Files
agent-framework/dotnet/samples/02-agents/Agents/Agent_Step02_StructuredOutput/Program.cs
T
westey 8b191de936 Merge and move scripts (#4308)
* .NET: Add Microsoft Fabric sample #3674 (#4230)

Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>

* Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)

* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference

Add embedding client implementations to existing provider packages:

- OllamaEmbeddingClient: Text embeddings via Ollama's embed API
- BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock
- AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI
  Inference, supporting Content | str input with separate model IDs for
  text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image
  (AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints

Additional changes:
- Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT
- Add otel_provider_name passthrough to all embedding clients
- Register integration pytest marker in all packages
- Add lazy-loading namespace exports for Ollama and Bedrock embeddings
- Add image embedding sample using Cohere-embed-v3-english
- Add azure-ai-inference dependency to azure-ai package

Part of #1188

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix mypy duplicate name and ruff lint issues

- Rename second 'vector' variable to 'img_vector' in image embedding loop
- Combine nested with statements in tests
- Remove unused result assignments in tests

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* updates from feedback

* Fix CI failures in embedding usage handling

- Fix Azure AI embedding mypy issues by normalizing vectors to list[float],
  safely accumulating optional usage token fields, and filtering None entries
  before constructing GeneratedEmbeddings
- Avoid Bandit false positive by initializing usage details as an empty dict
- Update OpenAI embedding tests to assert canonical usage keys
  (input_token_count/total_token_count)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* [Purview] Mark responses as responses and fix epoch bug for python long overflow (#4225)

* .NET: Support InvokeMcpTool for declarative workflows (#4204)

* Initial implementation of InvokeMcpTool in declarative workflow

* Cleaned up sample implementation

* Updated sample comments.

* Added missing executor routing attribute

* Fix PR comments.

* Updated based on PR comments.

* Updated based on PR comments.

* Removed unnecessary using statement.

* Update Python package versions to rc2 (#4258)

- Bump core and azure-ai to 1.0.0rc2
- Bump preview packages to 1.0.0b260225
- Update dependencies to >=1.0.0rc2
- Add CHANGELOG entries for changes since rc1
- Update uv.lock

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* .NET: Fixing issue where OpenTelemetry span is never exported in .NET in-process workflow execution (#4196)

* 1. Add reproduction test for issue #4155: workflow.run Activity never stopped in streaming OffThread path

The WorkflowRunActivity_IsStopped_Streaming_OffThread test demonstrates that
the workflow.run OpenTelemetry Activity created in StreamingRunEventStream.RunLoopAsync
is started but never stopped when using the OffThread/Default streaming execution.
The background run loop keeps running after event consumption completes, so the
using Activity? declaration never disposes until explicit StopAsync() is called.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

2. Fix workflow.run Activity never stopped in streaming OffThread execution (#4155)

The workflow.run OpenTelemetry Activity in StreamingRunEventStream.RunLoopAsync
was scoped to the method lifetime via 'using'. Since the run loop only exits on
cancellation, the Activity was never stopped/exported until explicit disposal.

Fix: Remove 'using' and explicitly dispose the Activity when the workflow reaches
Idle status (all supersteps complete). A safety-net disposal in the finally block
handles cancellation and error paths.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Add root-level workflow.session activity spanning run loop lifetime\n\nImplements two-level telemetry hierarchy per PR feedback from lokitoth:\n- workflow.session: spans the entire run loop / stream lifetime\n- workflow_invoke: per input-to-halt cycle, nested within the session\n\nThis ensures the session activity stays open across multiple turns,\nwhile individual run activities are created and disposed per cycle.\n\nAlso fixes linkedSource CancellationTokenSource disposal leak in\nStreamingRunEventStream (added using declaration)."

* Address Copilot review: fix Activity/CTS disposal, rename activity, add error tag\n\n1. LockstepRunEventStream: Remove 'using' from Activity in async iterator\n   and manually dispose in finally block (fixes #4155 pattern). Also dispose\n   linkedSource CTS in finally to prevent leak.\n2. Tags.cs: Add ErrorMessage (\"error.message\") tag for runtime errors,\n   distinct from BuildErrorMessage (\"build.error.message\").\n3. ActivityNames: Rename WorkflowRun from \"workflow_invoke\" to \"workflow.run\"\n   for cross-language consistency.\n4. WorkflowTelemetryContext: Fix XML doc to say \"outer/parent span\" instead\n   of \"root-level span\".\n5. ObservabilityTests: Assert WorkflowSession absence when DisableWorkflowRun\n   is true.\n6. WorkflowRunActivityStopTests: Fix streaming test race by disposing\n   StreamingRun before asserting activities are stopped.\n7. StreamingRunEventStream/LockstepRunEventStream: Use Tags.ErrorMessage\n   instead of Tags.BuildErrorMessage for runtime error events."

* Review fixes: revert workflow_invoke rename, use 'using' for linkedSource, move SessionStarted earlier\n\n- Revert ActivityNames.WorkflowRun back to \"workflow_invoke\" (OTEL semantic convention contract)\n- Use 'using' declaration for linkedSource CTS in LockstepRunEventStream (no timing sensitivity)\n- Move SessionStarted event before WaitForInputAsync in StreamingRunEventStream to match Lockstep behavior"

* Improve naming and comments in WorkflowRunActivityStopTests"

* Prevent session Activity.Current leak in lockstep mode, add nesting test

Save and restore Activity.Current in LockstepRunEventStream.Start() so the
session activity doesn't leak into caller code via AsyncLocal. Re-establish
Activity.Current = sessionActivity before creating the run activity in
TakeEventStreamAsync to preserve parent-child nesting.

Add test verifying app activities after RunAsync are not parented under the
session, and that the workflow_invoke activity nests under the session."

* Fix stale XML doc: WorkflowRun -> WorkflowInvoke in ObservabilityTests

---------

Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python / .NET Samples - Restructure and Improve Samples (Feature Branc… (#4092)

* Python: .NET Samples - Restructure and Improve Samples (Feature Branch) (#4091)

* Moved by agent (#4094)

* Fix readme links

* .NET Samples - Create `04-hosting` learning path step (#4098)

* Agent move

* Agent reorderd

* Remove A2A section from README 

Removed A2A section from the Getting Started README.

* Agent fixed links

* Fix broken sample links in durable-agents README (#4101)

* Initial plan

* Fix broken internal links in documentation

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Revert template link changes; keep only durable-agents README fix

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `03-workflows` learning path step (#4102)

* Fix solution project path

* Python: Fix broken markdown links to repo resources (outside /docs) (#4105)

* Initial plan

* Fix broken markdown links to repo resources

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update README to rename .NET Workflows Samples section

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `02-agents` learning path step (#4107)

* .NET: Fix broken relative link in GroupChatToolApproval README (#4108)

* Initial plan

* Fix broken link in GroupChatToolApproval README

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update labeler configuration for workflow samples

* .NET - Reorder Agents samples to start from Step01 instead of Step04 (#4110)

* Fix solution

* Resolve new sample paths

* Move new AgentSkills and AgentWithMemory_Step04 samples

* Fix link

* Fix readme path

* fix: update stale dotnet/samples/Durable path reference in AGENTS.md

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Moved new sample

* Update solution

* Resolve merge (new sample)

* Sync to new sample - FoundryAgents_Step21_BingCustomSearch

* Updated README

* .NET Samples - Configuration Naming Update (#4149)

* .NET: Restore AzureFunctions index parity with ConsoleApps under DurableAgents samples (#4221)

* Clean-up `05_host_your_agent`

* Config setting consistency

* Refine samples

* AGENTS.md

* Move new samples

* Re-order samples

* Move new project and fixup solution

* Fixup model config

* Fix up new UT project

---------

Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>

* Python: Fix Bedrock embedding test stub missing meta attribute (#4287)

* Fix Bedrock embedding test stub missing meta attribute

* Increase test coverage so gate passes

* Python: (ag-ui): fix approval payloads being re-processed on subsequent conversation turns (#4232)

* Fix ag-ui tool call issue

* Safe json fix

* Python: Update workflow orchestration samples to use AzureOpenAIResponsesClient (#4285)

* Update workflow orchestration samples to use AzureOpenAIResponsesClient

* Fix broken link

* Move scripts to scripts folder

---------

Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Rishabh Chawla <rishabhchawla1995@gmail.com>
Co-authored-by: Peter Ibekwe <109177538+peibekwe@users.noreply.github.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>
Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-02-26 10:49:07 +00:00

