Compare commits

..
Author SHA1 Message Date
Victoria Hall cb1ee732ed semi working 2025-11-14 16:27:37 -06:00
2715 changed files with 86256 additions and 247487 deletions
+4 -23
View File
@@ -1,34 +1,15 @@
{
"name": "C# (.NET)",
//"image": "mcr.microsoft.com/devcontainers/dotnet",
// Workaround for https://github.com/devcontainers/images/issues/1752
"build": {
"dockerfile": "dotnet.Dockerfile"
},
"image": "mcr.microsoft.com/devcontainers/dotnet:9.0",
"features": {
"ghcr.io/devcontainers/features/azure-cli:1.2.9": {},
"ghcr.io/devcontainers/features/github-cli:1": {
"version": "2"
},
"ghcr.io/devcontainers/features/powershell:1": {
"version": "latest"
},
"ghcr.io/azure/azure-dev/azd:0": {
"version": "latest"
},
"ghcr.io/devcontainers/features/dotnet:2": {
"version": "none",
"dotnetRuntimeVersions": "10.0",
"aspNetCoreRuntimeVersions": "10.0"
},
"ghcr.io/devcontainers/features/copilot-cli:1": {}
"ghcr.io/devcontainers/features/dotnet:2.4.0": {},
"ghcr.io/devcontainers/features/powershell:1.5.1": {},
"ghcr.io/devcontainers/features/azure-cli:1.2.8": {}
},
"workspaceFolder": "/workspaces/agent-framework/dotnet/",
"customizations": {
"vscode": {
"extensions": [
"GitHub.copilot",
"GitHub.vscode-github-actions",
"ms-dotnettools.csdevkit",
"vscode-icons-team.vscode-icons",
"ms-windows-ai-studio.windows-ai-studio"
-5
View File
@@ -1,5 +0,0 @@
FROM mcr.microsoft.com/devcontainers/universal:latest
# Remove Yarn repository with expired GPG key to prevent apt-get update failures
# Tracking issue: https://github.com/devcontainers/images/issues/1752
RUN rm -f /etc/apt/sources.list.d/yarn.list
-3
View File
@@ -2,6 +2,3 @@
# https://docs.github.com/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
python/packages/azurefunctions/ @microsoft/agentframework-durabletask-developers
python/packages/durabletask/ @microsoft/agentframework-durabletask-developers
python/samples/getting_started/azure_functions/ @microsoft/agentframework-durabletask-developers
python/samples/getting_started/durabletask/ @microsoft/agentframework-durabletask-developers
-8
View File
@@ -1,8 +0,0 @@
blank_issues_enabled: true
contact_links:
- name: Documentation
url: https://aka.ms/agent-framework
about: Check out the official documentation for guides and API reference.
- name: Discussions
url: https://github.com/microsoft/agent-framework/discussions
about: Ask questions about Agent Framework.
-70
View File
@@ -1,70 +0,0 @@
name: .NET Bug Report
description: Report a bug in the Agent Framework .NET SDK
title: ".NET: [Bug]: "
labels: ["bug", ".NET"]
type: bug
body:
- type: textarea
id: description
attributes:
label: Description
description: Please provide a clear and detailed description of the bug.
placeholder: |
- What happened?
- What did you expect to happen?
- Steps to reproduce the issue
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a minimal code sample that demonstrates the issue.
placeholder: |
```csharp
// Your code here
```
render: markdown
validations:
required: false
- type: textarea
id: error-messages
attributes:
label: Error Messages / Stack Traces
description: Include any error messages or stack traces you received.
placeholder: |
```
Paste error messages or stack traces here
```
render: markdown
validations:
required: false
- type: input
id: dotnet-packages
attributes:
label: Package Versions
description: List the Microsoft.Agents.* packages and versions you are using
placeholder: "e.g., Microsoft.Agents.AI.Abstractions: 1.0.0, Microsoft.Agents.AI.OpenAI: 1.0.0"
validations:
required: true
- type: input
id: dotnet-version
attributes:
label: .NET Version
description: What version of .NET are you using?
placeholder: "e.g., .NET 8.0"
validations:
required: false
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Add any other context or screenshots that might be helpful.
placeholder: "Any additional information..."
validations:
required: false
@@ -1,51 +0,0 @@
name: Feature Request
description: Request a new feature for Microsoft Agent Framework
title: "[Feature]: "
type: feature
body:
- type: textarea
id: description
attributes:
label: Description
description: Please describe the feature you'd like and why it would be useful.
placeholder: |
Describe the feature you're requesting:
- What problem does it solve?
- What would the expected behavior be?
- Are there any alternatives you've considered?
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a code sample showing how you'd like to use this feature.
placeholder: |
```python
# Your code here
```
or
```csharp
// Your code here
```
render: markdown
validations:
required: false
- type: dropdown
id: language
attributes:
label: Language/SDK
description: Which language/SDK does this feature apply to?
options:
- Both
- .NET
- Python
- Other / Not Applicable
default: 0
validations:
required: false
-70
View File
@@ -1,70 +0,0 @@
name: Python Bug Report
description: Report a bug in the Agent Framework Python SDK
title: "Python: [Bug]: "
labels: ["bug", "Python"]
type: bug
body:
- type: textarea
id: description
attributes:
label: Description
description: Please provide a clear and detailed description of the bug.
placeholder: |
- What happened?
- What did you expect to happen?
- Steps to reproduce the issue
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a minimal code sample that demonstrates the issue.
placeholder: |
```python
# Your code here
```
render: markdown
validations:
required: false
- type: textarea
id: error-messages
attributes:
label: Error Messages / Stack Traces
description: Include any error messages or stack traces you received.
placeholder: |
```
Paste error messages or stack traces here
```
render: markdown
validations:
required: false
- type: input
id: python-packages
attributes:
label: Package Versions
description: List the agent-framework-* packages and versions you are using
placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-azure-ai: 1.0.0"
validations:
required: true
- type: input
id: python-version
attributes:
label: Python Version
description: What version of Python are you using?
placeholder: "e.g., Python 3.11"
validations:
required: false
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Add any other context or screenshots that might be helpful.
placeholder: "Any additional information..."
validations:
required: false
@@ -12,7 +12,7 @@ runs:
docker rm -f dts-emulator
fi
echo "Starting Durable Task Scheduler Emulator"
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 -e DTS_USE_DYNAMIC_TASK_HUBS=true mcr.microsoft.com/dts/dts-emulator:latest
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest
echo "Waiting for Durable Task Scheduler Emulator to be ready"
timeout 30 bash -c 'until curl --silent http://localhost:8080/healthz; do sleep 1; done'
echo "Durable Task Scheduler Emulator is ready"
@@ -28,18 +28,6 @@ runs:
echo "Waiting for Azurite (Azure Storage emulator) to be ready"
timeout 30 bash -c 'until curl --silent http://localhost:10000/devstoreaccount1; do sleep 1; done'
echo "Azurite (Azure Storage emulator) is ready"
- name: Start Redis
shell: bash
run: |
if [ "$(docker ps -aq -f name=redis)" ]; then
echo "Stopping and removing existing Redis"
docker rm -f redis
fi
echo "Starting Redis"
docker run -d --name redis -p 6379:6379 redis:latest
echo "Waiting for Redis to be ready"
timeout 30 bash -c 'until docker exec redis redis-cli ping | grep -q PONG; do sleep 1; done'
echo "Redis is ready"
- name: Install Azure Functions Core Tools
shell: bash
run: |
+59 -11
View File
@@ -1,19 +1,67 @@
# GitHub Copilot Instructions
Microsoft Agent Framework - a multi-language framework for building, orchestrating, and deploying AI agents.
This repository contains both Python and C# code.
All python code resides under the `python/` directory.
All C# code resides under the `dotnet/` directory.
## Repository Structure
The purpose of the code is to provide a framework for building AI agents.
- `python/` - Python implementation → see [python/AGENTS.md](../python/AGENTS.md)
- `dotnet/` - C#/.NET implementation → see [dotnet/AGENTS.md](../dotnet/AGENTS.md)
- `docs/` - Design documents and architectural decision records
When contributing to this repository, please follow these guidelines:
## Architectural Decision Records (ADRs)
## C# Code Guidelines
ADRs in `docs/decisions/` capture significant design decisions and their rationale. They document considered alternatives, trade-offs, and the reasoning behind choices.
Here are some general guidelines that apply to all code.
**Templates:**
- `adr-template.md` - Full template with detailed sections
- `adr-short-template.md` - Abbreviated template for simpler decisions
- The top of all *.cs files should have a copyright notice: `// Copyright (c) Microsoft. All rights reserved.`
- All public methods and classes should have XML documentation comments.
When proposing architectural changes, create an ADR to capture options considered and the decision rationale. See [docs/decisions/README.md](../docs/decisions/README.md) for the full process.
### C# Sample Code Guidelines
Sample code is located in the `dotnet/samples` directory.
When adding a new sample, follow these steps:
- The sample should be a standalone .net project in one of the subdirectories of the samples directory.
- The directory name should be the same as the project name.
- The directory should contain a README.md file that explains what the sample does and how to run it.
- The README.md file should follow the same format as other samples.
- The csproj file should match the directory name.
- The csproj file should be configured in the same way as other samples.
- The project should preferably contain a single Program.cs file that contains all the sample code.
- The sample should be added to the solution file in the samples directory.
- The sample should be tested to ensure it works as expected.
- A reference to the new samples should be added to the README.md file in the parent directory of the new sample.
The sample code should follow these guidelines:
- Configuration settings should be read from environment variables, e.g. `var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");`.
- Environment variables should use upper snake_case naming convention.
- Secrets should not be hardcoded in the code or committed to the repository.
- The code should be well-documented with comments explaining the purpose of each step.
- The code should be simple and to the point, avoiding unnecessary complexity.
- Prefer inline literals over constants for values that are not reused. For example, use `new ChatClientAgent(chatClient, instructions: "You are a helpful assistant.")` instead of defining a constant for "instructions".
- Ensure that all private classes are sealed
- Use the Async suffix on the name of all async methods that return a Task or ValueTask.
- Prefer defining variables using types rather than var, to help users understand the types involved.
- Follow the patterns in the samples in the same directories where new samples are being added.
- The structure of the sample should be as follows:
- The top of the Program.cs should have a copyright notice: `// Copyright (c) Microsoft. All rights reserved.`
- Then add a comment describing what the sample is demonstrating.
- Then add the necessary using statements.
- Then add the main code logic.
- Finally, add any helper methods or classes at the bottom of the file.
### C# Unit Test Guidelines
Unit tests are located in the `dotnet/tests` directory in projects with a `.UnitTests.csproj` suffix.
Unit tests should follow these guidelines:
- Use `this.` for accessing class members
- Add Arrange, Act and Assert comments for each test
- Ensure that all private classes, that are not subclassed, are sealed
- Use the Async suffix on the name of all async methods
- Use the Moq library for mocking objects where possible
- Validate that each test actually tests the target behavior, e.g. we should not have tests that creates a mock, calls the mock and then verifies that the mock was called, without the target code being involved. We also shouldn't have tests that test language features, e.g. something that the compiler would catch anyway.
- Avoid adding excessive comments to tests. Instead favour clear easy to understand code.
- Follow the patterns in the unit tests in the same project or classes to which new tests are being added
+3 -8
View File
@@ -11,6 +11,9 @@ updates:
schedule:
interval: "cron"
cronjob: "0 8 * * 4,0" # Every Thursday(4) and Sunday(0) at 8:00 UTC
experimental:
nuget-native-updater: false
enable-cooldown-metrics-collection: false
ignore:
# For all System.* and Microsoft.Extensions/Bcl.* packages, ignore all major version updates
- dependency-name: "System.*"
@@ -25,14 +28,6 @@ updates:
- "dependencies"
# Maintain dependencies for python
- package-ecosystem: "pip"
directory: "python/"
schedule:
interval: "weekly"
day: "monday"
labels:
- "python"
- "dependencies"
- package-ecosystem: "uv"
directory: "python/"
schedule:
@@ -1,17 +0,0 @@
---
applyTo: "dotnet/src/Microsoft.Agents.AI.DurableTask/**,dotnet/src/Microsoft.Agents.AI.Hosting.AzureFunctions/**"
---
# Durable Task area code instructions
The following guidelines apply to pull requests that modify files under
`dotnet/src/Microsoft.Agents.AI.DurableTask/**` or
`dotnet/src/Microsoft.Agents.AI.Hosting.AzureFunctions/**`:
## CHANGELOG.md
- Each pull request that modifies code should add just one bulleted entry to the `CHANGELOG.md` file containing a change title (usually the PR title) and a link to the PR itself.
- New PRs should be added to the top of the `CHANGELOG.md` file under a "## [Unreleased]" heading.
- If the PR is the first since the last release, the existing "## [Unreleased]" heading should be replaced with a "## v[X.Y.Z]" heading and the PRs since the last release should be added to the new "## [Unreleased]" heading.
- The style of new `CHANGELOG.md` entries should match the style of the other entries in the file.
- If the PR introduces a breaking change, the changelog entry should be prefixed with "[BREAKING]".
@@ -105,7 +105,7 @@ After completing migration, verify these specific items:
1. **Compilation**: Execute `dotnet build` on all modified projects - zero errors required
2. **Namespace Updates**: Confirm all `using Microsoft.SemanticKernel.Agents` statements are replaced
3. **Method Calls**: Verify all `InvokeAsync` calls are changed to `RunAsync`
4. **Return Types**: Confirm handling of `AgentResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
4. **Return Types**: Confirm handling of `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
5. **Thread Creation**: Validate all thread creation uses `agent.GetNewThread()` pattern
6. **Tool Registration**: Ensure `[KernelFunction]` attributes are removed and `AIFunctionFactory.Create()` is used
7. **Options Configuration**: Verify `AgentRunOptions` or `ChatClientAgentRunOptions` replaces `AgentInvokeOptions`
@@ -119,7 +119,7 @@ Agent Framework provides functionality for creating and managing AI agents throu
Key API differences:
- Agent creation: Remove Kernel dependency, use direct client-based creation
- Method names: `InvokeAsync` → `RunAsync`, `InvokeStreamingAsync` → `RunStreamingAsync`
- Return types: `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
- Return types: `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentRunResponse`
- Thread creation: Provider-specific constructors → `agent.GetNewThread()`
- Tool registration: `KernelPlugin` system → Direct `AIFunction` registration
- Options: `AgentInvokeOptions` → Provider-specific run options (e.g., `ChatClientAgentRunOptions`)
@@ -142,9 +142,9 @@ Replace these Semantic Kernel agent classes with their Agent Framework equivalen
|----------------------|----------------------------|-------------------|
| `IChatCompletionService` | `IChatClient` | Convert to `IChatClient` using `chatService.AsChatClient()` extensions |
| `ChatCompletionAgent` | `ChatClientAgent` | Remove `Kernel` parameter, add `IChatClient` parameter |
| `OpenAIAssistantAgent` | `AIAgent` (via extension) | ⚠️ **Deprecated** - Use Responses API instead. <br> **New**: `OpenAIClient.GetAssistantClient().CreateAIAgent()` <br> **Existing**: `OpenAIClient.GetAssistantClient().GetAIAgent(assistantId)` |
| `OpenAIAssistantAgent` | `AIAgent` (via extension) | **New**: `OpenAIClient.GetAssistantClient().CreateAIAgent()` <br> **Existing**: `OpenAIClient.GetAssistantClient().GetAIAgent(assistantId)` |
| `AzureAIAgent` | `AIAgent` (via extension) | **New**: `PersistentAgentsClient.CreateAIAgent()` <br> **Existing**: `PersistentAgentsClient.GetAIAgent(agentId)` |
| `OpenAIResponseAgent` | `AIAgent` (via extension) | Replace with `OpenAIClient.GetOpenAIResponseClient(modelId).CreateAIAgent()` |
| `OpenAIResponseAgent` | `AIAgent` (via extension) | Replace with `OpenAIClient.GetOpenAIResponseClient().CreateAIAgent()` |
| `A2AAgent` | `AIAgent` (via extension) | Replace with `A2ACardResolver.GetAIAgentAsync()` |
| `BedrockAgent` | Not supported | Custom implementation required |
@@ -166,8 +166,8 @@ Replace these method calls:
| `thread.DeleteAsync()` | Provider-specific cleanup | Use provider client directly |
Return type changes:
- `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentResponseUpdate>`
- `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentRunResponse`
- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentRunResponseUpdate>`
</api_changes>
<configuration_changes>
@@ -191,8 +191,8 @@ Agent Framework changes these behaviors compared to Semantic Kernel Agents:
1. **Thread Management**: Agent Framework automatically manages thread state. Semantic Kernel required manual thread updates in some scenarios (e.g., OpenAI Responses).
2. **Return Types**:
- Non-streaming: Returns single `AgentResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
- Streaming: Returns `IAsyncEnumerable<AgentResponseUpdate>` instead of `IAsyncEnumerable<StreamingChatMessageContent>`
- Non-streaming: Returns single `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
- Streaming: Returns `IAsyncEnumerable<AgentRunResponseUpdate>` instead of `IAsyncEnumerable<StreamingChatMessageContent>`
3. **Tool Registration**: Agent Framework uses direct function registration without requiring `[KernelFunction]` attributes.
@@ -397,7 +397,7 @@ await foreach (AgentResponseItem<ChatMessageContent> item in agent.InvokeAsync(u
**With this Agent Framework non-streaming pattern:**
```csharp
AgentResponse result = await agent.RunAsync(userInput, thread, options);
AgentRunResponse result = await agent.RunAsync(userInput, thread, options);
Console.WriteLine(result);
```
@@ -411,7 +411,7 @@ await foreach (StreamingChatMessageContent update in agent.InvokeStreamingAsync(
**With this Agent Framework streaming pattern:**
```csharp
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
{
Console.Write(update);
}
@@ -420,8 +420,8 @@ await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(userInput,
**Required changes:**
1. Replace `agent.InvokeAsync()` with `agent.RunAsync()`
2. Replace `agent.InvokeStreamingAsync()` with `agent.RunStreamingAsync()`
3. Change return type handling from `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` to `AgentResponse`
4. Change streaming type from `StreamingChatMessageContent` to `AgentResponseUpdate`
3. Change return type handling from `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` to `AgentRunResponse`
4. Change streaming type from `StreamingChatMessageContent` to `AgentRunResponseUpdate`
5. Remove `await foreach` for non-streaming calls
6. Access message content directly from result object instead of iterating
</api_changes>
@@ -529,14 +529,14 @@ AIAgent agent = new OpenAIClient(apiKey)
.CreateAIAgent(instructions: instructions);
```
**OpenAI Assistants (New):** ⚠️ *Deprecated - Use Responses API instead*
**OpenAI Assistants (New):**
```csharp
AIAgent agent = new OpenAIClient(apiKey)
.GetAssistantClient()
.CreateAIAgent(modelId, instructions: instructions);
```
**OpenAI Assistants (Existing):** ⚠️ *Deprecated - Use Responses API instead*
**OpenAI Assistants (Existing):**
```csharp
AIAgent agent = new OpenAIClient(apiKey)
.GetAssistantClient()
@@ -562,20 +562,6 @@ AIAgent agent = await new PersistentAgentsClient(endpoint, credential)
.GetAIAgentAsync(agentId);
```
**OpenAI Responses:** *(Recommended for OpenAI)*
```csharp
AIAgent agent = new OpenAIClient(apiKey)
.GetOpenAIResponseClient(modelId)
.CreateAIAgent(instructions: instructions);
```
**Azure OpenAI Responses:** *(Recommended for Azure OpenAI)*
```csharp
AIAgent agent = new AzureOpenAIClient(endpoint, credential)
.GetOpenAIResponseClient(deploymentName)
.CreateAIAgent(instructions: instructions);
```
**A2A:**
```csharp
A2ACardResolver resolver = new(new Uri(agentHost));
@@ -661,7 +647,7 @@ await foreach (var result in agent.InvokeAsync(input, thread, options))
```csharp
ChatClientAgentRunOptions options = new(new ChatOptions { MaxOutputTokens = 1000 });
AgentResponse result = await agent.RunAsync(input, thread, options);
AgentRunResponse result = await agent.RunAsync(input, thread, options);
Console.WriteLine(result);
// Access underlying content when needed:
@@ -689,7 +675,7 @@ await foreach (var result in agent.InvokeAsync(input, thread, options))
**With this Agent Framework non-streaming usage pattern:**
```csharp
AgentResponse result = await agent.RunAsync(input, thread, options);
AgentRunResponse result = await agent.RunAsync(input, thread, options);
Console.WriteLine($"Tokens: {result.Usage.TotalTokenCount}");
```
@@ -709,7 +695,7 @@ await foreach (StreamingChatMessageContent response in agent.InvokeStreamingAsyn
**With this Agent Framework streaming usage pattern:**
```csharp
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
{
if (update.Contents.OfType<UsageContent>().FirstOrDefault() is { } usageContent)
{
@@ -776,57 +762,35 @@ await foreach (var content in agent.InvokeAsync(userInput, thread))
**With this Agent Framework CodeInterpreter pattern:**
```csharp
using System.Text;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
var result = await agent.RunAsync(userInput, thread);
Console.WriteLine(result);
// Get the CodeInterpreterToolCallContent (code input)
CodeInterpreterToolCallContent? toolCallContent = result.Messages
.SelectMany(m => m.Contents)
.OfType<CodeInterpreterToolCallContent>()
.FirstOrDefault();
// Extract chat response MEAI type via first level breaking glass
var chatResponse = result.RawRepresentation as ChatResponse;
if (toolCallContent?.Inputs is not null)
// Extract underlying SDK updates via second level breaking glass
var underlyingStreamingUpdates = chatResponse?.RawRepresentation as IEnumerable<object?> ?? [];
StringBuilder generatedCode = new();
foreach (object? underlyingUpdate in underlyingStreamingUpdates ?? [])
{
DataContent? codeInput = toolCallContent.Inputs.OfType<DataContent>().FirstOrDefault();
if (codeInput?.HasTopLevelMediaType("text") ?? false)
if (underlyingUpdate is RunStepDetailsUpdate stepDetailsUpdate && stepDetailsUpdate.CodeInterpreterInput is not null)
{
Console.WriteLine($"Code Input: {Encoding.UTF8.GetString(codeInput.Data.ToArray())}");
generatedCode.Append(stepDetailsUpdate.CodeInterpreterInput);
}
}
// Get the CodeInterpreterToolResultContent (code output)
CodeInterpreterToolResultContent? toolResultContent = result.Messages
.SelectMany(m => m.Contents)
.OfType<CodeInterpreterToolResultContent>()
.FirstOrDefault();
if (toolResultContent?.Outputs is not null)
if (!string.IsNullOrEmpty(generatedCode.ToString()))
{
TextContent? resultOutput = toolResultContent.Outputs.OfType<TextContent>().FirstOrDefault();
if (resultOutput is not null)
{
Console.WriteLine($"Code Tool Result: {resultOutput.Text}");
}
}
// Getting any annotations generated by the tool
foreach (AIAnnotation annotation in result.Messages
.SelectMany(m => m.Contents)
.SelectMany(c => c.Annotations ?? []))
{
Console.WriteLine($"Annotation: {annotation}");
Console.WriteLine($"\n# {chatResponse?.Messages[0].Role}:Generated Code:\n{generatedCode}");
}
```
**Functional differences:**
1. Code interpreter content is now available via MEAI abstractions - no breaking glass required
2. Use `CodeInterpreterToolCallContent` to access code inputs (the generated code)
3. Use `CodeInterpreterToolResultContent` to access code outputs (execution results)
4. Annotations are accessible via `AIAnnotation` on content items
1. Code interpreter output is separate from text content, not a metadata property
2. Access code via `RunStepDetailsUpdate.CodeInterpreterInput` instead of metadata
3. Use breaking glass pattern to access underlying SDK objects
4. Process text content and code interpreter output independently
</behavioral_changes>
#### Provider-Specific Options Configuration
@@ -839,7 +803,7 @@ var agentOptions = new ChatClientAgentRunOptions(new ChatOptions
{
MaxOutputTokens = 8000,
// Breaking glass to access provider-specific options
RawRepresentationFactory = (_) => new OpenAI.Responses.CreateResponseOptions()
RawRepresentationFactory = (_) => new OpenAI.Responses.ResponseCreationOptions()
{
ReasoningOptions = new()
{
@@ -1016,8 +980,6 @@ AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential(
### 3. OpenAI Assistants Migration
> ⚠️ **DEPRECATION WARNING**: The OpenAI Assistants API has been deprecated. The Agent Framework extension methods for Assistants are marked as `[Obsolete]`. **Please use the Responses API instead** (see Section 6: OpenAI Responses Migration).
