Python: Added examples for Azure OpenAI Responses agent (#363)

* Added examples for Azure OpenAI Responses agent

* Update python/samples/getting_started/agents/azure_responses_client/azure_responses_client_with_code_interpreter.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

python/samples/getting_started/agents/azure_responses_client/azure_responses_client_basic.py

@@ -0,0 +1,63 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from random import randint
+from typing import Annotated
+
+from agent_framework import ChatClientAgent
+from agent_framework.azure import AzureResponsesClient
+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 non_streaming_example() -> None:
+    """Example of non-streaming response (get the complete result at once)."""
+    print("=== Non-streaming Response Example ===")
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful weather agent.",
+        tools=get_weather,
+    )
+
+    query = "What's the weather like in Seattle?"
+    print(f"User: {query}")
+    result = await agent.run(query)
+    print(f"Result: {result}\n")
+
+
+async def streaming_example() -> None:
+    """Example of streaming response (get results as they are generated)."""
+    print("=== Streaming Response Example ===")
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful weather agent.",
+        tools=get_weather,
+    )
+
+    query = "What's the weather like in Portland?"
+    print(f"User: {query}")
+    print("Agent: ", end="", flush=True)
+    async for chunk in agent.run_streaming(query):
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+    print("\n")
+
+
+async def main() -> None:
+    print("=== Basic Azure OpenAI Responses Client Agent Example ===")
+
+    await non_streaming_example()
+    await streaming_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/getting_started/agents/azure_responses_client/azure_responses_client_with_code_interpreter.py

@@ -0,0 +1,38 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import ChatClientAgent, ChatResponse, HostedCodeInterpreterTool
+from agent_framework.azure import AzureResponsesClient
+from openai.types.responses.response import Response as OpenAIResponse
+from openai.types.responses.response_code_interpreter_tool_call import ResponseCodeInterpreterToolCall
+
+
+async def main() -> None:
+    """Example showing how to use the HostedCodeInterpreterTool with Azure OpenAI Responses."""
+    print("=== Azure OpenAI Responses Agent with Code Interpreter Example ===")
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful assistant that can write and execute Python code to solve problems.",
+        tools=HostedCodeInterpreterTool(),
+    )
+
+    query = "Use code to calculate the factorial of 100?"
+    print(f"User: {query}")
+    result = await agent.run(query)
+    print(f"Result: {result}\n")
+
+    if (
+        isinstance(result.raw_representation, ChatResponse)
+        and isinstance(result.raw_representation.raw_representation, OpenAIResponse)
+        and len(result.raw_representation.raw_representation.output) > 0
+        and isinstance(result.raw_representation.raw_representation.output[0], ResponseCodeInterpreterToolCall)
+    ):
+        generated_code = result.raw_representation.raw_representation.output[0].code
+
+        print(f"Generated code:\n{generated_code}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/getting_started/agents/azure_responses_client/azure_responses_client_with_function_tools.py

@@ -0,0 +1,120 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from datetime import datetime, timezone
+from random import randint
+from typing import Annotated
+
+from agent_framework import ChatClientAgent
+from agent_framework.azure import AzureResponsesClient
+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."
+
+
+def get_time() -> str:
+    """Get the current UTC time."""
+    current_time = datetime.now(timezone.utc)
+    return f"The current UTC time is {current_time.strftime('%Y-%m-%d %H:%M:%S')}."
+
+
+async def tools_on_agent_level() -> None:
+    """Example showing tools defined when creating the agent."""
+    print("=== Tools Defined on Agent Level ===")
+
+    # Tools are provided when creating the agent
+    # The agent can use these tools for any query during its lifetime
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful assistant that can provide weather and time information.",
+        tools=[get_weather, get_time],  # Tools defined at agent creation
+    )
+
+    # First query - agent can use weather tool
+    query1 = "What's the weather like in New York?"
+    print(f"User: {query1}")
+    result1 = await agent.run(query1)
+    print(f"Agent: {result1}\n")
+
+    # Second query - agent can use time tool
+    query2 = "What's the current UTC time?"
+    print(f"User: {query2}")
+    result2 = await agent.run(query2)
+    print(f"Agent: {result2}\n")
+
+    # Third query - agent can use both tools if needed
+    query3 = "What's the weather in London and what's the current UTC time?"
+    print(f"User: {query3}")
+    result3 = await agent.run(query3)
+    print(f"Agent: {result3}\n")
+
+
+async def tools_on_run_level() -> None:
+    """Example showing tools passed to the run method."""
+    print("=== Tools Passed to Run Method ===")
+
+    # Agent created without tools
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful assistant.",
+        # No tools defined here
+    )
+
+    # First query with weather tool
+    query1 = "What's the weather like in Seattle?"
+    print(f"User: {query1}")
+    result1 = await agent.run(query1, tools=[get_weather])  # Tool passed to run method
+    print(f"Agent: {result1}\n")
+
+    # Second query with time tool
+    query2 = "What's the current UTC time?"
+    print(f"User: {query2}")
+    result2 = await agent.run(query2, tools=[get_time])  # Different tool for this query
+    print(f"Agent: {result2}\n")
+
+    # Third query with multiple tools
+    query3 = "What's the weather in Chicago and what's the current UTC time?"
+    print(f"User: {query3}")
+    result3 = await agent.run(query3, tools=[get_weather, get_time])  # Multiple tools
+    print(f"Agent: {result3}\n")
+
+
+async def mixed_tools_example() -> None:
+    """Example showing both agent-level tools and run-method tools."""
+    print("=== Mixed Tools Example (Agent + Run Method) ===")
+
+    # Agent created with some base tools
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a comprehensive assistant that can help with various information requests.",
+        tools=[get_weather],  # Base tool available for all queries
+    )
+
+    # Query using both agent tool and additional run-method tools
+    query = "What's the weather in Denver and what's the current UTC time?"
+    print(f"User: {query}")
+
+    # Agent has access to get_weather (from creation) + additional tools from run method
+    result = await agent.run(
+        query,
+        tools=[get_time],  # Additional tools for this specific query
+    )
+    print(f"Agent: {result}\n")
+
+
+async def main() -> None:
+    print("=== Azure OpenAI Responses Client Agent with Function Tools Examples ===\n")
+
+    await tools_on_agent_level()
+    await tools_on_run_level()
+    await mixed_tools_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/getting_started/agents/azure_responses_client/azure_responses_client_with_thread.py

