Auto-finalize ResponseStream on iteration completion

python/samples/01-get-started/03b_multi_turn_streaming.py

@@ -0,0 +1,75 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+
+from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Multi-Turn Streaming — Combine streaming output with session history
+
+This sample shows how to stream responses while maintaining conversation
+history across turns. The key is calling get_final_response() after
+iterating the stream, which persists messages to the session.
+
+Without get_final_response(), the session history is not updated and
+the agent will not remember previous turns.
+
+Environment variables:
+  AZURE_AI_PROJECT_ENDPOINT        — Your Azure AI Foundry project endpoint
+  AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME — Model deployment name (e.g. gpt-4o)
+"""
+
+
+async def main() -> None:
+    # 1. Create the client and agent.
+    credential = AzureCliCredential()
+    client = AzureOpenAIResponsesClient(
+        project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+        deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
+        credential=credential,
+    )
+
+    agent = client.as_agent(
+        name="ConversationAgent",
+        instructions="You are a friendly assistant. Keep your answers brief.",
+    )
+
+    # 2. Create a session to maintain conversation history.
+    session = agent.create_session()
+
+    # 3. First turn — stream the response, then finalize to save history.
+    print("Agent: ", end="")
+    stream = agent.run("My name is Alice and I love hiking.", session=session, stream=True)
+    async for chunk in stream:
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+    await stream.get_final_response()  # Persists messages to the session
+    print("\n")
+
+    # 4. Second turn — the agent remembers context from the first turn.
+    print("Agent: ", end="")
+    stream = agent.run("What do you remember about me?", session=session, stream=True)
+    async for chunk in stream:
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+    await stream.get_final_response()
+    print()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
+
+"""
+Sample output:
+
+Agent: Hi Alice! That's awesome — hiking is such a great way to stay active
+and enjoy nature. Do you have a favorite trail or spot you like to hike?
+
+Agent: You're Alice, and you love hiking!
+"""

python/samples/01-get-started/README.md

@@ -22,7 +22,8 @@ export AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="gpt-4o"   # optional, defaults to
 |---|------|-------------------|
 | 1 | [01_hello_agent.py](01_hello_agent.py) | Create your first agent and run it (streaming and non-streaming). |
 | 2 | [02_add_tools.py](02_add_tools.py) | Define a function tool with `@tool` and attach it to an agent. |
-| 3 | [03_multi_turn.py](03_multi_turn.py) | Keep conversation history across turns with `AgentThread`. |
+| 3a | [03a_multi_turn.py](03a_multi_turn.py) | Keep conversation history across turns with `AgentSession`. |
+| 3b | [03b_multi_turn_streaming.py](03b_multi_turn_streaming.py) | Multi-turn conversations with streaming responses. |
 | 4 | [04_memory.py](04_memory.py) | Add dynamic context with a custom `ContextProvider`. |
 | 5 | [05_first_workflow.py](05_first_workflow.py) | Chain executors into a workflow with edges. |
 | 6 | [06_host_your_agent.py](06_host_your_agent.py) | Host a single agent with Azure Functions. |

python/samples/README.md

@@ -18,7 +18,8 @@ Start with `01-get-started/` and work through the numbered files:
 
 1. **[01_hello_agent.py](./01-get-started/01_hello_agent.py)** — Create and run your first agent
 2. **[02_add_tools.py](./01-get-started/02_add_tools.py)** — Add function tools with `@tool`
-3. **[03_multi_turn.py](./01-get-started/03_multi_turn.py)** — Multi-turn conversations with `AgentThread`
+3. **[03a_multi_turn.py](./01-get-started/03a_multi_turn.py)** — Multi-turn conversations with `AgentSession`
+3b. **[03b_multi_turn_streaming.py](./01-get-started/03b_multi_turn_streaming.py)** — Multi-turn streaming conversations
 4. **[04_memory.py](./01-get-started/04_memory.py)** — Agent memory with `ContextProvider`
 5. **[05_first_workflow.py](./01-get-started/05_first_workflow.py)** — Build a workflow with executors and edges
 6. **[06_host_your_agent.py](./01-get-started/06_host_your_agent.py)** — Host your agent via Azure Functions