<configuration_changes>
**Remove Semantic Kernel Packages:**
```xml
@@ -1329,7 +1291,52 @@ var result = await agent.RunAsync(userInput, thread);
```
</api_changes>
### 8. Unsupported Providers (Require Custom Implementation)
### 8. A2A Migration
<configuration_changes>
**Remove Semantic Kernel Packages:**
```xml
<PackageReference Include="Microsoft.SemanticKernel.Agents.A2A" />
```
**Add Agent Framework Packages:**
```xml
<PackageReference Include="Microsoft.Agents.AI.A2A" />
```
</configuration_changes>
<api_changes>
**Replace this Semantic Kernel pattern:**
```csharp
using A2A;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Agents;
using Microsoft.SemanticKernel.Agents.A2A;
using var httpClient = CreateHttpClient();
var client = new A2AClient(agentUrl, httpClient);
var cardResolver = new A2ACardResolver(url, httpClient);
var agentCard = await cardResolver.GetAgentCardAsync();
Console.WriteLine(JsonSerializer.Serialize(agentCard, s_jsonSerializerOptions));
var agent = new A2AAgent(client, agentCard);
```
**With this Agent Framework pattern:**
```csharp
using System;
using A2A;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.A2A;
// Initialize an A2ACardResolver to get an A2A agent card.
A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
AIAgent agent = await agentCardResolver.GetAIAgentAsync();
```
</api_changes>
### 9. Unsupported Providers (Require Custom Implementation)
<behavioral_changes>
#### BedrockAgent Migration
@@ -1500,7 +1507,7 @@ Console.WriteLine(result);
```
</behavioral_changes>
### 9. Function Invocation Filtering
### 10. Function Invocation Filtering
**Invocation Context**
@@ -1608,4 +1615,25 @@ var filteredAgent = originalAgent
.Build();
```
### 11. Function Invocation Contexts
**Invocation Context**
Semantic Kernel's `IAutoFunctionInvocationFilter` provides a `AutoFunctionInvocationContext` where Agent Framework provides `FunctionInvocationContext`
The property mapping guide from a `AutoFunctionInvocationContext` to a `FunctionInvocationContext` is as follows:
| Semantic Kernel | Agent Framework |
| --- | --- |
| RequestSequenceIndex | Iteration |
| FunctionSequenceIndex | FunctionCallIndex |
| ToolCallId | CallContent.CallId |
| ChatMessageContent | Messages[0] |
| ExecutionSettings | Options |
| ChatHistory | Messages |
| Function | Function |
| Kernel | N/A |
| Result | Use `return` from the delegate |
| Terminate | Terminate |
| CancellationToken | provided via argument to middleware delegate |
| Arguments | Arguments |
+1 -1
View File
@@ -32,7 +32,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
persist-credentials: false
+24 -55
View File
@@ -18,7 +18,6 @@ on:
env:
COVERAGE_THRESHOLD: 80
COVERAGE_FRAMEWORK: net10.0 # framework target for which we run/report code coverage
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -35,25 +34,19 @@ jobs:
contents: read
pull-requests: read
outputs:
dotnetChanges: ${{ steps.filter.outputs.dotnet }}
cosmosDbChanges: ${{ steps.filter.outputs.cosmosdb }}
dotnetChanges: ${{ steps.filter.outputs.dotnet}}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- uses: dorny/paths-filter@v3
id: filter
with:
filters: |
dotnet:
- 'dotnet/**'
cosmosdb:
- 'dotnet/src/Microsoft.Agents.AI.CosmosNoSql/**'
# run only if 'dotnet' files were changed
- name: dotnet tests
if: steps.filter.outputs.dotnet == 'true'
run: echo "Dotnet file"
- name: dotnet CosmosDB tests
if: steps.filter.outputs.cosmosdb == 'true'
run: echo "Dotnet CosmosDB changes"
# run only if not 'dotnet' files were changed
- name: not dotnet tests
if: steps.filter.outputs.dotnet != 'true'
@@ -66,36 +59,26 @@ jobs:
fail-fast: false
matrix:
include:
- { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
- { targetFramework: "net9.0", os: "windows-latest", configuration: Debug }
- { targetFramework: "net8.0", os: "ubuntu-latest", configuration: Release }
- { targetFramework: "net9.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
- { targetFramework: "net9.0", os: "ubuntu-latest", configuration: Debug }
- { targetFramework: "net9.0", os: "windows-latest", configuration: Release }
- { targetFramework: "net472", os: "windows-latest", configuration: Release, integration-tests: true, environment: "integration" }
runs-on: ${{ matrix.os }}
environment: ${{ matrix.environment }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
workflow-samples
# Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
- name: Start Azure Cosmos DB Emulator
if: ${{ runner.os == 'Windows' && (needs.paths-filter.outputs.cosmosDbChanges == 'true' || (github.event_name != 'pull_request' && matrix.integration-tests)) }}
shell: pwsh
run: |
Write-Host "Launching Azure Cosmos DB Emulator"
Import-Module "$env:ProgramFiles\Azure Cosmos DB Emulator\PSModules\Microsoft.Azure.CosmosDB.Emulator"
Start-CosmosDbEmulator -NoUI -Key "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
echo "COSMOS_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
workflow-samples
- name: Setup dotnet
uses: actions/setup-dotnet@v5.1.0
uses: actions/setup-dotnet@v5.0.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Build dotnet solutions
@@ -140,33 +123,25 @@ jobs:
popd
rm -rf "$TEMP_DIR"
- name: Run Unit Tests
- name: Run Unit Tests Windows
shell: bash
run: |
export UT_PROJECTS=$(find ./dotnet -type f -name "*.UnitTests.csproj" | tr '\n' ' ')
for project in $UT_PROJECTS; do
# Query the project's target frameworks using MSBuild with the current configuration
target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
# Check if the project supports the target framework
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
if [[ "${{ matrix.targetFramework }}" == "${{ env.COVERAGE_FRAMEWORK }}" ]]; then
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
else
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
fi
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
else
echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
fi
done
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
- name: Log event name and matrix integration-tests
shell: bash
run: echo "github.event_name:${{ github.event_name }} matrix.integration-tests:${{ matrix.integration-tests }} github.event.action:${{ github.event.action }} github.event.pull_request.merged:${{ github.event.pull_request.merged }}"
shell: bash
run: echo "github.event_name:${{ github.event_name }} matrix.integration-tests:${{ matrix.integration-tests }} github.event.action:${{ github.event.action }} github.event.pull_request.merged:${{ github.event.pull_request.merged }}"
- name: Azure CLI Login
if: github.event_name != 'pull_request' && matrix.integration-tests
@@ -192,18 +167,15 @@ jobs:
for project in $INTEGRATION_TEST_PROJECTS; do
# Query the project's target frameworks using MSBuild with the current configuration
target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
# Check if the project supports the target framework
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --filter "Category!=IntegrationDisabled"
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
else
echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
fi
done
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
# OpenAI Models
OpenAI__ApiKey: ${{ secrets.OPENAI__APIKEY }}
OpenAI__ChatModelId: ${{ vars.OPENAI__CHATMODELID }}
@@ -222,22 +194,19 @@ jobs:
# Generate test reports and check coverage
- name: Generate test reports
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: danielpalme/ReportGenerator-GitHub-Action@5.5.1
uses: danielpalme/ReportGenerator-GitHub-Action@5.4.18
with:
reports: "./TestResults/Coverage/**/coverage.cobertura.xml"
targetdir: "./TestResults/Reports"
reporttypes: "HtmlInline;JsonSummary"
- name: Upload coverage report artifact
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: actions/upload-artifact@v6
uses: actions/upload-artifact@v5
with:
name: CoverageReport-${{ matrix.os }}-${{ matrix.targetFramework }}-${{ matrix.configuration }} # Artifact name
path: ./TestResults/Reports # Directory containing files to upload
- name: Check coverage
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
shell: pwsh
run: .github/workflows/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
+2 -2
View File
@@ -22,7 +22,7 @@ jobs:
fail-fast: false
matrix:
include:
- { dotnet: "10.0", configuration: Release, os: ubuntu-latest }
- { dotnet: "9.0", configuration: Release, os: ubuntu-latest }
runs-on: ${{ matrix.os }}
env:
@@ -30,7 +30,7 @@ jobs:
steps:
- name: Check out code
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
persist-credentials: false
+11 -50
View File
@@ -45,58 +45,19 @@ jobs:
labels.push("triage")
}
// Helper function to extract field value from issue form body
// Issue forms format fields as: ### Field Name\n\nValue
function getFormFieldValue(body, fieldName) {
if (!body) return null
const regex = new RegExp(`###\\s*${fieldName}\\s*\\n\\n([^\\n#]+)`, 'i')
const match = body.match(regex)
return match ? match[1].trim() : null
// Check if the body or the title contains the word 'python' (case-insensitive)
if ((body != null && body.match(/python/i)) || (title != null && title.match(/python/i))) {
// Add the 'python' label to the array
labels.push("python")
}
// Check for language from issue form dropdown first
const languageField = getFormFieldValue(body, 'Language')
let languageLabelAdded = false
if (languageField) {
if (languageField === 'Python') {
labels.push("python")
languageLabelAdded = true
} else if (languageField === '.NET') {
labels.push(".NET")
languageLabelAdded = true
}
// 'None / Not Applicable' - don't add any language label
}
// Fallback: Check if the body or the title contains the word 'python' (case-insensitive)
// Only if language wasn't already determined from the form field
if (!languageLabelAdded) {
if ((body != null && body.match(/python/i)) || (title != null && title.match(/python/i))) {
// Add the 'python' label to the array
labels.push("python")
}
// Check if the body or the title contains the words 'dotnet', '.net', 'c#' or 'csharp' (case-insensitive)
if ((body != null && body.match(/\.net/i)) || (title != null && title.match(/\.net/i)) ||
(body != null && body.match(/dotnet/i)) || (title != null && title.match(/dotnet/i)) ||
(body != null && body.match(/C#/i)) || (title != null && title.match(/C#/i)) ||
(body != null && body.match(/csharp/i)) || (title != null && title.match(/csharp/i))) {
// Add the '.NET' label to the array
labels.push(".NET")
}
}
// Check for issue type from issue form dropdown
const issueTypeField = getFormFieldValue(body, 'Type of Issue')
if (issueTypeField) {
if (issueTypeField === 'Bug') {
labels.push("bug")
} else if (issueTypeField === 'Feature Request') {
labels.push("enhancement")
} else if (issueTypeField === 'Question') {
labels.push("question")
}
// Check if the body or the title contains the words 'dotnet', '.net', 'c#' or 'csharp' (case-insensitive)
if ((body != null && body.match(/.net/i)) || (title != null && title.match(/.net/i)) ||
(body != null && body.match(/dotnet/i)) || (title != null && title.match(/dotnet/i)) ||
(body != null && body.match(/C#/i)) || (title != null && title.match(/C#/i)) ||
(body != null && body.match(/csharp/i)) || (title != null && title.match(/csharp/i))) {
// Add the '.NET' label to the array
labels.push(".NET")
}
// Add the labels to the issue (only if there are labels to add)
+1 -1
View File
@@ -19,7 +19,7 @@ jobs:
runs-on: ubuntu-22.04
# check out the latest version of the code
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
with:
persist-credentials: false
-1
View File
@@ -29,4 +29,3 @@ jobs:
token: ${{ secrets.GITHUB_TOKEN }}
timeout: 3600
interval: 30
ignored: CodeQL,CodeQL analysis (csharp)
-268
View File
@@ -1,268 +0,0 @@
#!/usr/bin/env python3
# Copyright (c) Microsoft. All rights reserved.
"""Check Python test coverage against threshold for enforced modules.
This script parses a Cobertura XML coverage report and enforces a minimum
coverage threshold on specific modules. Non-enforced modules are reported
for visibility but don't block the build.
Usage:
python python-check-coverage.py <coverage-xml-path> <threshold>
Example:
python python-check-coverage.py python-coverage.xml 85
"""
import sys
import xml.etree.ElementTree as ET
from dataclasses import dataclass
# =============================================================================
# ENFORCED MODULES CONFIGURATION
# =============================================================================
# Add or remove modules from this set to control which packages must meet
# the coverage threshold. Only these modules will fail the build if below
# threshold. Other modules are reported for visibility only.
#
# Module paths should match the package paths as they appear in the coverage
# report (e.g., "packages.azure-ai.agent_framework_azure_ai" for packages/azure-ai).
# Sub-modules can be included by specifying their full path.
# =============================================================================
ENFORCED_MODULES: set[str] = {
"packages.azure-ai.agent_framework_azure_ai",
"packages.core.agent_framework",
"packages.core.agent_framework._workflows",
"packages.purview.agent_framework_purview",
# Add more modules here as coverage improves:
# "packages.azure-ai-search.agent_framework_azure_ai_search",
# "packages.anthropic.agent_framework_anthropic",
}
@dataclass
class PackageCoverage:
"""Coverage data for a single package."""
name: str
line_rate: float
branch_rate: float
lines_valid: int
lines_covered: int
branches_valid: int
branches_covered: int
@property
def line_coverage_percent(self) -> float:
"""Return line coverage as a percentage."""
return self.line_rate * 100
@property
def branch_coverage_percent(self) -> float:
"""Return branch coverage as a percentage."""
return self.branch_rate * 100
def parse_coverage_xml(xml_path: str) -> tuple[dict[str, PackageCoverage], float, float]:
"""Parse Cobertura XML and extract per-package coverage data.
Args:
xml_path: Path to the Cobertura XML coverage report.
Returns:
A tuple of (packages_dict, overall_line_rate, overall_branch_rate).
"""
tree = ET.parse(xml_path)
root = tree.getroot()
# Get overall coverage from root element
overall_line_rate = float(root.get("line-rate", 0))
overall_branch_rate = float(root.get("branch-rate", 0))
packages: dict[str, PackageCoverage] = {}
for package in root.findall(".//package"):
package_path = package.get("name", "unknown")
line_rate = float(package.get("line-rate", 0))
branch_rate = float(package.get("branch-rate", 0))
# Count lines and branches from classes within this package
lines_valid = 0
lines_covered = 0
branches_valid = 0
branches_covered = 0
for class_elem in package.findall(".//class"):
for line in class_elem.findall(".//line"):
lines_valid += 1
if int(line.get("hits", 0)) > 0:
lines_covered += 1
# Branch coverage from line elements
if line.get("branch") == "true":
condition_coverage = line.get("condition-coverage", "")
if condition_coverage:
# Parse "X% (covered/total)" format
try:
coverage_parts = condition_coverage.split("(")[1].rstrip(")").split("/")
branches_covered += int(coverage_parts[0])
branches_valid += int(coverage_parts[1])
except (IndexError, ValueError):
# Ignore malformed condition-coverage strings; treat this line as having no branch data.
pass
# Use full package path as the key (no aggregation)
packages[package_path] = PackageCoverage(
name=package_path,
line_rate=line_rate if lines_valid == 0 else lines_covered / lines_valid,
branch_rate=branch_rate if branches_valid == 0 else branches_covered / branches_valid,
lines_valid=lines_valid,
lines_covered=lines_covered,
branches_valid=branches_valid,
branches_covered=branches_covered,
)
return packages, overall_line_rate, overall_branch_rate
def format_coverage_value(coverage: float, threshold: float, is_enforced: bool) -> str:
"""Format a coverage value with optional pass/fail indicator.
Args:
coverage: Coverage percentage (0-100).
threshold: Minimum required coverage percentage.
is_enforced: Whether this module is enforced.
Returns:
Formatted string like "85.5%" or "85.5% ✅" or "75.0% ❌".
"""
formatted = f"{coverage:.1f}%"
if is_enforced:
icon = "✅" if coverage >= threshold else "❌"
formatted = f"{formatted} {icon}"
return formatted
def print_coverage_table(
packages: dict[str, PackageCoverage],
threshold: float,
overall_line_rate: float,
overall_branch_rate: float,
) -> None:
"""Print a formatted coverage summary table.
Args:
packages: Dictionary of package name to coverage data.
threshold: Minimum required coverage percentage.
overall_line_rate: Overall line coverage rate (0-1).
overall_branch_rate: Overall branch coverage rate (0-1).
"""
print("\n" + "=" * 80)
print("PYTHON TEST COVERAGE REPORT")
print("=" * 80)
# Overall coverage
print(f"\nOverall Line Coverage: {overall_line_rate * 100:.1f}%")
print(f"Overall Branch Coverage: {overall_branch_rate * 100:.1f}%")
print(f"Threshold: {threshold}%")
# Package table
print("\n" + "-" * 110)
print(f"{'Package':<80} {'Lines':<15} {'Line Cov':<15}")
print("-" * 110)
# Sort: enforced modules first, then alphabetically
sorted_packages = sorted(
packages.values(),
key=lambda p: (p.name not in ENFORCED_MODULES, p.name),
)
for pkg in sorted_packages:
is_enforced = pkg.name in ENFORCED_MODULES
enforced_marker = "[ENFORCED] " if is_enforced else ""
line_cov = format_coverage_value(pkg.line_coverage_percent, threshold, is_enforced)
lines_info = f"{pkg.lines_covered}/{pkg.lines_valid}"
package_label = f"{enforced_marker}{pkg.name}"
print(f"{package_label:<80} {lines_info:<15} {line_cov:<15}")
print("-" * 110)
def check_coverage(xml_path: str, threshold: float) -> bool:
"""Check if all enforced modules meet the coverage threshold.
Args:
xml_path: Path to the Cobertura XML coverage report.
threshold: Minimum required coverage percentage.
Returns:
True if all enforced modules pass, False otherwise.
"""
packages, overall_line_rate, overall_branch_rate = parse_coverage_xml(xml_path)
print_coverage_table(packages, threshold, overall_line_rate, overall_branch_rate)
# Check enforced modules
failed_modules: list[str] = []
missing_modules: list[str] = []
for module_name in ENFORCED_MODULES:
if module_name not in packages:
missing_modules.append(module_name)
continue
pkg = packages[module_name]
if pkg.line_coverage_percent < threshold:
failed_modules.append(f"{module_name} ({pkg.line_coverage_percent:.1f}%)")
# Report results
if missing_modules:
print(f"\n❌ FAILED: Enforced modules not found in coverage report: {', '.join(missing_modules)}")
return False
if failed_modules:
print(f"\n❌ FAILED: The following enforced modules are below {threshold}% coverage threshold:")
for module in failed_modules:
print(f" - {module}")
print("\nTo fix: Add more tests to improve coverage for the failing modules.")
return False
if ENFORCED_MODULES:
found_enforced = [m for m in ENFORCED_MODULES if m in packages]
if found_enforced:
print(f"\nâś… PASSED: All enforced modules meet the {threshold}% coverage threshold.")
return True
def main() -> int:
"""Main entry point.
Returns:
Exit code: 0 for success, 1 for failure.
"""
if len(sys.argv) != 3:
print(f"Usage: {sys.argv[0]} <coverage-xml-path> <threshold>")
print(f"Example: {sys.argv[0]} python-coverage.xml 85")
return 1
xml_path = sys.argv[1]
try:
threshold = float(sys.argv[2])
except ValueError:
print(f"Error: Invalid threshold value: {sys.argv[2]}")
return 1
try:
success = check_coverage(xml_path, threshold)
return 0 if success else 1
except FileNotFoundError:
print(f"Error: Coverage file not found: {xml_path}")
return 1
except ET.ParseError as e:
print(f"Error: Failed to parse coverage XML: {e}")
return 1
if __name__ == "__main__":
sys.exit(main())
+12 -106
View File
@@ -12,13 +12,13 @@ env:
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
pre-commit-hooks:
name: Pre-commit Hooks
pre-commit:
name: Checks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
python-version: ["3.10", "3.14"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
@@ -27,9 +27,7 @@ jobs:
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
@@ -37,107 +35,15 @@ jobs:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
- uses: actions/cache@v5
- uses: actions/cache@v4
with:
path: ~/.cache/prek
key: prek|${{ matrix.python-version }}|${{ hashFiles('python/.pre-commit-config.yaml') }}
- uses: j178/prek-action@v1
name: Run Pre-commit Hooks (excluding poe-check)
env:
SKIP: poe-check
path: ~/.cache/pre-commit
key: pre-commit|${{ matrix.python-version }}|${{ hashFiles('python/.pre-commit-config.yaml') }}
- uses: pre-commit/action@v3.0.1
name: Run Pre-Commit Hooks
with:
extra-args: --cd python --all-files
package-checks:
name: Package Checks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run fmt, lint, pyright in parallel across packages
run: uv run poe check-packages
samples-markdown:
name: Samples & Markdown
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run samples lint
run: uv run poe samples-lint
- name: Run samples syntax check
run: uv run poe samples-syntax
- name: Run markdown code lint
run: uv run poe markdown-code-lint
mypy:
name: Mypy Checks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
extra_args: --config python/.pre-commit-config.yaml --all-files
- name: Run Mypy
env:
GITHUB_BASE_REF: ${{ github.event.pull_request.base.ref || github.base_ref || 'main' }}
run: uv run poe ci-mypy
run: uv run poe mypy
+1 -1
View File
@@ -24,7 +24,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up uv
uses: astral-sh/setup-uv@v7
with:
+2 -2
View File
@@ -24,7 +24,7 @@ jobs:
outputs:
pythonChanges: ${{ steps.filter.outputs.python}}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- uses: dorny/paths-filter@v3
id: filter
with:
@@ -59,7 +59,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
+7 -6
View File
@@ -28,7 +28,7 @@ jobs:
outputs:
pythonChanges: ${{ steps.filter.outputs.python}}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- uses: dorny/paths-filter@v3
id: filter
with:
@@ -75,7 +75,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
@@ -96,7 +96,8 @@ jobs:
uses: ./.github/actions/azure-functions-integration-setup
id: azure-functions-setup
- name: Test with pytest
run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
timeout-minutes: 10
run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
working-directory: ./python
- name: Test core samples
timeout-minutes: 10
@@ -134,7 +135,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
@@ -152,8 +153,8 @@ jobs:
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest
timeout-minutes: 15
run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist loadfile --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
timeout-minutes: 10
run: uv run poe azure-ai-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
working-directory: ./python
- name: Test Azure AI samples
timeout-minutes: 10
+1 -1
View File
@@ -23,7 +23,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
@@ -19,9 +19,9 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Download coverage report
uses: actions/download-artifact@v7
uses: actions/download-artifact@v6
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
run-id: ${{ github.event.workflow_run.id }}
@@ -34,19 +34,12 @@ jobs:
# because the workflow_run event does not have access to the PR number
# The PR number is needed to post the comment on the PR
run: |
if [ ! -s pr_number ]; then
echo "PR number file 'pr_number' is missing or empty"
exit 1
fi
PR_NUMBER=$(head -1 pr_number | tr -dc '0-9')
if [ -z "$PR_NUMBER" ]; then
echo "PR number file 'pr_number' does not contain a valid PR number"
exit 1
fi
echo "PR_NUMBER=$PR_NUMBER" >> "$GITHUB_ENV"
PR_NUMBER=$(cat pr_number)
echo "PR number: $PR_NUMBER"
echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
- name: Pytest coverage comment
id: coverageComment
uses: MishaKav/pytest-coverage-comment@v1.2.0
uses: MishaKav/pytest-coverage-comment@v1.1.59
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
issue-number: ${{ env.PR_NUMBER }}
+2 -6
View File
@@ -9,8 +9,6 @@ on:
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
# Coverage threshold percentage for enforced modules
COVERAGE_THRESHOLD: 85
jobs:
python-tests-coverage:
@@ -22,7 +20,7 @@ jobs:
env:
UV_PYTHON: "3.10"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
# Save the PR number to a file since the workflow_run event
# in the coverage report workflow does not have access to it
- name: Save PR number
@@ -39,10 +37,8 @@ jobs:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run all tests with coverage report
run: uv run poe all-tests-cov --cov-report=xml:python-coverage.xml -q --junitxml=pytest.xml
- name: Check coverage threshold
run: python ${{ github.workspace }}/.github/workflows/python-check-coverage.py python-coverage.xml ${{ env.COVERAGE_THRESHOLD }}
- name: Upload coverage report
uses: actions/upload-artifact@v6
uses: actions/upload-artifact@v5
with:
path: |
python/python-coverage.xml
+1 -1
View File
@@ -27,7 +27,7 @@ jobs:
run:
working-directory: python
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
+7 -10
View File
@@ -199,22 +199,20 @@ temp*/
.tmp/
.temp/
agents.md
# AI
.claude/
WARP.md
**/memory-bank/
**/projectBrief.md
**/tmpclaude*
# Azurite storage emulator files
*/__azurite_db_blob__.json*
*/__azurite_db_blob_extent__.json*
*/__azurite_db_queue__.json*
*/__azurite_db_queue_extent__.json*
*/__azurite_db_table__.json*
*/__azurite_db_blob__.json
*/__azurite_db_blob_extent__.json
*/__azurite_db_queue__.json
*/__azurite_db_queue_extent__.json
*/__azurite_db_table__.json
*/__blobstorage__/
*/__queuestorage__/
*/AzuriteConfig
# Azure Functions local settings
local.settings.json
@@ -226,4 +224,3 @@ local.settings.json
# Database files
*.db
python/dotnet-ref
+10 -12
View File
@@ -48,12 +48,10 @@ dotnet add package Microsoft.Agents.AI
- **[Migration from Semantic Kernel](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-semantic-kernel)** - Guide to migrate from Semantic Kernel
- **[Migration from AutoGen](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen)** - Guide to migrate from AutoGen
Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-community-office-hours) or ask questions in our [Discord channel](https://discord.gg/b5zjErwbQM) to get help from the team and other users.
