource.create({service_attributes.SERVICE_NAME: "TelemetryExample"}) - -# Define the scenarios that can be run -SCENARIOS = ["ai_service", "kernel_function", "auto_function_invocation", "all"] - -if settings.connection_string: - configure_azure_monitor( - connection_string=settings.connection_string, enable_live_metrics=True, logger_name="agent_framework" - ) - - -def set_up_logging(): - class LogFilter(logging.Filter): - """A filter to not process records from several subpackages.""" - - # These are the namespaces that we want to exclude from logging for the purposes of this demo. - namespaces_to_exclude: list[str] = [ - "httpx", - "openai", - ] - - def filter(self, record): - return not any([record.name.startswith(namespace) for namespace in self.namespaces_to_exclude]) - - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPLogExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleLogExporter()) - - # Create and set a global logger provider for the application. - logger_provider = LoggerProvider(resource=resource) - # Log processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for log_exporter in exporters: - logger_provider.add_log_record_processor(BatchLogRecordProcessor(log_exporter)) - # Sets the global default logger provider - set_logger_provider(logger_provider) - - # Create a logging handler to write logging records, in OTLP format, to the exporter. - handler = LoggingHandler() - handler.addFilter(LogFilter()) - # Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger. - # Events from all child loggers will be processed by this handler. - logger = logging.getLogger() - logger.addHandler(handler) - # Set the logging level to WARNING, this will not log detailed events to the logger. - logger.setLevel(logging.WARNING) - - -def set_up_tracing(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPSpanExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleSpanExporter()) - - # Initialize a trace provider for the application. This is a factory for creating tracers. - tracer_provider = TracerProvider(resource=resource) - # Span processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for exporter in exporters: - tracer_provider.add_span_processor(BatchSpanProcessor(exporter)) - # Sets the global default tracer provider - set_tracer_provider(tracer_provider) - - -def set_up_metrics(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPMetricExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleMetricExporter()) - - # Initialize a metric provider for the application. This is a factory for creating meters. - metric_readers = [ - PeriodicExportingMetricReader(metric_exporter, export_interval_millis=5000) for metric_exporter in exporters - ] - meter_provider = MeterProvider( - metric_readers=metric_readers, - resource=resource, - views=[ - # Dropping all instrument names except for those starting with "agent_framework" - View(instrument_name="*", aggregation=DropAggregation()), - View(instrument_name="agent_framework*"), - ], - ) - # Sets the global default meter provider - set_meter_provider(meter_provider) - - -def get_weather( - location: Annotated[str, Field(description="The location to get the weather for.")], -) -> str: - """Get the weather for a given location.""" - conditions = ["sunny", "cloudy", "rainy", "stormy"] - return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." - - -async def main(): - # Set up the providers - # This must be done before any other telemetry calls - set_up_logging() - set_up_tracing() - set_up_metrics() - - tracer = trace.get_tracer("agent_framework") - with tracer.start_as_current_span("Scenario: Interactive Chat", kind=SpanKind.CLIENT) as current_span: - print("Running scenario: Interactive Chat") - print("Welcome to the chat, type 'exit' to quit.") - client = OpenAIChatClient() - messages: list[ChatMessage] = [] - message = input("User: ") - try: - while message.lower() != "exit": - messages.append(ChatMessage(role="user", text=message)) - print("Assistant: ", end="") - updates: list[ChatResponseUpdate] = [] - async for update in client.get_streaming_response(messages, tools=get_weather): - updates.append(update) - if update.text: - print(update.text, end="") - print("") - messages.extend(ChatResponse.from_chat_response_updates(updates).messages) - message = input("User: ") - except Exception as e: - current_span.record_exception(e) - print(f"\nError running interactive chat: {e}") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/manual_setup_console_output.py b/python/samples/getting_started/telemetry/manual_setup_console_output.py new file mode 100644 index 0000000000..2a74e67f5a --- /dev/null +++ b/python/samples/getting_started/telemetry/manual_setup_console_output.py @@ -0,0 +1,114 @@ +# Copyright (c) Microsoft. All rights reserved. +# type: ignore +import asyncio +import logging +from random import randint +from typing import Annotated + +from agent_framework.openai import OpenAIChatClient +from opentelemetry._logs import set_logger_provider +from opentelemetry.metrics import set_meter_provider +from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler +from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter +from opentelemetry.sdk.metrics import MeterProvider +from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader +from opentelemetry.sdk.resources import Resource +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter +from opentelemetry.semconv.resource import ResourceAttributes +from opentelemetry.trace import set_tracer_provider +from pydantic import Field + +""" +This sample shows how to manually set up OpenTelemetry to log to the console. +And this can also be used as a reference for more complex telemetry setups. +""" + +resource = Resource.create({ResourceAttributes.SERVICE_NAME: "ManualSetup"}) + + +def setup_console_telemetry(): + # Create and set a global logger provider for the application. + logger_provider = LoggerProvider(resource=resource) + # Log processors are initialized with an exporter which is responsible + logger_provider.add_log_record_processor(BatchLogRecordProcessor(ConsoleLogExporter())) + # Sets the global default logger provider + set_logger_provider(logger_provider) + + # Create a logging handler to write logging records, in OTLP format, to the exporter. + handler = LoggingHandler() + # Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger. + # Events from all child loggers will be processed by this handler. + logger = logging.getLogger() + logger.addHandler(handler) + # Set the logging level to NOTSET to allow all records to be processed by the handler. + logger.setLevel(logging.NOTSET) + # Initialize a trace provider for the application. This is a factory for creating tracers. + tracer_provider = TracerProvider(resource=resource) + # Span processors are initialized with an exporter which is responsible + # for sending the telemetry data to a particular backend. + tracer_provider.add_span_processor(BatchSpanProcessor(ConsoleSpanExporter())) + # Sets the global default tracer provider + set_tracer_provider(tracer_provider) + # Initialize a metric provider for the application. This is a factory for creating meters. + meter_provider = MeterProvider( + metric_readers=[PeriodicExportingMetricReader(ConsoleMetricExporter(), export_interval_millis=5000)], + resource=resource, + ) + # Sets the global default meter provider + set_meter_provider(meter_provider) + + +async def get_weather( + location: Annotated[str, Field(description="The location to get the weather for.")], +) -> str: + """Get the weather for a given location.""" + await asyncio.sleep(randint(0, 10) / 10.0) # Simulate a network call + conditions = ["sunny", "cloudy", "rainy", "stormy"] + return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + + +async def run_chat_client() -> None: + """Run an AI service. + + This function runs an AI service and prints the output. + Telemetry will be collected for the service execution behind the scenes, + and the traces will be sent to the configured telemetry backend. + + The telemetry will include information about the AI service execution. + + Args: + stream: Whether to use streaming for the plugin + + Remarks: + When function calling is outside the open telemetry loop + each of the call to the model is handled as a seperate span, + while when the open telemetry is put last, a single span + is shown, which might include one or more rounds of function calling. + + So for the scenario below, you should see the following: + + 2 spans with gen_ai.operation.name=chat + The first has finish_reason "tool_calls" + The second has finish_reason "stop" + 2 spans with gen_ai.operation.name=execute_tool + + """ + client = OpenAIChatClient() + message = "What's the weather in Amsterdam and in Paris?" + print(f"User: {message}") + print("Assistant: ", end="") + async for chunk in client.get_streaming_response(message, tools=get_weather): + if str(chunk): + print(str(chunk), end="") + print("") + + +async def main(): + """Run the selected scenario(s).""" + setup_console_telemetry() + await run_chat_client() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/getting_started/telemetry/scenarios.py b/python/samples/getting_started/telemetry/scenarios.py deleted file mode 100644 index 044260d8ca..0000000000 --- a/python/samples/getting_started/telemetry/scenarios.py +++ /dev/null @@ -1,249 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. -# type: ignore -import argparse -import asyncio -import logging -from random import randint -from typing import Annotated, Literal - -from agent_framework import ai_function -from agent_framework.openai import OpenAIChatClient -from azure.monitor.opentelemetry import configure_azure_monitor -from opentelemetry import trace -from opentelemetry._logs import set_logger_provider -from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter -from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter -from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter -from opentelemetry.metrics import set_meter_provider -from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler -from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter -from opentelemetry.sdk.metrics import MeterProvider -from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader -from opentelemetry.sdk.metrics.view import DropAggregation, View -from opentelemetry.sdk.resources import Resource -from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter -from opentelemetry.semconv.attributes import service_attributes -from opentelemetry.trace import SpanKind, set_tracer_provider -from opentelemetry.trace.span import format_trace_id -from pydantic import Field -from pydantic_settings import BaseSettings - - -class TelemetrySampleSettings(BaseSettings): - """Settings