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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
182 lines
6.3 KiB
Python
182 lines
6.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Sample weather agent for Agent Framework Debug UI."""
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import logging
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import os
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from collections.abc import AsyncIterable, Awaitable, Callable
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from typing import Annotated
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from agent_framework import (
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Agent,
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ChatContext,
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ChatResponse,
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ChatResponseUpdate,
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Content,
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FunctionInvocationContext,
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Message,
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MiddlewareTermination,
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ResponseStream,
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Role,
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chat_middleware,
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function_middleware,
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tool,
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)
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from agent_framework.azure import AzureOpenAIChatClient
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from agent_framework_devui import register_cleanup
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logger = logging.getLogger(__name__)
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def cleanup_resources():
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"""Cleanup function that runs when DevUI shuts down."""
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logger.info("=" * 60)
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logger.info(" Cleaning up resources...")
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logger.info(" (In production, this would close credentials, sessions, etc.)")
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logger.info("=" * 60)
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@chat_middleware
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async def security_filter_middleware(
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context: ChatContext,
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call_next: Callable[[], Awaitable[None]],
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) -> None:
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"""Chat middleware that blocks requests containing sensitive information."""
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blocked_terms = ["password", "secret", "api_key", "token"]
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# Check only the last message (most recent user input)
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last_message = context.messages[-1] if context.messages else None
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if last_message and last_message.role == Role.USER and last_message.text:
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message_lower = last_message.text.lower()
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for term in blocked_terms:
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if term in message_lower:
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error_message = (
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"I cannot process requests containing sensitive information. "
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"Please rephrase your question without including passwords, secrets, "
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"or other sensitive data."
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)
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if context.stream:
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# Streaming mode: wrap in ResponseStream
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async def blocked_stream(msg: str = error_message) -> AsyncIterable[ChatResponseUpdate]:
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yield ChatResponseUpdate(
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contents=[Content.from_text(text=msg)],
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role=Role.ASSISTANT,
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)
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response = ChatResponse(
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messages=[Message(role=Role.ASSISTANT, text=error_message)]
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)
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context.result = ResponseStream(blocked_stream(), finalizer=lambda _, r=response: r)
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else:
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# Non-streaming mode: return complete response
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context.result = ChatResponse(
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messages=[
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Message(
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role=Role.ASSISTANT,
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text=error_message,
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)
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]
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)
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raise MiddlewareTermination(result=context.result)
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await call_next()
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@function_middleware
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async def atlantis_location_filter_middleware(
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context: FunctionInvocationContext,
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call_next: Callable[[], Awaitable[None]],
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) -> None:
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"""Function middleware that blocks weather requests for Atlantis."""
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# Check if location parameter is "atlantis"
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location = getattr(context.arguments, "location", None)
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if location and location.lower() == "atlantis":
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context.result = (
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"Blocked! Hold up right there!! Tell the user that "
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"'Atlantis is a special place, we must never ask about the weather there!!'"
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)
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raise MiddlewareTermination(result=context.result)
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await call_next()
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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, "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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temperature = 53
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return f"The weather in {location} is {conditions[0]} with a high of {temperature}°C."
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@tool(approval_mode="never_require")
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def get_forecast(
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location: Annotated[str, "The location to get the forecast for."],
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days: Annotated[int, "Number of days for forecast"] = 3,
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) -> str:
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"""Get weather forecast for multiple days."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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forecast: list[str] = []
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for day in range(1, days + 1):
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condition = conditions[0]
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temp = 53
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forecast.append(f"Day {day}: {condition}, {temp}°C")
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return f"Weather forecast for {location}:\n" + "\n".join(forecast)
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@tool(approval_mode="always_require")
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def send_email(
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recipient: Annotated[str, "The email address of the recipient."],
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subject: Annotated[str, "The subject of the email."],
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body: Annotated[str, "The body content of the email."],
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) -> str:
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"""Simulate sending an email."""
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return f"Email sent to {recipient} with subject '{subject}'."
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# Agent instance following Agent Framework conventions
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agent = Agent(
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name="AzureWeatherAgent",
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description="A helpful agent that provides weather information and forecasts",
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instructions="""
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You are a weather assistant. You can provide current weather information
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and forecasts for any location. Always be helpful and provide detailed
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weather information when asked.
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""",
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client=AzureOpenAIChatClient(
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api_key=os.environ.get("AZURE_OPENAI_API_KEY", ""),
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),
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tools=[get_weather, get_forecast, send_email],
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middleware=[security_filter_middleware, atlantis_location_filter_middleware],
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)
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# Register cleanup hook - demonstrates resource cleanup on shutdown
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register_cleanup(agent, cleanup_resources)
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def main():
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"""Launch the Azure weather agent in DevUI."""
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import logging
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from agent_framework.devui import serve
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# Setup logging
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logging.basicConfig(level=logging.INFO, format="%(message)s")
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logger = logging.getLogger(__name__)
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logger.info("Starting Azure Weather Agent")
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logger.info("Available at: http://localhost:8090")
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logger.info("Entity ID: agent_AzureWeatherAgent")
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# Launch server with the agent
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serve(entities=[agent], port=8090, auto_open=True)
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if __name__ == "__main__":
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main()
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