### ✨ **Highlights**
- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
- [Python workflows](./python/samples/03-workflows/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/)
- [Python workflows](./python/samples/getting_started/workflows/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/)
- **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- [Labs directory](./python/packages/lab/)
- **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
@@ -73,11 +71,11 @@ Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-commu
- **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
- [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
- **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- [Python observability](./python/samples/02-agents/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/)
- [Python observability](./python/samples/getting_started/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/)
- **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
- [Python examples](./python/samples/02-agents/providers/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/)
- [Python examples](./python/samples/getting_started/agents/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/)
- **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- [Python middleware](./python/samples/02-agents/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/)
- [Python middleware](./python/samples/getting_started/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/)
### đź’¬ **We want your feedback!**
@@ -108,7 +106,7 @@ async def main():
# api_version=os.environ["AZURE_OPENAI_API_VERSION"],
# api_key=os.environ["AZURE_OPENAI_API_KEY"], # Optional if using AzureCliCredential
credential=AzureCliCredential(), # Optional, if using api_key
).as_agent(
).create_agent(
name="HaikuBot",
instructions="You are an upbeat assistant that writes beautifully.",
)
@@ -131,7 +129,7 @@ using OpenAI;
// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
.GetOpenAIResponseClient("gpt-4o-mini")
.AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
.CreateAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
@@ -150,7 +148,7 @@ var agent = new OpenAIClient(
new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions() { Endpoint = new Uri("https://<resource>.openai.azure.com/openai/v1") })
.GetOpenAIResponseClient("gpt-4o-mini")
.AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
.CreateAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
@@ -159,9 +157,9 @@ Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Fram
### Python
- [Getting Started with Agents](./python/samples/01-get-started): progressive tutorial from hello-world to hosting
- [Agent Concepts](./python/samples/02-agents): deep-dive samples by topic (tools, middleware, providers, etc.)
- [Getting Started with Workflows](./python/samples/03-workflows): workflow creation and integration with agents
- [Getting Started with Agents](./python/samples/getting_started/agents): basic agent creation and tool usage
- [Chat Client Examples](./python/samples/getting_started/chat_client): direct chat client usage patterns
- [Getting Started with Workflows](./python/samples/getting_started/workflows): basic workflow creation and integration with agents
### .NET
+2 -2
View File
@@ -42,9 +42,9 @@ Microsoft Agent Framework relies on existing LLMs. Using the framework retains c
**Framework-Specific Limitations**:
- **Platform Requirements**: Python 3.10+ required, specific .NET versions (.NET 8.0, 9.0, 10.0, netstandard2.0, net472)
- **Platform Requirements**: Python 3.10+ required, specific .NET versions (.NET 8.0, 9.0, netstandard2.0, net472)
- **API Dependencies**: Requires proper configuration of LLM provider keys and endpoints
- **Orchestration Features**: Advanced orchestration patterns including GroupChat, Sequential, and Concurrent workflows are now available in both Python and .NET implementations. See the respective language documentation for examples.
- **Orchestration Features**: Advanced orchestration patterns like GroupChat, Sequential, and Concurrent orchestrations are "coming soon" for Python implementation
- **Privacy and Data Protection**: The framework allows for human participation in conversations between agents. It is important to ensure that user data and conversations are protected and that developers use appropriate measures to safeguard privacy.
- **Accountability and Transparency**: The framework involves multiple agents conversing and collaborating, it is important to establish clear accountability and transparency mechanisms. Users should be able to understand and trace the decision-making process of the agents involved in order to ensure accountability and address any potential issues or biases.
- **Security & unintended consequences**: The use of multi-agent conversations and automation in complex tasks may have unintended consequences. Especially, allowing agents to make changes in external environments through tool calls or function execution could pose significant risks. Developers should carefully consider the potential risks and ensure that appropriate safeguards are in place to prevent harm or negative outcomes, including keeping a human in the loop for decision making.
-3
View File
@@ -1,3 +0,0 @@
# Declarative Agents
This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/02-agents/declarative/).
-25
View File
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: =Env.AZURE_OPENAI_DEPLOYMENT_NAME
provider: AzureOpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Assistants as the type in your response.
model:
id: gpt-4o-mini
provider: AzureOpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-25
View File
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: gpt-4o-mini
provider: AzureOpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Responses as the type in your response.
model:
id: gpt-4o-mini
provider: AzureOpenAI
apiType: Responses
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-18
View File
@@ -1,18 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format.
model:
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
-29
View File
@@ -1,29 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions using the tools provided.
model:
options:
temperature: 0.9
topP: 0.95
allowMultipleToolCalls: true
chatToolMode: auto
tools:
- kind: function
name: GetWeather
description: Get the weather for a given location.
bindings:
get_weather: get_weather
parameters:
properties:
location:
kind: string
description: The city and state, e.g. San Francisco, CA
required: true
unit:
kind: string
description: The unit of temperature. Possible values are 'celsius' and 'fahrenheit'.
required: false
enum:
- celsius
- fahrenheit
-22
View File
@@ -1,22 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format.
model:
id: gpt-4.1-mini
options:
temperature: 0.9
topP: 0.95
connection:
kind: Remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
@@ -1,21 +0,0 @@
kind: Prompt
name: MicrosoftLearnAgent
description: Microsoft Learn Agent
instructions: You answer questions by searching the Microsoft Learn content only.
model:
id: =Env.AZURE_FOUNDRY_PROJECT_MODEL_ID
options:
temperature: 0.9
topP: 0.95
connection:
kind: remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
tools:
- kind: mcp
name: microsoft_learn
description: Get information from Microsoft Learn.
url: https://learn.microsoft.com/api/mcp
approvalMode:
kind: never
allowedTools:
- microsoft_docs_search
@@ -1,22 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format.
model:
id: =Env.AZURE_FOUNDRY_PROJECT_MODEL_ID
options:
temperature: 0.9
topP: 0.95
connection:
kind: remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
-28
View File
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: =Env.OPENAI_MODEL
provider: OpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
connection:
kind: key
key: =Env.OPENAI_API_KEY
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Assistants as the type in your response.
model:
id: gpt-4.1-mini
provider: OpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
connection:
kind: ApiKey
key: =Env.OPENAI_API_KEY
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-28
View File
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: gpt-4.1-mini
provider: OpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
connection:
kind: ApiKey
key: =Env.OPENAI_API_KEY
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-28
View File
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format. You must include Responses as the type in your response.
model:
id: gpt-4.1-mini
provider: OpenAI
apiType: Responses
options:
temperature: 0.9
topP: 0.95
connection:
kind: key
apiKey: =Env.OPENAI_APIKEY
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
+22 -22
View File
@@ -64,7 +64,7 @@ Approaches observed from the compared SDKs:
| AutoGen | **Approach 1** Separates messages into Agent-Agent (maps to Primary) and Internal (maps to Secondary) and these are returned as separate properties on the agent response object. See [types of messages](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/messages.html#types-of-messages) and [Response](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.Response) | **Approach 2** Returns a stream of internal events and the last item is a Response object. See [ChatAgent.on_messages_stream](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.ChatAgent.on_messages_stream) |
| OpenAI Agent SDK | **Approach 1** Separates new_items (Primary+Secondary) from final output (Primary) as separate properties on the [RunResult](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L39) | **Approach 1** Similar to non-streaming, has a way of streaming updates via a method on the response object which includes all data, and then a separate final output property on the response object which is populated only when the run is complete. See [RunResultStreaming](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L136) |
| Google ADK | **Approach 2** [Emits events](https://google.github.io/adk-docs/runtime/#step-by-step-breakdown) with [FinalResponse](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L232) true (Primary) / false (Secondary) and callers have to filter out those with false to get just the final response message | **Approach 2** Similar to non-streaming except [events](https://google.github.io/adk-docs/runtime/#streaming-vs-non-streaming-output-partialtrue) are emitted with [Partial](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L133) true to indicate that they are streaming messages. A final non partial event is also emitted. |
| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.stream_async) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent_result.AgentResult) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent.Agent.stream_async) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
| LangGraph | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
| Agno | **Combination of various approaches** Returns a [RunResponse](https://docs.agno.com/reference/agents/run-response) object with text content, messages (essentially chat history including inputs and instructions), reasoning and thinking text properties. Secondary events could potentially be extracted from messages. | **Approach 2** Returns [RunResponseEvent](https://docs.agno.com/reference/agents/run-response#runresponseevent-types-and-attributes) objects including tool call, memory update, etc, information, where the [RunResponseCompletedEvent](https://docs.agno.com/reference/agents/run-response#runresponsecompletedevent) has similar properties to RunResponse|
| A2A | **Approach 3** Returns a [Task or Message](https://a2aproject.github.io/A2A/latest/specification/#71-messagesend) where the message is the final result (Primary) and task is a reference to a long running process. | **Approach 2** Returns a [stream](https://a2aproject.github.io/A2A/latest/specification/#72-messagestream) that contains task updates (Secondary) and a final message (Primary) |
@@ -163,8 +163,8 @@ foreach (var update in response.Messages)
### Option 2 Run: Container with Primary and Secondary Properties, RunStreaming: Stream of Primary + Secondary
Run returns a new response type that has separate properties for the Primary Content and the Secondary Updates leading up to it.
The Primary content is available in the `AgentResponse.Messages` property while Secondary updates are in a new `AgentResponse.Updates` property.
`AgentResponse.Text` returns the Primary content text.
The Primary content is available in the `AgentRunResponse.Messages` property while Secondary updates are in a new `AgentRunResponse.Updates` property.
`AgentRunResponse.Text` returns the Primary content text.
Since streaming would still need to return an `IAsyncEnumerable` of updates, the design would differ from non-streaming.
With non-streaming Primary and Secondary content is split into separate lists, while with streaming it's combined in one stream.
@@ -232,24 +232,24 @@ await foreach (var update in responses)
```csharp
class Agent
{
public abstract Task<AgentResponse> RunAsync(
public abstract Task<AgentRunResponse> RunAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
}
class AgentResponse : ChatResponse
class AgentRunResponse : ChatResponse
{
}
public class AgentResponseUpdate : ChatResponseUpdate
public class AgentRunResponseUpdate : ChatResponseUpdate
{
}
```
@@ -265,20 +265,20 @@ The new types could also exclude properties that make less sense for agents, lik
```csharp
class Agent
{
public abstract Task<AgentResponse> RunAsync(
public abstract Task<AgentRunResponse> RunAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
}
class AgentResponse // Compare with ChatResponse
class AgentRunResponse // Compare with ChatResponse
{
public string Text { get; } // Aggregation of TextContent from messages.
@@ -294,12 +294,12 @@ class AgentResponse // Compare with ChatResponse
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
}
// Not Included in AgentResponse compared to ChatResponse
// Not Included in AgentRunResponse compared to ChatResponse
public ChatFinishReason? FinishReason { get; set; }
public string? ConversationId { get; set; }
public string? ModelId { get; set; }
public class AgentResponseUpdate // Compare with ChatResponseUpdate
public class AgentRunResponseUpdate // Compare with ChatResponseUpdate
{
public string Text { get; } // Aggregation of TextContent from Contents.
@@ -317,7 +317,7 @@ public class AgentResponseUpdate // Compare with ChatResponseUpdate
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
}
// Not Included in AgentResponseUpdate compared to ChatResponseUpdate
// Not Included in AgentRunResponseUpdate compared to ChatResponseUpdate
public ChatFinishReason? FinishReason { get; set; }
public string? ConversationId { get; set; }
public string? ModelId { get; set; }
@@ -360,7 +360,7 @@ public class ChatFinishReason
### Option 2: Add another property on responses for AgentRun
```csharp
class AgentResponse
class AgentRunResponse
{
...
public AgentRun RunReference { get; set; } // Reference to long running process
@@ -368,7 +368,7 @@ class AgentResponse
}
public class AgentResponseUpdate
public class AgentRunResponseUpdate
{
...
public AgentRun RunReference { get; set; } // Reference to long running process
@@ -424,7 +424,7 @@ Note that where an agent doesn't support structured output, it may also be possi
See [Structured Outputs Support](#structured-outputs-support) for a comparison on what other agent frameworks and protocols support.
To support a good user experience for structured outputs, I'm proposing that we follow the pattern used by MEAI.
We would add a generic version of `AgentResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
We would add a generic version of `AgentRunResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
This would be coupled with generic overload extension methods for Run that automatically builds a schema from the supplied type and updates
the run options.
@@ -438,14 +438,14 @@ class Movie
public int ReleaseYear { get; set; }
}
AgentResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
AgentRunResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
Movie[] movies = response.Result
```
If we only support requesting a schema at agent creation time or where an agent has a built in schema, the following would be the preferred approach:
```csharp
AgentResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
AgentRunResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
Movie[] movies = response.TryParseStructuredOutput<Movie[]>();
```
@@ -463,7 +463,7 @@ Option 2 chosen so that we can vary Agent responses independently of Chat Client
### StructuredOutputs Decision
We will not support structured output per run request, but individual agents are free to allow this on the concrete implementation or at construction time.
We will however add support for easily extracting a structured output type from the `AgentResponse`.
We will however add support for easily extracting a structured output type from the `AgentRunResponse`.
## Addendum 1: AIContext Derived Types for different response types / Gap Analysis (Work in progress)
@@ -495,8 +495,8 @@ We need to decide what AIContent types, each agent response type will be mapped
| SDK | Structured Outputs support |
|-|-|
| AutoGen | **Approach 1** Supports [configuring an agent](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html#structured-output) at agent creation. |
| Google ADK | **Approach 1** Both [input and output schemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.structured_output) |
| Google ADK | **Approach 1** Both [input and output shemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent.Agent.structured_output) |
| LangGraph | **Approach 1** Supports [configuring an agent](https://langchain-ai.github.io/langgraph/agents/agents/?h=structured#6-configure-structured-output) at agent construction time, and a [structured response](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) can be retrieved as a special property on the agent response |
| Agno | **Approach 1** Supports [configuring an agent](https://docs.agno.com/examples/getting-started/structured-output) at agent construction time |
| A2A | **Informal Approach 2** Doesn't formally support schema negotiation, but [hints can be provided via metadata](https://a2a-protocol.org/latest/specification/#97-structured-data-exchange-requesting-and-providing-json) at invocation time |
@@ -508,7 +508,7 @@ We need to decide what AIContent types, each agent response type will be mapped
|-|-|
| AutoGen | Supports a [stop reason](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.TaskResult.stop_reason) which is a freeform text string |
| Google ADK | [No equivalent present](https://github.com/google/adk-python/blob/main/src/google/adk/events/event.py) |
| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/latest/documentation/docs/api-reference/python/types/event_loop/#strands.types.event_loop.StopReason) property on the [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) class with options that are tied closely to LLM operations. |
| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/latest/api-reference/types/#strands.types.event_loop.StopReason) property on the [AgentResult](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent_result.AgentResult) class with options that are tied closely to LLM operations. |
| LangGraph | No equivalent present, output contains only [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
| Agno | [No equivalent present](https://docs.agno.com/reference/agents/run-response) |
| A2A | No equivalent present, response only contains a [message](https://a2a-protocol.org/latest/specification/#64-message-object) or [task](https://a2a-protocol.org/latest/specification/#61-task-object). |
@@ -54,7 +54,7 @@ The table below represents the majority of the naming changes discussed in issue
| *Mcp* & *Http* | *MCP* & *HTTP* | accepted | Acronyms should be uppercased in class names, according to PEP 8. | None |
| `agent.run_streaming` | `agent.run_stream` | accepted | Shorter and more closely aligns with AutoGen and Semantic Kernel names for the same methods. | None |
| `workflow.run_streaming` | `workflow.run_stream` | accepted | In sync with `agent.run_stream` and shorter and more closely aligns with AutoGen and Semantic Kernel names for the same methods. | None |
| AgentResponse & AgentResponseUpdate | AgentResponse & AgentResponseUpdate | rejected | Rejected, because it is the response to a run invocation and AgentResponse is too generic. | None |
| AgentRunResponse & AgentRunResponseUpdate | AgentResponse & AgentResponseUpdate | rejected | Rejected, because it is the response to a run invocation and AgentResponse is too generic. | None |
| *Content | * | rejected | Rejected other content type renames (removing `Content` suffix) because it would reduce clarity and discoverability. | Item was also considered, but rejected as it is very similar to Content, but would be inconsistent with dotnet. |
| ChatResponse & ChatResponseUpdate | Response & ResponseUpdate | rejected | Rejected, because Response is too generic. | None |
+6 -6
View File
@@ -161,11 +161,11 @@ while (response.ApprovalRequests.Count > 0)
response = await agent.RunAsync(messages, thread);
}
class AgentResponse
class AgentRunResponse
{
...
// A new property on AgentResponse to aggregate the ApprovalRequestContent items from
// A new property on AgentRunResponse to aggregate the ApprovalRequestContent items from
// the response messages (Similar to the Text property).
public IEnumerable<ApprovalRequestContent> ApprovalRequests { get; set; }
@@ -251,11 +251,11 @@ while (response.UserInputRequests.Any())
response = await agent.RunAsync(messages, thread);
}
class AgentResponse
class AgentRunResponse
{
...
// A new property on AgentResponse to aggregate the UserInputRequestContent items from
// A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
// the response messages (Similar to the Text property).
public IReadOnlyList<UserInputRequestContent> UserInputRequests { get; set; }
@@ -366,11 +366,11 @@ while (response.UserInputRequests.Any())
response = await agent.RunAsync(messages, thread);
}
class AgentResponse
class AgentRunResponse
{
...
// A new property on AgentResponse to aggregate the UserInputRequestContent items from
// A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
// the response messages (Similar to the Text property).
public IEnumerable<UserInputRequestContent> UserInputRequests { get; set; }
@@ -115,7 +115,7 @@ public class AIAgent
}
}
public async Task<AgentResponse> RunAsync(
public async Task<AgentRunResponse> RunAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
@@ -135,7 +135,7 @@ public class AIAgent
return context.Response ?? throw new InvalidOperationException("Agent execution did not produce a response");
}
protected abstract Task<AgentResponse> ExecuteCoreLogicAsync(
protected abstract Task<AgentRunResponse> ExecuteCoreLogicAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread,
AgentRunOptions? options,
@@ -190,7 +190,7 @@ internal sealed class GuardrailCallbackAgent : DelegatingAIAgent
public GuardrailCallbackAgent(AIAgent innerAgent) : base(innerAgent) { }
public override async Task<AgentResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
var filteredMessages = this.FilterMessages(messages);
Console.WriteLine($"Guardrail Middleware - Filtered messages: {new ChatResponse(filteredMessages).Text}");
@@ -202,14 +202,14 @@ internal sealed class GuardrailCallbackAgent : DelegatingAIAgent
return response;
}
public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
{
var filteredMessages = this.FilterMessages(messages);
await foreach (var update in this.InnerAgent.RunStreamingAsync(filteredMessages, thread, options, cancellationToken))
{
if (update.Text != null)
{
yield return new AgentResponseUpdate(update.Role, this.FilterContent(update.Text));
yield return new AgentRunResponseUpdate(update.Role, this.FilterContent(update.Text));
}
else
{
@@ -252,7 +252,7 @@ internal sealed class RunningCallbackHandlerAgent : DelegatingAIAgent
this._func = func;
}
public override async Task<AgentResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
var context = new AgentInvokeCallbackContext(this, messages, thread, options, isStreaming: false, cancellationToken);
@@ -469,7 +469,7 @@ public sealed class CallbackEnabledAgent : DelegatingAIAgent
this._callbacksProcessor = callbackMiddlewareProcessor ?? new();
}
public override async Task<AgentResponse> RunAsync(
public override async Task<AgentRunResponse> RunAsync(
IEnumerable<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
@@ -541,7 +541,7 @@ public abstract class AgentContext
public class AgentRunContext : AgentContext
{
public IList<ChatMessage> Messages { get; set; }
public AgentResponse? Response { get; set; }
public AgentRunResponse? Response { get; set; }
public AgentThread? Thread { get; }
public AgentRunContext(AIAgent agent, IList<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options)
@@ -687,7 +687,7 @@ This section considers different options for exposing the `RunId`, `Status`, and
#### 4.1. As AIContent
The `AsyncRunContent` class will represent a long-running operation initiated and managed by an agent/LLM.
Items of this content type will be returned in a chat message as part of the `AgentResponse` or `ChatResponse`
Items of this content type will be returned in a chat message as part of the `AgentRunResponse` or `ChatResponse`
response to represent the long-running operation.
The `AsyncRunContent` class has two properties: `RunId` and `Status`. The `RunId` identifies the
@@ -1162,29 +1162,29 @@ For cancellation and deletion of long-running operations, new methods will be ad
public abstract class AIAgent
{
// Existing methods...
public Task<AgentResponse> RunAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
public IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
public Task<AgentRunResponse> RunAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
public IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
// New methods for uncommon operations
public virtual Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
public virtual Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
{
return Task.FromResult<AgentResponse?>(null);
return Task.FromResult<AgentRunResponse?>(null);
}
public virtual Task<AgentResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
public virtual Task<AgentRunResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
{
return Task.FromResult<AgentResponse?>(null);
return Task.FromResult<AgentRunResponse?>(null);
}
}
// Agent that supports update and cancellation
public class CustomAgent : AIAgent
{
public override async Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
public override async Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
{
var response = await this._client.CancelRunAsync(id, options?.Thread?.ConversationId);
return ConvertToAgentResponse(response);
return ConvertToAgentRunResponse(response);
}
// No overload for DeleteRunAsync as it's not supported by the underlying API
@@ -1195,7 +1195,7 @@ AIAgent agent = new CustomAgent();
AgentThread thread = agent.GetNewThread();
AgentResponse response = await agent.RunAsync("What is the capital of France?");
AgentRunResponse response = await agent.RunAsync("What is the capital of France?");
response = await agent.CancelRunAsync(response.ResponseId, new AgentCancelRunOptions { Thread = thread });
```
@@ -1251,10 +1251,10 @@ public class AgentRunOptions
AIAgent agent = ...; // Get an instance of an AIAgent
// Start a long-running execution for the prompt if supported by the underlying API
AgentResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });
AgentRunResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });
// Start a quick prompt
AgentResponse response = await agent.RunAsync("<prompt>");
AgentRunResponse response = await agent.RunAsync("<prompt>");
```
**Pros:**
@@ -1279,7 +1279,7 @@ Below are the details of the option selected for chat clients that is also selec
#### 3.1 Continuation Token of a Custom Type
This option suggests using `ContinuationToken` to encapsulate all properties representing a long-running operation. The continuation token will be returned by agents in the
`ContinuationToken` property of the `AgentResponse` and `AgentResponseUpdate` responses to indicate that the response is part of a long-running operation. A null value
`ContinuationToken` property of the `AgentRunResponse` and `AgentRunResponseUpdate` responses to indicate that the response is part of a long-running operation. A null value
of the property will indicate that the response is not part of a long-running operation or the long-running operation has been completed. Callers will set the token in the
`ContinuationToken` property of the `AgentRunOptions` class in follow-up calls to the `Run{Streaming}Async` methods to indicate that they want to "continue" the long-running
operation identified by the token.
