Python: add(azure-ai): support reasoning config for AzureAIClient (#3403)

* add(azure-ai): support reasoning config for AzureAIClient

* Update sample

* Merge main

* improvements

* improve sample

python/packages/azure-ai/agent_framework_azure_ai/_client.py

@@ -22,12 +22,7 @@ from agent_framework.observability import use_instrumentation
 from agent_framework.openai import OpenAIResponsesOptions
 from agent_framework.openai._responses_client import OpenAIBaseResponsesClient
 from azure.ai.projects.aio import AIProjectClient
-from azure.ai.projects.models import (
-    MCPTool,
-    PromptAgentDefinition,
-    PromptAgentDefinitionText,
-    RaiConfig,
-)
+from azure.ai.projects.models import MCPTool, PromptAgentDefinition, PromptAgentDefinitionText, RaiConfig, Reasoning
 from azure.core.credentials_async import AsyncTokenCredential
 from azure.core.exceptions import ResourceNotFoundError
 from pydantic import ValidationError
@@ -51,12 +46,15 @@ else:
 logger = get_logger("agent_framework.azure")
 
 
-class AzureAIProjectAgentOptions(OpenAIResponsesOptions):
+class AzureAIProjectAgentOptions(OpenAIResponsesOptions, total=False):
     """Azure AI Project Agent options."""
 
     rai_config: RaiConfig
     """Configuration for Responsible AI (RAI) content filtering and safety features."""
 
+    reasoning: Reasoning  # type: ignore[misc]
+    """Configuration for enabling reasoning capabilities (requires azure.ai.projects.models.Reasoning)."""
+
 
 TAzureAIClientOptions = TypeVar(
     "TAzureAIClientOptions",
@@ -343,6 +341,10 @@ class AzureAIClient(OpenAIBaseResponsesClient[TAzureAIClientOptions], Generic[TA
                 args["temperature"] = run_options["temperature"]
             if "top_p" in run_options:
                 args["top_p"] = run_options["top_p"]
+            if "reasoning" in run_options:
+                args["reasoning"] = run_options["reasoning"]
+            if "rai_config" in run_options:
+                args["rai_config"] = run_options["rai_config"]
 
             # response_format is accessed from chat_options or additional_properties
             # since the base class excludes it from run_options
@@ -408,6 +410,7 @@ class AzureAIClient(OpenAIBaseResponsesClient[TAzureAIClientOptions], Generic[TA
             "top_p",
             "text",
             "text_format",
+            "reasoning",
         ]
 
         for property in exclude:

python/packages/azure-ai/agent_framework_azure_ai/_project_provider.py

@@ -195,6 +195,7 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
         opts = dict(default_options) if default_options else {}
         response_format = opts.get("response_format")
         rai_config = opts.get("rai_config")
+        reasoning = opts.get("reasoning")
 
         args: dict[str, Any] = {"model": resolved_model}
 
@@ -206,6 +207,8 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
             )
         if rai_config:
             args["rai_config"] = rai_config
+        if reasoning:
+            args["reasoning"] = reasoning
 
         # Normalize tools and separate MCP tools from other tools
         normalized_tools = normalize_tools(tools)

python/packages/azure-ai/tests/test_provider.py

@@ -251,6 +251,50 @@ async def test_provider_create_agent_with_rai_config(
         assert definition.rai_config is mock_rai_config
 
 
+async def test_provider_create_agent_with_reasoning(
+    mock_project_client: MagicMock,
+    azure_ai_unit_test_env: dict[str, str],
+) -> None:
+    """Test AzureAIProjectAgentProvider.create_agent passes reasoning from default_options."""
+    with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
+        mock_settings.return_value.project_endpoint = azure_ai_unit_test_env["AZURE_AI_PROJECT_ENDPOINT"]
+        mock_settings.return_value.model_deployment_name = azure_ai_unit_test_env["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
+
+        provider = AzureAIProjectAgentProvider(project_client=mock_project_client)
+
+        # Mock agent creation response
+        mock_agent_version = MagicMock(spec=AgentVersionDetails)
+        mock_agent_version.id = "agent-id"
+        mock_agent_version.name = "test-agent"
+        mock_agent_version.version = "1.0"
+        mock_agent_version.description = None
+        mock_agent_version.definition = MagicMock(spec=PromptAgentDefinition)
+        mock_agent_version.definition.model = "gpt-5.2"
+        mock_agent_version.definition.instructions = None
+        mock_agent_version.definition.temperature = None
+        mock_agent_version.definition.top_p = None
+        mock_agent_version.definition.tools = []
+
+        mock_project_client.agents.create_version = AsyncMock(return_value=mock_agent_version)
+
+        # Create a mock Reasoning-like object
+        mock_reasoning = MagicMock()
+        mock_reasoning.effort = "medium"
+        mock_reasoning.summary = "concise"
+
+        # Call create_agent with reasoning in default_options
+        await provider.create_agent(
+            name="test-agent",
+            model="gpt-5.2",
+            default_options={"reasoning": mock_reasoning},
+        )
+
+        # Verify reasoning was passed to PromptAgentDefinition
+        call_args = mock_project_client.agents.create_version.call_args
+        definition = call_args[1]["definition"]
+        assert definition.reasoning is mock_reasoning
+
+
 async def test_provider_get_agent_with_name(mock_project_client: MagicMock) -> None:
     """Test AzureAIProjectAgentProvider.get_agent with name parameter."""
     provider = AzureAIProjectAgentProvider(project_client=mock_project_client)

