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
125 lines
4.3 KiB
Python
125 lines
4.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
|
|
|
|
"""Example of using Agent Framework DevUI with in-memory entity registration.
|
|
|
|
This demonstrates the simplest way to serve agents and workflows as OpenAI-compatible API endpoints.
|
|
Includes both agents and a basic workflow to showcase different entity types.
|
|
"""
|
|
|
|
import logging
|
|
import os
|
|
from typing import Annotated
|
|
|
|
from agent_framework import Agent, Executor, WorkflowBuilder, WorkflowContext, handler, tool
|
|
from agent_framework.azure import AzureOpenAIChatClient
|
|
from agent_framework.devui import serve
|
|
from typing_extensions import Never
|
|
|
|
|
|
# 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.
|
|
@tool(approval_mode="never_require")
|
|
# Tool functions for the agent
|
|
@tool(approval_mode="never_require")
|
|
def get_weather(
|
|
location: Annotated[str, "The location to get the weather for."],
|
|
) -> str:
|
|
"""Get the weather for a given location."""
|
|
conditions = ["sunny", "cloudy", "rainy", "stormy"]
|
|
temperature = 53
|
|
return f"The weather in {location} is {conditions[0]} with a high of {temperature}°C."
|
|
|
|
|
|
@tool(approval_mode="never_require")
|
|
def get_time(
|
|
timezone: Annotated[str, "The timezone to get time for."] = "UTC",
|
|
) -> str:
|
|
"""Get current time for a timezone."""
|
|
from datetime import datetime
|
|
|
|
# Simplified for example
|
|
return f"Current time in {timezone}: {datetime.now().strftime('%H:%M:%S')}"
|
|
|
|
|
|
# Basic workflow executors
|
|
class UpperCase(Executor):
|
|
"""Convert text to uppercase."""
|
|
|
|
@handler
|
|
async def to_upper(self, text: str, ctx: WorkflowContext[str]) -> None:
|
|
"""Convert input to uppercase and forward to next executor."""
|
|
result = text.upper()
|
|
await ctx.send_message(result)
|
|
|
|
|
|
class AddExclamation(Executor):
|
|
"""Add exclamation mark to text."""
|
|
|
|
@handler
|
|
async def add_exclamation(self, text: str, ctx: WorkflowContext[Never, str]) -> None:
|
|
"""Add exclamation and yield as workflow output."""
|
|
result = f"{text}!"
|
|
await ctx.yield_output(result)
|
|
|
|
|
|
def main():
|
|
"""Main function demonstrating in-memory entity registration."""
|
|
# Setup logging
|
|
logging.basicConfig(level=logging.INFO, format="%(message)s")
|
|
logger = logging.getLogger(__name__)
|
|
|
|
# Create Azure OpenAI chat client
|
|
client = AzureOpenAIChatClient(
|
|
api_key=os.environ.get("AZURE_OPENAI_API_KEY"),
|
|
azure_endpoint=os.environ.get("AZURE_OPENAI_ENDPOINT"),
|
|
api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2024-10-21"),
|
|
model_id=os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "gpt-4o"),
|
|
)
|
|
|
|
# Create agents
|
|
weather_agent = Agent(
|
|
name="weather-assistant",
|
|
description="Provides weather information and time",
|
|
instructions=(
|
|
"You are a helpful weather and time assistant. Use the available tools to "
|
|
"provide accurate weather information and current time for any location."
|
|
),
|
|
client=client,
|
|
tools=[get_weather, get_time],
|
|
)
|
|
|
|
simple_agent = Agent(
|
|
name="general-assistant",
|
|
description="A simple conversational agent",
|
|
instructions="You are a helpful assistant.",
|
|
client=client,
|
|
)
|
|
|
|
# Create a basic workflow: Input -> UpperCase -> AddExclamation -> Output
|
|
upper_executor = UpperCase(id="upper_case")
|
|
exclaim_executor = AddExclamation(id="add_exclamation")
|
|
|
|
basic_workflow = (
|
|
WorkflowBuilder(
|
|
name="Text Transformer",
|
|
description="Simple 2-step workflow that converts text to uppercase and adds exclamation",
|
|
start_executor=upper_executor,
|
|
)
|
|
.add_edge(upper_executor, exclaim_executor)
|
|
.build()
|
|
)
|
|
|
|
# Collect entities for serving
|
|
entities = [weather_agent, simple_agent, basic_workflow]
|
|
|
|
logger.info("Starting DevUI on http://localhost:8090")
|
|
logger.info("Entities available:")
|
|
logger.info(" - Agents: weather-assistant, general-assistant")
|
|
logger.info(" - Workflow: basic text transformer (uppercase + exclamation)")
|
|
|
|
# Launch server with auto-generated entity IDs
|
|
serve(entities=entities, port=8090, auto_open=True)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|