184 lines
8.8 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to configure ChatClientAgent to produce structured output.
using System.ComponentModel;
using System.Text.Json;
using System.Text.Json.Serialization;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
using SampleApp;
using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// Create chat client to be used by chat client agents.
// 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.
ChatClient chatClient = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName);
// Demonstrates how to work with structured output via ResponseFormat with the non-generic RunAsync method.
// This approach is useful when:
// a. Structured output is used for inter-agent communication, where one agent produces structured output
// and passes it as text to another agent as input, without the need for the caller to directly work with the structured output.
// b. The type of the structured output is not known at compile time, so the generic RunAsync<T> method cannot be used.
// c. The type of the structured output is represented by JSON schema only, without a corresponding class or type in the code.
await UseStructuredOutputWithResponseFormatAsync(chatClient);
// Demonstrates how to work with structured output via the generic RunAsync<T> method.
// This approach is useful when the caller needs to directly work with the structured output in the code
// via an instance of the corresponding class or type and the type is known at compile time.
await UseStructuredOutputWithRunAsync(chatClient);
// Demonstrates how to work with structured output when streaming using the RunStreamingAsync method.
await UseStructuredOutputWithRunStreamingAsync(chatClient);
// Demonstrates how to add structured output support to agents that don't natively support it using the structured output middleware.
// This approach is useful when working with agents that don't support structured output natively, or agents using models
// that don't have the capability to produce structured output, allowing you to still leverage structured output features by transforming
// the text output from the agent into structured data using a chat client.
await UseStructuredOutputWithMiddlewareAsync(chatClient);
static async Task UseStructuredOutputWithResponseFormatAsync(ChatClient chatClient)
{
Console.WriteLine("=== Structured Output with ResponseFormat ===");
// Create the agent
AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions()
{
Name = "HelpfulAssistant",
ChatOptions = new()
{
Instructions = "You are a helpful assistant.",
// Specify CityInfo as the type parameter of ForJsonSchema to indicate the expected structured output from the agent.
ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<CityInfo>()
}
});
// Invoke the agent with some unstructured input to extract the structured information from.
AgentResponse response = await agent.RunAsync("Provide information about the capital of France.");
// Access the structured output via the Text property of the agent response as JSON in scenarios when JSON as text is required
// and no object instance is needed (e.g., for logging, forwarding to another service, or storing in a database).
Console.WriteLine("Assistant Output (JSON):");
Console.WriteLine(response.Text);
Console.WriteLine();
// Deserialize the JSON text to work with the structured object in scenarios when you need to access properties,
// perform operations, or pass the data to methods that require the typed object instance.
CityInfo cityInfo = JsonSerializer.Deserialize<CityInfo>(response.Text)!;
Console.WriteLine("Assistant Output (Deserialized):");
Console.WriteLine($"Name: {cityInfo.Name}");
Console.WriteLine();
}
static async Task UseStructuredOutputWithRunAsync(ChatClient chatClient)
{
Console.WriteLine("=== Structured Output with RunAsync<T> ===");
// Create the agent
AIAgent agent = chatClient.AsAIAgent(name: "HelpfulAssistant", instructions: "You are a helpful assistant.");
// Set CityInfo as the type parameter of RunAsync method to specify the expected structured output from the agent and invoke it with some unstructured input.
AgentResponse<CityInfo> response = await agent.RunAsync<CityInfo>("Provide information about the capital of France.");
// Access the structured output via the Result property of the agent response.
CityInfo cityInfo = response.Result;
Console.WriteLine("Assistant Output:");
Console.WriteLine($"Name: {cityInfo.Name}");
Console.WriteLine();
}
static async Task UseStructuredOutputWithRunStreamingAsync(ChatClient chatClient)
{
Console.WriteLine("=== Structured Output with RunStreamingAsync ===");
// Create the agent
AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions()
{
Name = "HelpfulAssistant",
ChatOptions = new()
{
Instructions = "You are a helpful assistant.",
// Specify CityInfo as the type parameter of ForJsonSchema to indicate the expected structured output from the agent.
ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<CityInfo>()
}
});
// Invoke the agent with some unstructured input while streaming, to extract the structured information from.
IAsyncEnumerable<AgentResponseUpdate> updates = agent.RunStreamingAsync("Provide information about the capital of France.");
// Assemble all the parts of the streamed output.
AgentResponse nonGenericResponse = await updates.ToAgentResponseAsync();
// Access the structured output by deserializing JSON in the Text property.
CityInfo cityInfo = JsonSerializer.Deserialize<CityInfo>(nonGenericResponse.Text)!;
Console.WriteLine("Assistant Output:");
Console.WriteLine($"Name: {cityInfo.Name}");
Console.WriteLine();
}
static async Task UseStructuredOutputWithMiddlewareAsync(ChatClient chatClient)
{
Console.WriteLine("=== Structured Output with UseStructuredOutput Middleware ===");
// Create chat client that will transform the agent text response into structured output.
IChatClient meaiChatClient = chatClient.AsIChatClient();
// Create the agent
AIAgent agent = meaiChatClient.AsAIAgent(name: "HelpfulAssistant", instructions: "You are a helpful assistant.");
// Add structured output middleware via UseStructuredOutput method to add structured output support to the agent.
// This middleware transforms the agent's text response into structured data using a chat client.
// Since our agent does support structured output natively, we will add a middleware that removes ResponseFormat
// from the AgentRunOptions to emulate an agent that doesn't support structured output natively
agent = agent
.AsBuilder()
.UseStructuredOutput(meaiChatClient)
.Use(ResponseFormatRemovalMiddleware, null)
.Build();
// Set CityInfo as the type parameter of RunAsync method to specify the expected structured output from the agent and invoke it with some unstructured input.
AgentResponse<CityInfo> response = await agent.RunAsync<CityInfo>("Provide information about the capital of France.");
// Access the structured output via the Result property of the agent response.
CityInfo cityInfo = response.Result;
Console.WriteLine("Assistant Output:");
Console.WriteLine($"Name: {cityInfo.Name}");
Console.WriteLine();
}
static Task<AgentResponse> ResponseFormatRemovalMiddleware(IEnumerable<ChatMessage> messages, AgentSession? session, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
{
// Remove any ResponseFormat from the options to emulate an agent that doesn't support structured output natively.
options = options?.Clone();
options?.ResponseFormat = null;
return innerAgent.RunAsync(messages, session, options, cancellationToken);
}
namespace SampleApp
{
/// <summary>
/// Represents information about a city, including its name.
/// </summary>
[Description("Information about a city")]
public sealed class CityInfo
{
[JsonPropertyName("name")]
public string? Name { get; set; }
}
}