python/samples/getting_started/agents/azure_ai/README.md

@@ -36,6 +36,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_ai_with_memory_search.py`](azure_ai_with_memory_search.py) | Shows how to use memory search functionality with Azure AI agents for conversation persistence. Demonstrates creating memory stores and enabling agents to search through conversation history. |
 | [`azure_ai_with_microsoft_fabric.py`](azure_ai_with_microsoft_fabric.py) | Shows how to use Microsoft Fabric with Azure AI agents to query Fabric data sources and provide responses based on data analysis. Requires a Microsoft Fabric connection configured in your Azure AI project. |
 | [`azure_ai_with_openapi.py`](azure_ai_with_openapi.py) | Shows how to integrate OpenAPI specifications with Azure AI agents using dictionary-based tool configuration. Demonstrates using external REST APIs for dynamic data lookup. |
+| [`azure_ai_with_reasoning.py`](azure_ai_with_reasoning.py) | Shows how to enable reasoning for a model that supports it. |
 | [`azure_ai_with_web_search.py`](azure_ai_with_web_search.py) | Shows how to use the `HostedWebSearchTool` with Azure AI agents to perform web searches and retrieve up-to-date information from the internet. |
 
 ## Environment Variables

python/samples/getting_started/agents/azure_ai/azure_ai_with_reasoning.py

@@ -0,0 +1,94 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework.azure import AzureAIProjectAgentProvider
+from azure.ai.projects.models import Reasoning
+from azure.identity.aio import AzureCliCredential
+
+"""
+Azure AI Agent with Reasoning Example
+
+Demonstrates how to enable reasoning capabilities using the Reasoning option.
+Shows both non-streaming and streaming approaches, including how to access
+reasoning content (type="text_reasoning") separately from answer content.
+
+Requires a reasoning-capable model (e.g., gpt-5.2) deployed in your Azure AI Project configured
+as `AZURE_AI_MODEL_DEPLOYMENT_NAME` in your environment.
+"""
+
+
+async def non_streaming_example() -> None:
+    """Example of non-streaming response (get the complete result at once)."""
+    print("=== Non-streaming Response Example ===")
+
+    # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
+    # authentication option.
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIProjectAgentProvider(credential=credential) as provider,
+    ):
+        agent = await provider.create_agent(
+            name="ReasoningWeatherAgent",
+            instructions="You are a helpful weather agent who likes to understand the underlying physics.",
+            default_options={"reasoning": Reasoning(effort="medium", summary="concise")},
+        )
+
+        query = "How does the Bernoulli effect work?"
+        print(f"User: {query}")
+        result = await agent.run(query)
+
+        for msg in result.messages:
+            for content in msg.contents:
+                if content.type == "text_reasoning":
+                    print(f"[Reasoning]: {content.text}")
+                elif content.type == "text":
+                    print(f"[Answer]: {content.text}")
+            print()
+
+
+async def streaming_example() -> None:
+    """Example of streaming response (get results as they are generated)."""
+    print("=== Streaming Response Example ===")
+
+    # For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
+    # authentication option.
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIProjectAgentProvider(credential=credential) as provider,
+    ):
+        agent = await provider.create_agent(
+            name="ReasoningWeatherAgent",
+            instructions="You are a helpful weather agent who likes to understand the underlying physics.",
+            default_options={"reasoning": Reasoning(effort="medium", summary="concise")},
+        )
+
+        query = "Help explain how air updrafts work?"
+        print(f"User: {query}")
+
+        shown_reasoning_label = False
+        shown_text_label = False
+        async for chunk in agent.run_stream(query):
+            for content in chunk.contents:
+                if content.type == "text_reasoning":
+                    if not shown_reasoning_label:
+                        print("[Reasoning]: ", end="", flush=True)
+                        shown_reasoning_label = True
+                    print(content.text, end="", flush=True)
+                elif content.type == "text":
+                    if not shown_text_label:
+                        print("\n\n[Answer]: ", end="", flush=True)
+                        shown_text_label = True
+                    print(content.text, end="", flush=True)
+        print("\n")
+
+
+async def main() -> None:
+    print("=== Azure AI Agent with Reasoning Example ===")
+
+    # await non_streaming_example()
+    await streaming_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())