for the telemetry sample application. - - Optional settings are: - - connection_string: str - The connection string for the Application Insights resource. - This value can be found in the Overview section when examining - your resource from the Azure portal. - (Env var CONNECTION_STRING) - - otlp_endpoint: str - The OTLP endpoint to send telemetry data to. - Depending on the exporter used, you may find this value in different places. - (Env var OTLP_ENDPOINT) - - If no connection string or OTLP endpoint is provided, the telemetry data will be - exported to the console. - """ - - connection_string: str | None = None - otlp_endpoint: str | None = None - - -# Load settings -settings = TelemetrySampleSettings() - -# Create a resource to represent the service/sample -resource = Resource.create({service_attributes.SERVICE_NAME: "TelemetryExample"}) - -# Define the scenarios that can be run -SCENARIOS = ["chat_client", "chat_client_stream", "ai_function", "all"] - -if settings.connection_string: - configure_azure_monitor( - connection_string=settings.connection_string, - enable_live_metrics=True, - logger_name="agent_framework", - ) - - -def set_up_logging(): - class LogFilter(logging.Filter): - """A filter to not process records from several subpackages.""" - - # These are the namespaces that we want to exclude from logging for the purposes of this demo. - namespaces_to_exclude: list[str] = [ - "httpx", - "openai", - ] - - def filter(self, record): - return not any([record.name.startswith(namespace) for namespace in self.namespaces_to_exclude]) - - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPLogExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleLogExporter()) - - # Create and set a global logger provider for the application. - logger_provider = LoggerProvider(resource=resource) - # Log processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for log_exporter in exporters: - logger_provider.add_log_record_processor(BatchLogRecordProcessor(log_exporter)) - # Sets the global default logger provider - set_logger_provider(logger_provider) - - # Create a logging handler to write logging records, in OTLP format, to the exporter. - handler = LoggingHandler() - handler.addFilter(LogFilter()) - # Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger. - # Events from all child loggers will be processed by this handler. - logger = logging.getLogger() - logger.addHandler(handler) - # Set the logging level to NOTSET to allow all records to be processed by the handler. - logger.setLevel(logging.NOTSET) - - -def set_up_tracing(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPSpanExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleSpanExporter()) - - # Initialize a trace provider for the application. This is a factory for creating tracers. - tracer_provider = TracerProvider(resource=resource) - # Span processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for exporter in exporters: - tracer_provider.add_span_processor(BatchSpanProcessor(exporter)) - # Sets the global default tracer provider - set_tracer_provider(tracer_provider) - - -def set_up_metrics(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPMetricExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleMetricExporter()) - - # Initialize a metric provider for the application. This is a factory for creating meters. - metric_readers = [ - PeriodicExportingMetricReader(metric_exporter, export_interval_millis=5000) for metric_exporter in exporters - ] - meter_provider = MeterProvider( - metric_readers=metric_readers, - resource=resource, - views=[ - # Dropping all instrument names except for those starting with "agent_framework" - View(instrument_name="*", aggregation=DropAggregation()), - View(instrument_name="agent_framework*"), - ], - ) - # Sets the global default meter provider - set_meter_provider(meter_provider) - - -def get_weather( - location: Annotated[str, Field(description="The location to get the weather for.")], -) -> str: - """Get the weather for a given location.""" - conditions = ["sunny", "cloudy", "rainy", "stormy"] - return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." - - -async def run_chat_client(stream: bool = False) -> None: - """Run an AI service. - - This function runs an AI service and prints the output. - Telemetry will be collected for the service execution behind the scenes, - and the traces will be sent to the configured telemetry backend. - - The telemetry will include information about the AI service execution. - - Args: - stream (bool): Whether to use streaming for the plugin - """ - - tracer = trace.get_tracer(__name__) - with tracer.start_as_current_span( - "Scenario: Chat Client Stream" if stream else "Scenario: Chat Client", kind=SpanKind.CLIENT - ) as current_span: - print("Running scenario: Chat Client" if not stream else "Running scenario: Chat Client Stream") - try: - client = OpenAIChatClient() - message = "What's the weather in Amsterdam and in Paris?" - print(f"User: {message}") - if stream: - print("Assistant: ", end="") - async for chunk in client.get_streaming_response(message, tools=get_weather): - if str(chunk): - print(str(chunk), end="") - print("") - else: - response = await client.get_response(message, tools=get_weather) - print(f"Assistant: {response}") - except Exception as e: - current_span.record_exception(e) - print(f"Error running AI service: {e}") - - -async def run_ai_function() -> None: - """Run a AI function. - - This function runs a AI function and prints the output. - Telemetry will be collected for the function execution behind the scenes, - and the traces will be sent to the configured telemetry backend. - - The telemetry will include information about the AI function execution - and the AI service execution. - """ - - tracer = trace.get_tracer(__name__) - with tracer.start_as_current_span("Scenario: AI Function", kind=SpanKind.CLIENT) as current_span: - print("Running scenario: AI Function") - try: - func = ai_function(get_weather) - weather = await func.invoke(location="Amsterdam") - print(f"Weather in Amsterdam:\n{weather}") - except Exception as e: - current_span.record_exception(e) - print(f"Error running kernel plugin: {e}") - - -async def main(scenario: Literal["chat_client", "chat_client_stream", "ai_function", "all"] = "all"): - # Set up the providers - # This must be done before any other telemetry calls - set_up_logging() - set_up_tracing() - set_up_metrics() - - tracer = trace.get_tracer("agent_framework") - with tracer.start_as_current_span("Scenario's", kind=SpanKind.CLIENT) as current_span: - print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}") - - # Scenarios where telemetry is collected in the SDK, from the most basic to the most complex. - if scenario == "chat_client" or scenario == "all": - await run_chat_client(stream=False) - if scenario == "chat_client_stream" or scenario == "all": - await run_chat_client(stream=True) - if scenario == "ai_function" or scenario == "all": - await run_ai_function() - - -if __name__ == "__main__": - arg_parser = argparse.ArgumentParser() - - arg_parser.add_argument( - "--scenario", - type=str, - choices=SCENARIOS, - default="all", - help="The scenario to run. Default is all.", - ) - - args = arg_parser.parse_args() - asyncio.run(main(args.scenario)) diff --git a/python/samples/getting_started/telemetry/workflow.py b/python/samples/getting_started/telemetry/workflow.py deleted file mode 100644 index 830e2794cb..0000000000 --- a/python/samples/getting_started/telemetry/workflow.py +++ /dev/null @@ -1,253 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. -# type: ignore -import asyncio -import logging -from typing import Any - -from agent_framework.workflow import ( - Executor, - WorkflowBuilder, - WorkflowCompletedEvent, - WorkflowContext, - handler, -) -from azure.monitor.opentelemetry import configure_azure_monitor -from opentelemetry import trace -from opentelemetry._logs import set_logger_provider -from opentelemetry.exporter.otlp.proto.grpc._log_exporter import OTLPLogExporter -from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter -from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter -from opentelemetry.metrics import set_meter_provider -from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler -from opentelemetry.sdk._logs.export import BatchLogRecordProcessor, ConsoleLogExporter -from opentelemetry.sdk.metrics import MeterProvider -from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader -from opentelemetry.sdk.metrics.view import DropAggregation, View -from opentelemetry.sdk.resources import Resource -from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter -from opentelemetry.semconv.attributes import service_attributes -from opentelemetry.trace import SpanKind, set_tracer_provider -from opentelemetry.trace.span import format_trace_id -from pydantic_settings import BaseSettings - -"""Telemetry sample demonstrating OpenTelemetry integration with Agent Framework workflows. - -This sample runs a simple sequential workflow with telemetry collection, -showing telemetry collection for workflow execution, executor processing, -and message publishing between executors. -""" - - -class TelemetrySampleSettings(BaseSettings): - """Settings for the telemetry sample application. - - Optional settings are: - - connection_string: str - The connection string for the Application Insights resource. - This value can be found in the Overview section when examining - your resource from the Azure portal. - (Env var CONNECTION_STRING) - - otlp_endpoint: str - The OTLP endpoint to send telemetry data to. - Depending on the exporter used, you may find this value in different places. - (Env var OTLP_ENDPOINT) - - If no connection string or OTLP endpoint is provided, the telemetry data will be - exported to the console. - """ - - connection_string: str | None = None - otlp_endpoint: str | None = None - - -# Load settings -settings = TelemetrySampleSettings() - -# Create a resource to represent the service/sample -resource = Resource.create({service_attributes.SERVICE_NAME: "WorkflowTelemetryExample"}) - -if settings.connection_string: - configure_azure_monitor( - connection_string=settings.connection_string, - enable_live_metrics=True, - logger_name="agent_framework", - ) - - -def set_up_logging(): - class LogFilter(logging.Filter): - """A filter to not process records from several subpackages.""" - - # These are the namespaces that we want to exclude from logging for the purposes of this demo. - namespaces_to_exclude: list[str] = [ - "httpx", - "openai", - ] - - def filter(self, record): - return not any([record.name.startswith(namespace) for namespace in self.namespaces_to_exclude]) - - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPLogExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleLogExporter()) - - # Create and set a global logger provider for the application. - logger_provider = LoggerProvider(resource=resource) - # Log processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for log_exporter in exporters: - logger_provider.add_log_record_processor(BatchLogRecordProcessor(log_exporter)) - # Sets the global default logger provider - set_logger_provider(logger_provider) - - # Create a logging handler to write logging records, in OTLP format, to the exporter. - handler = LoggingHandler() - handler.addFilter(LogFilter()) - # Attach the handler to the root logger. `getLogger()` with no arguments returns the root logger. - # Events from all child loggers will be processed by this handler. - logger = logging.getLogger() - logger.addHandler(handler) - # Set the logging level to NOTSET to allow all records to be processed by the handler. - logger.setLevel(logging.NOTSET) - - -def set_up_tracing(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPSpanExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleSpanExporter()) - - # Initialize a trace provider for the application. This is a factory for creating tracers. - tracer_provider = TracerProvider(resource=resource) - # Span processors are initialized with an exporter which is responsible - # for sending the telemetry data to a particular backend. - for exporter in exporters: - tracer_provider.add_span_processor(BatchSpanProcessor(exporter)) - # Sets the global default tracer provider - set_tracer_provider(tracer_provider) - - -def set_up_metrics(): - exporters = [] - if settings.otlp_endpoint: - exporters.append(OTLPMetricExporter(endpoint=settings.otlp_endpoint)) - if not exporters: - exporters.append(ConsoleMetricExporter()) - - # Initialize a metric provider for the application. This is a factory for creating meters. - metric_readers = [ - PeriodicExportingMetricReader(metric_exporter, export_interval_millis=5000) for metric_exporter in exporters - ] - meter_provider = MeterProvider( - metric_readers=metric_readers, - resource=resource, - views=[ - # Dropping all instrument names except for those starting with "agent_framework" - View(instrument_name="*", aggregation=DropAggregation()), - View(instrument_name="agent_framework*"), - ], - ) - # Sets the global default meter provider - set_meter_provider(meter_provider) - - -# Executors for sequential workflow -class UpperCaseExecutor(Executor): - """An executor that converts text to uppercase.""" - - @handler - async def to_upper_case(self, text: str, ctx: WorkflowContext[str]) -> None: - """Execute the task by converting the input string to uppercase.""" - print(f"UpperCaseExecutor: Processing '{text}'") - result = text.upper() - print(f"UpperCaseExecutor: Result '{result}'") - - # Send the result to the next executor in the workflow. - await ctx.send_message(result) - - -class ReverseTextExecutor(Executor): - """An executor that reverses text.""" - - @handler - async def reverse_text(self, text: str, ctx: WorkflowContext[Any]) -> None: - """Execute the task by reversing the input string.""" - print(f"ReverseTextExecutor: Processing '{text}'") - result = text[::-1] - print(f"ReverseTextExecutor: Result '{result}'") - - # Send the result with a workflow completion event. - await ctx.add_event(WorkflowCompletedEvent(result)) - - -async def run_sequential_workflow() -> None: - """Run a simple sequential workflow demonstrating telemetry collection. - - This workflow processes a string through two executors in sequence: - 1. UpperCaseExecutor converts the input to uppercase - 2. ReverseTextExecutor reverses the string and completes the workflow - - Telemetry data collected includes: - - Overall workflow execution spans - - Individual executor processing spans - - Message publishing between executors - - Workflow completion events - """ - - tracer = trace.get_tracer(__name__) - with tracer.start_as_current_span("Scenario: Sequential Workflow", kind=SpanKind.CLIENT) as current_span: - print("Running scenario: Sequential Workflow") - try: - # Step 1: Create the executors. - upper_case_executor = UpperCaseExecutor(id="upper_case_executor") - reverse_text_executor = ReverseTextExecutor(id="reverse_text_executor") - - # Step 2: Build the workflow with the defined edges. - workflow = ( - WorkflowBuilder() - .add_edge(upper_case_executor, reverse_text_executor) - .set_start_executor(upper_case_executor) - .build() - ) - - # Step 3: Run the workflow with an initial message. - input_text = "hello world" - print(f"Starting workflow with input: '{input_text}'") - - completion_event = None - async for event in workflow.run_stream(input_text): - print(f"Event: {event}") - if isinstance(event, WorkflowCompletedEvent): - # The WorkflowCompletedEvent contains the final result. - completion_event = event - - if completion_event: - print(f"Workflow completed with result: '{completion_event.data}'") - else: - print("Workflow completed without a completion event") - - except Exception as e: - current_span.record_exception(e) - print(f"Error running workflow: {e}") - - -async def main(): - """Run the telemetry sample with a simple sequential workflow.""" - # Set up the providers - # This must be done before any other telemetry calls - set_up_logging() - set_up_tracing() - set_up_metrics() - - tracer = trace.get_tracer("agent_framework") - with tracer.start_as_current_span("Sequential Workflow Scenario", kind=SpanKind.CLIENT) as current_span: - print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}") - - # Run the sequential workflow scenario - await run_sequential_workflow() - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/python/samples/getting_started/threads/suspend_resume_thread.py b/python/samples/getting_started/threads/suspend_resume_thread.py index 28f445816e..88065aa987 100644 --- a/python/samples/getting_started/threads/suspend_resume_thread.py +++ b/python/samples/getting_started/threads/suspend_resume_thread.py @@ -2,46 +2,38 @@ import asyncio -from agent_framework.foundry import FoundryChatClient from agent_framework.openai import OpenAIChatClient -from azure.identity.aio import AzureCliCredential async def suspend_resume_service_managed_thread() -> None: """Demonstrates how to suspend and resume a service-managed thread.""" print("=== Suspend-Resume Service-Managed Thread ===") - # Foundry Chat Client is used as an example here, + # OpenAI Chat Client is used as an example here, # other chat clients can be used as well. - # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred - # authentication option. - async with ( - AzureCliCredential() as credential, - FoundryChatClient(async_credential=credential).create_agent( - name="Joker", instructions="You are good at telling jokes." - ) as agent, - ): - # Start a new thread for the agent conversation. - thread = agent.get_new_thread() + agent = OpenAIChatClient().create_agent(name="Joker", instructions="You are good at telling jokes.") - # Respond to user input. - query = "Tell me a joke about a pirate." - print(f"User: {query}") - print(f"Agent: {await agent.run(query, thread=thread)}\n") + # Start a new thread for the agent conversation. + thread = agent.get_new_thread() - # Serialize the thread state, so it can be stored for later use. - serialized_thread = await thread.serialize() + # Respond to user input. + query = "Tell me a joke about a pirate." + print(f"User: {query}") + print(f"Agent: {await agent.run(query, thread=thread)}\n") - # The thread can now be saved to a database, file, or any other storage mechanism and loaded again later. - print(f"Serialized thread: {serialized_thread}\n") + # Serialize the thread state, so it can be stored for later use. + serialized_thread = await thread.serialize() - # Deserialize the thread state after loading from storage. - resumed_thread = await agent.deserialize_thread(serialized_thread) + # The thread can now be saved to a database, file, or any other storage mechanism and loaded again later. + print(f"Serialized thread: {serialized_thread}\n") - # Respond to user input. - query = "Now tell the same joke in the voice of a pirate, and add some emojis to the joke." - print(f"User: {query}") - print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n") + # Deserialize the thread state after loading from storage. + resumed_thread = await agent.deserialize_thread(serialized_thread) + + # Respond to user input. + query = "Now tell the same joke in the voice of a pirate, and add some emojis to the joke." + print(f"User: {query}") + print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n") async def suspend_resume_in_memory_thread() -> None: diff --git a/python/samples/getting_started/workflow/README.md b/python/samples/getting_started/workflow/README.md index c453877414..744ad3c9c0 100644 --- a/python/samples/getting_started/workflow/README.md +++ b/python/samples/getting_started/workflow/README.md @@ -2,13 +2,13 @@ ## Installation -To install the base `agent_framework.workflow` package, please run: +To install the base `agent_framework.workflow` package, run: ```bash pip install agent-framework-workflow ``` -You can install the workflow package with visualization dependency: +To install with visualization support: ```bash pip install agent-framework-workflow[viz] @@ -20,15 +20,15 @@ To export visualization images you also need to [install GraphViz](https://graph ## Foundational Concepts - Start Here -Begin with the `foundational` folder in order. These three samples introduce the core ideas of executors, edges, agents in workflows, and streaming. +Begin with the `_start-here` folder in order. These three samples introduce the core ideas of executors, edges, agents in workflows, and streaming. | Sample | File | Concepts | |--------|------|----------| -| Executors and Edges | [foundational/step1_executors_and_edges.py](./foundational/step1_executors_and_edges.py) | Minimal workflow with basic executors and edges | -| Agents in a Workflow | [foundational/step2_agents_in_a_workflow.py](./foundational/step2_agents_in_a_workflow.py) | Introduces `AgentExecutor`; calling agents inside a workflow | -| Streaming | [foundational/step3_streaming.py](./foundational/step3_streaming.py) | Extends workflows with event streaming | +| Executors and Edges | [_start-here/step1_executors_and_edges.py](./_start-here/step1_executors_and_edges.py) | Minimal workflow with basic executors and edges | +| Agents in a Workflow | [_start-here/step2_agents_in_a_workflow.py](./_start-here/step2_agents_in_a_workflow.py) | Introduces adding Agents as nodes; calling agents inside a workflow | +| Streaming (Basics) | [_start-here/step3_streaming.py](./_start-here/step3_streaming.py) | Extends