@@ -0,0 +1,144 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from random import randint
+from typing import Annotated
+
+from agent_framework import ChatClientAgent, ChatClientAgentThread
+from agent_framework.azure import AzureResponsesClient
+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 example_with_automatic_thread_creation() -> None:
+    """Example showing automatic thread creation."""
+    print("=== Automatic Thread Creation Example ===")
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful weather agent.",
+        tools=get_weather,
+    )
+
+    # First conversation - no thread provided, will be created automatically
+    query1 = "What's the weather like in Seattle?"
+    print(f"User: {query1}")
+    result1 = await agent.run(query1)
+    print(f"Agent: {result1.text}")
+
+    # Second conversation - still no thread provided, will create another new thread
+    query2 = "What was the last city I asked about?"
+    print(f"\nUser: {query2}")
+    result2 = await agent.run(query2)
+    print(f"Agent: {result2.text}")
+    print("Note: Each call creates a separate thread, so the agent doesn't remember previous context.\n")
+
+
+async def example_with_thread_persistence_in_memory() -> None:
+    """
+    Example showing thread persistence across multiple conversations.
+    In this example, messages are stored in-memory.
+    """
+    print("=== Thread Persistence Example (In-Memory) ===")
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful weather agent.",
+        tools=get_weather,
+    )
+
+    # Create a new thread that will be reused
+    thread = agent.get_new_thread()
+    assert isinstance(thread, ChatClientAgentThread)
+
+    # First conversation
+    query1 = "What's the weather like in Tokyo?"
+    print(f"User: {query1}")
+    result1 = await agent.run(query1, thread=thread)
+    print(f"Agent: {result1.text}")
+    print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
+
+    # Second conversation using the same thread - maintains context
+    query2 = "How about London?"
+    print(f"\nUser: {query2}")
+    result2 = await agent.run(query2, thread=thread)
+    print(f"Agent: {result2.text}")
+    print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
+
+    # Third conversation - agent should remember both previous cities
+    query3 = "Which of the cities I asked about has better weather?"
+    print(f"\nUser: {query3}")
+    result3 = await agent.run(query3, thread=thread)
+    print(f"Agent: {result3.text}")
+    print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
+    print("Note: The agent remembers context from previous messages in the same thread.\n")
+
+
+async def example_with_existing_thread_id() -> None:
+    """
+    Example showing how to work with an existing thread ID from the service.
+    In this example, messages are stored on the server using Azure OpenAI conversation state.
+    """
+    print("=== Existing Thread ID Example ===")
+
+    # First, create a conversation and capture the thread ID
+    existing_thread_id = None
+
+    agent = ChatClientAgent(
+        chat_client=AzureResponsesClient(),
+        instructions="You are a helpful weather agent.",
+        tools=get_weather,
+    )
+
+    # Start a conversation and get the thread ID
+    thread = agent.get_new_thread()
+    assert isinstance(thread, ChatClientAgentThread)
+
+    query1 = "What's the weather in Paris?"
+    print(f"User: {query1}")
+    # Enable Azure OpenAI conversation state by setting `store` parameter to True
+    result1 = await agent.run(query1, thread=thread, store=True)
+    print(f"Agent: {result1.text}")
+    print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
+
+    # The thread ID is set after the first response
+    existing_thread_id = thread.id
+    print(f"Thread ID: {existing_thread_id}")
+
+    if existing_thread_id:
+        print("\n--- Continuing with the same thread ID in a new agent instance ---")
+
+        agent = ChatClientAgent(
+            chat_client=AzureResponsesClient(),
+            instructions="You are a helpful weather agent.",
+            tools=get_weather,
+        )
+
+        # Create a thread with the existing ID
+        thread = ChatClientAgentThread(id=existing_thread_id)
+
+        query2 = "What was the last city I asked about?"
+        print(f"User: {query2}")
+        result2 = await agent.run(query2, thread=thread, store=True)
+        print(f"Agent: {result2.text}")
+        print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
+        print("Note: The agent continues the conversation from the previous thread by using thread ID.\n")
+
+
+async def main() -> None:
+    print("=== Azure OpenAI Response Client Agent Thread Management Examples ===\n")
+
+    await example_with_automatic_thread_creation()
+    await example_with_thread_persistence_in_memory()
+    await example_with_existing_thread_id()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/getting_started/agents/openai_responses_client/openai_responses_client_with_thread.py

@@ -129,7 +129,7 @@ async def example_with_existing_thread_id() -> None:
         result2 = await agent.run(query2, thread=thread, store=True)
         print(f"Agent: {result2.text}")
         print(f"Thread contains {len(thread.chat_messages or [])} messages in-memory.")
-        print("Note: The agent continues the conversation from the previous thread.\n")
+        print("Note: The agent continues the conversation from the previous thread by using thread ID.\n")
 
 
 async def main() -> None: