mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
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
191 lines
6.0 KiB
Python
191 lines
6.0 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
|
|
|
|
import asyncio
|
|
import random
|
|
import sys
|
|
from collections.abc import AsyncIterable, Awaitable, Mapping, Sequence
|
|
from typing import Any, ClassVar, Generic
|
|
|
|
from agent_framework import (
|
|
BaseChatClient,
|
|
ChatMiddlewareLayer,
|
|
ChatResponse,
|
|
ChatResponseUpdate,
|
|
Content,
|
|
FunctionInvocationLayer,
|
|
Message,
|
|
ResponseStream,
|
|
Role,
|
|
)
|
|
from agent_framework._clients import OptionsCoT
|
|
from agent_framework.observability import ChatTelemetryLayer
|
|
|
|
if sys.version_info >= (3, 13):
|
|
pass
|
|
else:
|
|
pass
|
|
if sys.version_info >= (3, 12):
|
|
from typing import override # type: ignore # pragma: no cover
|
|
else:
|
|
from typing_extensions import override # type: ignore[import] # pragma: no cover
|
|
|
|
|
|
"""
|
|
Custom Chat Client Implementation Example
|
|
|
|
This sample demonstrates implementing a custom chat client and optionally composing
|
|
middleware, telemetry, and function invocation layers explicitly.
|
|
"""
|
|
|
|
|
|
class EchoingChatClient(BaseChatClient[OptionsCoT], Generic[OptionsCoT]):
|
|
"""A custom chat client that echoes messages back with modifications.
|
|
|
|
This demonstrates how to implement a custom chat client by extending BaseChatClient
|
|
and implementing the required _inner_get_response() method.
|
|
"""
|
|
|
|
OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClient"
|
|
|
|
def __init__(self, *, prefix: str = "Echo:", **kwargs: Any) -> None:
|
|
"""Initialize the EchoingChatClient.
|
|
|
|
Args:
|
|
prefix: Prefix to add to echoed messages.
|
|
**kwargs: Additional keyword arguments passed to BaseChatClient.
|
|
"""
|
|
super().__init__(**kwargs)
|
|
self.prefix = prefix
|
|
|
|
@override
|
|
def _inner_get_response(
|
|
self,
|
|
*,
|
|
messages: Sequence[Message],
|
|
stream: bool = False,
|
|
options: Mapping[str, Any],
|
|
**kwargs: Any,
|
|
) -> Awaitable[ChatResponse] | ResponseStream[ChatResponseUpdate, ChatResponse]:
|
|
"""Echo back the user's message with a prefix."""
|
|
if not messages:
|
|
response_text = "No messages to echo!"
|
|
else:
|
|
# Echo the last user message
|
|
last_user_message = None
|
|
for message in reversed(messages):
|
|
if message.role == Role.USER:
|
|
last_user_message = message
|
|
break
|
|
|
|
if last_user_message and last_user_message.text:
|
|
response_text = f"{self.prefix} {last_user_message.text}"
|
|
else:
|
|
response_text = f"{self.prefix} [No text message found]"
|
|
|
|
response_message = Message(role=Role.ASSISTANT, contents=[Content.from_text(response_text)])
|
|
|
|
response = ChatResponse(
|
|
messages=[response_message],
|
|
model_id="echo-model-v1",
|
|
response_id=f"echo-resp-{random.randint(1000, 9999)}",
|
|
)
|
|
|
|
if not stream:
|
|
|
|
async def _get_response() -> ChatResponse:
|
|
return response
|
|
|
|
return _get_response()
|
|
|
|
async def _stream() -> AsyncIterable[ChatResponseUpdate]:
|
|
response_text_local = response_message.text or ""
|
|
for char in response_text_local:
|
|
yield ChatResponseUpdate(
|
|
contents=[Content.from_text(char)],
|
|
role=Role.ASSISTANT,
|
|
response_id=f"echo-stream-resp-{random.randint(1000, 9999)}",
|
|
model_id="echo-model-v1",
|
|
)
|
|
await asyncio.sleep(0.05)
|
|
|
|
return ResponseStream(_stream(), finalizer=lambda updates: response)
|
|
|
|
|
|
class EchoingChatClientWithLayers( # type: ignore[misc,type-var]
|
|
ChatMiddlewareLayer[OptionsCoT],
|
|
ChatTelemetryLayer[OptionsCoT],
|
|
FunctionInvocationLayer[OptionsCoT],
|
|
EchoingChatClient[OptionsCoT],
|
|
Generic[OptionsCoT],
|
|
):
|
|
"""Echoing chat client that explicitly composes middleware, telemetry, and function layers."""
|
|
|
|
OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClientWithLayers"
|
|
|
|
|
|
async def main() -> None:
|
|
"""Demonstrates how to implement and use a custom chat client with Agent."""
|
|
print("=== Custom Chat Client Example ===\n")
|
|
|
|
# Create the custom chat client
|
|
print("--- EchoingChatClient Example ---")
|
|
|
|
echo_client = EchoingChatClientWithLayers(prefix="🔊 Echo:")
|
|
|
|
# Use the chat client directly
|
|
print("Using chat client directly:")
|
|
direct_response = await echo_client.get_response("Hello, custom chat client!")
|
|
print(f"Direct response: {direct_response.messages[0].text}")
|
|
|
|
# Create an agent using the custom chat client
|
|
echo_agent = echo_client.as_agent(
|
|
name="EchoAgent",
|
|
instructions="You are a helpful assistant that echoes back what users say.",
|
|
)
|
|
|
|
print(f"\nAgent Name: {echo_agent.name}")
|
|
|
|
# Test non-streaming with agent
|
|
query = "This is a test message"
|
|
print(f"\nUser: {query}")
|
|
result = await echo_agent.run(query)
|
|
print(f"Agent: {result.messages[0].text}")
|
|
|
|
# Test streaming with agent
|
|
query2 = "Stream this message back to me"
|
|
print(f"\nUser: {query2}")
|
|
print("Agent: ", end="", flush=True)
|
|
async for chunk in echo_agent.run(query2, stream=True):
|
|
if chunk.text:
|
|
print(chunk.text, end="", flush=True)
|
|
print()
|
|
|
|
# Example: Using with sessions and conversation history
|
|
print("\n--- Using Custom Chat Client with Session ---")
|
|
|
|
session = echo_agent.create_session()
|
|
|
|
# Multiple messages in conversation
|
|
messages = [
|
|
"Hello, I'm starting a conversation",
|
|
"How are you doing?",
|
|
"Thanks for chatting!",
|
|
]
|
|
|
|
for msg in messages:
|
|
result = await echo_agent.run(msg, session=session)
|
|
print(f"User: {msg}")
|
|
print(f"Agent: {result.messages[0].text}\n")
|
|
|
|
# Check conversation history
|
|
memory_state = session.state.get("memory", {})
|
|
session_messages = memory_state.get("messages", [])
|
|
if session_messages:
|
|
print(f"Session contains {len(session_messages)} messages")
|
|
else:
|
|
print("Session has no messages stored")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|