@@ -1313,18 +1313,18 @@ public class AgentRunOptions
public ResponseContinuationToken? ContinuationToken { get; set; }
}
public class AgentResponse
public class AgentRunResponse
{
public ResponseContinuationToken? ContinuationToken { get; }
}
public class AgentResponseUpdate
public class AgentRunResponseUpdate
{
public ResponseContinuationToken? ContinuationToken { get; }
}
// Usage example
AgentResponse response = await agent.RunAsync("What is the capital of France?");
AgentRunResponse response = await agent.RunAsync("What is the capital of France?");
AgentRunOptions options = new() { ContinuationToken = response.ContinuationToken };
+2 -2
View File
@@ -36,7 +36,7 @@ Chosen option: "Current approach with internal event types and framework-native
- Protects consumers from protocol changes by keeping AG-UI events internal
- Maintains framework abstractions through conversion at boundaries
- Uses existing framework types (AgentResponseUpdate, ChatMessage) for public API
- Uses existing framework types (AgentRunResponseUpdate, ChatMessage) for public API
- Focuses on core text streaming functionality
- Leverages existing properties (ConversationId, ResponseId, ErrorContent) instead of custom types
- Provides bidirectional client and server support
@@ -69,7 +69,7 @@ Chosen option: "Current approach with internal event types and framework-native
3. **Agent Factory Pattern** - `MapAGUIAgent` uses factory function `(messages) => AIAgent` to allow request-specific agent configuration supporting multi-tenancy
4. **Bidirectional Conversion Architecture** - Symmetric conversion logic in shared namespace compiled into both packages for server (`AgentResponseUpdate` → AG-UI events) and client (AG-UI events → `AgentResponseUpdate`)
4. **Bidirectional Conversion Architecture** - Symmetric conversion logic in shared namespace compiled into both packages for server (`AgentRunResponseUpdate` → AG-UI events) and client (AG-UI events → `AgentRunResponseUpdate`)
5. **Thread Management** - `AGUIAgentThread` stores only `ThreadId` with thread ID communicated via `ConversationId`; applications manage persistence for parity with other implementations and to be compliant with the protocol. Future extensions will support having the server manage the conversation.
-368
View File
@@ -1,368 +0,0 @@
---
status: proposed
contact: dmytrostruk
date: 2025-12-12
deciders: dmytrostruk, markwallace-microsoft, eavanvalkenburg, giles17
---
# Create/Get Agent API
## Context and Problem Statement
There is a misalignment between the create/get agent API in the .NET and Python implementations.
In .NET, the `CreateAIAgent` method can create either a local instance of an agent or a remote instance if the backend provider supports it. For remote agents, once the agent is created, you can retrieve an existing remote agent by using the `GetAIAgent` method. If a backend provider doesn't support remote agents, `CreateAIAgent` just initializes a new local agent instance and `GetAIAgent` is not available. There is also a `BuildAIAgent` method, which is an extension for the `ChatClientBuilder` class from `Microsoft.Extensions.AI`. It builds pipelines of `IChatClient` instances with an `IServiceProvider`. This functionality does not exist in Python, so `BuildAIAgent` is out of scope.
In Python, there is only one `create_agent` method, which always creates a local instance of the agent. If the backend provider supports remote agents, the remote agent is created only on the first `agent.run()` invocation.
Below is a short summary of different providers and their APIs in .NET:
| Package | Method | Behavior | Python support |
|---|---|---|---|
| Microsoft.Agents.AI | `CreateAIAgent` (based on `IChatClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
| Microsoft.Agents.AI.Anthropic | `CreateAIAgent` (based on `IBetaService` and `IAnthropicClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`AnthropicClient` inherits `BaseChatClient`, which exposes `create_agent`). |
| Microsoft.Agents.AI.AzureAI (V2) | `GetAIAgent` (based on `AIProjectClient` with `AgentReference`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
| Microsoft.Agents.AI.AzureAI (V2) | `GetAIAgent`/`GetAIAgentAsync` (with `Name`/`ChatClientAgentOptions`) | Fetches `AgentRecord` via HTTP, then creates a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.AzureAI (V2) | `CreateAIAgent`/`CreateAIAgentAsync` (based on `AIProjectClient`) | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `GetAIAgent` (based on `PersistentAgentsClient` with `PersistentAgent`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `GetAIAgent`/`GetAIAgentAsync` (with `AgentId`) | Fetches `PersistentAgent` via HTTP, then creates a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `CreateAIAgent`/`CreateAIAgentAsync` | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.OpenAI | `GetAIAgent` (based on `AssistantClient` with `Assistant`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
| Microsoft.Agents.AI.OpenAI | `GetAIAgent`/`GetAIAgentAsync` (with `AgentId`) | Fetches `Assistant` via HTTP, then creates a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.OpenAI | `CreateAIAgent`/`CreateAIAgentAsync` (based on `AssistantClient`) | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
| Microsoft.Agents.AI.OpenAI | `CreateAIAgent` (based on `ChatClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
| Microsoft.Agents.AI.OpenAI | `CreateAIAgent` (based on `OpenAIResponseClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
Another difference between Python and .NET implementation is that in .NET `CreateAIAgent`/`GetAIAgent` methods are implemented as extension methods based on underlying SDK client, like `AIProjectClient` from Azure AI or `AssistantClient` from OpenAI:
```csharp
// Definition
public static ChatClientAgent CreateAIAgent(
this AIProjectClient aiProjectClient,
string name,
string model,
string instructions,
string? description = null,
IList<AITool>? tools = null,
Func<IChatClient, IChatClient>? clientFactory = null,
IServiceProvider? services = null,
CancellationToken cancellationToken = default)
{ }
// Usage
AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential()); // Initialization of underlying SDK client
var newAgent = await aiProjectClient.CreateAIAgentAsync(name: AgentName, model: deploymentName, instructions: AgentInstructions, tools: [tool]); // ChatClientAgent creation from underlying SDK client
// Alternative usage (same as extension method, just explicit syntax)
var newAgent = await AzureAIProjectChatClientExtensions.CreateAIAgentAsync(
aiProjectClient,
name: AgentName,
model: deploymentName,
instructions: AgentInstructions,
tools: [tool]);
```
Python doesn't support extension methods. Currently `create_agent` method is defined on `BaseChatClient`, but this method only creates a local instance of `ChatAgent` and it can't create remote agents for providers that support it for a couple of reasons:
- It's defined as non-async.
- `BaseChatClient` implementation is stateful for providers like Azure AI or OpenAI Assistants. The implementation stores agent/assistant metadata like `AgentId` and `AgentName`, so currently it's not possible to create different instances of `ChatAgent` from a single `BaseChatClient` in case if the implementation is stateful.
## Decision Drivers
- API should be aligned between .NET and Python.
- API should be intuitive and consistent between backend providers in .NET and Python.
## Considered Options
Add missing implementations on the Python side. This should include the following:
### agent-framework-azure-ai (both V1 and V2)
- Add a `get_agent` method that accepts an underlying SDK agent instance and creates a local instance of `ChatAgent`.
- Add a `get_agent` method that accepts an agent identifier, performs an additional HTTP request to fetch agent data, and then creates a local instance of `ChatAgent`.
- Override the `create_agent` method from `BaseChatClient` to create a remote agent instance and wrap it into a local `ChatAgent`.
.NET:
```csharp
var agent1 = new AIProjectClient(...).GetAIAgent(agentInstanceFromSdkType); // Creates a local ChatClientAgent instance from Azure.AI.Projects.OpenAI.AgentReference
var agent2 = new AIProjectClient(...).GetAIAgent(agentName); // Fetches agent data, creates a local ChatClientAgent instance
var agent3 = new AIProjectClient(...).CreateAIAgent(...); // Creates a remote agent, returns a local ChatClientAgent instance
```
### agent-framework-core (OpenAI Assistants)
- Add a `get_agent` method that accepts an underlying SDK agent instance and creates a local instance of `ChatAgent`.
- Add a `get_agent` method that accepts an agent name, performs an additional HTTP request to fetch agent data, and then creates a local instance of `ChatAgent`.
- Override the `create_agent` method from `BaseChatClient` to create a remote agent instance and wrap it into a local `ChatAgent`.
.NET:
```csharp
var agent1 = new AssistantClient(...).GetAIAgent(agentInstanceFromSdkType); // Creates a local ChatClientAgent instance from OpenAI.Assistants.Assistant
var agent2 = new AssistantClient(...).GetAIAgent(agentId); // Fetches agent data, creates a local ChatClientAgent instance
var agent3 = new AssistantClient(...).CreateAIAgent(...); // Creates a remote agent, returns a local ChatClientAgent instance
```
### Possible Python implementations
Methods like `create_agent` and `get_agent` should be implemented separately or defined on some stateless component that will allow to create multiple agents from the same instance/place.
Possible options:
#### Option 1: Module-level functions
Implement free functions in the provider package that accept the underlying SDK client as the first argument (similar to .NET extension methods, but expressed in Python).
Example:
```python
from agent_framework.azure import create_agent, get_agent
ai_project_client = AIProjectClient(...)
# Creates a remote agent first, then returns a local ChatAgent wrapper
created_agent = await create_agent(
ai_project_client,
name="",
instructions="",
tools=[tool],
)
# Gets an existing remote agent and returns a local ChatAgent wrapper
first_agent = await get_agent(ai_project_client, agent_id=agent_id)
# Wraps an SDK agent instance (no extra HTTP call)
second_agent = get_agent(ai_project_client, agent_reference)
```
Pros:
- Naturally supports async `create_agent` / `get_agent`.
- Supports multiple agents per SDK client.
- Closest conceptual match to .NET extension methods while staying Pythonic.
Cons:
- Discoverability is lower (users need to know where the functions live).
- Verbose when creating multiple agents (client must be passed every time):
```python
agent1 = await azure_agents.create_agent(client, name="Agent1", ...)
agent2 = await azure_agents.create_agent(client, name="Agent2", ...)
```
#### Option 2: Provider object
Introduce a dedicated provider type that is constructed from the underlying SDK client, and exposes async `create_agent` / `get_agent` methods.
Example:
```python
from agent_framework.azure import AzureAIAgentProvider
ai_project_client = AIProjectClient(...)
provider = AzureAIAgentProvider(ai_project_client)
agent = await provider.create_agent(
name="",
instructions="",
tools=[tool],
)
agent = await provider.get_agent(agent_id=agent_id)
agent = provider.get_agent(agent_reference=agent_reference)
```
Pros:
- High discoverability and clear grouping of related behavior.
- Keeps SDK clients unchanged and supports multiple agents per SDK client.
- Concise when creating multiple agents (client passed once):
```python
provider = AzureAIAgentProvider(ai_project_client)
agent1 = await provider.create_agent(name="Agent1", ...)
agent2 = await provider.create_agent(name="Agent2", ...)
```
Cons:
- Adds a new public concept/type for users to learn.
#### Option 3: Inheritance (SDK client subclass)
Create a subclass of the underlying SDK client and add `create_agent` / `get_agent` methods.
Example:
```python
class ExtendedAIProjectClient(AIProjectClient):
async def create_agent(self, *, name: str, model: str, instructions: str, **kwargs) -> ChatAgent:
...
async def get_agent(self, *, agent_id: str | None = None, sdk_agent=None, **kwargs) -> ChatAgent:
...
client = ExtendedAIProjectClient(...)
agent = await client.create_agent(name="", instructions="")
```
Pros:
- Discoverable and ergonomic call sites.
- Mirrors the .NET “methods on the client” feeling.
Cons:
- Many SDK clients are not designed for inheritance; SDK upgrades can break subclasses.
- Users must opt into subclass everywhere.
- Typing/initialization can be tricky if the SDK client has non-trivial constructors.
#### Option 4: Monkey patching
Attach `create_agent` / `get_agent` methods to an SDK client class (or instance) at runtime.
Example:
```python
def _create_agent(self, *, name: str, model: str, instructions: str, **kwargs) -> ChatAgent:
...
AIProjectClient.create_agent = _create_agent # monkey patch
```
Pros:
- Produces “extension method-like” call sites without wrappers or subclasses.
Cons:
- Fragile across SDK updates and difficult to type-check.
- Surprising behavior (global side effects), potential conflicts across packages.
- Harder to support/debug, especially in larger apps and test suites.
## Decision Outcome
Implement `create_agent`/`get_agent`/`as_agent` API via **Option 2: Provider object**.
### Rationale
| Aspect | Option 1 (Functions) | Option 2 (Provider) |
|--------|----------------------|---------------------|
| Multiple implementations | One package may contain V1, V2, and other agent types. Function names like `create_agent` become ambiguous - which agent type does it create? | Each provider class is explicit: `AzureAIAgentsProvider` vs `AzureAIProjectAgentProvider` |
| Discoverability | Users must know to import specific functions from the package | IDE autocomplete on provider instance shows all available methods |
| Client reuse | SDK client must be passed to every function call: `create_agent(client, ...)`, `get_agent(client, ...)` | SDK client passed once at construction: `provider = Provider(client)` |
**Option 1 example:**
```python
from agent_framework.azure import create_agent, get_agent
agent1 = await create_agent(client, name="Agent1", ...) # Which agent type, V1 or V2?
agent2 = await create_agent(client, name="Agent2", ...) # Repetitive client passing
```
**Option 2 example:**
```python
from agent_framework.azure import AzureAIProjectAgentProvider
provider = AzureAIProjectAgentProvider(client) # Clear which service, client passed once
agent1 = await provider.create_agent(name="Agent1", ...)
agent2 = await provider.create_agent(name="Agent2", ...)
```
### Method Naming
| Operation | Python | .NET | Async |
|-----------|--------|------|-------|
| Create on service | `create_agent()` | `CreateAIAgent()` | Yes |
| Get from service | `get_agent(id=...)` | `GetAIAgent(agentId)` | Yes |
| Wrap SDK object | `as_agent(reference)` | `AsAIAgent(agentInstance)` | No |
The method names (`create_agent`, `get_agent`) do not explicitly mention "service" or "remote" because:
- In Python, the provider class name explicitly identifies the service (`AzureAIAgentsProvider`, `OpenAIAssistantProvider`), making additional qualifiers in method names redundant.
- In .NET, these are extension methods on `AIProjectClient` or `AssistantClient`, which already imply service operations.
### Provider Class Naming
| Package | Provider Class | SDK Client | Service |
|---------|---------------|------------|---------|
| `agent_framework.azure` | `AzureAIProjectAgentProvider` | `AIProjectClient` | Azure AI Agent Service, based on Responses API (V2) |
| `agent_framework.azure` | `AzureAIAgentsProvider` | `AgentsClient` | Azure AI Agent Service (V1) |
| `agent_framework.openai` | `OpenAIAssistantProvider` | `AsyncOpenAI` | OpenAI Assistants API |
> **Note:** Azure AI naming is temporary. Final naming will be updated according to Azure AI / Microsoft Foundry renaming decisions.
### Usage Examples
#### Azure AI Agent Service V2 (based on Responses API)
```python
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects import AIProjectClient
client = AIProjectClient(endpoint, credential)
provider = AzureAIProjectAgentProvider(client)
# Create new agent on service
agent = await provider.create_agent(name="MyAgent", model="gpt-4", instructions="...")
# Get existing agent by name
agent = await provider.get_agent(agent_name="MyAgent")
# Wrap already-fetched SDK object (no HTTP calls)
agent_ref = await client.agents.get("MyAgent")
agent = provider.as_agent(agent_ref)
```
#### Azure AI Persistent Agents V1
```python
from agent_framework.azure import AzureAIAgentsProvider
from azure.ai.agents import AgentsClient
client = AgentsClient(endpoint, credential)
provider = AzureAIAgentsProvider(client)
agent = await provider.create_agent(name="MyAgent", model="gpt-4", instructions="...")
agent = await provider.get_agent(agent_id="persistent-agent-456")
agent = provider.as_agent(persistent_agent)
```
#### OpenAI Assistants
```python
from agent_framework.openai import OpenAIAssistantProvider
from openai import OpenAI
client = OpenAI()
provider = OpenAIAssistantProvider(client)
agent = await provider.create_agent(name="MyAssistant", model="gpt-4", instructions="...")
agent = await provider.get_agent(assistant_id="asst_123")
agent = provider.as_agent(assistant)
```
#### Local-Only Agents (No Provider)
Current method `create_agent` (python) / `CreateAIAgent` (.NET) can be renamed to `as_agent` (python) / `AsAIAgent` (.NET) to emphasize the conversion logic rather than creation/initialization logic and to avoid collision with `create_agent` method for remote calls.
```python
from agent_framework import ChatAgent
from agent_framework.openai import OpenAIChatClient
# Convert chat client to ChatAgent (no remote service involved)
client = OpenAIChatClient(model="gpt-4")
agent = client.as_agent(name="LocalAgent", instructions="...") # instead of create_agent
```
### Adding New Agent Types
Python:
1. Create provider class in appropriate package.
2. Implement `create_agent`, `get_agent`, `as_agent` as applicable.
.NET:
1. Create static class for extension methods.
2. Implement `CreateAIAgentAsync`, `GetAIAgentAsync`, `AsAIAgent` as applicable.
@@ -1,129 +0,0 @@
---
# These are optional elements. Feel free to remove any of them.
status: proposed
contact: eavanvalkenburg
date: 2026-01-08
deciders: eavanvalkenburg, markwallace-microsoft, sphenry, alliscode, johanst, brettcannon
consulted: taochenosu, moonbox3, dmytrostruk, giles17
---
# Leveraging TypedDict and Generic Options in Python Chat Clients
## Context and Problem Statement
The Agent Framework Python SDK provides multiple chat client implementations for different providers (OpenAI, Anthropic, Azure AI, Bedrock, Ollama, etc.). Each provider has unique configuration options beyond the common parameters defined in `ChatOptions`. Currently, developers using these clients lack type safety and IDE autocompletion for provider-specific options, leading to runtime errors and a poor developer experience.
How can we provide type-safe, discoverable options for each chat client while maintaining a consistent API across all implementations?
## Decision Drivers
- **Type Safety**: Developers should get compile-time/static analysis errors when using invalid options
- **IDE Support**: Full autocompletion and inline documentation for all available options
- **Extensibility**: Users should be able to define custom options that extend provider-specific options
- **Consistency**: All chat clients should follow the same pattern for options handling
- **Provider Flexibility**: Each provider can expose its unique options without affecting the common interface
## Considered Options
- **Option 1: Status Quo - Class `ChatOptions` with `**kwargs`**
- **Option 2: TypedDict with Generic Type Parameters**
### Option 1: Status Quo - Class `ChatOptions` with `**kwargs`
The current approach uses a base `ChatOptions` Class with common parameters, and provider-specific options are passed via `**kwargs` or loosely typed dictionaries.
```python
# Current usage - no type safety for provider-specific options
response = await client.get_response(
messages=messages,
temperature=0.7,
top_k=40,
random=42, # No validation
)
```
**Pros:**
- Simple implementation
- Maximum flexibility
**Cons:**
- No type checking for provider-specific options
- No IDE autocompletion for available options
- Runtime errors for typos or invalid options
- Documentation must be consulted for each provider
### Option 2: TypedDict with Generic Type Parameters (Chosen)
Each chat client is parameterized with a TypeVar bound to a provider-specific `TypedDict` that extends `ChatOptions`. This enables full type safety and IDE support.
```python
# Provider-specific TypedDict
class AnthropicChatOptions(ChatOptions, total=False):
"""Anthropic-specific chat options."""
top_k: int
thinking: ThinkingConfig
# ... other Anthropic-specific options
# Generic chat client
class AnthropicChatClient(ChatClientBase[TAnthropicChatOptions]):
...
client = AnthropicChatClient(...)
# Usage with full type safety
response = await client.get_response(
messages=messages,
options={
"temperature": 0.7,
"top_k": 40,
"random": 42, # fails type checking and IDE would flag this
}
)
# Users can extend for custom options
class MyAnthropicOptions(AnthropicChatOptions, total=False):
custom_field: str
client = AnthropicChatClient[MyAnthropicOptions](...)
# Usage of custom options with full type safety
response = await client.get_response(
messages=messages,
options={
"temperature": 0.7,
"top_k": 40,
"custom_field": "value",
}
)
```
**Pros:**
- Full type safety with static analysis
- IDE autocompletion for all options
- Compile-time error detection
- Self-documenting through type hints
- Users can extend options for their specific needs or advances in models
**Cons:**
- More complex implementation
- Some type: ignore comments needed for TypedDict field overrides
- Minor: Requires TypeVar with default (Python 3.13+ or typing_extensions)
> [NOTE!]
> In .NET this is already achieved through overloads on the `GetResponseAsync` method for each provider-specific options class, e.g., `AnthropicChatOptions`, `OpenAIChatOptions`, etc. So this does not apply to .NET.
### Implementation Details
1. **Base Protocol**: `ChatClientProtocol[TOptions]` is generic over options type, with default set to `ChatOptions` (the new TypedDict)
2. **Provider TypedDicts**: Each provider defines its options extending `ChatOptions`
They can even override fields with type=None to indicate they are not supported.
3. **TypeVar Pattern**: `TProviderOptions = TypeVar("TProviderOptions", bound=TypedDict, default=ProviderChatOptions, contravariant=True)`
4. **Option Translation**: Common options are kept in place,and explicitly documented in the Options class how they are used. (e.g., `user` → `metadata.user_id`) in `_prepare_options` (for Anthropic) to preserve easy use of common options.
## Decision Outcome
Chosen option: **"Option 2: TypedDict with Generic Type Parameters"**, because it provides full type safety, excellent IDE support with autocompletion, and allows users to extend provider-specific options for their use cases. Extended this Generic to ChatAgents in order to also properly type the options used in agent construction and run methods.
See [typed_options.py](../../python/samples/02-agents/typed_options.py) for a complete example demonstrating the usage of typed options with custom extensions.
@@ -1,258 +0,0 @@
---
status: Accepted
contact: eavanvalkenburg
date: 2026-01-06
deciders: markwallace-microsoft, dmytrostruk, taochenosu, alliscode, moonbox3, sphenry
consulted: sergeymenshykh, rbarreto, dmytrostruk, westey-m
informed:
---
# Simplify Python Get Response API into a single method
## Context and Problem Statement
Currently chat clients must implement two separate methods to get responses, one for streaming and one for non-streaming. This adds complexity to the client implementations and increases the maintenance burden. This was likely done because the .NET version cannot do proper typing with a single method, in Python this is possible and this for instance is also how the OpenAI python client works, this would then also make it simpler to work with the Python version because there is only one method to learn about instead of two.
## Implications of this change
### Current Architecture Overview
The current design has **two separate methods** at each layer:
| Layer | Non-streaming | Streaming |
|-------|---------------|-----------|
| **Protocol** | `get_response()` → `ChatResponse` | `get_streaming_response()` → `AsyncIterable[ChatResponseUpdate]` |
| **BaseChatClient** | `get_response()` (public) | `get_streaming_response()` (public) |
| **Implementation** | `_inner_get_response()` (private) | `_inner_get_streaming_response()` (private) |
### Key Usage Areas Identified
#### 1. **ChatAgent** (_agents.py)
- `run()` → calls `self.chat_client.get_response()`
- `run_stream()` → calls `self.chat_client.get_streaming_response()`
These are parallel methods on the agent, so consolidating the client methods would **not break** the agent API. You could keep `agent.run()` and `agent.run_stream()` unchanged while internally calling `get_response(stream=True/False)`.
#### 2. **Function Invocation Decorator** (_tools.py)
This is **the most impacted area**. Currently:
- `_handle_function_calls_response()` decorates `get_response`
- `_handle_function_calls_streaming_response()` decorates `get_streaming_response`
- The `use_function_invocation` class decorator wraps **both methods separately**
**Impact**: The decorator logic is almost identical (~200 lines each) with small differences:
- Non-streaming collects response, returns it
- Streaming yields updates, returns async iterable
With a unified method, you'd need **one decorator** that:
- Checks the `stream` parameter
- Uses `@overload` to determine return type
- Handles both paths with conditional logic
- The new decorator could be applied just on the method, instead of the whole class.
This would **reduce code duplication** but add complexity to a single function.
#### 3. **Observability/Instrumentation** (observability.py)
Same pattern as function invocation:
- `_trace_get_response()` wraps `get_response`
- `_trace_get_streaming_response()` wraps `get_streaming_response`
- `use_instrumentation` decorator applies both
**Impact**: Would need consolidation into a single tracing wrapper.
#### 4. **Chat Middleware** (_middleware.py)
The `use_chat_middleware` decorator also wraps both methods separately with similar logic.