workflows with event streaming | -Once comfortable with these, explore the rest of the samples. +Once comfortable with these, explore the rest of the samples below. --- @@ -37,39 +37,43 @@ Once comfortable with these, explore the rest of the samples. ### agents | Sample | File | Concepts | |---|---|---| -| Azure Chat Agents Streaming | [agents/azure_chat_agents_streaming.py](./agents/azure_chat_agents_streaming.py) | Directly adds Azure agents as edges and handling streaming events | +| Azure Chat Agents (Streaming) | [agents/azure_chat_agents_streaming.py](./agents/azure_chat_agents_streaming.py) | Add Azure agents as edges and handle streaming events | | Custom Agent Executors | [agents/custom_agent_executors.py](./agents/custom_agent_executors.py) | Create executors to handle agent run methods | -| Foundry Chat Agents Streaming | [agents/foundry_chat_agents_streaming.py](./agents/foundry_chat_agents_streaming.py) | Directly adds Foundry agents as edges and handling streaming events | -| Workflow as Agent | [ai_agent/workflow_as_agent.py](./agents/workflow_as_agent.py) | Wrap a workflow so it can behave like an agent | -| Workflow as Agent + HITL | [ai_agent/workflow_as_agent_human_in_the_loop.py](./agents/workflow_as_agent_human_in_the_loop.py) | Extend workflow-as-agent with human-in-the-loop capability | +| Foundry Chat Agents (Streaming) | [agents/foundry_chat_agents_streaming.py](./agents/foundry_chat_agents_streaming.py) | Add Foundry agents as edges and handle streaming events | +| Workflow as Agent (Reflection Pattern) | [agents/workflow_as_agent_reflection_pattern.py](./agents/workflow_as_agent_reflection_pattern.py) | Wrap a workflow so it can behave like an agent (reflection pattern) | +| Workflow as Agent + HITL | [agents/workflow_as_agent_human_in_the_loop.py](./agents/workflow_as_agent_human_in_the_loop.py) | Extend workflow-as-agent with human-in-the-loop capability | ### checkpoint | Sample | File | Concepts | |---|---|---| | Checkpoint & Resume | [checkpoint/checkpoint_with_resume.py](./checkpoint/checkpoint_with_resume.py) | Create checkpoints, inspect them, and resume execution | -### conditional_edges +### composition | Sample | File | Concepts | |---|---|---| -| Edge Condition | [conditional_edges/edge_condition.py](./conditional_edges/edge_condition.py) | Conditional routing based on agent classification | -| Switch-Case Edge Group | [conditional_edges/switch_case_edge_group.py](./conditional_edges/switch_case_edge_group.py) | Switch-case branching using classifier outputs | -| Multi-Selection Edge Group | [conditional_edges/multi_selection_edge_group.py](./conditional_edges/multi_selection_edge_group.py) | Select one or many targets dynamically (subset fan-out) | +| Sub-Workflow (Basics) | [composition/sub_workflow_basics.py](./composition/sub_workflow_basics.py) | Wrap a workflow as an executor and orchestrate sub-workflows | +| Sub-Workflow: Request Interception | [composition/sub_workflow_request_interception.py](./composition/sub_workflow_request_interception.py) | Intercept and forward requests with decorators and request handling | +| Sub-Workflow: Parallel Requests | [composition/sub_workflow_parallel_requests.py](./composition/sub_workflow_parallel_requests.py) | Multi-type interception and external forwarding patterns | -### fan_out_fan_in +### control-flow | Sample | File | Concepts | |---|---|---| -| Concurrent (Fan-out/Fan-in) | [fan_out_fan_in/fan_out_fan_in_edges.py](./fan_out_fan_in/fan_out_fan_in_edges.py) | Dispatch to multiple executors and aggregate results | -| Map-Reduce with Visualization | [fan_out_fan_in/map_reduce_and_visualization.py](./fan_out_fan_in/map_reduce_and_visualization.py) | Fan-out/fan-in pattern with GraphViz/diagram export | +| Sequential Executors | [control-flow/sequential_executors.py](./control-flow/sequential_executors.py) | Sequential workflow with explicit executor setup | +| Sequential (Streaming) | [control-flow/sequential_streaming.py](./control-flow/sequential_streaming.py) | Stream events from a simple sequential run | +| Edge Condition | [control-flow/edge_condition.py](./control-flow/edge_condition.py) | Conditional routing based on agent classification | +| Switch-Case Edge Group | [control-flow/switch_case_edge_group.py](./control-flow/switch_case_edge_group.py) | Switch-case branching using classifier outputs | +| Multi-Selection Edge Group | [control-flow/multi_selection_edge_group.py](./control-flow/multi_selection_edge_group.py) | Select one or many targets dynamically (subset fan-out) | +| Simple Loop | [control-flow/simple_loop.py](./control-flow/simple_loop.py) | Feedback loop where an agent judges ABOVE/BELOW/MATCHED | -### human_in_the_loop +### human-in-the-loop | Sample | File | Concepts | |---|---|---| -| Human-In-The-Loop (Guessing Game) | [human_in_the_loop/guessing_game_with_human_input.py](./human_in_the_loop/guessing_game_with_human_input.py) | Interactive request/response prompts with a human | +| Human-In-The-Loop (Guessing Game) | [human-in-the-loop/guessing_game_with_human_input.py](./human-in-the-loop/guessing_game_with_human_input.py) | Interactive request/response prompts with a human | -### loop +### observability | Sample | File | Concepts | |---|---|---| -| Simple Loop | [loop/simple_loop.py](./loop/simple_loop.py) | Feedback loop where an agent judges ABOVE/BELOW/MATCHED | +| Tracing (Basics) | [observability/tracing_basics.py](./observability/tracing_basics.py) | Use basic tracing for workflow telemetry | ### orchestration | Sample | File | Concepts | @@ -77,36 +81,31 @@ Once comfortable with these, explore the rest of the samples. | Magentic Workflow (Multi-Agent) | [orchestration/magentic.py](./orchestration/magentic.py) | Orchestrate multiple agents with Magentic manager and streaming | | Magentic + Human Plan Review | [orchestration/magentic_human_plan_update.py](./orchestration/magentic_human_plan_update.py) | Human reviews/updates the plan before execution | -### sequential +### parallelism | Sample | File | Concepts | |---|---|---| -| Sequential Executors | [sequential/sequential_executors.py](./sequential/sequential_executors.py) | Sequential workflow with explicit executor setup | -| Sequential (Streaming) | [sequential/sequential_streaming.py](./sequential/sequential_streaming.py) | Stream events from a simple sequential run | +| Concurrent (Fan-out/Fan-in) | [parallelism/fan_out_fan_in_edges.py](./parallelism/fan_out_fan_in_edges.py) | Dispatch to multiple executors and aggregate results | +| Map-Reduce with Visualization | [parallelism/map_reduce_and_visualization.py](./parallelism/map_reduce_and_visualization.py) | Fan-out/fan-in pattern with diagram export | -### shared_states +### state-management | Sample | File | Concepts | |---|---|---| -| Shared States | [shared_states/shared_states_with_agents.py](./shared_states/shared_states_with_agents.py) | Store in shared state once and later reuse across agents | - -### sub_workflow -| Sample | File | Concepts | -|---|---|---| -| Sub-Workflow (Basics) | [sub_workflow/sub_workflow_basics.py](./sub_workflow/sub_workflow.py) | Wrap a workflow as an executor and orchestrate sub-workflows | -| Sub-Workflow: Request Interception | [sub_workflow/sub_workflow_request_interception.py](./sub_workflow/sub_workflow_request_interception.py) | Intercept/forward requests with decorators and request handling | -| Sub-Workflow: Parallel Requests | [sub_workflow/sub_workflow_parallel_requests.py](./sub_workflow/sub_workflow_parallel_requests.py) | Multi-type interception and external forwarding patterns | - -### tracing -| Sample | File | Concepts | -|---|---|---| -| Tracing (Basics) | [tracing/tracing_basics.py](./tracing/tracing_basics.py) | Use basic tracing for workflow telemetry | +| Shared States | [state-management/shared_states_with_agents.py](./state-management/shared_states_with_agents.py) | Store in shared state once and later reuse across agents | ### visualization | Sample | File | Concepts | |---|---|---| | Concurrent with Visualization | [visualization/concurrent_with_visualization.py](./visualization/concurrent_with_visualization.py) | Fan-out/fan-in workflow with diagram export | +### resources +- Sample text inputs used by certain workflows: + - [resources/long_text.txt](./resources/long_text.txt) + - [resources/email.txt](./resources/email.txt) + - [resources/spam.txt](./resources/spam.txt) + - [resources/ambiguous_email.txt](./resources/ambiguous_email.txt) + Notes -- Agent‑based samples use provider SDKs (Azure/OpenAI, etc.). Ensure credentials are configured, or adapt agents accordingly. +- Agent-based samples use provider SDKs (Azure/OpenAI, etc.). Ensure credentials are configured, or adapt agents accordingly. ### Environment Variables diff --git a/python/samples/getting_started/workflow/foundational/step1_executors_and_edges.py b/python/samples/getting_started/workflow/_start-here/step1_executors_and_edges.py similarity index 100% rename from python/samples/getting_started/workflow/foundational/step1_executors_and_edges.py rename to python/samples/getting_started/workflow/_start-here/step1_executors_and_edges.py diff --git a/python/samples/getting_started/workflow/foundational/step2_agents_in_a_workflow.py b/python/samples/getting_started/workflow/_start-here/step2_agents_in_a_workflow.py similarity index 100% rename from python/samples/getting_started/workflow/foundational/step2_agents_in_a_workflow.py rename to python/samples/getting_started/workflow/_start-here/step2_agents_in_a_workflow.py diff --git a/python/samples/getting_started/workflow/foundational/step3_streaming.py b/python/samples/getting_started/workflow/_start-here/step3_streaming.py similarity index 100% rename from python/samples/getting_started/workflow/foundational/step3_streaming.py rename to python/samples/getting_started/workflow/_start-here/step3_streaming.py diff --git a/python/samples/getting_started/workflow/agents/azure_chat_agents_streaming.py b/python/samples/getting_started/workflow/agents/azure_chat_agents_streaming.py index 97d563215a..4f39385a92 100644 --- a/python/samples/getting_started/workflow/agents/azure_chat_agents_streaming.py +++ b/python/samples/getting_started/workflow/agents/azure_chat_agents_streaming.py @@ -64,7 +64,7 @@ async def main(): # AgentRunUpdateEvent contains incremental text deltas from the underlying agent. # Print a prefix when the executor changes, then append updates on the same line. eid = event.executor_id - if eid != last_executor_id: + if eid != last_executor_id: # type: ignore[reportUnnecessaryComparison] if last_executor_id is not None: print() print(f"{eid}:", end=" ", flush=True) diff --git a/python/samples/getting_started/workflow/sub_workflow/sub_workflow_basics.py