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agent-framework/python/samples/02-agents/devui/in_memory_mode.py
T
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

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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()