#### 5. **AG-UI Client** (_client.py)
Wraps both methods to unwrap server function calls:
```python
original_get_streaming_response = chat_client.get_streaming_response
original_get_response = chat_client.get_response
```
#### 6. **Provider Implementations** (all subpackages)
All subclasses implement both `_inner_*` methods, except:
- OpenAI Assistants Client (and similar clients, such as Foundry Agents V1) - it implements `_inner_get_response` by calling `_inner_get_streaming_response`
### Implications of Consolidation
| Aspect | Impact |
|--------|--------|
| **Type Safety** | Overloads work well: `@overload` with `Literal[True]` → `AsyncIterable`, `Literal[False]` → `ChatResponse`. Runtime return type based on `stream` param. |
| **Breaking Change** | **Major breaking change** for anyone implementing custom chat clients. They'd need to update from 2 methods to 1 (or 2 inner methods to 1). |
| **Decorator Complexity** | All 3 decorator systems (function invocation, middleware, observability) would need refactoring to handle both paths in one wrapper. |
| **Code Reduction** | Significant reduction in _tools.py (~200 lines of near-duplicate code) and other decorators. |
| **Samples/Tests** | Many samples call `get_streaming_response()` directly - would need updates. |
| **Protocol Simplification** | `ChatClientProtocol` goes from 2 methods + 1 property to 1 method + 1 property. |
### Recommendation
The consolidation makes sense architecturally, but consider:
1. **The overload pattern with `stream: bool`** works well in Python typing:
```python
@overload
async def get_response(self, messages, *, stream: Literal[True] = True, ...) -> AsyncIterable[ChatResponseUpdate]: ...
@overload
async def get_response(self, messages, *, stream: Literal[False] = False, ...) -> ChatResponse: ...
```
2. **The decorator complexity** is the biggest concern. The current approach of separate decorators for separate methods is cleaner than conditional logic inside one wrapper.
## Decision Drivers
- Reduce code needed to implement a Chat Client, simplify the public API for chat clients
- Reduce code duplication in decorators and middleware
- Maintain type safety and clarity in method signatures
## Considered Options
1. Status quo: Keep separate methods for streaming and non-streaming
2. Consolidate into a single `get_response` method with a `stream` parameter
3. Option 2 plus merging `agent.run` and `agent.run_stream` into a single method with a `stream` parameter as well
## Option 1: Status Quo
- Good: Clear separation of streaming vs non-streaming logic
- Good: Aligned with .NET design, although it is already `run` for Python and `RunAsync` for .NET
- Bad: Code duplication in decorators and middleware
- Bad: More complex client implementations
## Option 2: Consolidate into Single Method
- Good: Simplified public API for chat clients
- Good: Reduced code duplication in decorators
- Good: Smaller API footprint for users to get familiar with
- Good: People using OpenAI directly already expect this pattern
- Bad: Increased complexity in decorators and middleware
- Bad: Less alignment with .NET design (`get_response(stream=True)` vs `GetStreamingResponseAsync`)
## Option 3: Consolidate + Merge Agent and Workflow Methods
- Good: Further simplifies agent and workflow implementation
- Good: Single method for all chat interactions
- Good: Smaller API footprint for users to get familiar with
- Good: People using OpenAI directly already expect this pattern
- Good: Workflows internally already use a single method (_run_workflow_with_tracing), so would eliminate public API duplication as well, with hardly any code changes
- Bad: More breaking changes for agent users
- Bad: Increased complexity in agent implementation
- Bad: More extensive misalignment with .NET design (`run(stream=True)` vs `RunStreamingAsync` in addition to `get_response` change)
## Misc
Smaller questions to consider:
- Should default be `stream=False` or `stream=True`? (Current is False)
- Default to `False` makes it simpler for new users, as non-streaming is easier to handle.
- Default to `False` aligns with existing behavior.
- Streaming tends to be faster, so defaulting to `True` could improve performance for common use cases.
- Should this differ between ChatClient, Agent and Workflows? (e.g., Agent and Workflow defaults to streaming, ChatClient to non-streaming)
## Decision Outcome
Chosen Option: **Option 3: Consolidate + Merge Agent and Workflow Methods**
Since this is the most pythonic option and it reduces the API surface and code duplication the most, we will go with this option.
We will keep the default of `stream=False` for all methods to maintain backward compatibility and simplicity for new users.
# Appendix
## Code Samples for Consolidated Method
### Python - Option 3: Direct ChatClient + Agent with Single Method
```python
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from random import randint
from typing import Annotated
from agent_framework import ChatAgent
from agent_framework.openai import OpenAIChatClient
from pydantic import Field
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() -> None:
# Example 1: Direct ChatClient usage with single method
client = OpenAIChatClient()
message = "What's the weather in Amsterdam and in Paris?"
# Non-streaming usage
print(f"User: {message}")
response = await client.get_response(message, tools=get_weather)
print(f"Assistant: {response.text}")
# Streaming usage - same method, different parameter
print(f"\nUser: {message}")
print("Assistant: ", end="")
async for chunk in client.get_response(message, tools=get_weather, stream=True):
if chunk.text:
print(chunk.text, end="")
print("")
# Example 2: Agent usage with single method
agent = ChatAgent(
chat_client=client,
tools=get_weather,
name="WeatherAgent",
instructions="You are a weather assistant.",
)
thread = agent.get_new_thread()
# Non-streaming agent
print(f"\nUser: {message}")
result = await agent.run(message, thread=thread) # default would be stream=False
print(f"{agent.name}: {result.text}")
# Streaming agent - same method, different parameter
print(f"\nUser: {message}")
print(f"{agent.name}: ", end="")
async for update in agent.run(message, thread=thread, stream=True):
if update.text:
print(update.text, end="")
print("")
if __name__ == "__main__":
asyncio.run(main())
```
### .NET - Current pattern for comparison
```csharp
// Copyright (c) Microsoft. All rights reserved.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI.Chat;
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";
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
.GetChatClient(deploymentName)
.CreateAIAgent(
instructions: "You are good at telling jokes about pirates.",
name: "PirateJoker");
// Non-streaming: Returns a string directly
Console.WriteLine("=== Non-streaming ===");
string result = await agent.RunAsync("Tell me a joke about a pirate.");
Console.WriteLine(result);
// Streaming: Returns IAsyncEnumerable<AgentUpdate>
Console.WriteLine("\n=== Streaming ===");
await foreach (AgentUpdate update in agent.RunStreamingAsync("Tell me a joke about a pirate."))
{
Console.Write(update);
}
Console.WriteLine();
```
-423
View File
@@ -1,423 +0,0 @@
---
status: accepted
contact: westey-m
date: 2025-01-21
deciders: sergeymenshykh, markwallace, rbarreto, westey-m, stephentoub
consulted: reubenbond
informed:
---
# Feature Collections
## Context and Problem Statement
When using agents, we often have cases where we want to pass some arbitrary services or data to an agent or some component in the agent execution stack.
These services or data are not necessarily known at compile time and can vary by the agent stack that the user has built.
E.g., there may be an agent decorator or chat client decorator that was added to the stack by the user, and an arbitrary payload needs to be passed to that decorator.
Since these payloads are related to components that are not integral parts of the agent framework, they cannot be added as strongly typed settings to the agent run options.
However, the payloads could be added to the agent run options as loosely typed 'features', that can be retrieved as needed.
In some cases certain classes of agents may support the same capability, but not all agents do.
Having the configuration for such a capability on the main abstraction would advertise the functionality to all users, even if their chosen agent does not support it.
The user may type test for certain agent types, and call overloads on the appropriate agent types, with the strongly typed configuration.
Having a feature collection though, would be an alternative way of passing such configuration, without needing to type check the agent type.
All agents that support the functionality would be able to check for the configuration and use it, simplifying the user code.
If the agent does not support the capability, that configuration would be ignored.
### Sample Scenario 1 - Per Run ChatMessageStore Override for hosting Libraries
We are building an agent hosting library, that can host any agent built using the agent framework.
Where an agent is not built on a service that uses in-service chat history storage, the hosting library wants to force the agent to use
the hosting library's chat history storage implementation.
This chat history storage implementation may be specifically tailored to the type of protocol that the hosting library uses, e.g. conversation id based storage or response id based storage.
The hosting library does not know what type of agent it is hosting, so it cannot provide a strongly typed parameter on the agent.
Instead, it adds the chat history storage implementation to a feature collection, and if the agent supports custom chat history storage, it retrieves the implementation from the feature collection and uses it.
```csharp
// Pseudo-code for an agent hosting library that supports conversation id based hosting.
public async Task<string> HandleConversationsBasedRequestAsync(AIAgent agent, string conversationId, string userInput)
{
var thread = await this._threadStore.GetOrCreateThread(conversationId);
// The hosting library can set a per-run chat message store via Features that only applies for that run.
// This message store will load and save messages under the conversation id provided.
ConversationsChatMessageStore messageStore = new(this._dbClient, conversationId);
var response = await agent.RunAsync(
userInput,
thread,
options: new AgentRunOptions()
{
Features = new AgentFeatureCollection().WithFeature<ChatMessageStore>(messageStore)
});
await this._threadStore.SaveThreadAsync(conversationId, thread);
return response.Text;
}
// Pseudo-code for an agent hosting library that supports response id based hosting.
public async Task<(string responseMessage, string responseId)> HandleResponseIdBasedRequestAsync(AIAgent agent, string previousResponseId, string userInput)
{
var thread = await this._threadStore.GetOrCreateThreadAsync(previousResponseId);
// The hosting library can set a per-run chat message store via Features that only applies for that run.
// This message store will buffer newly added messages until explicitly saved after the run.
ResponsesChatMessageStore messageStore = new(this._dbClient, previousResponseId);
var response = await agent.RunAsync(
userInput,
thread,
options: new AgentRunOptions()
{
Features = new AgentFeatureCollection().WithFeature<ChatMessageStore>(messageStore)
});
// Since the message store may not actually have been used at all (if the agent's underlying chat client requires service-based chat history storage),
// we may not have anything to save back to the database.
// We still want to generate a new response id though, so that we can save the updated thread state under that id.
// We should also use the same id to save any buffered messages in the message store if there are any.
var newResponseId = this.GenerateResponseId();
if (messageStore.HasBufferedMessages)
{
await messageStore.SaveBufferedMessagesAsync(newResponseId);
}
// Save the updated thread state under the new response id that was generated by the store.
await this._threadStore.SaveThreadAsync(newResponseId, thread);
return (response.Text, newResponseId);
}
```
### Sample Scenario 2 - Structured output
Currently our base abstraction does not support structured output, since the capability is not supported by all agents.
For those agents that don't support structured output, we could add an agent decorator that takes the response from the underlying agent, and applies structured output parsing on top of it via an additional LLM call.
If we add structured output configuration as a feature, then any agent that supports structured output could retrieve the configuration from the feature collection and apply it, and where it is not supported, the configuration would simply be ignored.
We could add a simple StructuredOutputAgentFeature that can be added to the list of features and also be used to return the generated structured output.
```csharp
internal class StructuredOutputAgentFeature
{
public Type? OutputType { get; set; }
public JsonSerializerOptions? SerializerOptions { get; set; }
public bool? UseJsonSchemaResponseFormat { get; set; }
// Contains the result of the structured output parsing request.
public ChatResponse? ChatResponse { get; set; }
}
```
We can add a simple decorator class that does the chat client invocation.
```csharp
public class StructuredOutputAgent : DelegatingAIAgent
{
private readonly IChatClient _chatClient;
public StructuredOutputAgent(AIAgent innerAgent, IChatClient chatClient)
: base(innerAgent)
{
this._chatClient = Throw.IfNull(chatClient);
}
public override async Task<AgentRunResponse> RunAsync(
IEnumerable<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default)
{
// Run the inner agent first, to get back the text response we want to convert.
var response = await base.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false);
if (options?.Features?.TryGet<StructuredOutputAgentFeature>(out var responseFormatFeature) is true
&& responseFormatFeature.OutputType is not null)
{
// Create the chat options to request structured output.
ChatOptions chatOptions = new()
{
ResponseFormat = ChatResponseFormat.ForJsonSchema(responseFormatFeature.OutputType, responseFormatFeature.SerializerOptions)
};
// Invoke the chat client to transform the text output into structured data.
// The feature is updated with the result.
// The code can be simplified by adding a non-generic structured output GetResponseAsync
// overload that takes Type as input.
responseFormatFeature.ChatResponse = await this._chatClient.GetResponseAsync(
messages: new[]
{
new ChatMessage(ChatRole.System, "You are a json expert and when provided with any text, will convert it to the requested json format."),
new ChatMessage(ChatRole.User, response.Text)
},
options: chatOptions,
cancellationToken: cancellationToken).ConfigureAwait(false);
}
return response;
}
}
```
Finally, we can add an extension method on `AIAgent` that can add the feature to the run options and check the feature for the structured output result and add the deserialized result to the response.
```csharp
public static async Task<AgentRunResponse<T>> RunAsync<T>(
this AIAgent agent,
IEnumerable<ChatMessage> messages,
AgentThread? thread = null,
JsonSerializerOptions? serializerOptions = null,
AgentRunOptions? options = null,
bool? useJsonSchemaResponseFormat = null,
CancellationToken cancellationToken = default)
{
// Create the structured output feature.
var structuredOutputFeature = new StructuredOutputAgentFeature();
structuredOutputFeature.OutputType = typeof(T);
structuredOutputFeature.UseJsonSchemaResponseFormat = useJsonSchemaResponseFormat;
// Run the agent.
options ??= new AgentRunOptions();
options.Features ??= new AgentFeatureCollection();
options.Features.Set(structuredOutputFeature);
var response = await agent.RunAsync(messages, thread, options, cancellationToken).ConfigureAwait(false);
// Deserialize the JSON output.
if (structuredOutputFeature.ChatResponse is not null)
{
var typed = new ChatResponse<T>(structuredOutputFeature.ChatResponse, serializerOptions ?? AgentJsonUtilities.DefaultOptions);
return new AgentRunResponse<T>(response, typed.Result);
}
throw new InvalidOperationException("No structured output response was generated by the agent.");
}
```
We can then use the extension method with any agent that supports structured output or that has
been decorated with the `StructuredOutputAgent` decorator.
```csharp
agent = new StructuredOutputAgent(agent, chatClient);
AgentRunResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>([new ChatMessage(
ChatRole.User,
"Please provide information about John Smith, who is a 35-year-old software engineer.")]);
```
## Implementation Options
Three options were considered for implementing feature collections:
- **Option 1**: FeatureCollections similar to ASP.NET Core
- **Option 2**: AdditionalProperties Dictionary
- **Option 3**: IServiceProvider
Here are some comparisons about their suitability for our use case:
| Criteria | Feature Collection | Additional Properties | IServiceProvider |
|------------------|--------------------|-----------------------|------------------|
|Ease of use |✅ Good |❌ Bad |✅ Good |
|User familiarity |❌ Bad |✅ Good |✅ Good |
|Type safety |✅ Good |❌ Bad |✅ Good |
|Ability to modify registered options when progressing down the stack|✅ Supported|✅ Supported|❌ Not-Supported (IServiceProvider is read-only)|
|Already available in MEAI stack|❌ No|✅ Yes|❌ No|
|Ambiguity with existing AdditionalProperties|❌ Yes|✅ No|❌ Yes|
## IServiceProvider
Service Collections and Service Providers provide a very popular way to register and retrieve services by type and could be used as a way to pass features to agents and chat clients.
However, since IServiceProvider is read-only, it is not possible to modify the registered services when progressing down the execution stack.
E.g. an agent decorator cannot add additional services to the IServiceProvider passed to it when calling into the inner agent.
IServiceProvider also does not expose a way to list all services contained in it, making it difficult to copy services from one provider to another.
This lack of mutability makes IServiceProvider unsuitable for our use case, since we will not be able to use it to build sample scenario 2.
## AdditionalProperties dictionary
The AdditionalProperties dictionary is already available on various options classes in the agent framework as well as in the MEAI stack and
allows storing arbitrary key/value pairs, where the key is a string and the value is an object.
While FeatureCollection uses Type as a key, AdditionalProperties uses string keys.
This means that users need to agree on string keys to use for specific features, however it is also possible to use Type.FullName as a key by convention
to avoid key collisions, which is an easy convention to follow.
Since the value of AdditionalProperties is of type object, users need to cast the value to the expected type when retrieving it, which is also
a drawback, but when using the convention of using Type.FullName as a key, there is at least a clear expectation of what type to cast to.
```csharp
// Setting a feature
options.AdditionalProperties[typeof(MyFeature).FullName] = new MyFeature();
// Retrieving a feature
if (options.AdditionalProperties.TryGetValue(typeof(MyFeature).FullName, out var featureObj)
&& featureObj is MyFeature myFeature)
{
// Use myFeature
}
```
It would also be possible to add extension methods to simplify setting and getting features from AdditionalProperties.
Having a base class for features should help make this more feature rich.
```csharp
// Setting a feature, this can use Type.FullName as the key.
options.AdditionalProperties
.WithFeature(new MyFeature());
// Retrieving a feature, this can use Type.FullName as the key.
if (options.AdditionalProperties.TryGetFeature<MyFeature>(out var myFeature))
{
// Use myFeature
}
```
It would also be possible to add extension methods for a feature to simplify setting and getting features from AdditionalProperties.
```csharp
// Setting a feature
options.AdditionalProperties
.WithMyFeature(new MyFeature());
// Retrieving a feature
if (options.AdditionalProperties.TryGetMyFeature(out var myFeature))
{
// Use myFeature
}
```
## Feature Collection
If we choose the feature collection option, we need to decide on the design of the feature collection itself.
### Feature Collections extension points
We need to decide the set of actions that feature collections would be supported for. Here is the suggested list of actions:
**MAAI.AIAgent:**
1. GetNewThread
1. E.g. this would allow passing an already existing storage id for the thread to use, or an initialized custom chat message store to use.
1. DeserializeThread
1. E.g. this would allow passing an already existing storage id for the thread to use, or an initialized custom chat message store to use.
1. Run / RunStreaming
1. E.g. this would allow passing an override chat message store just for that run, or a desired schema for a structured output middleware component.
**MEAI.ChatClient:**
1. GetResponse / GetStreamingResponse
### Reconciling with existing AdditionalProperties
If we decide to add feature collections, separately from the existing AdditionalProperties dictionaries, we need to consider how to explain to users when to use each one.
One possible approach though is to have the one use the other under the hood.
AdditionalProperties could be stored as a feature in the feature collection.
Users would be able to retrieve additional properties from the feature collection, in addition to retrieving it via a dedicated AdditionalProperties property.
E.g. `features.Get<AdditionalPropertiesDictionary>()`
One challenge with this approach is that when setting a value in the AdditionalProperties dictionary, the feature collection would need to be created first if it does not already exist.
```csharp
public class AgentRunOptions
{
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
public IAgentFeatureCollection? Features { get; set; }
}
var options = new AgentRunOptions();
// This would need to create the feature collection first, if it does not already exist.
options.AdditionalProperties ??= new AdditionalPropertiesDictionary();
```
Since IAgentFeatureCollection is an interface, AgentRunOptions would need to have a concrete implementation of the interface to create, meaning that the user cannot decide.
It also means that if the user doesn't realise that AdditionalProperties is implemented using feature collections, they may set a value on AdditionalProperties, and then later overwrite the entire feature collection, losing the AdditionalProperties feature.
Options to avoid these issues:
1. Make `Features` readonly.
1. This would prevent the user from overwriting the feature collection after setting AdditionalProperties.
1. Since the user cannot set their own implementation of IAgentFeatureCollection, having an interface for it may not be necessary.
### Feature Collection Implementation
We have two options for implementing feature collections:
1. Create our own [IAgentFeatureCollection interface](https://github.com/microsoft/agent-framework/pull/2354/files#diff-9c42f3e60d70a791af9841d9214e038c6de3eebfc10e3997cb4cdffeb2f1246d) and [implementation](https://github.com/microsoft/agent-framework/pull/2354/files#diff-a435cc738baec500b8799f7f58c1538e3bb06c772a208afc2615ff90ada3f4ca).
2. Reuse the asp.net [IFeatureCollection interface](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/IFeatureCollection.cs) and [implementation](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/FeatureCollection.cs).
#### Roll our own
Advantages:
Creating our own IAgentFeatureCollection interface and implementation has the advantage of being more clearly associated with the agent framework and allows us to
improve on some of the design decisions made in asp.net core's IFeatureCollection.
Drawbacks:
It would mean a different implementation to maintain and test.
#### Reuse asp.net IFeatureCollection
Advantages:
Reusing the asp.net IFeatureCollection has the advantage of being able to reuse the well-established and tested implementation from asp.net
core. Users who are using agents in an asp.net core application may be able to pass feature collections from asp.net core to the agent framework directly.
Drawbacks:
While the package name is `Microsoft.Extensions.Features`, the namespaces of the types are `Microsoft.AspNetCore.Http.Features`, which may create confusion for users of agent framework who are not building web applications or services.
Users may rightly ask: Why do I need to use a class from asp.net core when I'm not building a web application / service?
The current design has some design issues that would be good to avoid. E.g. it does not distinguish between a feature being "not set" and "null". Get returns both as null and there is no tryget method.
Since the [default implementation](https://github.com/dotnet/aspnetcore/blob/main/src/Extensions/Features/src/FeatureCollection.cs) also supports value types, it throws for null values of value types.
A TryGet method would be more appropriate.
## Feature Layering
One possible scenario when adding support for feature collections is to allow layering of features by scope.
The following levels of scope could be supported:
1. Application - Application wide features that apply to all agents / chat clients
2. Artifact (Agent / ChatClient) - Features that apply to all runs of a specific agent or chat client instance
3. Action (GetNewThread / Run / GetResponse) - Feature that apply to a single action only
When retrieving a feature from the collection, the search would start from the most specific scope (Action) and progress to the least specific scope (Application), returning the first matching feature found.
Introducing layering adds some challenges:
- There may be multiple feature collections at the same scope level, e.g. an Agent that uses a ChatClient where both have their own feature collections.
- Do we layer the agent feature collection over the chat client feature collection (Application -> ChatClient -> Agent -> Run), or only use the agent feature collection in the agent (Application -> Agent -> Run), and the chat client feature collection in the chat client (Application -> ChatClient -> Run)?
- The appropriate base feature collection may change when progressing down the stack, e.g. when an Agent calls a ChatClient, the action feature collection stays the same, but the artifact feature collection changes.
- Who creates the feature collection hierarchy?
- Since the hierarchy changes as it progresses down the execution stack, and the caller can only pass in the action level feature collection, the callee needs to combine it with its own artifact level feature collection and the application level feature collection. Each action will need to build the appropriate feature collection hierarchy, at the start of its execution.
- For Artifact level features, it seems odd to pass them in as a bag of untyped features, when we are constructing a known artifact type and therefore can have typed settings.
- E.g. today we have a strongly typed setting on ChatClientAgentOptions to configure a ChatMessageStore for the agent.
- To avoid global statics for application level features, the user would need to pass in the application level feature collection to each artifact that they create.
- This would be very odd if the user also already has to strongly typed settings for each feature that they want to set at the artifact level.
### Layering Options
1. No layering - only a single feature collection is supported per action (the caller can still create a layered collection if desired, but the callee does not do any layering automatically).
1. Fallback is to any features configured on the artifact via strongly typed settings.
1. Full layering - support layering at all levels (Application -> Artifact -> Action).
1. Only apply applicable artifact level features when calling into that artifact.
1. Apply upstream artifact features when calling into downstream artifacts, e.g. Feature hierarchy in ChatClientAgent would be `Application -> Agent -> Run` and in ChatClient would be `Application -> ChatClient -> Agent -> Run` or `Application -> Agent -> ChatClient -> Run`
1. The user needs to provide the application level feature collection to each artifact that they create and artifact features are passed via strongly typed settings.
### Accessing application level features Options
We need to consider how application level features would be accessed if supported.
1. The user provides the application level feature collection to each artifact that the user constructs
1. Passing the application level feature collection to each artifact is tedious for the user.
1. There is a static application level feature collection that can be accessed globally.
1. Statics create issues with testing and isolation.
## Decisions
- Feature Collections Container: Use AdditionalProperties
- Feature Layering: No layering - only a single collection/dictionary is supported per action. Application layers can be added later if needed.
