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agent-framework/python/samples/02-agents/background_responses.py
T
Eduard van Valkenburg 1e350ea22f Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)
* PR2: Wire context provider pipeline and update all internal consumers

- Replace AgentThread with AgentSession across all packages
- Replace ContextProvider with BaseContextProvider across all packages
- Replace context_provider param with context_providers (Sequence)
- Replace thread= with session= in run() signatures
- Replace get_new_thread() with create_session()
- Add get_session(service_session_id) to agent interface
- DurableAgentThread -> DurableAgentSession
- Remove _notify_thread_of_new_messages from WorkflowAgent
- Wire before_run/after_run context provider pipeline in RawAgent
- Auto-inject InMemoryHistoryProvider when no providers configured

* fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files

* refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider)

* fix: update remaining ag-ui references (client docstring, getting_started sample)

* fix: make get_session service_session_id keyword-only to avoid confusion with session_id

* refactor: rename _RunContext.thread_messages to session_messages

* refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists

* rename: remove _new_ prefix from test files

* refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider)

* fix: read full history from session state directly instead of reaching into provider internals

* fix: update stale .pyi stubs, sample imports, and README references for new provider types

* fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples

* refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider

* refactor: UserInfoMemory stores state in session.state instead of instance attributes

* feat: add Pydantic BaseModel support to session state serialization

Pydantic models stored in session.state are now automatically serialized
via model_dump() and restored via model_validate() during to_dict()/from_dict()
round-trips. Models are auto-registered on first serialization; use
register_state_type() for cold-start deserialization.

Also export register_state_type as a public API.

* fix mem0

* Update sample README links and descriptions for session terminology

- Replace 'thread' with 'session' in sample descriptions across all READMEs
- Update file links for renamed samples (mem0_sessions, redis_sessions, etc.)
- Fix Threads section → Sessions section in main samples/README.md
- Update tools, middleware, workflows, durabletask, azure_functions READMEs
- Update architecture diagrams in concepts/tools/README.md
- Update migration guides (autogen, semantic-kernel)

* Fix broken Redis README link to renamed sample

* Fix Mem0 OSS client search: pass scoping params as direct kwargs

AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs,
while AsyncMemoryClient (Platform) expects them in a filters dict.
Adds tests for both client types.

Port of fix from #3844 to new Mem0ContextProvider.

* Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic

- Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase
- Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages
- Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests
- Add tests/workflow/__init__.py for relative import support
- Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep)

* Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection

Chat clients that store history server-side by default (OpenAI Responses API,
Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this
during auto-injection and skips InMemoryHistoryProvider unless the user
explicitly sets store=False.

* Fix broken markdown links in azure_ai and redis READMEs

* Fix getting-started samples to use session API instead of removed thread/ContextProvider API

* updates to workflow as agent

* fix group chat import

* Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread

- Fix: Propagate conversation_id from ChatResponse back to session.service_session_id
  in both streaming and non-streaming paths in _agents.py
- Rename AgentThreadException → AgentSessionException
- Remove stale AGUIThread from ag_ui lazy-loader
- Rename use_service_thread → use_service_session in ag-ui package
- Rename test functions from *_thread_* to *_session_*
- Rename sample files from *_thread* to *_session*
- Update docstrings and comments: thread → session
- Update _mcp.py kwargs filter: add 'session' alongside 'thread'
- Fix ContinuationToken docstring example: thread=thread → session=session
- Fix _clients.py docstring: 'Agent threads' → 'Agent sessions'

* Fix broken markdown links after thread→session file renames

* fix azure ai test
2026-02-12 21:00:32 +00:00

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# Copyright (c) Microsoft. All rights reserved.
import asyncio
from agent_framework import Agent
from agent_framework.openai import OpenAIResponsesClient
"""Background Responses Sample.
This sample demonstrates long-running agent operations using the OpenAI
Responses API ``background`` option. Two patterns are shown:
1. **Non-streaming polling** start a background run, then poll with the
``continuation_token`` until the operation completes.
2. **Streaming with resumption** start a background streaming run, simulate
an interruption, and resume from the last ``continuation_token``.
Prerequisites:
- Set the ``OPENAI_API_KEY`` environment variable.
- A model that benefits from background execution (e.g. ``o3``).
"""
# 1. Create the agent with an OpenAI Responses client.
agent = Agent(
name="researcher",
instructions="You are a helpful research assistant. Be concise.",
client=OpenAIResponsesClient(model_id="o3"),
)
async def non_streaming_polling() -> None:
"""Demonstrate non-streaming background run with polling."""
print("=== Non-Streaming Polling ===\n")
session = agent.create_session()
# 2. Start a background run — returns immediately.
response = await agent.run(
messages="Briefly explain the theory of relativity in two sentences.",
session=session,
options={"background": True},
)
print(f"Initial status: continuation_token={'set' if response.continuation_token else 'None'}")
# 3. Poll until the operation completes.
poll_count = 0
while response.continuation_token is not None:
poll_count += 1
await asyncio.sleep(2)
response = await agent.run(
session=session,
options={"continuation_token": response.continuation_token},
)
print(f" Poll {poll_count}: continuation_token={'set' if response.continuation_token else 'None'}")
# 4. Done — print the final result.
print(f"\nResult ({poll_count} poll(s)):\n{response.text}\n")
async def streaming_with_resumption() -> None:
"""Demonstrate streaming background run with simulated interruption and resumption."""
print("=== Streaming with Resumption ===\n")
session = agent.create_session()
# 2. Start a streaming background run.
last_token = None
stream = agent.run(
messages="Briefly list three benefits of exercise.",
stream=True,
session=session,
options={"background": True},
)
# 3. Read some chunks, then simulate an interruption.
chunk_count = 0
print("First stream (before interruption):")
async for update in stream:
last_token = update.continuation_token
if update.text:
print(update.text, end="", flush=True)
chunk_count += 1
if chunk_count >= 3:
print("\n [simulated interruption]")
break
# 4. Resume from the last continuation token.
if last_token is not None:
print("Resumed stream:")
stream = agent.run(
stream=True,
session=session,
options={"continuation_token": last_token},
)
async for update in stream:
if update.text:
print(update.text, end="", flush=True)
print("\n")
async def main() -> None:
await non_streaming_polling()
await streaming_with_resumption()
if __name__ == "__main__":
asyncio.run(main())
"""
Sample output:
=== Non-Streaming Polling ===
Initial status: continuation_token=set
Poll 1: continuation_token=set
Poll 2: continuation_token=None
Result (2 poll(s)):
The theory of relativity, developed by Albert Einstein, consists of special
relativity (1905), which shows that the laws of physics are the same for all
non-accelerating observers and that the speed of light is constant, and general
relativity (1915), which describes gravity as the curvature of spacetime caused
by mass and energy.
=== Streaming with Resumption ===
First stream (before interruption):
Here are three
[simulated interruption]
Resumed stream:
key benefits of regular exercise:
1. **Improved cardiovascular health** ...
2. **Better mental health** ...
3. **Stronger muscles and bones** ...
"""