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
212 lines
7.1 KiB
Python
212 lines
7.1 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
|
|
|
|
import asyncio
|
|
from collections.abc import AsyncIterable
|
|
from typing import Any
|
|
|
|
from agent_framework import (
|
|
AgentResponse,
|
|
AgentResponseUpdate,
|
|
AgentSession,
|
|
BaseAgent,
|
|
Content,
|
|
Message,
|
|
Role,
|
|
normalize_messages,
|
|
)
|
|
|
|
"""
|
|
Custom Agent Implementation Example
|
|
|
|
This sample demonstrates implementing a custom agent by extending BaseAgent class,
|
|
showing the minimal requirements for both streaming and non-streaming responses.
|
|
"""
|
|
|
|
|
|
class EchoAgent(BaseAgent):
|
|
"""A simple custom agent that echoes user messages with a prefix.
|
|
|
|
This demonstrates how to create a fully custom agent by extending BaseAgent
|
|
and implementing the required run() method with stream support.
|
|
"""
|
|
|
|
echo_prefix: str = "Echo: "
|
|
|
|
def __init__(
|
|
self,
|
|
*,
|
|
name: str | None = None,
|
|
description: str | None = None,
|
|
echo_prefix: str = "Echo: ",
|
|
**kwargs: Any,
|
|
) -> None:
|
|
"""Initialize the EchoAgent.
|
|
|
|
Args:
|
|
name: The name of the agent.
|
|
description: The description of the agent.
|
|
echo_prefix: The prefix to add to echoed messages.
|
|
**kwargs: Additional keyword arguments passed to BaseAgent.
|
|
"""
|
|
super().__init__(
|
|
name=name,
|
|
description=description,
|
|
echo_prefix=echo_prefix, # type: ignore
|
|
**kwargs,
|
|
)
|
|
|
|
def run(
|
|
self,
|
|
messages: str | Message | list[str] | list[Message] | None = None,
|
|
*,
|
|
stream: bool = False,
|
|
session: AgentSession | None = None,
|
|
**kwargs: Any,
|
|
) -> "AsyncIterable[AgentResponseUpdate] | asyncio.Future[AgentResponse]":
|
|
"""Execute the agent and return a response.
|
|
|
|
Args:
|
|
messages: The message(s) to process.
|
|
stream: If True, return an async iterable of updates. If False, return an awaitable response.
|
|
session: The conversation session (optional).
|
|
**kwargs: Additional keyword arguments.
|
|
|
|
Returns:
|
|
When stream=False: An awaitable AgentResponse containing the agent's reply.
|
|
When stream=True: An async iterable of AgentResponseUpdate objects.
|
|
"""
|
|
if stream:
|
|
return self._run_stream(messages=messages, session=session, **kwargs)
|
|
return self._run(messages=messages, session=session, **kwargs)
|
|
|
|
async def _run(
|
|
self,
|
|
messages: str | Message | list[str] | list[Message] | None = None,
|
|
*,
|
|
session: AgentSession | None = None,
|
|
**kwargs: Any,
|
|
) -> AgentResponse:
|
|
"""Non-streaming implementation."""
|
|
# Normalize input messages to a list
|
|
normalized_messages = normalize_messages(messages)
|
|
|
|
if not normalized_messages:
|
|
response_message = Message(
|
|
role=Role.ASSISTANT,
|
|
contents=[Content.from_text(text="Hello! I'm a custom echo agent. Send me a message and I'll echo it back.")],
|
|
)
|
|
else:
|
|
# For simplicity, echo the last user message
|
|
last_message = normalized_messages[-1]
|
|
if last_message.text:
|
|
echo_text = f"{self.echo_prefix}{last_message.text}"
|
|
else:
|
|
echo_text = f"{self.echo_prefix}[Non-text message received]"
|
|
|
|
response_message = Message(role=Role.ASSISTANT, contents=[Content.from_text(text=echo_text)])
|
|
|
|
# Store messages in session state if provided
|
|
if session is not None:
|
|
stored = session.state.setdefault("memory", {}).setdefault("messages", [])
|
|
stored.extend(normalized_messages)
|
|
stored.append(response_message)
|
|
|
|
return AgentResponse(messages=[response_message])
|
|
|
|
async def _run_stream(
|
|
self,
|
|
messages: str | Message | list[str] | list[Message] | None = None,
|
|
*,
|
|
session: AgentSession | None = None,
|
|
**kwargs: Any,
|
|
) -> AsyncIterable[AgentResponseUpdate]:
|
|
"""Streaming implementation."""
|
|
# Normalize input messages to a list
|
|
normalized_messages = normalize_messages(messages)
|
|
|
|
if not normalized_messages:
|
|
response_text = "Hello! I'm a custom echo agent. Send me a message and I'll echo it back."
|
|
else:
|
|
# For simplicity, echo the last user message
|
|
last_message = normalized_messages[-1]
|
|
if last_message.text:
|
|
response_text = f"{self.echo_prefix}{last_message.text}"
|
|
else:
|
|
response_text = f"{self.echo_prefix}[Non-text message received]"
|
|
|
|
# Simulate streaming by yielding the response word by word
|
|
words = response_text.split()
|
|
for i, word in enumerate(words):
|
|
# Add space before word except for the first one
|
|
chunk_text = f" {word}" if i > 0 else word
|
|
|
|
yield AgentResponseUpdate(
|
|
contents=[Content.from_text(text=chunk_text)],
|
|
role=Role.ASSISTANT,
|
|
)
|
|
|
|
# Small delay to simulate streaming
|
|
await asyncio.sleep(0.1)
|
|
|
|
# Store messages in session state if provided
|
|
if session is not None:
|
|
complete_response = Message(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)])
|
|
stored = session.state.setdefault("memory", {}).setdefault("messages", [])
|
|
stored.extend(normalized_messages)
|
|
stored.append(complete_response)
|
|
|
|
|
|
async def main() -> None:
|
|
"""Demonstrates how to use the custom EchoAgent."""
|
|
print("=== Custom Agent Example ===\n")
|
|
|
|
# Create EchoAgent
|
|
print("--- EchoAgent Example ---")
|
|
echo_agent = EchoAgent(
|
|
name="EchoBot", description="A simple agent that echoes messages with a prefix", echo_prefix="🔊 Echo: "
|
|
)
|
|
|
|
# Test non-streaming
|
|
print(f"Agent Name: {echo_agent.name}")
|
|
print(f"Agent ID: {echo_agent.id}")
|
|
|
|
query = "Hello, custom agent!"
|
|
print(f"\nUser: {query}")
|
|
result = await echo_agent.run(query)
|
|
print(f"Agent: {result.messages[0].text}")
|
|
|
|
# Test streaming
|
|
query2 = "This is a streaming test"
|
|
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 with sessions
|
|
print("\n--- Using Custom Agent with Session ---")
|
|
session = echo_agent.create_session()
|
|
|
|
# First message
|
|
result1 = await echo_agent.run("First message", session=session)
|
|
print("User: First message")
|
|
print(f"Agent: {result1.messages[0].text}")
|
|
|
|
# Second message in same thread
|
|
result2 = await echo_agent.run("Second message", session=session)
|
|
print("User: Second message")
|
|
print(f"Agent: {result2.messages[0].text}")
|
|
|
|
# Check conversation history
|
|
memory_state = session.state.get("memory", {})
|
|
messages = memory_state.get("messages", [])
|
|
if messages:
|
|
print(f"\nSession contains {len(messages)} messages in history")
|
|
else:
|
|
print("\nSession has no messages stored")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|