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* 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
133 lines
4.9 KiB
Python
133 lines
4.9 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from collections.abc import Awaitable, Callable
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from random import randint
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from typing import Annotated
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from agent_framework import (
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FunctionInvocationContext,
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tool,
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)
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from agent_framework.azure import AzureAIAgentClient
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from azure.identity.aio import AzureCliCredential
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from pydantic import Field
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"""
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Shared State Function-based MiddlewareTypes Example
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This sample demonstrates how to implement function-based middleware within a class to share state.
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The example includes:
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- A MiddlewareContainer class with two simple function middleware methods
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- First middleware: Counts function calls and stores the count in shared state
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- Second middleware: Uses the shared count to add call numbers to function results
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This approach shows how middleware can work together by sharing state within the same class instance.
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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_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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@tool(approval_mode="never_require")
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def get_time(
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timezone: Annotated[str, Field(description="The timezone to get the time for.")] = "UTC",
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) -> str:
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"""Get the current time for a given timezone."""
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import datetime
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return f"The current time in {timezone} is {datetime.datetime.now().strftime('%H:%M:%S')}"
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class MiddlewareContainer:
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"""Container class that holds middleware functions with shared state."""
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def __init__(self) -> None:
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# Simple shared state: count function calls
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self.call_count: int = 0
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async def call_counter_middleware(
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self,
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context: FunctionInvocationContext,
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call_next: Callable[[], Awaitable[None]],
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) -> None:
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"""First middleware: increments call count in shared state."""
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# Increment the shared call count
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self.call_count += 1
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print(f"[CallCounter] This is function call #{self.call_count}")
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# Call the next middleware/function
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await call_next()
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async def result_enhancer_middleware(
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self,
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context: FunctionInvocationContext,
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call_next: Callable[[], Awaitable[None]],
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) -> None:
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"""Second middleware: uses shared call count to enhance function results."""
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print(f"[ResultEnhancer] Current total calls so far: {self.call_count}")
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# Call the next middleware/function
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await call_next()
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# After function execution, enhance the result using shared state
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if context.result:
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enhanced_result = f"[Call #{self.call_count}] {context.result}"
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context.result = enhanced_result
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print("[ResultEnhancer] Enhanced result with call number")
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async def main() -> None:
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"""Example demonstrating shared state function-based middleware."""
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print("=== Shared State Function-based MiddlewareTypes Example ===")
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# Create middleware container with shared state
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middleware_container = MiddlewareContainer()
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="UtilityAgent",
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instructions="You are a helpful assistant that can provide weather information and current time.",
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tools=[get_weather, get_time],
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# Pass both middleware functions from the same container instance
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# Order matters: counter runs first to increment count,
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# then result enhancer uses the updated count
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middleware=[
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middleware_container.call_counter_middleware,
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middleware_container.result_enhancer_middleware,
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],
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) as agent,
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):
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# Test multiple requests to see shared state in action
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queries = [
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"What's the weather like in New York?",
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"What time is it in London?",
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"What's the weather in Tokyo?",
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]
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for i, query in enumerate(queries, 1):
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print(f"\n--- Query {i} ---")
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text if result.text else 'No response'}")
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# Display final statistics
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print("\n=== Final Statistics ===")
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print(f"Total function calls made: {middleware_container.call_count}")
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if __name__ == "__main__":
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asyncio.run(main())
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