mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
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
76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from typing import Annotated, Any
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import anyio
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from agent_framework import tool
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from agent_framework.openai import OpenAIResponsesClient
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"""
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This sample demonstrates how to expose an Agent as an MCP server.
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To run this sample, set up your MCP host (like Claude Desktop or VSCode GitHub Copilot Agents)
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with the following configuration:
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```json
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{
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"servers": {
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"agent-framework": {
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"command": "uv",
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"args": [
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"--directory=<path to project>/agent-framework/python/samples/getting_started/mcp",
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"run",
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"agent_as_mcp_server.py"
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],
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"env": {
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"OPENAI_API_KEY": "<OpenAI API key>",
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"OPENAI_RESPONSES_MODEL_ID": "<OpenAI Responses model ID>",
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}
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}
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}
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}
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```
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
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@tool(approval_mode="never_require")
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def get_specials() -> Annotated[str, "Returns the specials from the menu."]:
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return """
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Special Soup: Clam Chowder
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Special Salad: Cobb Salad
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Special Drink: Chai Tea
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"""
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@tool(approval_mode="never_require")
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def get_item_price(
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menu_item: Annotated[str, "The name of the menu item."],
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) -> Annotated[str, "Returns the price of the menu item."]:
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return "$9.99"
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async def run() -> None:
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# Define an agent
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# Agent's name and description provide better context for AI model
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agent = OpenAIResponsesClient().as_agent(
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name="RestaurantAgent",
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description="Answer questions about the menu.",
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tools=[get_specials, get_item_price],
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)
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# Expose the agent as an MCP server
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server = agent.as_mcp_server()
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# Run server
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from mcp.server.stdio import stdio_server
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async def handle_stdin(stdin: Any | None = None, stdout: Any | None = None) -> None:
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async with stdio_server() as (read_stream, write_stream):
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await server.run(read_stream, write_stream, server.create_initialization_options())
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await handle_stdin()
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if __name__ == "__main__":
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anyio.run(run)
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