b/python/samples/getting_started/workflow/composition/sub_workflow_basics.py similarity index 100% rename from python/samples/getting_started/workflow/sub_workflow/sub_workflow_basics.py rename to python/samples/getting_started/workflow/composition/sub_workflow_basics.py diff --git a/python/samples/getting_started/workflow/sub_workflow/sub_workflow_parallel_requests.py b/python/samples/getting_started/workflow/composition/sub_workflow_parallel_requests.py similarity index 100% rename from python/samples/getting_started/workflow/sub_workflow/sub_workflow_parallel_requests.py rename to python/samples/getting_started/workflow/composition/sub_workflow_parallel_requests.py diff --git a/python/samples/getting_started/workflow/sub_workflow/sub_workflow_request_interception.py b/python/samples/getting_started/workflow/composition/sub_workflow_request_interception.py similarity index 100% rename from python/samples/getting_started/workflow/sub_workflow/sub_workflow_request_interception.py rename to python/samples/getting_started/workflow/composition/sub_workflow_request_interception.py diff --git a/python/samples/getting_started/workflow/conditional_edges/edge_condition.py b/python/samples/getting_started/workflow/control-flow/edge_condition.py similarity index 98% rename from python/samples/getting_started/workflow/conditional_edges/edge_condition.py rename to python/samples/getting_started/workflow/control-flow/edge_condition.py index 2dace8b484..63d2977ca4 100644 --- a/python/samples/getting_started/workflow/conditional_edges/edge_condition.py +++ b/python/samples/getting_started/workflow/control-flow/edge_condition.py @@ -177,9 +177,7 @@ async def main() -> None: # Read Email content from the sample resource file. # This keeps the sample deterministic since the model sees the same email every run. - email_path = os.path.join( - os.path.dirname(os.path.dirname(os.path.realpath(__file__))), "workflow", "resources", "email.txt" - ) + email_path = os.path.join(os.path.dirname(os.path.dirname(os.path.realpath(__file__))), "resources", "email.txt") with open(email_path) as email_file: # noqa: ASYNC230 email = email_file.read() diff --git a/python/samples/getting_started/workflow/conditional_edges/multi_selection_edge_group.py b/python/samples/getting_started/workflow/control-flow/multi_selection_edge_group.py similarity index 97% rename from python/samples/getting_started/workflow/conditional_edges/multi_selection_edge_group.py rename to python/samples/getting_started/workflow/control-flow/multi_selection_edge_group.py index afed90325b..d14a1ab539 100644 --- a/python/samples/getting_started/workflow/conditional_edges/multi_selection_edge_group.py +++ b/python/samples/getting_started/workflow/control-flow/multi_selection_edge_group.py @@ -250,11 +250,16 @@ async def main() -> None: ) # Read an email sample - resources_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "resources", "email.txt") + resources_path = os.path.join( + os.path.dirname(os.path.dirname(os.path.realpath(__file__))), + "resources", + "email.txt", + ) if os.path.exists(resources_path): with open(resources_path, encoding="utf-8") as f: # noqa: ASYNC230 email = f.read() else: + print("Unable to find resource file, using default text.") email = "Hello team, here are the updates for this week..." async for event in workflow.run_stream(email): diff --git a/python/samples/getting_started/workflow/sequential/sequential_executors.py b/python/samples/getting_started/workflow/control-flow/sequential_executors.py similarity index 100% rename from python/samples/getting_started/workflow/sequential/sequential_executors.py rename to python/samples/getting_started/workflow/control-flow/sequential_executors.py diff --git a/python/samples/getting_started/workflow/sequential/sequential_streaming.py b/python/samples/getting_started/workflow/control-flow/sequential_streaming.py similarity index 100% rename from python/samples/getting_started/workflow/sequential/sequential_streaming.py rename to python/samples/getting_started/workflow/control-flow/sequential_streaming.py diff --git a/python/samples/getting_started/workflow/loop/simple_loop.py b/python/samples/getting_started/workflow/control-flow/simple_loop.py similarity index 100% rename from python/samples/getting_started/workflow/loop/simple_loop.py rename to python/samples/getting_started/workflow/control-flow/simple_loop.py diff --git a/python/samples/getting_started/workflow/conditional_edges/switch_case_edge_group.py b/python/samples/getting_started/workflow/control-flow/switch_case_edge_group.py similarity index 97% rename from python/samples/getting_started/workflow/conditional_edges/switch_case_edge_group.py rename to python/samples/getting_started/workflow/control-flow/switch_case_edge_group.py index ba6eed5fc2..b23ffafb08 100644 --- a/python/samples/getting_started/workflow/conditional_edges/switch_case_edge_group.py +++ b/python/samples/getting_started/workflow/control-flow/switch_case_edge_group.py @@ -201,11 +201,14 @@ async def main(): ) # Read ambiguous email if available. Otherwise use a simple inline sample. - resources_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "resources", "ambiguous_email.txt") + resources_path = os.path.join( + os.path.dirname(os.path.dirname(os.path.realpath(__file__))), "resources", "ambiguous_email.txt" + ) if os.path.exists(resources_path): with open(resources_path, encoding="utf-8") as f: # noqa: ASYNC230 email = f.read() else: + print("Unable to find resource file, using default text.") email = ( "Hey there, I noticed you might be interested in our latest offer—no pressure, but it expires soon. " "Let me know if you'd like more details." diff --git a/python/samples/getting_started/workflow/human_in_the_loop/guessing_game_with_human_input.py b/python/samples/getting_started/workflow/human-in-the-loop/guessing_game_with_human_input.py similarity index 100% rename from python/samples/getting_started/workflow/human_in_the_loop/guessing_game_with_human_input.py rename to python/samples/getting_started/workflow/human-in-the-loop/guessing_game_with_human_input.py diff --git a/python/samples/getting_started/workflow/tracing/tracing_basics.py b/python/samples/getting_started/workflow/observability/tracing_basics.py similarity index 100% rename from python/samples/getting_started/workflow/tracing/tracing_basics.py rename to python/samples/getting_started/workflow/observability/tracing_basics.py diff --git a/python/samples/getting_started/workflow/fan_out_fan_in/fan_out_fan_in_edges.py b/python/samples/getting_started/workflow/parallelism/fan_out_fan_in_edges.py similarity index 100% rename from python/samples/getting_started/workflow/fan_out_fan_in/fan_out_fan_in_edges.py rename to python/samples/getting_started/workflow/parallelism/fan_out_fan_in_edges.py diff --git a/python/samples/getting_started/workflow/fan_out_fan_in/map_reduce_and_visualization.py b/python/samples/getting_started/workflow/parallelism/map_reduce_and_visualization.py similarity index 100% rename from python/samples/getting_started/workflow/fan_out_fan_in/map_reduce_and_visualization.py rename to python/samples/getting_started/workflow/parallelism/map_reduce_and_visualization.py diff --git a/python/samples/getting_started/workflow/shared_states/shared_states_with_agents.py b/python/samples/getting_started/workflow/state-management/shared_states_with_agents.py similarity index 89% rename from python/samples/getting_started/workflow/shared_states/shared_states_with_agents.py rename to python/samples/getting_started/workflow/state-management/shared_states_with_agents.py index 82777dd63e..45c71b516c 100644 --- a/python/samples/getting_started/workflow/shared_states/shared_states_with_agents.py +++ b/python/samples/getting_started/workflow/state-management/shared_states_with_agents.py @@ -9,7 +9,6 @@ from uuid import uuid4 from agent_framework import ChatMessage, Role from agent_framework.azure import AzureChatClient from agent_framework.workflow import ( - AgentExecutor, AgentExecutorRequest, AgentExecutorResponse, WorkflowBuilder, @@ -158,26 +157,22 @@ async def main() -> None: # Create chat client and agents. response_format enforces structured JSON from each agent. chat_client = AzureChatClient(credential=AzureCliCredential()) - spam_detection_agent = AgentExecutor( - chat_client.create_agent( - instructions=( - "You are a spam detection assistant that identifies spam emails. " - "Always return JSON with fields is_spam (bool) and reason (string)." - ), - response_format=DetectionResultAgent, + spam_detection_agent = chat_client.create_agent( + instructions=( + "You are a spam detection assistant that identifies spam emails. " + "Always return JSON with fields is_spam (bool) and reason (string)." ), - id="spam_detection_agent", + response_format=DetectionResultAgent, + name="spam_detection_agent", ) - email_assistant_agent = AgentExecutor( - chat_client.create_agent( - instructions=( - "You are an email assistant that helps users draft responses to emails with professionalism. " - "Return JSON with a single field 'response' containing the drafted reply." - ), - response_format=EmailResponse, + email_assistant_agent = chat_client.create_agent( + instructions=( + "You are an email assistant that helps users draft responses to emails with professionalism. " + "Return JSON with a single field 'response' containing the drafted reply." ), - id="email_assistant_agent", + response_format=EmailResponse, + name="email_assistant_agent", ) # Build the workflow graph with conditional edges. @@ -198,17 +193,22 @@ async def main() -> None: ) # Read an email from resources/spam.txt if available; otherwise use a default sample. - resources_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "resources", "spam.txt") + resources_path = os.path.join( + os.path.dirname(os.path.dirname(os.path.realpath(__file__))), + "resources", + "spam.txt", + ) if os.path.exists(resources_path): with open(resources_path, encoding="utf-8") as f: # noqa: ASYNC230 email = f.read() else: + print("Unable to find resource file, using default text.") email = "You are a WINNER! Click here for a free lottery offer!!!" # Run and print the terminal result. Streaming surfaces intermediate execution events as well. async for event in workflow.run_stream(email): if isinstance(event, WorkflowCompletedEvent): - print(f"{event}") + print(event) """ Sample Output: diff --git a/python/tests/__init__.py b/python/tests/__init__.py new file mode 100644 index 0000000000..58b29ef7f3 --- /dev/null +++ b/python/tests/__init__.py @@ -0,0 +1,3 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Test utilities for sample testing.""" diff --git a/python/tests/sample_utils.py b/python/tests/sample_utils.py new file mode 100644 index 0000000000..878566e223 --- /dev/null +++ b/python/tests/sample_utils.py @@ -0,0 +1,43 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +import logging +from collections.abc import Awaitable, Callable +from typing import Any + +logger = logging.getLogger(__name__) + + +async def retry( + func: Callable[[], Awaitable[Any]], + retries: int = 3, + reset: Callable[[], None] | None = None, + name: str | None = None, +) -> None: + """Retry function with reset capability and proper logging. + + Args: + func: The function to retry. + retries: Number of retries. + reset: Function to reset the state of any variables used in the function. + name: Optional name for logging purposes. + """ + func_name = name or func.