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agent-framework/python/samples/02-agents/middleware/middleware_termination.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

180 lines
6.7 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
from collections.abc import Awaitable, Callable
from random import randint
from typing import Annotated
from agent_framework import (
AgentContext,
AgentMiddleware,
AgentResponse,
Message,
MiddlewareTermination,
tool,
)
from agent_framework.azure import AzureAIAgentClient
from azure.identity.aio import AzureCliCredential
from pydantic import Field
"""
MiddlewareTypes Termination Example
This sample demonstrates how middleware can terminate execution using the `context.terminate` flag.
The example includes:
- PreTerminationMiddleware: Terminates execution before calling call_next() to prevent agent processing
- PostTerminationMiddleware: Allows processing to complete but terminates further execution
This is useful for implementing security checks, rate limiting, or early exit conditions.
"""
# 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")
def get_weather(
location: Annotated[str, Field(description="The location to get the weather for.")],
) -> str:
"""Get the weather for a given location."""
conditions = ["sunny", "cloudy", "rainy", "stormy"]
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
class PreTerminationMiddleware(AgentMiddleware):
"""MiddlewareTypes that terminates execution before calling the agent."""
def __init__(self, blocked_words: list[str]):
self.blocked_words = [word.lower() for word in blocked_words]
async def process(
self,
context: AgentContext,
call_next: Callable[[], Awaitable[None]],
) -> None:
# Check if the user message contains any blocked words
last_message = context.messages[-1] if context.messages else None
if last_message and last_message.text:
query = last_message.text.lower()
for blocked_word in self.blocked_words:
if blocked_word in query:
print(f"[PreTerminationMiddleware] Blocked word '{blocked_word}' detected. Terminating request.")
# Set a custom response
context.result = AgentResponse(
messages=[
Message(
role="assistant",
text=(
f"Sorry, I cannot process requests containing '{blocked_word}'. "
"Please rephrase your question."
),
)
]
)
# Terminate to prevent further processing
raise MiddlewareTermination(result=context.result)
await call_next()
class PostTerminationMiddleware(AgentMiddleware):
"""MiddlewareTypes that allows processing but terminates after reaching max responses across multiple runs."""
def __init__(self, max_responses: int = 1):
self.max_responses = max_responses
self.response_count = 0
async def process(
self,
context: AgentContext,
call_next: Callable[[], Awaitable[None]],
) -> None:
print(f"[PostTerminationMiddleware] Processing request (response count: {self.response_count})")
# Check if we should terminate before processing
if self.response_count >= self.max_responses:
print(
f"[PostTerminationMiddleware] Maximum responses ({self.max_responses}) reached. "
"Terminating further processing."
)
raise MiddlewareTermination
# Allow the agent to process normally
await call_next()
# Increment response count after processing
self.response_count += 1
async def pre_termination_middleware() -> None:
"""Demonstrate pre-termination middleware that blocks requests with certain words."""
print("\n--- Example 1: Pre-termination MiddlewareTypes ---")
async with (
AzureCliCredential() as credential,
AzureAIAgentClient(credential=credential).as_agent(
name="WeatherAgent",
instructions="You are a helpful weather assistant.",
tools=get_weather,
middleware=[PreTerminationMiddleware(blocked_words=["bad", "inappropriate"])],
) as agent,
):
# Test with normal query
print("\n1. Normal query:")
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text}")
# Test with blocked word
print("\n2. Query with blocked word:")
query = "What's the bad weather in New York?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text}")
async def post_termination_middleware() -> None:
"""Demonstrate post-termination middleware that limits responses across multiple runs."""
print("\n--- Example 2: Post-termination MiddlewareTypes ---")
async with (
AzureCliCredential() as credential,
AzureAIAgentClient(credential=credential).as_agent(
name="WeatherAgent",
instructions="You are a helpful weather assistant.",
tools=get_weather,
middleware=[PostTerminationMiddleware(max_responses=1)],
) as agent,
):
# First run (should work)
print("\n1. First run:")
query = "What's the weather in Paris?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text}")
# Second run (should be terminated by middleware)
print("\n2. Second run (should be terminated):")
query = "What about the weather in London?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text if result and result.text else 'No response (terminated)'}")
# Third run (should also be terminated)
print("\n3. Third run (should also be terminated):")
query = "And New York?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Agent: {result.text if result and result.text else 'No response (terminated)'}")
async def main() -> None:
"""Example demonstrating middleware termination functionality."""
print("=== MiddlewareTypes Termination Example ===")
await pre_termination_middleware()
await post_termination_middleware()
if __name__ == "__main__":
asyncio.run(main())