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Eduard van Valkenburg 1e350ea22f Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)
* 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
2026-02-12 21:00:32 +00:00

151 lines
5.6 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
"""Example showing Agent with AGUIChatClient for hybrid tool execution.
This demonstrates the HYBRID pattern matching .NET AGUIClient implementation:
1. AgentSession Pattern (like .NET):
- Create session with agent.create_session()
- Pass session to agent.run(stream=True) on each turn
- Session maintains conversation context via context providers
2. Hybrid Tool Execution:
- AGUIChatClient uses function invocation mixin
- Client-side tools (get_weather) can execute locally when server requests them
- Server may also have its own tools that execute server-side
- Both work together: server LLM decides which tool to call, decorator handles client execution
This matches .NET pattern: session maintains state, tools execute on appropriate side.
"""
from __future__ import annotations
import asyncio
import logging
import os
from agent_framework import Agent, tool
from agent_framework.ag_ui import AGUIChatClient
# Enable debug logging
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
logger = logging.getLogger(__name__)
@tool(description="Get the current weather for a location.")
def get_weather(location: str) -> str:
"""Get the current weather for a location.
Args:
location: The city or location name
"""
print(f"[CLIENT] get_weather tool called with location: {location}")
weather_data = {
"seattle": "Rainy, 55°F",
"san francisco": "Foggy, 62°F",
"new york": "Sunny, 68°F",
"london": "Cloudy, 52°F",
}
result = weather_data.get(location.lower(), f"Weather data not available for {location}")
print(f"[CLIENT] get_weather returning: {result}")
return result
async def main():
"""Demonstrate Agent + AGUIChatClient hybrid tool execution.
This matches the .NET pattern from Program.cs where:
- AIAgent agent = chatClient.CreateAIAgent(tools: [...])
- AgentSession session = agent.CreateSession()
- RunStreamingAsync(messages, session)
Python equivalent:
- agent = Agent(client=AGUIChatClient(...), tools=[...])
- session = agent.create_session() # Creates session
- agent.run(message, stream=True, session=session) # Session tracks context
"""
server_url = os.environ.get("AGUI_SERVER_URL", "http://127.0.0.1:5100/")
print("=" * 70)
print("Agent + AGUIChatClient: Hybrid Tool Execution")
print("=" * 70)
print(f"\nServer: {server_url}")
print("\nThis example demonstrates:")
print(" 1. AgentSession maintains conversation state (like .NET)")
print(" 2. Client-side tools execute locally via function invocation mixin")
print(" 3. Server may have additional tools that execute server-side")
print(" 4. HYBRID: Client and server tools work together simultaneously\n")
try:
# Create remote client in async context manager
async with AGUIChatClient(endpoint=server_url) as remote_client:
# Wrap in Agent for conversation history management
agent = Agent(
name="remote_assistant",
instructions="You are a helpful assistant. Remember user information across the conversation.",
client=remote_client,
tools=[get_weather],
)
# Create a session to maintain conversation state (like .NET AgentSession)
session = agent.create_session()
print("=" * 70)
print("CONVERSATION WITH HISTORY")
print("=" * 70)
# Turn 1: Introduce
print("\nUser: My name is Alice and I live in Seattle\n")
async for chunk in agent.run("My name is Alice and I live in Seattle", stream=True, session=session):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
# Turn 2: Ask about name (tests history)
print("User: What's my name?\n")
async for chunk in agent.run("What's my name?", stream=True, session=session):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
# Turn 3: Ask about location (tests history)
print("User: Where do I live?\n")
async for chunk in agent.run("Where do I live?", stream=True, session=session):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
# Turn 4: Test client-side tool (get_weather is client-side)
print("User: What's the weather forecast for today in Seattle?\n")
async for chunk in agent.run(
"What's the weather forecast for today in Seattle?",
stream=True,
session=session,
):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
# Turn 5: Test server-side tool (get_time_zone is server-side only)
print("User: What time zone is Seattle in?\n")
async for chunk in agent.run("What time zone is Seattle in?", stream=True, session=session):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
except ConnectionError as e:
print(f"\n\033[91mConnection Error: {e}\033[0m")
print("\nMake sure an AG-UI server is running at the specified endpoint.")
except Exception as e:
print(f"\n\033[91mError: {e}\033[0m")
import traceback
traceback.print_exc()
if __name__ == "__main__":
asyncio.run(main())