-147
View File
@@ -1,147 +0,0 @@
---
status: proposed
contact: westey-m
date: 2026-01-27
deciders: sergeymenshykh, markwallace, rbarreto, dmytrostruk, westey-m, eavanvalkenburg, stephentoub, lokitoth, alliscode, taochenosu, moonbox3
consulted:
informed:
---
# AgentRunContext for Agent Run
## Context and Problem Statement
During an agent run, various components involved in the execution (middleware, filters, tools, nested agents, etc.) may need access to contextual information about the current run, such as:
1. The agent that is executing the run
2. The session associated with the run
3. The request messages passed to the agent
4. The run options controlling the agent's behavior
Additionally, some components may need to modify this context during execution, for example:
- Replacing the session with a different one
- Modifying the request messages before they reach the agent core
- Updating or replacing the run options entirely
Currently, there is no standardized way to access or modify this context from arbitrary code that executes during an agent run, especially from deeply nested call stacks where the context is not explicitly passed.
## Sample Scenario
When using an Agent as an AIFunction developers may want to pass context from the parent agent run to the child agent run. For example, the developer may want to copy chat history to the child agent, or share the same session across both agents.
To enable these scenarios, we need a way to access the parent agent run context, including e.g. the parent agent itself, the parent agent session, and the parent run options from function tool calls.
```csharp
public static AIFunction AsAIFunctionWithSessionPropagation(this ChatClientAgent agent, AIFunctionFactoryOptions? options = null)
{
Throw.IfNull(agent);
[Description("Invoke an agent to retrieve some information.")]
async Task<string> InvokeAgentAsync(
[Description("Input query to invoke the agent.")] string query,
CancellationToken cancellationToken)
{
// Get the session from the parent agent and pass it to the child agent.
var session = AIAgent.CurrentRunContext?.Session;
// Alternatively, the developer may want to create a new session but copy over the chat history from the parent agent.
// var parentChatHistory = AIAgent.CurrentRunContext?.Session?.GetService<IList<ChatMessage>>();
// if (parentChatHistory != null)
// {
// var chp = new InMemoryChatHistoryProvider();
// foreach (var message in parentChatHistory)
// {
// chp.Add(message);
// }
// session = agent.GetNewSession(chp);
// }
var response = await agent.RunAsync(query, session: session, cancellationToken: cancellationToken).ConfigureAwait(false);
return response.Text;
}
options ??= new();
options.Name ??= SanitizeAgentName(agent.Name);
options.Description ??= agent.Description;
return AIFunctionFactory.Create(InvokeAgentAsync, options);
}
```
## Decision Drivers
- Components executing during an agent run need access to run context without explicit parameter passing through every layer
- Context should flow naturally across async calls without manual propagation
- The design should allow modification of context properties by agent decorators (e.g., replacing options or session)
- Solution should be consistent with patterns used in similar frameworks (e.g., `FunctionInvokingChatClient.CurrentContext` `HttpContext.Current`, `Activity.Current`)
## Considered Options
- **Option 1**: Pass context explicitly through all method signatures
- **Option 2**: Use `AsyncLocal<T>` to provide ambient context accessible anywhere during the run
- **Option 3**: Use a combination of explicit parameters for `RunCoreAsync` and `AsyncLocal<T>` for ambient access
## Decision Outcome
Chosen option: **Option 3** - Combination of explicit parameters and AsyncLocal ambient access.
This approach provides the best of both worlds:
1. **Explicit parameters are passed to `RunCoreAsync`**: The core agent implementation receives the parameters explicitly, making it clear what data is available and enabling easy unit testing. Any modification of these in a decorator will require calling `RunAsync` on the inner agent with the updated parameters, which would result in the inner agent creating a new `AgentRunContext` instance.
```csharp
public async Task<AgentResponse> RunAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default)
{
CurrentRunContext = new(this, session, messages as IReadOnlyCollection<ChatMessage> ?? messages.ToList(), options);
return await this.RunCoreAsync(messages, session, options, cancellationToken).ConfigureAwait(false);
}
```
2. **`AsyncLocal<AgentRunContext?>` for ambient access**: The context is stored in an `AsyncLocal<T>` field, making it accessible from any code executing during the agent run via a static property.
The main scenario for this is to allow deeply nested components (e.g., tools, chat client middleware) to access the context without needing to pass it through every method signature. These are external components that cannot easily be modified to accept additional parameters. For internal components, we prefer passing any parameters explicitly.
```csharp
public static AgentRunContext? CurrentRunContext
{
get => s_currentContext.Value;
protected set => s_currentContext.Value = value;
}
```
### AgentRunContext Design
The `AgentRunContext` class encapsulates all run-related state:
```csharp
public class AgentRunContext
{
public AgentRunContext(
AIAgent agent,
AgentSession? session,
IReadOnlyCollection<ChatMessage> requestMessages,
AgentRunOptions? agentRunOptions)
public AIAgent Agent { get; }
public AgentSession? Session { get; }
public IReadOnlyCollection<ChatMessage> RequestMessages { get; }
public AgentRunOptions? RunOptions { get; }
}
```
Key design decisions:
- **All properties are read-only**: While some of the sub-properties on the provided properties (like `AgentRunOptions.AllowBackgroundResponses`) may be mutable, the `AgentRunContext` itself is immutable and we want to discourage anyone modifying the values in the context. Modifying the context is unlikely to result in the desired behavior, as the values will typically already have been used by the time any custom code accesses them.
### Benefits
1. **Ambient Access**: Any code executing during the run can access context via `AIAgent.CurrentRunContext` without needing explicit parameters
2. **Async Flow**: `AsyncLocal<T>` automatically flows across async/await boundaries
3. **Modifiability**: Components can modify or replace session, messages, or options as needed
4. **Testability**: The explicit parameter to `RunCoreAsync` makes unit testing straightforward
File diff suppressed because it is too large Load Diff
@@ -1,147 +0,0 @@
# Time-To-Live (TTL) for durable agent sessions
## Overview
The durable agents automatically maintain conversation history and state for each session. Without automatic cleanup, this state can accumulate indefinitely, consuming storage resources and increasing costs. The Time-To-Live (TTL) feature provides automatic cleanup of idle agent sessions, ensuring that sessions are automatically deleted after a period of inactivity.
## What is TTL?
Time-To-Live (TTL) is a configurable duration that determines how long an agent session state will be retained after its last interaction. When an agent session is idle (no messages sent to it) for longer than the TTL period, the session state is automatically deleted. Each new interaction with an agent resets the TTL timer, extending the session's lifetime.
## Benefits
- **Automatic cleanup**: No manual intervention required to clean up idle agent sessions
- **Cost optimization**: Reduces storage costs by automatically removing unused session state
- **Resource management**: Prevents unbounded growth of agent session state in storage
- **Configurable**: Set TTL globally or per-agent type to match your application's needs
## Configuration
TTL can be configured at two levels:
1. **Global default TTL**: Applies to all agent sessions unless overridden
2. **Per-agent type TTL**: Overrides the global default for specific agent types
Additionally, you can configure a **minimum deletion delay** that controls how frequently deletion operations are scheduled. The default value is 5 minutes, and the maximum allowed value is also 5 minutes.
> [!NOTE]
> Reducing the minimum deletion delay below 5 minutes can be useful for testing or for ensuring rapid cleanup of short-lived agent sessions. However, this can also increase the load on the system and should be used with caution.
### Default values
- **Default TTL**: 14 days
- **Minimum TTL deletion delay**: 5 minutes (maximum allowed value, subject to change in future releases)
### Configuration examples
#### .NET
```csharp
// Configure global default TTL and minimum signal delay
services.ConfigureDurableAgents(
options =>
{
// Set global default TTL to 7 days
options.DefaultTimeToLive = TimeSpan.FromDays(7);
// Add agents (will use global default TTL)
options.AddAIAgent(myAgent);
});
// Configure per-agent TTL
services.ConfigureDurableAgents(
options =>
{
options.DefaultTimeToLive = TimeSpan.FromDays(14); // Global default
// Agent with custom TTL of 1 day
options.AddAIAgent(shortLivedAgent, timeToLive: TimeSpan.FromDays(1));
// Agent with custom TTL of 90 days
options.AddAIAgent(longLivedAgent, timeToLive: TimeSpan.FromDays(90));
// Agent using global default (14 days)
options.AddAIAgent(defaultAgent);
});
// Disable TTL for specific agents by setting TTL to null
services.ConfigureDurableAgents(
options =>
{
options.DefaultTimeToLive = TimeSpan.FromDays(14);
// Agent with no TTL (never expires)
options.AddAIAgent(permanentAgent, timeToLive: null);
});
```
## How TTL works
The following sections describe how TTL works in detail.
### Expiration tracking
Each agent session maintains an expiration timestamp in its internally managed state that is updated whenever the session processes a message:
1. When a message is sent to an agent session, the expiration time is set to `current time + TTL`
2. The runtime schedules a delete operation for the expiration time (subject to minimum delay constraints)
3. When the delete operation runs, if the current time is past the expiration time, the session state is deleted. Otherwise, the delete operation is rescheduled for the next expiration time.
### State deletion
When an agent session expires, its entire state is deleted, including:
- Conversation history
- Any custom state data
- Expiration timestamps
After deletion, if a message is sent to the same agent session, a new session is created with a fresh conversation history.
## Behavior examples
The following examples illustrate how TTL works in different scenarios.
### Example 1: Agent session expires after TTL
1. Agent configured with 30-day TTL
2. User sends message at Day 0 → agent session created, expiration set to Day 30
3. No further messages sent
4. At Day 30 → Agent session is deleted
5. User sends message at Day 31 → New agent session created with fresh conversation history
### Example 2: TTL reset on interaction
1. Agent configured with 30-day TTL
2. User sends message at Day 0 → agent session created, expiration set to Day 30
3. User sends message at Day 15 → Expiration reset to Day 45
4. User sends message at Day 40 → Expiration reset to Day 70
5. Agent session remains active as long as there are regular interactions
## Logging
The TTL feature includes comprehensive logging to track state changes:
- **Expiration time updated**: Logged when TTL expiration time is set or updated
- **Deletion scheduled**: Logged when a deletion check signal is scheduled
- **Deletion check**: Logged when a deletion check operation runs
- **Session expired**: Logged when an agent session is deleted due to expiration
- **TTL rescheduled**: Logged when a deletion signal is rescheduled
These logs help monitor TTL behavior and troubleshoot any issues.
## Best practices
1. **Choose appropriate TTL values**: Balance between storage costs and user experience. Too short TTLs may delete active sessions, while too long TTLs may accumulate unnecessary state.
2. **Use per-agent TTLs**: Different agents may have different usage patterns. Configure TTLs per-agent based on expected session lifetimes.
3. **Monitor expiration logs**: Review logs to understand TTL behavior and adjust configuration as needed.
4. **Test with short TTLs**: During development, use short TTLs (e.g., minutes) to verify TTL behavior without waiting for long periods.
## Limitations
- TTL is based on wall-clock time, not activity time. The expiration timer starts from the last message timestamp.
- Deletion checks are durably scheduled operations and may have slight delays depending on system load.
- Once an agent session is deleted, its conversation history cannot be recovered.
- TTL deletion requires at least one worker to be available to process the deletion operation message.
+5 -5
View File
@@ -125,7 +125,7 @@ The proposed solution is to add helper methods which allow developers to either
- [Foundry SDK] Create a `PersistentAgentsClient`
- [Foundry SDK] Create a `PersistentAgent` using the `PersistentAgentsClient`
- [Foundry SDK] Retrieve an `AIAgent` using the `PersistentAgentsClient`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse`
- [Foundry SDK] Clean up the agent
@@ -156,7 +156,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
- [Foundry SDK] Create a `PersistentAgentsClient`
- [Foundry SDK] Create a `AIAgent` using the `PersistentAgentsClient`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse`
- [Foundry SDK] Clean up the agent
```csharp
@@ -184,7 +184,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
- [Foundry SDK] Create a `PersistentAgentsClient`
- [Foundry SDK] Create a `AIAgent` using the `PersistentAgentsClient`
- [Agent Framework SDK] Optionally create an `AgentThread` for the agent run
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse`
- [Foundry SDK] Clean up the agent and the agent thread
```csharp
@@ -227,7 +227,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
- [Foundry SDK] Create a `PersistentAgentsClient`
- [Foundry SDK] Create multiple `AIAgent` instances using the `PersistentAgentsClient`
- [Agent Framework SDK] Create a `SequentialOrchestration` and add all of the agents to it
- [Agent Framework SDK] Invoke the `SequentialOrchestration` instance and access response from the `AgentResponse`
- [Agent Framework SDK] Invoke the `SequentialOrchestration` instance and access response from the `AgentRunResponse`
- [Foundry SDK] Clean up the agents
```csharp
@@ -281,7 +281,7 @@ SequentialOrchestration orchestration =
// Run the orchestration
string input = "An eco-friendly stainless steel water bottle that keeps drinks cold for 24 hours";
Console.WriteLine($"\n# INPUT: {input}\n");
AgentResponse result = await orchestration.RunAsync(input);
AgentRunResponse result = await orchestration.RunAsync(input);
Console.WriteLine($"\n# RESULT: {result}");
// Cleanup
-1
View File
@@ -209,7 +209,6 @@ dotnet_diagnostic.CA2000.severity = none # Call System.IDisposable.Dispose on ob
dotnet_diagnostic.CA2225.severity = none # Operator overloads have named alternates
dotnet_diagnostic.CA2227.severity = none # Change to be read-only by removing the property setter
dotnet_diagnostic.CA2249.severity = suggestion # Consider using 'Contains' method instead of 'IndexOf' method
dotnet_diagnostic.CA2252.severity = none # Requires preview
dotnet_diagnostic.CA2253.severity = none # Named placeholders in the logging message template should not be comprised of only numeric characters
dotnet_diagnostic.CA2253.severity = none # Named placeholders in the logging message template should not be comprised of only numeric characters
dotnet_diagnostic.CA2263.severity = suggestion # Use generic overload
-66
View File
@@ -1,66 +0,0 @@
# AGENTS.md
Instructions for AI coding agents working in the .NET codebase.
## Build, Test, and Lint Commands
```bash
# From dotnet/ directory
dotnet build # Build all projects
dotnet test # Run all tests
dotnet format # Auto-fix formatting
# Build/test a specific project (preferred for isolated changes)
dotnet build src/Microsoft.Agents.AI.<Package>
dotnet test tests/Microsoft.Agents.AI.<Package>.UnitTests
# Run a single test
dotnet test --filter "FullyQualifiedName~TestClassName.TestMethodName"
```
**Note**: Changes to core packages (`Microsoft.Agents.AI`, `Microsoft.Agents.AI.Abstractions`) affect dependent projects - run checks across the entire solution. For isolated changes, build/test only the affected project to save time.
## Project Structure
```
dotnet/
├── src/
│ ├── Microsoft.Agents.AI/ # Core AI agent abstractions
│ ├── Microsoft.Agents.AI.Abstractions/ # Shared abstractions and interfaces
│ ├── Microsoft.Agents.AI.OpenAI/ # OpenAI provider
│ ├── Microsoft.Agents.AI.AzureAI/ # Azure AI provider
│ ├── Microsoft.Agents.AI.Anthropic/ # Anthropic provider
│ ├── Microsoft.Agents.AI.Workflows/ # Workflow orchestration
│ └── ... # Other packages
├── samples/ # Sample applications
└── tests/ # Unit and integration tests
```
### External Dependencies
The framework integrates with `Microsoft.Extensions.AI` and `Microsoft.Extensions.AI.Abstractions` (external NuGet packages) using types like `IChatClient`, `FunctionInvokingChatClient`, `AITool`, and `AIContent`.
## Key Conventions
- **Copyright header**: `// Copyright (c) Microsoft. All rights reserved.` at top of all `.cs` files
- **XML docs**: Required for all public methods and classes
- **Async**: Use `Async` suffix for methods returning `Task`/`ValueTask`
- **Private classes**: Should be `sealed` unless subclassed
- **Config**: Read from environment variables with `UPPER_SNAKE_CASE` naming
- **Tests**: Add Arrange/Act/Assert comments; use Moq for mocking
## Sample Structure
1. Copyright header: `// Copyright (c) Microsoft. All rights reserved.`
2. Description comment explaining what the sample demonstrates
3. Using statements
4. Main code logic
5. Helper methods at bottom
Configuration via environment variables (never hardcode secrets). Keep samples simple and focused.
When adding a new sample:
- Create a standalone project in `samples/` with matching directory and project names
- Include a README.md explaining what the sample does and how to run it
- Add the project to the solution file
- Reference the sample in the parent directory's README.md
+8 -5
View File
@@ -3,14 +3,17 @@
<!-- Default properties inherited by all projects. Projects can override. -->
<RunAnalyzersDuringBuild>true</RunAnalyzersDuringBuild>
<EnableNETAnalyzers>true</EnableNETAnalyzers>
<AnalysisLevel>10.0-all</AnalysisLevel>
<AnalysisMode>AllEnabledByDefault</AnalysisMode>
<AnalysisLevel>latest</AnalysisLevel>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
<LangVersion>latest</LangVersion>
<LangVersion>13</LangVersion>
<Nullable>enable</Nullable>
<NoWarn>$(NoWarn);NU5128;CS8002</NoWarn>
<NoWarn>$(NoWarn);NU5128</NoWarn>
<TreatWarningsAsErrors>true</TreatWarningsAsErrors>
<TargetFrameworksCore>net10.0;net9.0;net8.0</TargetFrameworksCore>
<TargetFrameworks>$(TargetFrameworksCore);netstandard2.0;net472</TargetFrameworks>
<ProjectsCoreTargetFrameworks>net9.0;net8.0</ProjectsCoreTargetFrameworks>
<ProjectsDebugCoreTargetFrameworks>net9.0</ProjectsDebugCoreTargetFrameworks>
<ProjectsTargetFrameworks>net9.0;net8.0;netstandard2.0;net472</ProjectsTargetFrameworks>
<ProjectsDebugTargetFrameworks>net9.0;net472</ProjectsDebugTargetFrameworks>
<IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net7.0'))">true</IsAotCompatible>
<Configurations>Debug;Release;Publish</Configurations>
</PropertyGroup>
+1 -1
View File
@@ -5,7 +5,7 @@
<Sdk Name="Microsoft.Build.CentralPackageVersions" Version="2.1.3" />
<!-- Only run 'dotnet format' on dev machines, Release builds. Skip on GitHub Actions -->
<!-- as this runs in its own Actions job. -->
<Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' ">
<Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' AND '$(TargetFramework)' == '$(ProjectsDebugTargetFrameworks)'">
<Message Text="Running dotnet format" Importance="high" />
<Exec Command="dotnet format --no-restore -v diag $(ProjectFileName)" />
</Target>
+41 -58
View File
@@ -7,46 +7,34 @@
</PropertyGroup>
<PropertyGroup>
<!-- Aspire -->
<AspireAppHostSdkVersion>13.0.2</AspireAppHostSdkVersion>
<AspireAppHostSdkVersion>13.0.0</AspireAppHostSdkVersion>
</PropertyGroup>
<ItemGroup>
<!-- Aspire.* -->
<PackageVersion Include="Anthropic" Version="12.3.0" />
<PackageVersion Include="Anthropic.Foundry" Version="0.4.1" />
<PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
<PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
<PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0-beta.435" />
<!-- Azure.* -->
<PackageVersion Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
<PackageVersion Include="Azure.AI.Projects.OpenAI" Version="1.0.0-beta.5" />
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.8" />
<PackageVersion Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
<PackageVersion Include="Azure.Identity" Version="1.17.1" />
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.7" />
<PackageVersion Include="Azure.AI.OpenAI" Version="2.5.0-beta.1" />
<PackageVersion Include="Azure.Identity" Version="1.17.0" />
<PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
<!-- Google Gemini -->
<PackageVersion Include="Google.GenAI" Version="0.11.0" />
<PackageVersion Include="Mscc.GenerativeAI.Microsoft" Version="2.9.3" />
<!-- Microsoft.Azure.* -->
<PackageVersion Include="Microsoft.Azure.Cosmos" Version="3.54.0" />
<!-- Newtonsoft.Json -->
<PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
<!-- System.* -->
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.3" />
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.0" />
<PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
<PackageVersion Include="System.ClientModel" Version="1.8.1" />
<PackageVersion Include="System.ClientModel" Version="1.8.0" />
<PackageVersion Include="System.CodeDom" Version="10.0.0" />
<PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
<PackageVersion Include="System.Collections.Immutable" Version="10.0.0" />
<PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.3" />
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.0" />
<PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0" />
<PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.1" />
<PackageVersion Include="System.Text.Json" Version="10.0.3" />
<PackageVersion Include="System.Threading.Channels" Version="10.0.3" />
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.0" />
<PackageVersion Include="System.Text.Json" Version="10.0.0" />
<PackageVersion Include="System.Threading.Channels" Version="10.0.0" />
<PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
<PackageVersion Include="System.Net.Security" Version="4.3.2" />
<!-- OpenTelemetry -->
<PackageVersion Include="OpenTelemetry" Version="1.13.1" />
<PackageVersion Include="OpenTelemetry.Api" Version="1.13.1" />
@@ -58,12 +46,13 @@
<PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
<PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.13.0" />
<!-- Microsoft.AspNetCore.* -->
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="9.0.11" />
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
<!-- Microsoft.Extensions.* -->
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.3.0" />
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.3.0" />
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.AI.AzureAIInference" Version="10.0.0-preview.1.25559.3" />
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.0.0-preview.1.25559.3" />
<PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
@@ -71,11 +60,11 @@
<PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.3" />
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.3" />
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
@@ -89,62 +78,56 @@
<PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
<!-- Agent SDKs -->
<PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.23" />
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
<!-- M365 Agents SDK -->
<PackageVersion Include="AdaptiveCards" Version="3.1.0" />
<PackageVersion Include="Microsoft.Agents.Authentication.Msal" Version="1.3.171-beta" />
<PackageVersion Include="Microsoft.Agents.Hosting.AspNetCore" Version="1.3.171-beta" />
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.2.41" />
<!-- A2A -->
<PackageVersion Include="A2A" Version="0.3.3-preview" />
<PackageVersion Include="A2A.AspNetCore" Version="0.3.3-preview" />
<!-- MCP -->
<PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.3" />
<!-- Inference SDKs -->
<PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.5.1" />
<PackageVersion Include="Anthropic.SDK" Version="5.8.0" />
<PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.6" />
<PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
<PackageVersion Include="OllamaSharp" Version="5.4.8" />
<PackageVersion Include="OpenAI" Version="2.8.0" />
<PackageVersion Include="OpenAI" Version="2.6.0" />
<!-- Identity -->
<PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.78.0" />
<!-- Workflows -->
<PackageVersion Include="Microsoft.Agents.ObjectModel" Version="2026.1.2.3" />
<PackageVersion Include="Microsoft.Agents.ObjectModel.Json" Version="2026.1.2.3" />
<PackageVersion Include="Microsoft.Agents.ObjectModel.PowerFx" Version="2026.1.2.3" />
<PackageVersion Include="Microsoft.PowerFx.Interpreter" Version="1.5.0-build.20251008-1002" />
<PackageVersion Include="Microsoft.Bot.ObjectModel" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.Json" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.PowerFx" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.PowerFx.Interpreter" Version="1.4.0" />
<!-- Durable Task -->
<PackageVersion Include="Microsoft.DurableTask.Client" Version="1.18.0" />
<PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.18.0" />
<PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.18.0" />
<PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.18.0" />
<PackageVersion Include="Microsoft.DurableTask.Client" Version="1.16.2" />
<PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.16.2-preview.1" />
<PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.16.2" />
<PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.16.2-preview.1" />
<!-- Azure Functions -->
<PackageVersion Include="Microsoft.Azure.Functions.Worker" Version="2.50.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.ApplicationInsights" Version="2.50.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.11.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.1" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.9.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http" Version="3.3.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" Version="2.1.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Mcp" Version="1.0.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.7" />
<!-- Redis -->
<PackageVersion Include="StackExchange.Redis" Version="2.10.1" />
<!-- Community -->
<PackageVersion Include="System.Linq.Async" Version="6.0.3" />
<!-- Test -->
<PackageVersion Include="FluentAssertions" Version="8.8.0" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net8.0'" Version="8.0.22" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net9.0'" Version="9.0.11" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net10.0'" Version="10.0.0" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Version="9.0.11" />
<PackageVersion Include="Microsoft.NET.Test.Sdk" Version="18.0.0" />
<PackageVersion Include="Moq" Version="[4.18.4]" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Abstractions" Version="1.67.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Yaml" Version="1.67.0-beta" />
<PackageVersion Include="xunit" Version="2.9.3" />
<PackageVersion Include="xunit.abstractions" Version="2.0.3" />
<PackageVersion Include="xunit.runner.visualstudio" Version="3.1.3" />
<PackageVersion Include="Xunit.SkippableFact" Version="1.5.23" />
<PackageVersion Include="xretry" Version="1.9.0" />
