Files
agent-framework/python/samples/04-hosting/durabletask/01_single_agent/client.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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3.7 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
"""Client application for interacting with a Durable Task hosted agent.
This client connects to the Durable Task Scheduler and sends requests to
registered agents, demonstrating how to interact with agents from external processes.
Prerequisites:
- The worker must be running with the agent registered
- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
(plus AZURE_OPENAI_API_KEY or Azure CLI authentication)
- Durable Task Scheduler must be running
"""
import asyncio
import logging
import os
from agent_framework.azure import DurableAIAgentClient
from azure.identity import DefaultAzureCredential
from durabletask.azuremanaged.client import DurableTaskSchedulerClient
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def get_client(
taskhub: str | None = None,
endpoint: str | None = None,
log_handler: logging.Handler | None = None
) -> DurableAIAgentClient:
"""Create a configured DurableAIAgentClient.
Args:
taskhub: Task hub name (defaults to TASKHUB env var or "default")
endpoint: Scheduler endpoint (defaults to ENDPOINT env var or "http://localhost:8080")
log_handler: Optional logging handler for client logging
Returns:
Configured DurableAIAgentClient instance
"""
taskhub_name = taskhub or os.getenv("TASKHUB", "default")
endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080")
logger.debug(f"Using taskhub: {taskhub_name}")
logger.debug(f"Using endpoint: {endpoint_url}")
credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential()
dts_client = DurableTaskSchedulerClient(
host_address=endpoint_url,
secure_channel=endpoint_url != "http://localhost:8080",
taskhub=taskhub_name,
token_credential=credential,
log_handler=log_handler
)
return DurableAIAgentClient(dts_client)
def run_client(agent_client: DurableAIAgentClient) -> None:
"""Run client interactions with the Joker agent.
Args:
agent_client: The DurableAIAgentClient instance
"""
# Get a reference to the Joker agent
logger.debug("Getting reference to Joker agent...")
joker = agent_client.get_agent("Joker")
# Create a new session for the conversation
session = joker.create_session()
logger.debug(f"Session ID: {session.session_id}")
logger.info("Start chatting with the Joker agent! (Type 'exit' to quit)")
# Interactive conversation loop
while True:
# Get user input
try:
user_message = input("You: ").strip()
except (EOFError, KeyboardInterrupt):
logger.info("\nExiting...")
break
# Check for exit command
if user_message.lower() == "exit":
logger.info("Goodbye!")
break
# Skip empty messages
if not user_message:
continue
# Send message to agent and get response
try:
response = joker.run(user_message, session=session)
logger.info(f"Joker: {response.text} \n")
except Exception as e:
logger.error(f"Error getting response: {e}")
logger.info("Conversation completed.")
async def main() -> None:
"""Main entry point for the client application."""
logger.debug("Starting Durable Task Agent Client...")
# Create client using helper function
agent_client = get_client()
try:
run_client(agent_client)
except Exception as e:
logger.exception(f"Error during agent interaction: {e}")
finally:
logger.debug("Client shutting down")
if __name__ == "__main__":
asyncio.run(main())