__module__ + logger.info(f"Running {retries} retries with func: {func_name}") + + for i in range(retries): + logger.info(f" Try {i + 1} for {func_name}") + try: + if reset: + reset() + await func() + return + except Exception as e: + logger.warning(f" On try {i + 1} got this error: {e}") + if i == retries - 1: # Last retry + raise + + # Binary exponential backoff like Semantic Kernel + backoff = 2**i + logger.info(f" Sleeping for {backoff} seconds before retrying") + await asyncio.sleep(backoff) diff --git a/python/tests/samples/__init__.py b/python/tests/samples/__init__.py new file mode 100644 index 0000000000..1857030e0e --- /dev/null +++ b/python/tests/samples/__init__.py @@ -0,0 +1,3 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Sample tests package.""" diff --git a/python/tests/samples/getting_started/__init__.py b/python/tests/samples/getting_started/__init__.py new file mode 100644 index 0000000000..9c75ed9a9b --- /dev/null +++ b/python/tests/samples/getting_started/__init__.py @@ -0,0 +1,3 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Getting started sample tests.""" diff --git a/python/tests/samples/getting_started/test_agents.py b/python/tests/samples/getting_started/test_agents.py new file mode 100644 index 0000000000..32ae175d4a --- /dev/null +++ b/python/tests/samples/getting_started/test_agents.py @@ -0,0 +1,595 @@ +# Copyright (c) Microsoft. All rights reserved. + +import copy +import os +from collections.abc import Awaitable, Callable +from typing import Any + +import pytest +from pytest import MonkeyPatch, mark, param + +from samples.getting_started.agents.azure_assistants_client.azure_assistants_basic import ( + main as azure_assistants_basic, +) +from samples.getting_started.agents.azure_assistants_client.azure_assistants_with_code_interpreter import ( + main as azure_assistants_with_code_interpreter, +) +from samples.getting_started.agents.azure_assistants_client.azure_assistants_with_existing_assistant import ( + main as azure_assistants_with_existing_assistant, +) +from samples.getting_started.agents.azure_assistants_client.azure_assistants_with_explicit_settings import ( + main as azure_assistants_with_explicit_settings, +) +from samples.getting_started.agents.azure_assistants_client.azure_assistants_with_function_tools import ( + main as azure_assistants_with_function_tools, +) +from samples.getting_started.agents.azure_assistants_client.azure_assistants_with_thread import ( + main as azure_assistants_with_thread, +) +from samples.getting_started.agents.azure_chat_client.azure_chat_client_basic import ( + main as azure_chat_client_basic, +) +from samples.getting_started.agents.azure_chat_client.azure_chat_client_with_explicit_settings import ( + main as azure_chat_client_with_explicit_settings, +) +from samples.getting_started.agents.azure_chat_client.azure_chat_client_with_function_tools import ( + main as azure_chat_client_with_function_tools, +) +from samples.getting_started.agents.azure_chat_client.azure_chat_client_with_thread import ( + main as azure_chat_client_with_thread, +) +from samples.getting_started.agents.azure_responses_client.azure_responses_client_basic import ( + main as azure_responses_client_basic, +) +from samples.getting_started.agents.azure_responses_client.azure_responses_client_with_code_interpreter import ( + main as azure_responses_client_with_code_interpreter, +) +from samples.getting_started.agents.azure_responses_client.azure_responses_client_with_explicit_settings import ( + main as azure_responses_client_with_explicit_settings, +) +from samples.getting_started.agents.azure_responses_client.azure_responses_client_with_function_tools import ( + main as azure_responses_client_with_function_tools, +) +from samples.getting_started.agents.azure_responses_client.azure_responses_client_with_thread import ( + main as azure_responses_client_with_thread, +) +from samples.getting_started.agents.foundry.foundry_basic import ( + main as foundry_basic, +) +from samples.getting_started.agents.foundry.foundry_with_code_interpreter import ( + main as foundry_with_code_interpreter, +) +from samples.getting_started.agents.foundry.foundry_with_existing_agent import ( + main as foundry_with_existing_agent, +) +from samples.getting_started.agents.foundry.foundry_with_explicit_settings import ( + main as foundry_with_explicit_settings, +) +from samples.getting_started.agents.foundry.foundry_with_function_tools import ( + mixed_tools_example as foundry_with_function_tools_mixed, +) +from samples.getting_started.agents.foundry.foundry_with_function_tools import ( + tools_on_agent_level as foundry_with_function_tools_agent, +) +from samples.getting_started.agents.foundry.foundry_with_function_tools import ( + tools_on_run_level as foundry_with_function_tools_run, +) +from samples.getting_started.agents.foundry.foundry_with_local_mcp import ( + main as foundry_with_local_mcp, +) +from samples.getting_started.agents.foundry.foundry_with_thread import ( + main as foundry_with_thread, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_basic import ( + main as openai_assistants_basic, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_code_interpreter import ( + main as openai_assistants_with_code_interpreter, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_existing_assistant import ( + main as openai_assistants_with_existing_assistant, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_explicit_settings import ( + main as openai_assistants_with_explicit_settings, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_file_search import ( + main as openai_assistants_with_file_search, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_function_tools import ( + main as openai_assistants_with_function_tools, +) +from samples.getting_started.agents.openai_assistants_client.openai_assistants_with_thread import ( + main as openai_assistants_with_thread, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_basic import ( + main as openai_chat_client_basic, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_with_explicit_settings import ( + main as openai_chat_client_with_explicit_settings, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_with_function_tools import ( + main as openai_chat_client_with_function_tools, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_with_local_mcp import ( + main as openai_chat_client_with_local_mcp, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_with_thread import ( + main as openai_chat_client_with_thread, +) +from samples.getting_started.agents.openai_chat_client.openai_chat_client_with_web_search import ( + main as openai_chat_client_with_web_search, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_basic import ( + main as openai_responses_client_basic, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_reasoning import ( + main as openai_responses_client_reasoning, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_code_interpreter import ( + main as openai_responses_client_with_code_interpreter, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_explicit_settings import ( + main as openai_responses_client_with_explicit_settings, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_file_search import ( + main as openai_responses_client_with_file_search, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_function_tools import ( + main as openai_responses_client_with_function_tools, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_local_mcp import ( + main as openai_responses_client_with_local_mcp, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_thread import ( + main as openai_responses_client_with_thread, +) +from samples.getting_started.agents.openai_responses_client.openai_responses_client_with_web_search import ( + main as openai_responses_client_with_web_search, +) +from tests.sample_utils import retry + +# Environment variable for controlling sample tests +RUN_SAMPLES_TESTS = "RUN_SAMPLES_TESTS" + +# All agent samples across providers +agent_samples = [ + # Azure Assistants Agent samples + param( + azure_assistants_basic, + [], # Non-interactive sample + id="azure_assistants_basic", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_assistants_with_code_interpreter, + [], # Non-interactive sample + id="azure_assistants_with_code_interpreter", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_assistants_with_function_tools, + [], # Non-interactive sample + id="azure_assistants_with_function_tools", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_assistants_with_existing_assistant, + [], # Non-interactive sample + id="azure_assistants_with_existing_assistant", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_assistants_with_explicit_settings, + [], # Non-interactive sample + id="azure_assistants_with_explicit_settings", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_assistants_with_thread, + [], # Non-interactive sample + id="azure_assistants_with_thread", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # Azure Chat Client Agent samples + param( + azure_chat_client_basic, + [], # Non-interactive sample + id="azure_chat_client_basic", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_chat_client_with_explicit_settings, + [], # Non-interactive sample + id="azure_chat_client_with_explicit_settings", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_chat_client_with_function_tools, + [], # Non-interactive sample + id="azure_chat_client_with_function_tools", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_chat_client_with_thread, + [], # Non-interactive sample + id="azure_chat_client_with_thread", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # Azure Responses Client Agent samples + param( + azure_responses_client_basic, + [], # Non-interactive sample + id="azure_responses_client_basic", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_responses_client_with_code_interpreter, + [], # Non-interactive sample + id="azure_responses_client_with_code_interpreter", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_responses_client_with_explicit_settings, + [], # Non-interactive sample + id="azure_responses_client_with_explicit_settings", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_responses_client_with_function_tools, + [], # Non-interactive sample + id="azure_responses_client_with_function_tools", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_responses_client_with_thread, + [], # Non-interactive sample + id="azure_responses_client_with_thread", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # Foundry Agent samples + param( + foundry_basic, + [], # Non-interactive sample + id="foundry_basic", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_code_interpreter, + [], # Non-interactive sample + id="foundry_with_code_interpreter", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_existing_agent, + [], # Non-interactive sample + id="foundry_with_existing_agent", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_explicit_settings, + [], # Non-interactive sample + id="foundry_with_explicit_settings", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_function_tools_agent, + [], # Non-interactive sample + id="foundry_with_function_tools", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_function_tools_run, + [], # Non-interactive sample + id="foundry_with_function_tools", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_function_tools_mixed, + [], # Non-interactive sample + id="foundry_with_function_tools", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_thread, + [], # Non-interactive sample + id="foundry_with_thread", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + foundry_with_local_mcp, + [], # Non-interactive sample + id="foundry_with_local_mcp", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # OpenAI Assistants Agent samples + param( + openai_assistants_basic, + [], # Non-interactive sample + id="openai_assistants_basic", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_assistants_with_code_interpreter, + [], # Non-interactive sample + id="openai_assistants_with_code_interpreter", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_assistants_with_existing_assistant, + [], # Non-interactive sample + id="openai_assistants_with_existing_assistant", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_assistants_with_explicit_settings, + [], # Non-interactive sample + id="openai_assistants_with_explicit_settings", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_assistants_with_file_search, + [], # Non-interactive sample + id="openai_assistants_with_file_search", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue"), + ], + ), + param( + openai_assistants_with_function_tools, + [], # Non-interactive sample + id="openai_assistants_with_function_tools", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_assistants_with_thread, + [], # Non-interactive sample + id="openai_assistants_with_thread", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # OpenAI Chat Client Agent samples + param( + openai_chat_client_basic, + [], # Non-interactive sample + id="openai_chat_client_basic", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client_with_explicit_settings, + [], # Non-interactive sample + id="openai_chat_client_with_explicit_settings", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client_with_function_tools, + [], # Non-interactive sample + id="openai_chat_client_with_function_tools", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client_with_local_mcp, + [], # Non-interactive sample + id="openai_chat_client_with_local_mcp", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client_with_thread, + [], # Non-interactive sample + id="openai_chat_client_with_thread", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client_with_web_search, + [], # Non-interactive sample + id="openai_chat_client_with_web_search", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # OpenAI Responses Client Agent samples + param( + openai_responses_client_basic, + [], # Non-interactive sample + id="openai_responses_client_basic", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_reasoning, + [], # Non-interactive sample + id="openai_responses_client_reasoning", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_code_interpreter, + [], # Non-interactive sample + id="openai_responses_client_with_code_interpreter", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_explicit_settings, + [], # Non-interactive sample + id="openai_responses_client_with_explicit_settings", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_file_search, + [], # Non-interactive sample + id="openai_responses_client_with_file_search", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + pytest.mark.skip(reason="OpenAI file search functionality is currently broken - tracked in GitHub issue"), + ], + ), + param( + openai_responses_client_with_function_tools, + [], # Non-interactive sample + id="openai_responses_client_with_function_tools", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_local_mcp, + [], # Non-interactive sample + id="openai_responses_client_with_local_mcp", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_thread, + [], # Non-interactive sample + id="openai_responses_client_with_thread", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client_with_web_search, + [], # Non-interactive sample + id="openai_responses_client_with_web_search", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), +] + + +@mark.parametrize("sample, responses", agent_samples) +async def test_agent_samples(sample: Callable[..., Awaitable[Any]], responses: list[str], monkeypatch: MonkeyPatch): + """Test agent samples with input mocking and retry logic.""" + saved_responses = copy.deepcopy(responses) + + def reset(): + responses.clear() + responses.extend(saved_responses) + + def mock_input(prompt: str = "") -> str: + return responses.pop(0) if responses else "exit" + + monkeypatch.setattr("builtins.input", mock_input) + await retry(sample, retries=3, reset=reset) diff --git a/python/tests/samples/getting_started/test_chat_client.py b/python/tests/samples/getting_started/test_chat_client.py new file mode 100644 index 0000000000..2c93ee0804 --- /dev/null +++ b/python/tests/samples/getting_started/test_chat_client.py @@ -0,0 +1,135 @@ +# Copyright (c) Microsoft. All rights reserved. + +import copy +import os +from collections.abc import Awaitable, Callable +from typing import Any + +import pytest +from pytest import MonkeyPatch, mark, param + +from samples.getting_started.chat_client.azure_assistants_client import ( + main as azure_assistants_client, +) +from samples.getting_started.chat_client.azure_chat_client import ( + main as azure_chat_client, +) +from samples.getting_started.chat_client.azure_responses_client import ( + main as azure_responses_client, +) +from samples.getting_started.chat_client.chat_response_cancellation import ( + main as chat_response_cancellation, +) +from samples.getting_started.chat_client.foundry_chat_client import ( + main as foundry_chat_client, +) +from samples.getting_started.chat_client.openai_assistants_client import ( + main as openai_assistants_client, +) +from samples.getting_started.chat_client.openai_chat_client import ( + main as openai_chat_client, +) +from samples.getting_started.chat_client.openai_responses_client import ( + main as openai_responses_client, +) +from tests.sample_utils import retry + +# Environment variable for controlling sample tests +RUN_SAMPLES_TESTS = "RUN_SAMPLES_TESTS" + +# All chat client samples across providers +chat_client_samples = [ + # Azure Chat Client samples + param( + azure_assistants_client, + [], # Non-interactive sample + id="azure_assistants_client", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_chat_client, + [], # Non-interactive sample + id="azure_chat_client", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + azure_responses_client, + [], # Non-interactive sample + id="azure_responses_client", + marks=[ + pytest.mark.azure, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # Foundry Chat Client samples + param( + foundry_chat_client, + [], # Non-interactive sample + id="foundry_chat_client", + marks=[ + pytest.mark.foundry, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # OpenAI Chat Client samples + param( + openai_assistants_client, + [], # Non-interactive sample + id="openai_assistants_client", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_chat_client, + [], # Non-interactive sample + id="openai_chat_client", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + openai_responses_client, + [], # Non-interactive sample + id="openai_responses_client", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + # General Chat Client samples (no provider-specific environment variable) + param( + chat_response_cancellation, + [], # Non-interactive sample + id="chat_response_cancellation", + marks=pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ), +] + + +@mark.parametrize("sample, responses", chat_client_samples) +async def test_chat_client_samples( + sample: Callable[..., Awaitable[Any]], + responses: list[str], + monkeypatch: MonkeyPatch, +): + """Test chat client samples with input mocking and retry logic.""" + saved_responses = copy.deepcopy(responses) + + def reset(): + responses.clear() + responses.extend(saved_responses) + + def mock_input(prompt: str = "") -> str: + return responses.pop(0) if responses else "exit" + + monkeypatch.setattr("builtins.input", mock_input) + await retry(sample, retries=3, reset=reset) diff --git a/python/tests/samples/getting_started/test_threads.py b/python/tests/samples/getting_started/test_threads.py new file mode 100644 index 0000000000..ec530efa6e --- /dev/null +++ b/python/tests/samples/getting_started/test_threads.py @@ -0,0 +1,54 @@ +# Copyright (c) Microsoft. All rights reserved. + +import copy +import os +from collections.abc import Awaitable, Callable +from typing import Any + +import pytest +from pytest import MonkeyPatch, mark, param + +from samples.getting_started.threads.custom_chat_message_store_thread import main as threads_custom_store +from samples.getting_started.threads.suspend_resume_thread import main as threads_suspend_resume +from tests.sample_utils import retry + +# Environment variable for controlling sample tests +RUN_SAMPLES_TESTS = "RUN_SAMPLES_TESTS" + +# All thread samples +thread_samples = [ + param( + threads_custom_store, + [], # Non-interactive sample + id="threads_custom_store", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), + param( + threads_suspend_resume, + [], # Non-interactive sample + id="threads_suspend_resume", + marks=[ + pytest.mark.openai, + pytest.mark.skipif(os.getenv(RUN_SAMPLES_TESTS, None) is None, reason="Not running sample tests."), + ], + ), +] + + +@mark.parametrize("sample, responses", thread_samples) +async def test_thread_samples(sample: Callable[..., Awaitable[Any]], responses: list[str], monkeypatch: MonkeyPatch): + """Test thread samples with input mocking and retry logic.""" + saved_responses = copy.deepcopy(responses) + + def reset(): + responses.clear() + responses.extend(saved_responses) + + def mock_input(prompt: str = "") -> str: + return responses.pop(0) if responses else "exit" + + monkeypatch.setattr("builtins.input", mock_input) + await retry(sample, retries=3, reset=reset) diff --git a/python/uv.lock b/python/uv.lock index 1f995f10f7..1eddb3c2c7 100644 --- a/python/uv.lock +++ b/python/uv.lock @@ -1,12 +1,18 @@ version = 1 -revision = 3 +revision = 1 requires-python = ">=3.10" resolution-markers = [ - "python_full_version >= '3.11' and sys_platform == 'darwin'", + "python_full_version >= '3.13' and sys_platform == 'darwin'", + "python_full_version == '3.12.