<PackageVersion Include="coverlet.collector" Version="6.0.4" />
<!-- Symbols -->
<PackageVersion Include="Microsoft.SourceLink.GitHub" Version="8.0.0" />
<!-- Toolset -->
<PackageVersion Include="Microsoft.CodeAnalysis.Analyzers" Version="3.11.0" />
<PackageVersion Include="Microsoft.CodeAnalysis.CSharp" Version="4.14.0" />
<PackageVersion Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100" />
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers">
@@ -166,17 +149,17 @@
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageVersion Include="Roslynator.Analyzers" Version="4.14.1" />
<PackageVersion Include="Roslynator.Analyzers" Version="[4.14.1]" />
<PackageReference Include="Roslynator.Analyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageVersion Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1" />
<PackageVersion Include="Roslynator.CodeAnalysis.Analyzers" Version="[4.14.0]" />
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageVersion Include="Roslynator.Formatting.Analyzers" Version="4.14.1" />
<PackageVersion Include="Roslynator.Formatting.Analyzers" Version="[4.14.0]" />
<PackageReference Include="Roslynator.Formatting.Analyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+1 -1
View File
@@ -21,7 +21,7 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
var agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
.GetOpenAIResponseClient(deploymentName)
.AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
.CreateAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
+16 -134
View File
@@ -23,29 +23,16 @@
<Project Path="samples/AGUIClientServer/AGUIDojoServer/AGUIDojoServer.csproj" />
<Project Path="samples/AGUIClientServer/AGUIServer/AGUIServer.csproj" />
</Folder>
<Folder Name="/Samples/Durable/" />
<Folder Name="/Samples/Durable/Agents/" />
<Folder Name="/Samples/Durable/Agents/AzureFunctions/">
<File Path="samples/Durable/Agents/AzureFunctions/.editorconfig" />
<File Path="samples/Durable/Agents/AzureFunctions/README.md" />
<Project Path="samples/Durable/Agents/AzureFunctions/01_SingleAgent/01_SingleAgent.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/02_AgentOrchestration_Chaining/02_AgentOrchestration_Chaining.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/03_AgentOrchestration_Concurrency/03_AgentOrchestration_Concurrency.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/06_LongRunningTools/06_LongRunningTools.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
<Project Path="samples/Durable/Agents/AzureFunctions/08_ReliableStreaming/08_ReliableStreaming.csproj" />
</Folder>
<Folder Name="/Samples/Durable/Agents/ConsoleApps/">
<File Path="samples/Durable/Agents/ConsoleApps/README.md" />
<Project Path="samples/Durable/Agents/ConsoleApps/01_SingleAgent/01_SingleAgent.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/02_AgentOrchestration_Chaining/02_AgentOrchestration_Chaining.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/03_AgentOrchestration_Concurrency/03_AgentOrchestration_Concurrency.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/06_LongRunningTools/06_LongRunningTools.csproj" />
<Project Path="samples/Durable/Agents/ConsoleApps/07_ReliableStreaming/07_ReliableStreaming.csproj" />
<Folder Name="/Samples/AzureFunctions/">
<File Path="samples/AzureFunctions/.editorconfig" />
<File Path="samples/AzureFunctions/README.md" />
<Project Path="samples/AzureFunctions/01_SingleAgent/01_SingleAgent.csproj" />
<Project Path="samples/AzureFunctions/02_AgentOrchestration_Chaining/02_AgentOrchestration_Chaining.csproj" />
<Project Path="samples/AzureFunctions/03_AgentOrchestration_Concurrency/03_AgentOrchestration_Concurrency.csproj" />
<Project Path="samples/AzureFunctions/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
<Project Path="samples/AzureFunctions/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
<Project Path="samples/AzureFunctions/06_LongRunningTools/06_LongRunningTools.csproj" />
<Project Path="samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/">
<File Path="samples/GettingStarted/README.md" />
@@ -53,20 +40,15 @@
<Folder Name="/Samples/GettingStarted/A2A/">
<File Path="samples/GettingStarted/A2A/README.md" />
<Project Path="samples/GettingStarted/A2A/A2AAgent_AsFunctionTools/A2AAgent_AsFunctionTools.csproj" />
<Project Path="samples/GettingStarted/A2A/A2AAgent_PollingForTaskCompletion/A2AAgent_PollingForTaskCompletion.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentProviders/">
<File Path="samples/GettingStarted/AgentProviders/README.md" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_A2A/Agent_With_A2A.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_Anthropic/Agent_With_Anthropic.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgentsPersistent/Agent_With_AzureAIAgentsPersistent.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIProject/Agent_With_AzureAIProject.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryAgent/Agent_With_AzureFoundryAgent.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryModel/Agent_With_AzureFoundryModel.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Agent_With_AzureOpenAIChatCompletion.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIResponses/Agent_With_AzureOpenAIResponses.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_GitHubCopilot/Agent_With_GitHubCopilot.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/Agent_With_GoogleGemini.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_ONNX/Agent_With_ONNX.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Agent_With_OpenAIAssistants.csproj" />
@@ -81,7 +63,7 @@
<Project Path="samples/GettingStarted/Agents/Agent_Step04_UsingFunctionToolsWithApprovals/Agent_Step04_UsingFunctionToolsWithApprovals.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step05_StructuredOutput/Agent_Step05_StructuredOutput.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step06_PersistedConversations/Agent_Step06_PersistedConversations.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step07_3rdPartyChatHistoryStorage/Agent_Step07_3rdPartyChatHistoryStorage.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step07_3rdPartyThreadStorage/Agent_Step07_3rdPartyThreadStorage.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step08_Observability/Agent_Step08_Observability.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step09_DependencyInjection/Agent_Step09_DependencyInjection.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step10_AsMcpTool/Agent_Step10_AsMcpTool.csproj" />
@@ -93,46 +75,11 @@
<Project Path="samples/GettingStarted/Agents/Agent_Step16_ChatReduction/Agent_Step16_ChatReduction.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/Agent_Step17_BackgroundResponses.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step18_DeepResearch/Agent_Step18_DeepResearch.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step19_Declarative/Agent_Step19_Declarative.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step20_AdditionalAIContext/Agent_Step20_AdditionalAIContext.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/DeclarativeAgents/">
<Project Path="samples/GettingStarted/DeclarativeAgents/ChatClient/DeclarativeChatClientAgents.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/">
<File Path="samples/GettingStarted/AGUI/README.md" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/Step01_GettingStarted/">
<Project Path="samples/GettingStarted/AGUI/Step01_GettingStarted/Client/Client.csproj" />
<Project Path="samples/GettingStarted/AGUI/Step01_GettingStarted/Server/Server.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/Step02_BackendTools/">
<Project Path="samples/GettingStarted/AGUI/Step02_BackendTools/Client/Client.csproj" />
<Project Path="samples/GettingStarted/AGUI/Step02_BackendTools/Server/Server.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/Step03_FrontendTools/">
<Project Path="samples/GettingStarted/AGUI/Step03_FrontendTools/Client/Client.csproj" />
<Project Path="samples/GettingStarted/AGUI/Step03_FrontendTools/Server/Server.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/Step04_HumanInLoop/">
<Project Path="samples/GettingStarted/AGUI/Step04_HumanInLoop/Client/Client.csproj" />
<Project Path="samples/GettingStarted/AGUI/Step04_HumanInLoop/Server/Server.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AGUI/Step05_StateManagement/">
<Project Path="samples/GettingStarted/AGUI/Step05_StateManagement/Client/Client.csproj" />
<Project Path="samples/GettingStarted/AGUI/Step05_StateManagement/Server/Server.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/DevUI/">
<File Path="samples/GettingStarted/DevUI/README.md" />
<Project Path="samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/DevUI_Step01_BasicUsage.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithAnthropic/">
<File Path="samples/GettingStarted/AgentWithAnthropic/README.md" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step01_Running/Agent_Anthropic_Step01_Running.csproj" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step02_Reasoning/Agent_Anthropic_Step02_Reasoning.csproj" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step03_UsingFunctionTools/Agent_Anthropic_Step03_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step04_UsingSkills/Agent_Anthropic_Step04_UsingSkills.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithMemory/">
<File Path="samples/GettingStarted/AgentWithMemory/README.md" />
<Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step01_ChatHistoryMemory/AgentWithMemory_Step01_ChatHistoryMemory.csproj" />
@@ -143,39 +90,12 @@
<File Path="samples/GettingStarted/AgentWithOpenAI/README.md" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Agent_OpenAI_Step01_Running.csproj" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step02_Reasoning/Agent_OpenAI_Step02_Reasoning.csproj" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step03_CreateFromChatClient/Agent_OpenAI_Step03_CreateFromChatClient.csproj" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient.csproj" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step05_Conversation/Agent_OpenAI_Step05_Conversation.csproj" />
</Folder>
<Folder Name="/Samples/Purview/" />
<Folder Name="/Samples/Purview/AgentWithPurview/">
<Project Path="samples/Purview/AgentWithPurview/AgentWithPurview.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithRAG/">
<File Path="samples/GettingStarted/AgentWithRAG/README.md" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/AgentWithRAG_Step01_BasicTextRAG.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_CustomVectorStoreRAG/AgentWithRAG_Step02_CustomVectorStoreRAG.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step03_CustomRAGDataSource/AgentWithRAG_Step03_CustomRAGDataSource.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/AgentWithRAG_Step04_FoundryServiceRAG.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/FoundryAgents/">
<File Path="samples/GettingStarted/FoundryAgents/README.md" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step01.1_Basics/FoundryAgents_Step01.1_Basics.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step01.2_Running/FoundryAgents_Step01.2_Running.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step02_MultiturnConversation/FoundryAgents_Step02_MultiturnConversation.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step03_UsingFunctionTools/FoundryAgents_Step03_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step04_UsingFunctionToolsWithApprovals/FoundryAgents_Step04_UsingFunctionToolsWithApprovals.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step05_StructuredOutput/FoundryAgents_Step05_StructuredOutput.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step06_PersistedConversations/FoundryAgents_Step06_PersistedConversations.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step07_Observability/FoundryAgents_Step07_Observability.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step08_DependencyInjection/FoundryAgents_Step08_DependencyInjection.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step09_UsingMcpClientAsTools/FoundryAgents_Step09_UsingMcpClientAsTools.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step10_UsingImages/FoundryAgents_Step10_UsingImages.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step11_AsFunctionTool/FoundryAgents_Step11_AsFunctionTool.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step12_Middleware/FoundryAgents_Step12_Middleware.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step13_Plugins/FoundryAgents_Step13_Plugins.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step14_CodeInterpreter/FoundryAgents_Step14_CodeInterpreter.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step15_ComputerUse/FoundryAgents_Step15_ComputerUse.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/ModelContextProtocol/">
<File Path="samples/GettingStarted/ModelContextProtocol/README.md" />
@@ -201,22 +121,13 @@
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Declarative/">
<File Path="samples/GettingStarted/Workflows/Declarative/README.md" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ConfirmInput/ConfirmInput.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/CustomerSupport/CustomerSupport.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/DeepResearch/DeepResearch.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ExecuteCode/ExecuteCode.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ExecuteWorkflow/ExecuteWorkflow.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/FunctionTools/FunctionTools.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/GenerateCode/GenerateCode.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/HostedWorkflow/HostedWorkflow.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/InputArguments/InputArguments.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/Marketing/Marketing.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/StudentTeacher/StudentTeacher.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ToolApproval/ToolApproval.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Declarative/Examples/">
<File Path="../workflow-samples/CustomerSupport.yaml" />
<File Path="../workflow-samples/DeepResearch.yaml" />
<File Path="../workflow-samples/HumanInLoop.yaml" />
<File Path="../workflow-samples/Marketing.yaml" />
<File Path="../workflow-samples/MathChat.yaml" />
<File Path="../workflow-samples/README.md" />
@@ -231,7 +142,6 @@
<Folder Name="/Samples/GettingStarted/Workflows/Agents/">
<Project Path="samples/GettingStarted/Workflows/Agents/CustomAgentExecutors/CustomAgentExecutors.csproj" />
<Project Path="samples/GettingStarted/Workflows/Agents/FoundryAgent/FoundryAgent.csproj" />
<Project Path="samples/GettingStarted/Workflows/Agents/GroupChatToolApproval/GroupChatToolApproval.csproj" />
<Project Path="samples/GettingStarted/Workflows/Agents/WorkflowAsAnAgent/WorkflowAsAnAgent.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Checkpoint/">
@@ -248,7 +158,7 @@
<Project Path="samples/GettingStarted/Workflows/Observability/WorkflowAsAnAgent/WorkflowAsAnAgentObservability.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Visualization/">
<Project Path="samples/GettingStarted/Workflows/Visualization/Visualization.csproj" />
<Project Path="samples/GettingStarted/Workflows/Visualization/Visualization.csproj" Id="99bf0bc6-2440-428e-b3e7-d880e4b7a5fd" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/_Foundational/">
<Project Path="samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj" />
@@ -262,11 +172,8 @@
</Folder>
<Folder Name="/Samples/HostedAgents/">
<Project Path="samples/HostedAgents/AgentsInWorkflows/AgentsInWorkflows.csproj" />
<Project Path="samples/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
<Project Path="samples/HostedAgents/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
</Folder>
<Folder Name="/Samples/M365Agent/">
<Project Path="samples/M365Agent/M365Agent.csproj" />
<Project Path="samples/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
</Folder>
<Folder Name="/Solution Items/">
<File Path=".editorconfig" />
@@ -302,11 +209,6 @@
<File Path="../docs/decisions/0007-agent-filtering-middleware.md" />
<File Path="../docs/decisions/0008-python-subpackages.md" />
<File Path="../docs/decisions/0009-support-long-running-operations.md" />
<File Path="../docs/decisions/0010-ag-ui-support.md" />
<File Path="../docs/decisions/0011-create-get-agent-api.md" />
<File Path="../docs/decisions/0012-python-typeddict-options.md" />
<File Path="../docs/decisions/0013-python-get-response-simplification.md" />
<File Path="../docs/decisions/0014-feature-collections.md" />
<File Path="../docs/decisions/adr-short-template.md" />
<File Path="../docs/decisions/adr-template.md" />
<File Path="../docs/decisions/README.md" />
@@ -372,7 +274,6 @@
<File Path="src/Shared/Demos/SampleEnvironment.cs" />
</Folder>
<Folder Name="/Solution Items/src/Shared/IntegrationTests/">
<File Path="src/Shared/IntegrationTests/AnthropicConfiguration.cs" />
<File Path="src/Shared/IntegrationTests/AzureAIConfiguration.cs" />
<File Path="src/Shared/IntegrationTests/Mem0Configuration.cs" />
<File Path="src/Shared/IntegrationTests/OpenAIConfiguration.cs" />
@@ -397,13 +298,8 @@
<Project Path="src/Microsoft.Agents.AI.A2A/Microsoft.Agents.AI.A2A.csproj" />
<Project Path="src/Microsoft.Agents.AI.Abstractions/Microsoft.Agents.AI.Abstractions.csproj" />
<Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Anthropic/Microsoft.Agents.AI.Anthropic.csproj" />
<Project Path="src/Microsoft.Agents.AI.GitHub.Copilot/Microsoft.Agents.AI.GitHub.Copilot.csproj" />
<Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
<Project Path="src/Microsoft.Agents.AI.AzureAI/Microsoft.Agents.AI.AzureAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
<Project Path="src/Microsoft.Agents.AI.CosmosNoSql/Microsoft.Agents.AI.CosmosNoSql.csproj" />
<Project Path="src/Microsoft.Agents.AI.Declarative/Microsoft.Agents.AI.Declarative.csproj" />
<Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
<Project Path="src/Microsoft.Agents.AI.DurableTask/Microsoft.Agents.AI.DurableTask.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
@@ -414,21 +310,15 @@
<Project Path="src/Microsoft.Agents.AI.Hosting/Microsoft.Agents.AI.Hosting.csproj" />
<Project Path="src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj" />
<Project Path="src/Microsoft.Agents.AI.OpenAI/Microsoft.Agents.AI.OpenAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Purview/Microsoft.Agents.AI.Purview.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.AzureAI/Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative/Microsoft.Agents.AI.Workflows.Declarative.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows.Generators/Microsoft.Agents.AI.Workflows.Generators.csproj" />
<Project Path="src/Microsoft.Agents.AI/Microsoft.Agents.AI.csproj" />
</Folder>
<Folder Name="/Tests/" />
<Folder Name="/Tests/IntegrationTests/">
<Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
<Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.IntegrationTests.csproj" />
<Project Path="tests/AzureAI.IntegrationTests/AzureAI.IntegrationTests.csproj" />
<Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
<Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
@@ -442,13 +332,7 @@
<Project Path="tests/Microsoft.Agents.AI.A2A.UnitTests/Microsoft.Agents.AI.A2A.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Abstractions.UnitTests/Microsoft.Agents.AI.Abstractions.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Anthropic.UnitTests/Microsoft.Agents.AI.Anthropic.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AzureAI.UnitTests/Microsoft.Agents.AI.AzureAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.CosmosNoSql.UnitTests/Microsoft.Agents.AI.CosmosNoSql.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Declarative.UnitTests/Microsoft.Agents.AI.Declarative.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DevUI.UnitTests/Microsoft.Agents.AI.DevUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.UnitTests/Microsoft.Agents.AI.DurableTask.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
@@ -457,10 +341,8 @@
<Project Path="tests/Microsoft.Agents.AI.Hosting.UnitTests/Microsoft.Agents.AI.Hosting.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Mem0.UnitTests/Microsoft.Agents.AI.Mem0.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.OpenAI.UnitTests/Microsoft.Agents.AI.OpenAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Purview.UnitTests/Microsoft.Agents.AI.Purview.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.UnitTests/Microsoft.Agents.AI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.Generators.UnitTests/Microsoft.Agents.AI.Workflows.Generators.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.UnitTests/Microsoft.Agents.AI.Workflows.UnitTests.csproj" />
</Folder>
</Solution>
</Solution>
-33
View File
@@ -1,33 +0,0 @@
{
"solution": {
"path": "agent-framework-dotnet.slnx",
"projects": [
"src\\Microsoft.Agents.AI.A2A\\Microsoft.Agents.AI.A2A.csproj",
"src\\Microsoft.Agents.AI.Abstractions\\Microsoft.Agents.AI.Abstractions.csproj",
"src\\Microsoft.Agents.AI.AGUI\\Microsoft.Agents.AI.AGUI.csproj",
"src\\Microsoft.Agents.AI.Anthropic\\Microsoft.Agents.AI.Anthropic.csproj",
"src\\Microsoft.Agents.AI.GitHub.Copilot\\Microsoft.Agents.AI.GitHub.Copilot.csproj",
"src\\Microsoft.Agents.AI.AzureAI.Persistent\\Microsoft.Agents.AI.AzureAI.Persistent.csproj",
"src\\Microsoft.Agents.AI.AzureAI\\Microsoft.Agents.AI.AzureAI.csproj",
"src\\Microsoft.Agents.AI.CopilotStudio\\Microsoft.Agents.AI.CopilotStudio.csproj",
"src\\Microsoft.Agents.AI.CosmosNoSql\\Microsoft.Agents.AI.CosmosNoSql.csproj",
"src\\Microsoft.Agents.AI.Declarative\\Microsoft.Agents.AI.Declarative.csproj",
"src\\Microsoft.Agents.AI.DevUI\\Microsoft.Agents.AI.DevUI.csproj",
"src\\Microsoft.Agents.AI.DurableTask\\Microsoft.Agents.AI.DurableTask.csproj",
"src\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj",
"src\\Microsoft.Agents.AI.Hosting.A2A\\Microsoft.Agents.AI.Hosting.A2A.csproj",
"src\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj",
"src\\Microsoft.Agents.AI.Hosting.AzureFunctions\\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj",
"src\\Microsoft.Agents.AI.Hosting.OpenAI\\Microsoft.Agents.AI.Hosting.OpenAI.csproj",
"src\\Microsoft.Agents.AI.Hosting\\Microsoft.Agents.AI.Hosting.csproj",
"src\\Microsoft.Agents.AI.Mem0\\Microsoft.Agents.AI.Mem0.csproj",
"src\\Microsoft.Agents.AI.OpenAI\\Microsoft.Agents.AI.OpenAI.csproj",
"src\\Microsoft.Agents.AI.Purview\\Microsoft.Agents.AI.Purview.csproj",
"src\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj",
"src\\Microsoft.Agents.AI.Workflows.Declarative\\Microsoft.Agents.AI.Workflows.Declarative.csproj",
"src\\Microsoft.Agents.AI.Workflows.Generators\\Microsoft.Agents.AI.Workflows.Generators.csproj",
"src\\Microsoft.Agents.AI.Workflows\\Microsoft.Agents.AI.Workflows.csproj",
"src\\Microsoft.Agents.AI\\Microsoft.Agents.AI.csproj"
]
}
}
-9
View File
@@ -11,13 +11,4 @@
<ItemGroup Condition="'$(InjectSharedBuildTestCode)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\CodeTests\*.cs" LinkBase="Shared\CodeTests" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedWorkflowsExecution)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Workflows\Execution\*.cs" LinkBase="Shared\Workflows" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedWorkflowsSettings)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Workflows\Settings\*.cs" LinkBase="Shared\Workflows" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedFoundryAgents)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Foundry\Agents\*.cs" LinkBase="Shared\Foundry" />
</ItemGroup>
</Project>
+2 -2
View File
@@ -1,7 +1,7 @@
{
"sdk": {
"version": "10.0.100",
"rollForward": "minor",
"version": "9.0.300",
"rollForward": "latestMajor",
"allowPrerelease": false
}
}
+3 -3
View File
@@ -2,9 +2,9 @@
<PropertyGroup>
<!-- Central version prefix - applies to all nuget packages. -->
<VersionPrefix>1.0.0</VersionPrefix>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260212.1</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260212.1</PackageVersion>
<GitTag>1.0.0-preview.260212.1</GitTag>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251112.1</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251112.1</PackageVersion>
<GitTag>1.0.0-preview.251112.1</GitTag>
<Configurations>Debug;Release;Publish</Configurations>
<IsPackable>true</IsPackable>
-1
View File
@@ -1,7 +1,6 @@
# Suppressing errors for Sample projects under dotnet/samples folder
[*.cs]
dotnet_diagnostic.CA1716.severity = none # Add summary to documentation comment.
dotnet_diagnostic.CA1873.severity = none # Evaluation of logging arguments may be expensive
dotnet_diagnostic.CA2000.severity = none # Call System.IDisposable.Dispose on object before all references to it are out of scope
dotnet_diagnostic.CA2007.severity = none # Do not directly await a Task
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>5ee045b0-aea3-4f08-8d31-32d1a6f8fed0</UserSecretsId>
@@ -12,6 +12,8 @@
<PackageReference Include="A2A" />
<PackageReference Include="System.CommandLine" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -4,7 +4,6 @@ using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.Logging;
using OpenAI;
using OpenAI.Chat;
namespace A2A;
@@ -29,7 +28,7 @@ internal sealed class HostClientAgent
// Create the agent that uses the remote agents as tools
this.Agent = new OpenAIClient(new ApiKeyCredential(apiKey))
.GetChatClient(modelId)
.AsAIAgent(instructions: "You specialize in handling queries for users and using your tools to provide answers.", name: "HostClient", tools: tools);
.CreateAIAgent(instructions: "You specialize in handling queries for users and using your tools to provide answers.", name: "HostClient", tools: tools);
}
catch (Exception ex)
{
@@ -42,7 +42,7 @@ public static class Program
// Create the Host agent
var hostAgent = new HostClientAgent(loggerFactory);
await hostAgent.InitializeAgentAsync(modelId, apiKey, agentUrls!.Split(";"));
AgentSession session = await hostAgent.Agent!.CreateSessionAsync(cancellationToken);
AgentThread thread = hostAgent.Agent!.GetNewThread();
try
{
while (true)
@@ -61,7 +61,7 @@ public static class Program
break;
}
var agentResponse = await hostAgent.Agent!.RunAsync(message, session, cancellationToken: cancellationToken);
var agentResponse = await hostAgent.Agent!.RunAsync(message, thread, cancellationToken: cancellationToken);
foreach (var chatMessage in agentResponse.Messages)
{
Console.ForegroundColor = ConsoleColor.Cyan;
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>5ee045b0-aea3-4f08-8d31-32d1a6f8fed0</UserSecretsId>
@@ -11,11 +11,8 @@
<ItemGroup>
<PackageReference Include="Azure.AI.Agents.Persistent" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" />
<PackageReference Include="System.Linq.AsyncEnumerable" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -6,7 +6,6 @@ using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI;
using OpenAI.Chat;
namespace A2AServer;
@@ -14,10 +13,7 @@ internal static class HostAgentFactory
{
internal static async Task<(AIAgent, AgentCard)> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string assistantId, IList<AITool>? tools = null)
{
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
PersistentAgent persistentAgent = await persistentAgentsClient.Administration.GetAgentAsync(assistantId);
AIAgent agent = await persistentAgentsClient
@@ -38,7 +34,7 @@ internal static class HostAgentFactory
{
AIAgent agent = new OpenAIClient(apiKey)
.GetChatClient(model)
.AsAIAgent(instructions, name, tools: tools);
.CreateAIAgent(instructions, name, tools: tools);
AgentCard agentCard = agentType.ToUpperInvariant() switch
{
+1 -1
View File
@@ -103,7 +103,7 @@ dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentId "<Log
### Testing the Agents using the Rest Client
This sample contains a [.http file](https://learn.microsoft.com/aspnet/core/test/http-files?view=aspnetcore-10.0) which can be used to test the agent.
