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Eduard van Valkenburg
1e350ea22f
* 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
1e350ea22f
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2026-02-12 21:00:32 +00:00
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Single Agent Sample (Python)
This sample demonstrates how to use the Durable Extension for Agent Framework to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
Key Concepts Demonstrated
- Defining a simple agent with the Microsoft Agent Framework and wiring it into an Azure Functions app via the Durable Extension for Agent Framework.
- Calling the agent through generated HTTP endpoints (
/api/agents/Joker/run). - Managing conversation state with session identifiers, so multiple clients can interact with the agent concurrently without sharing context.
Prerequisites
Follow the common setup steps in ../README.md to install tooling, configure Azure OpenAI credentials, and install the Python dependencies for this sample.
Running the Sample
Send a prompt to the Joker agent:
Bash (Linux/macOS/WSL):
curl -i -X POST http://localhost:7071/api/agents/Joker/run \
-d "Tell me a short joke about cloud computing."
PowerShell:
Invoke-RestMethod -Method Post -Uri http://localhost:7071/api/agents/Joker/run `
-Body "Tell me a short joke about cloud computing."
The agent responds with a JSON payload that includes the generated joke.
Tip
To return immediately with an HTTP 202 response instead of waiting for the agent output, set the
x-ms-wait-for-responseheader or include"wait_for_response": falsein the request body. The default behavior waits for the response.
Expected Output
The default plain-text response looks like the following:
HTTP/1.1 200 OK
Content-Type: text/plain; charset=utf-8
x-ms-thread-id: 4f205157170244bfbd80209df383757e
Why did the cloud break up with the server?
Because it found someone more "uplifting"!
When you specify the x-ms-wait-for-response header or include "wait_for_response": false in the request body, the Functions host responds with an HTTP 202 and queues the request to run in the background. A typical response body looks like the following:
{
"status": "accepted",
"response": "Agent request accepted",
"message": "Tell me a short joke about cloud computing.",
"thread_id": "<guid>",
"correlation_id": "<guid>"
}