*' and sys_platform == 'darwin'", + "python_full_version == '3.11.*' and sys_platform == 'darwin'", "python_full_version < '3.11' and sys_platform == 'darwin'", - "python_full_version >= '3.11' and sys_platform == 'linux'", + "python_full_version >= '3.13' and sys_platform == 'linux'", + "python_full_version == '3.12.*' and sys_platform == 'linux'", + "python_full_version == '3.11.*' and sys_platform == 'linux'", "python_full_version < '3.11' and sys_platform == 'linux'", - "python_full_version >= '3.11' and sys_platform == 'win32'", + "python_full_version >= '3.13' and sys_platform == 'win32'", + "python_full_version == '3.12.*' and sys_platform == 'win32'", + "python_full_version == '3.11.*' and sys_platform == 'win32'", "python_full_version < '3.11' and sys_platform == 'win32'", ] supported-markers = [ @@ -20,6 +26,7 @@ members = [ "agent-framework", "agent-framework-azure", "agent-framework-foundry", + "agent-framework-mem0", "agent-framework-project", "agent-framework-runtime", "agent-framework-workflow", @@ -32,9 +39,9 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "pygments", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/bc/c1/bbac6a50d02774f91572938964c582fff4270eee73ab822a4aeea4d8b11b/accessible_pygments-0.0.5.tar.gz", hash = "sha256:40918d3e6a2b619ad424cb91e556bd3bd8865443d9f22f1dcdf79e33c8046872", size = 1377899, upload-time = "2024-05-10T11:23:10.216Z" } +sdist = { url = "https://files.pythonhosted.org/packages/bc/c1/bbac6a50d02774f91572938964c582fff4270eee73ab822a4aeea4d8b11b/accessible_pygments-0.0.5.tar.gz", hash = "sha256:40918d3e6a2b619ad424cb91e556bd3bd8865443d9f22f1dcdf79e33c8046872", size = 1377899 } wheels = [ - { url = "https://files.pythonhosted.org/packages/8d/3f/95338030883d8c8b91223b4e21744b04d11b161a3ef117295d8241f50ab4/accessible_pygments-0.0.5-py3-none-any.whl", hash = "sha256:88ae3211e68a1d0b011504b2ffc1691feafce124b845bd072ab6f9f66f34d4b7", size = 1395903, upload-time = "2024-05-10T11:23:08.421Z" }, + { url = "https://files.pythonhosted.org/packages/8d/3f/95338030883d8c8b91223b4e21744b04d11b161a3ef117295d8241f50ab4/accessible_pygments-0.0.5-py3-none-any.whl", hash = "sha256:88ae3211e68a1d0b011504b2ffc1691feafce124b845bd072ab6f9f66f34d4b7", size = 1395903 }, ] [[package]] @@ -42,13 +49,17 @@ name = "agent-framework" version = "0.1.0b1" source = { editable = "packages/main" } dependencies = [ + { name = "azure-monitor-opentelemetry", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, + { name = "azure-monitor-opentelemetry-exporter", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "mcp", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "openai", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "opentelemetry-api", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, + { name = "opentelemetry-exporter-otlp-proto-grpc", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "opentelemetry-sdk", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "pydantic", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "pydantic-settings", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, + { name = "websockets", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, ] [package.optional-dependencies] @@ -71,13 +82,17 @@ requires-dist = [ { name = "agent-framework-foundry", marker = "extra == 'foundry'", editable = "packages/foundry" }, { name = "agent-framework-runtime", marker = "extra == 'runtime'", editable = "packages/runtime" }, { name = "agent-framework-workflow", marker = "extra == 'workflow'", editable = "packages/workflow" }, + { name = "azure-monitor-opentelemetry", specifier = ">=1.7.0" }, + { name = "azure-monitor-opentelemetry-exporter", specifier = ">=1.0.0b41" }, { name = "mcp", specifier = ">=1.12" }, - { name = "openai", specifier = ">=1.103.0" }, + { name = "openai", specifier = ">=1.99.0" }, { name = "opentelemetry-api", specifier = "~=1.24" }, + { name = "opentelemetry-exporter-otlp-proto-grpc", specifier = ">=1.36.0" }, { name = "opentelemetry-sdk", specifier = "~=1.24" }, { name = "pydantic", specifier = ">=2.11.7" }, { name = "pydantic-settings", specifier = ">=2.10.1" }, { name = "typing-extensions", specifier = ">=4.14.0" }, + { name = "websockets", specifier = ">=15.0.1" }, ] provides-extras = ["azure", "foundry", "workflow", "runtime"] @@ -115,6 +130,21 @@ requires-dist = [ { name = "azure-ai-projects", specifier = ">=1.0.0b11" }, ] +[[package]] +name = "agent-framework-mem0" +version = "0.1.0b1" +source = { editable = "packages/mem0" } +dependencies = [ + { name = "agent-framework", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, + { name = "mem0ai", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, +] + +[package.metadata] +requires-dist = [ + { name = "agent-framework", editable = "packages/main" }, + { name = "mem0ai", specifier = ">=0.1.117" }, +] + [[package]] name = "agent-framework-project" version = "0.0.0" @@ -123,6 +153,7 @@ dependencies = [ { name = "agent-framework", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "agent-framework-azure", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "agent-framework-foundry", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, + { name = "agent-framework-mem0", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "agent-framework-workflow", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, ] @@ -166,6 +197,7 @@ requires-dist = [ { name = "agent-framework", editable = "packages/main" }, { name = "agent-framework-azure", editable = "packages/azure" }, { name = "agent-framework-foundry", editable = "packages/foundry" }, + { name = "agent-framework-mem0", editable = "packages/mem0" }, { name = "agent-framework-workflow", editable = "packages/workflow" }, ] @@ -237,18 +269,18 @@ provides-extras = ["viz"] name = "aiofiles" version = "24.1.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = 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"https://github.com/microsoft/agent-framework.git", ref = "main", subdirectory = "python/packages/main" } -"agent-framework-azure" = { git = "https://github.com/microsoft/agent-framework.git", ref = "main", subdirectory = "python/packages/azure" } -"agent-framework-foundry" = { git = "https://github.com/microsoft/agent-framework.git", ref = "main", subdirectory = "python/packages/foundry" } -"agent-framework-workflow" = { git = "https://github.com/microsoft/agent-framework.git", ref = "main", subdirectory = "python/packages/workflow" } +"agent-framework" = { git = "https://github.com/microsoft/agent-framework.git", branch = "main", subdirectory = "python/packages/main" } +"agent-framework-azure" = { git = "https://github.com/microsoft/agent-framework.git", branch = "main", subdirectory = "python/packages/azure" } +"agent-framework-foundry" = { git = "https://github.com/microsoft/agent-framework.git", branch = "main", subdirectory = "python/packages/foundry" } +"agent-framework-workflow" = { git = "https://github.com/microsoft/agent-framework.git", branch = "main", subdirectory = "python/packages/workflow" } ``` Then create a virtual environment: ```bash diff --git a/user-documentation-python/user-guide/agent-types.md b/user-documentation-python/user-guide/agent-types.md index 55dfc0637d..7364795c23 100644 --- a/user-documentation-python/user-guide/agent-types.md +++ b/user-documentation-python/user-guide/agent-types.md @@ -120,6 +120,53 @@ async with ( For code interpreter examples, see: - [Foundry with code interpreter](../../../python/samples/getting_started/agents/foundry/foundry_with_code_interpreter.py) +### Model Context Protocol (MCP) Tools + +Foundry agents support Model Context Protocol (MCP) tools for connecting to external services and data sources. + +Learn more about MCP tools in the [Azure AI Foundry documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol). + +```python +from agent_framework import ChatAgent, MCPStreamableHTTPTool +from agent_framework.foundry import FoundryChatClient +from azure.identity.aio import AzureCliCredential + +# Tools can be defined at agent creation +async with ( + AzureCliCredential() as credential, + FoundryChatClient(async_credential=credential).create_agent( + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + tools=MCPStreamableHTTPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + ), + ) as agent +): + response = await agent.run("How to create an Azure storage account using az cli?") +``` + +You can also provide MCP tools when running the agent: + +```python +async with ( + AzureCliCredential() as credential, + MCPStreamableHTTPTool( + name="Microsoft Learn MCP", + url="https://learn.microsoft.com/api/mcp", + ) as mcp_server, + ChatAgent( + chat_client=FoundryChatClient(async_credential=credential), + name="DocsAgent", + instructions="You are a helpful assistant that can help with microsoft documentation questions.", + ) as agent, +): + response = await agent.run("What is Microsoft Semantic Kernel?", tools=mcp_server) +``` + +For complete MCP examples, see: +- [Foundry with MCP tools](../../../python/samples/getting_started/agents/foundry/foundry_with_local_mcp.py) + ## Custom agents It is also possible to create fully custom agents that are not just wrappers around a chat client. diff --git a/workflows/README.md b/workflows/README.md index c7ceb0d517..56911c1783 100644 --- a/workflows/README.md +++ b/workflows/README.md @@ -1,7 +1,7 @@ # Declarative Workflows This folder contains sample workflow definitions than be ran using the -[Declarative Workflow](../dotnet/demos/DeclarativeWorkflow) demo. +[Declarative Workflow](../dotnet/samples/GettingStarted/Workflows/Declarative) demo. Each workflow is defined in a single YAML file and contains comments with additional information specific to that workflow.