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:
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
@@ -11,6 +11,8 @@
<ItemGroup>
<PackageReference Include="System.CommandLine" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -83,12 +83,12 @@ public static class Program
serverUrl,
jsonSerializerOptions: AGUIClientSerializerContext.Default.Options);
AIAgent agent = chatClient.AsAIAgent(
AIAgent agent = chatClient.CreateAIAgent(
name: "agui-client",
description: "AG-UI Client Agent",
tools: [changeBackground, readClientClimateSensors]);
AgentSession session = await agent.CreateSessionAsync(cancellationToken);
AgentThread thread = agent.GetNewThread();
List<ChatMessage> messages = [new(ChatRole.System, "You are a helpful assistant.")];
try
{
@@ -112,23 +112,23 @@ public static class Program
// Call RunStreamingAsync to get streaming updates
bool isFirstUpdate = true;
string? sessionId = null;
string? threadId = null;
var updates = new List<ChatResponseUpdate>();
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, session, cancellationToken: cancellationToken))
await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
{
// Use AsChatResponseUpdate to access ChatResponseUpdate properties
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
updates.Add(chatUpdate);
if (chatUpdate.ConversationId != null)
{
sessionId = chatUpdate.ConversationId;
threadId = chatUpdate.ConversationId;
}
// Display run started information from the first update
if (isFirstUpdate && sessionId != null && update.ResponseId != null)
if (isFirstUpdate && threadId != null && update.ResponseId != null)
{
Console.ForegroundColor = ConsoleColor.Yellow;
Console.WriteLine($"\n[Run Started - Session: {sessionId}, Run: {update.ResponseId}]");
Console.WriteLine($"\n[Run Started - Thread: {threadId}, Run: {update.ResponseId}]");
Console.ResetColor();
isFirstUpdate = false;
}
@@ -177,7 +177,7 @@ public static class Program
var lastUpdate = updates[^1];
Console.ForegroundColor = ConsoleColor.Yellow;
Console.WriteLine();
Console.WriteLine($"[Run Ended - Session: {sessionId}, Run: {lastUpdate.ResponseId}]");
Console.WriteLine($"[Run Ended - Thread: {threadId}, Run: {lastUpdate.ResponseId}]");
Console.ResetColor();
}
messages.Clear();
@@ -201,12 +201,12 @@ public static class Program
{
return "";
}
var builder = new StringBuilder().AppendLine();
var builder = new StringBuilder();
builder.AppendLine();
foreach (var kvp in arguments)
{
builder
.AppendLine($" Name: {kvp.Key}")
.AppendLine($" Value: {kvp.Value}");
builder.AppendLine($" Name: {kvp.Key}");
builder.AppendLine($" Value: {kvp.Value}");
}
return builder.ToString();
}
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>b9c3f1e1-2fb4-5g29-0e52-53e2b7g9gf21</UserSecretsId>
@@ -11,6 +11,8 @@
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -1,10 +1,6 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
using AGUIDojoServer.AgenticUI;
using AGUIDojoServer.BackendToolRendering;
using AGUIDojoServer.PredictiveStateUpdates;
using AGUIDojoServer.SharedState;
namespace AGUIDojoServer;
@@ -12,12 +8,4 @@ namespace AGUIDojoServer;
[JsonSerializable(typeof(Recipe))]
[JsonSerializable(typeof(Ingredient))]
[JsonSerializable(typeof(RecipeResponse))]
[JsonSerializable(typeof(Plan))]
[JsonSerializable(typeof(Step))]
[JsonSerializable(typeof(StepStatus))]
[JsonSerializable(typeof(StepStatus?))]
[JsonSerializable(typeof(JsonPatchOperation))]
[JsonSerializable(typeof(List<JsonPatchOperation>))]
[JsonSerializable(typeof(List<string>))]
[JsonSerializable(typeof(DocumentState))]
internal sealed partial class AGUIDojoServerSerializerContext : JsonSerializerContext;
@@ -1,52 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
namespace AGUIDojoServer.AgenticUI;
internal static class AgenticPlanningTools
{
[Description("Create a plan with multiple steps.")]
public static Plan CreatePlan([Description("List of step descriptions to create the plan.")] List<string> steps)
{
return new Plan
{
Steps = [.. steps.Select(s => new Step { Description = s, Status = StepStatus.Pending })]
};
}
[Description("Update a step in the plan with new description or status.")]
public static async Task<List<JsonPatchOperation>> UpdatePlanStepAsync(
[Description("The index of the step to update.")] int index,
[Description("The new description for the step (optional).")] string? description = null,
[Description("The new status for the step (optional).")] StepStatus? status = null)
{
var changes = new List<JsonPatchOperation>();
if (description is not null)
{
changes.Add(new JsonPatchOperation
{
Op = "replace",
Path = $"/steps/{index}/description",
Value = description
});
}
if (status.HasValue)
{
// Status must be lowercase to match AG-UI frontend expectations: "pending" or "completed"
string statusValue = status.Value == StepStatus.Pending ? "pending" : "completed";
changes.Add(new JsonPatchOperation
{
Op = "replace",
Path = $"/steps/{index}/status",
Value = statusValue
});
}
await Task.Delay(1000);
return changes;
}
}
@@ -1,88 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Diagnostics.CodeAnalysis;
using System.Runtime.CompilerServices;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace AGUIDojoServer.AgenticUI;
[SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by ChatClientAgentFactory.CreateAgenticUI")]
internal sealed class AgenticUIAgent : DelegatingAIAgent
{
private readonly JsonSerializerOptions _jsonSerializerOptions;
public AgenticUIAgent(AIAgent innerAgent, JsonSerializerOptions jsonSerializerOptions)
: base(innerAgent)
{
this._jsonSerializerOptions = jsonSerializerOptions;
}
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
}
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentRunOptions? options = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
// Track function calls that should trigger state events
var trackedFunctionCalls = new Dictionary<string, FunctionCallContent>();
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
{
// Process contents: track function calls and emit state events for results
List<AIContent> stateEventsToEmit = new();
foreach (var content in update.Contents)
{
if (content is FunctionCallContent callContent)
{
if (callContent.Name == "create_plan" || callContent.Name == "update_plan_step")
{
trackedFunctionCalls[callContent.CallId] = callContent;
break;
}
}
else if (content is FunctionResultContent resultContent)
{
// Check if this result matches a tracked function call
if (trackedFunctionCalls.TryGetValue(resultContent.CallId, out var matchedCall))
{
var bytes = JsonSerializer.SerializeToUtf8Bytes((JsonElement)resultContent.Result!, this._jsonSerializerOptions);
// Determine event type based on the function name
if (matchedCall.Name == "create_plan")
{
stateEventsToEmit.Add(new DataContent(bytes, "application/json"));
}
else if (matchedCall.Name == "update_plan_step")
{
stateEventsToEmit.Add(new DataContent(bytes, "application/json-patch+json"));
}
}
}
}
yield return update;
yield return new AgentResponseUpdate(
new ChatResponseUpdate(role: ChatRole.System, stateEventsToEmit)
{
MessageId = "delta_" + Guid.NewGuid().ToString("N"),
CreatedAt = update.CreatedAt,
ResponseId = update.ResponseId,
AuthorName = update.AuthorName,
Role = update.Role,
ContinuationToken = update.ContinuationToken,
AdditionalProperties = update.AdditionalProperties,
})
{
AgentId = update.AgentId
};
}
}
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer.AgenticUI;
internal sealed class JsonPatchOperation
{
[JsonPropertyName("op")]
public required string Op { get; set; }
[JsonPropertyName("path")]
public required string Path { get; set; }
[JsonPropertyName("value")]
public object? Value { get; set; }
[JsonPropertyName("from")]
public string? From { get; set; }
}
@@ -1,11 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer.AgenticUI;
internal sealed class Plan
{
[JsonPropertyName("steps")]
public List<Step> Steps { get; set; } = [];
}
@@ -1,14 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer.AgenticUI;
internal sealed class Step
{
[JsonPropertyName("description")]
public required string Description { get; set; }
[JsonPropertyName("status")]
public StepStatus Status { get; set; } = StepStatus.Pending;
}
@@ -1,12 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer.AgenticUI;
[JsonConverter(typeof(JsonStringEnumConverter<StepStatus>))]
internal enum StepStatus
{
Pending,
Completed
}
@@ -2,10 +2,6 @@
using System.ComponentModel;
using System.Text.Json;
using AGUIDojoServer.AgenticUI;
using AGUIDojoServer.BackendToolRendering;
using AGUIDojoServer.PredictiveStateUpdates;
using AGUIDojoServer.SharedState;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
@@ -24,9 +20,6 @@ internal static class ChatClientAgentFactory
string endpoint = configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
s_deploymentName = configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
s_azureOpenAIClient = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential());
@@ -36,7 +29,7 @@ internal static class ChatClientAgentFactory
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().AsAIAgent(
return chatClient.AsIChatClient().CreateAIAgent(
name: "AgenticChat",
description: "A simple chat agent using Azure OpenAI");
}
@@ -45,7 +38,7 @@ internal static class ChatClientAgentFactory
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().AsAIAgent(
return chatClient.AsIChatClient().CreateAIAgent(
name: "BackendToolRenderer",
description: "An agent that can render backend tools using Azure OpenAI",
tools: [AIFunctionFactory.Create(
@@ -59,7 +52,7 @@ internal static class ChatClientAgentFactory
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().AsAIAgent(
return chatClient.AsIChatClient().CreateAIAgent(
name: "HumanInTheLoopAgent",
description: "An agent that involves human feedback in its decision-making process using Azure OpenAI");
}
@@ -68,102 +61,31 @@ internal static class ChatClientAgentFactory
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().AsAIAgent(
return chatClient.AsIChatClient().CreateAIAgent(
name: "ToolBasedGenerativeUIAgent",
description: "An agent that uses tools to generate user interfaces using Azure OpenAI");
}
public static AIAgent CreateAgenticUI(JsonSerializerOptions options)
public static ChatClientAgent CreateAgenticUI()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
{
Name = "AgenticUIAgent",
Description = "An agent that generates agentic user interfaces using Azure OpenAI",
ChatOptions = new ChatOptions
{
Instructions = """
When planning use tools only, without any other messages.
IMPORTANT:
- Use the `create_plan` tool to set the initial state of the steps
- Use the `update_plan_step` tool to update the status of each step
- Do NOT repeat the plan or summarise it in a message
- Do NOT confirm the creation or updates in a message
- Do NOT ask the user for additional information or next steps
- Do NOT leave a plan hanging, always complete the plan via `update_plan_step` if one is ongoing.
- Continue calling update_plan_step until all steps are marked as completed.
Only one plan can be active at a time, so do not call the `create_plan` tool
again until all the steps in current plan are completed.
""",
Tools = [
AIFunctionFactory.Create(
AgenticPlanningTools.CreatePlan,
name: "create_plan",
description: "Create a plan with multiple steps.",
AGUIDojoServerSerializerContext.Default.Options),
AIFunctionFactory.Create(
AgenticPlanningTools.UpdatePlanStepAsync,
name: "update_plan_step",
description: "Update a step in the plan with new description or status.",
AGUIDojoServerSerializerContext.Default.Options)
],
AllowMultipleToolCalls = false
}
});
return new AgenticUIAgent(baseAgent, options);
return chatClient.AsIChatClient().CreateAIAgent(
name: "AgenticUIAgent",
description: "An agent that generates agentic user interfaces using Azure OpenAI");
}
public static AIAgent CreateSharedState(JsonSerializerOptions options)
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
var baseAgent = chatClient.AsIChatClient().AsAIAgent(
var baseAgent = chatClient.AsIChatClient().CreateAIAgent(
name: "SharedStateAgent",
description: "An agent that demonstrates shared state patterns using Azure OpenAI");
return new SharedStateAgent(baseAgent, options);
}
public static AIAgent CreatePredictiveStateUpdates(JsonSerializerOptions options)
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
{
Name = "PredictiveStateUpdatesAgent",
Description = "An agent that demonstrates predictive state updates using Azure OpenAI",
ChatOptions = new ChatOptions
{
Instructions = """
You are a document editor assistant. When asked to write or edit content:
IMPORTANT:
- Use the `write_document` tool with the full document text in Markdown format
- Format the document extensively so it's easy to read
- You can use all kinds of markdown (headings, lists, bold, etc.)
- However, do NOT use italic or strike-through formatting
- You MUST write the full document, even when changing only a few words
- When making edits to the document, try to make them minimal - do not change every word
- Keep stories SHORT!
- After you are done writing the document you MUST call a confirm_changes tool after you call write_document
After the user confirms the changes, provide a brief summary of what you wrote.
""",
Tools = [
AIFunctionFactory.Create(
WriteDocument,
name: "write_document",
description: "Write a document. Use markdown formatting to format the document.",
AGUIDojoServerSerializerContext.Default.Options)
]
}
});
return new PredictiveStateUpdatesAgent(baseAgent, options);
}
[Description("Get the weather for a given location.")]
private static WeatherInfo GetWeather([Description("The location to get the weather for.")] string location) => new()
{
@@ -173,11 +95,4 @@ internal static class ChatClientAgentFactory
WindSpeed = 10,
FeelsLike = 25
};
[Description("Write a document in markdown format.")]
private static string WriteDocument([Description("The document content to write.")] string document)
{
// Simply return success - the document is tracked via state updates
return "Document written successfully";
}
}
@@ -2,7 +2,7 @@
using System.Text.Json.Serialization;
namespace AGUIDojoServer.SharedState;
namespace AGUIDojoServer;
internal sealed class Ingredient
{
@@ -1,11 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer.PredictiveStateUpdates;
internal sealed class DocumentState
{
[JsonPropertyName("document")]
public string Document { get; set; } = string.Empty;
}
@@ -1,104 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Diagnostics.CodeAnalysis;
using System.Runtime.CompilerServices;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace AGUIDojoServer.PredictiveStateUpdates;
[SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by ChatClientAgentFactory.CreatePredictiveStateUpdates")]
internal sealed class PredictiveStateUpdatesAgent : DelegatingAIAgent
{
private readonly JsonSerializerOptions _jsonSerializerOptions;
private const int ChunkSize = 10; // Characters per chunk for streaming effect
public PredictiveStateUpdatesAgent(AIAgent innerAgent, JsonSerializerOptions jsonSerializerOptions)
: base(innerAgent)
{
this._jsonSerializerOptions = jsonSerializerOptions;
}
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
}
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentRunOptions? options = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
// Track the last emitted document state to avoid duplicates
string? lastEmittedDocument = null;
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
{
// Check if we're seeing a write_document tool call and emit predictive state
bool hasToolCall = false;
string? documentContent = null;
foreach (var content in update.Contents)
{
if (content is FunctionCallContent callContent && callContent.Name == "write_document")
{
hasToolCall = true;
// Try to extract the document argument directly from the dictionary
if (callContent.Arguments?.TryGetValue("document", out var documentValue) == true)
{
documentContent = documentValue?.ToString();
}
}
}
// Always yield the original update first
yield return update;
// If we got a complete tool call with document content, "fake" stream it in chunks
if (hasToolCall && documentContent != null && documentContent != lastEmittedDocument)
{
// Chunk the document content and emit progressive state updates
int startIndex = 0;
if (lastEmittedDocument != null && documentContent.StartsWith(lastEmittedDocument, StringComparison.Ordinal))
{
// Only stream the new portion that was added
startIndex = lastEmittedDocument.Length;
}
// Stream the document in chunks
for (int i = startIndex; i < documentContent.Length; i += ChunkSize)
{
int length = Math.Min(ChunkSize, documentContent.Length - i);
string chunk = documentContent.Substring(0, i + length);
// Prepare predictive state update as DataContent
var stateUpdate = new DocumentState { Document = chunk };
byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
stateUpdate,
this._jsonSerializerOptions.GetTypeInfo(typeof(DocumentState)));
yield return new AgentResponseUpdate(
new ChatResponseUpdate(role: ChatRole.Assistant, [new DataContent(stateBytes, "application/json")])
{
MessageId = "snapshot" + Guid.NewGuid().ToString("N"),
CreatedAt = update.CreatedAt,
ResponseId = update.ResponseId,
AdditionalProperties = update.AdditionalProperties,
AuthorName = update.AuthorName,
ContinuationToken = update.ContinuationToken,
})
{
AgentId = update.AgentId
};
// Small delay to simulate streaming
await Task.Delay(50, cancellationToken).ConfigureAwait(false);
}
lastEmittedDocument = documentContent;
}
}
}
}
@@ -35,13 +35,11 @@ app.MapAGUI("/human_in_the_loop", ChatClientAgentFactory.CreateHumanInTheLoop())
app.MapAGUI("/tool_based_generative_ui", ChatClientAgentFactory.CreateToolBasedGenerativeUI());
app.MapAGUI("/agentic_generative_ui", ChatClientAgentFactory.CreateAgenticUI());
var jsonOptions = app.Services.GetRequiredService<IOptions<Microsoft.AspNetCore.Http.Json.JsonOptions>>();
app.MapAGUI("/agentic_generative_ui", ChatClientAgentFactory.CreateAgenticUI(jsonOptions.Value.SerializerOptions));
app.MapAGUI("/shared_state", ChatClientAgentFactory.CreateSharedState(jsonOptions.Value.SerializerOptions));
app.MapAGUI("/predictive_state_updates", ChatClientAgentFactory.CreatePredictiveStateUpdates(jsonOptions.Value.SerializerOptions));
await app.RunAsync();
public partial class Program;
public partial class Program { }
@@ -2,7 +2,7 @@
using System.Text.Json.Serialization;
namespace AGUIDojoServer.SharedState;
namespace AGUIDojoServer;
internal sealed class Recipe
{
@@ -2,7 +2,7 @@
using System.Text.Json.Serialization;
namespace AGUIDojoServer.SharedState;
namespace AGUIDojoServer;
#pragma warning disable CA1812 // Used for the JsonSchema response format
internal sealed class RecipeResponse
@@ -6,7 +6,7 @@ using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace AGUIDojoServer.SharedState;
namespace AGUIDojoServer;
[SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by ChatClientAgentFactory.CreateSharedState")]
internal sealed class SharedStateAgent : DelegatingAIAgent
@@ -19,21 +19,21 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
this._jsonSerializerOptions = jsonSerializerOptions;
}
protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
return this.RunCoreStreamingAsync(messages, session, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
}
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentThread? thread = null,
AgentRunOptions? options = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
if (options is not ChatClientAgentRunOptions { ChatOptions.AdditionalProperties: { } properties } chatRunOptions ||
!properties.TryGetValue("ag_ui_state", out JsonElement state))
{
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
{
yield return update;
}
@@ -63,8 +63,8 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
var firstRunMessages = messages.Append(stateUpdateMessage);
var allUpdates = new List<AgentResponseUpdate>();
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, session, firstRunOptions, cancellationToken).ConfigureAwait(false))
var allUpdates = new List<AgentRunResponseUpdate>();
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
{
allUpdates.Add(update);
@@ -76,14 +76,14 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
}
}
var response = allUpdates.ToAgentResponse();
var response = allUpdates.ToAgentRunResponse();
if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
{
byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
stateSnapshot,
this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
yield return new AgentResponseUpdate
yield return new AgentRunResponseUpdate
{
Contents = [new DataContent(stateBytes, "application/json")]
};
@@ -98,7 +98,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
ChatRole.System,
[new TextContent("Please provide a concise summary of the state changes in at most two sentences.")]));
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, session, options, cancellationToken).ConfigureAwait(false))
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, thread, options, cancellationToken).ConfigureAwait(false))
{
yield return update;
}
@@ -2,7 +2,7 @@
using System.Text.Json.Serialization;
namespace AGUIDojoServer.BackendToolRendering;
namespace AGUIDojoServer;
internal sealed class WeatherInfo
{
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
@@ -11,6 +11,8 @@
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -6,7 +6,7 @@ using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
using OpenAI;
WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
builder.Services.AddHttpClient().AddLogging();
@@ -19,14 +19,11 @@ string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new In
string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
// Create the AI agent with tools
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
var agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsAIAgent(
.CreateAIAgent(
name: "AGUIAssistant",
tools: [
AIFunctionFactory.Create(
+8 -8
View File
@@ -119,7 +119,7 @@ The `AGUIServer` uses the `MapAGUI` extension method to expose an agent through
```csharp
AIAgent agent = new OpenAIClient(apiKey)
.GetChatClient(model)
.AsAIAgent(
.CreateAIAgent(
instructions: "You are a helpful assistant.",
name: "AGUIAssistant");
@@ -144,16 +144,16 @@ var chatClient = new AGUIChatClient(
modelId: "agui-client",
jsonSerializerOptions: null);
AIAgent agent = chatClient.AsAIAgent(
AIAgent agent = chatClient.CreateAIAgent(
instructions: null,
name: "agui-client",
description: "AG-UI Client Agent",
tools: []);
bool isFirstUpdate = true;
AgentResponseUpdate? currentUpdate = null;
AgentRunResponseUpdate? currentUpdate = null;
await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
{
// First update indicates run started
if (isFirstUpdate)
@@ -190,19 +190,19 @@ if (currentUpdate != null)
The `RunStreamingAsync` method:
1. Sends messages to the server via HTTP POST
2. Receives server-sent events (SSE) stream
3. Parses events into `AgentResponseUpdate` objects
3. Parses events into `AgentRunResponseUpdate` objects
4. Yields updates as they arrive for real-time display
## Key Concepts
- **Thread**: Represents a conversation context that persists across multiple runs (accessed via `ConversationId` property)
- **Run**: A single execution of the agent for a given set of messages (identified by `ResponseId` property)
- **AgentResponseUpdate**: Contains the response data with:
- **AgentRunResponseUpdate**: Contains the response data with:
- `ResponseId`: The unique run identifier
- `ConversationId`: The thread/conversation identifier
- `Contents`: Collection of content items (TextContent, ErrorContent, etc.)
- **Run Lifecycle**:
- The **first** `AgentResponseUpdate` in a run indicates the run has started
- The **first** `AgentRunResponseUpdate` in a run indicates the run has started
- Subsequent updates contain streaming content as the agent processes
- The **last** `AgentResponseUpdate` in a run indicates the run has finished
- The **last** `AgentRunResponseUpdate` in a run indicates the run has finished
- If an error occurs, the update will contain `ErrorContent`
@@ -1,14 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<BlazorDisableThrowNavigationException>true</BlazorDisableThrowNavigationException>
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
</ItemGroup>
</Project>
@@ -1,23 +0,0 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<base href="/" />
<link rel="stylesheet" href="app.css" />
<link rel="stylesheet" href="AGUIWebChatClient.styles.css" />
<link rel="icon" type="image/png" href="favicon.png" />
<HeadOutlet @rendermode="@renderMode" />
</head>
<body>
<Routes @rendermode="@renderMode" />
<script src="_framework/blazor.web.js"></script>
</body>
</html>
@code {
private readonly IComponentRenderMode renderMode = new InteractiveServerRenderMode(prerender: false);
}

Some files were not shown because too many files have changed in this diff Show More