mirror of
https://github.com/microsoft/agent-framework.git
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838a7fd61d
* Replace Role and FinishReason classes with NewType + Literal
- Remove EnumLike metaclass from _types.py
- Replace Role class with NewType('Role', str) + RoleLiteral
- Replace FinishReason class with NewType('FinishReason', str) + FinishReasonLiteral
- Update all usages across codebase to use string literals
- Remove .value access patterns (direct string comparison now works)
- Add backward compatibility for legacy dict serialization format
- Update tests to reflect new string-based types
Addresses #3591, #3615
* Simplify ChatResponse and AgentResponse type hints (#3592)
- Remove overloads from ChatResponse.__init__
- Remove text parameter from ChatResponse.__init__
- Remove | dict[str, Any] from finish_reason and usage_details params
- Remove **kwargs from AgentResponse.__init__
- Both now accept ChatMessage | Sequence[ChatMessage] | None for messages
- Update docstrings and examples to reflect changes
- Fix tests that were using removed kwargs
- Fix Role type hint usage in ag-ui utils
* Remove text parameter from ChatResponseUpdate and AgentResponseUpdate (#3597)
- Remove text parameter from ChatResponseUpdate.__init__
- Remove text parameter from AgentResponseUpdate.__init__
- Remove **kwargs from both update classes
- Simplify contents parameter type to Sequence[Content] | None
- Update all usages to use contents=[Content.from_text(...)] pattern
- Fix imports in test files
- Update docstrings and examples
* Rename from_chat_response_updates to from_updates (#3593)
- ChatResponse.from_chat_response_updates → ChatResponse.from_updates
- ChatResponse.from_chat_response_generator → ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates → AgentResponse.from_updates
* Remove try_parse_value method from ChatResponse and AgentResponse (#3595)
- Remove try_parse_value method from ChatResponse
- Remove try_parse_value method from AgentResponse
- Remove try_parse_value calls from from_updates and from_update_generator methods
- Update samples to use try/except with response.value instead
- Update tests to use response.value pattern
- Users should now use response.value with try/except for safe parsing
* Add agent_id to AgentResponse and clarify author_name documentation (#3596)
- Add agent_id parameter to AgentResponse class
- Document that author_name is on ChatMessage objects, not responses
- Update ChatResponse docstring with author_name note
- Update AgentResponse docstring with author_name note
* Simplify ChatMessage.__init__ signature (#3618)
- Make contents a positional argument accepting Sequence[Content | str]
- Auto-convert strings in contents to TextContent
- Remove overloads, keep text kwarg for backward compatibility with serialization
- Update _parse_content_list to handle string items
- Update all usages across codebase to use new format: ChatMessage("role", ["text"])
* Allow Content as input on run and get_response
- Update prepare_messages and normalize_messages to accept Content
- Update type signatures in _agents.py and _clients.py
- Add tests for Content input handling
* Fix ChatMessage usage across packages and samples
Update all remaining ChatMessage(role=..., text=...) to use new
ChatMessage('role', ['text']) signature.
* Fix Role string usage and response format parsing
- Fix redis provider: remove .value access on string literals
- Fix durabletask ensure_response_format: set _response_format before accessing .value
* Fix ollama .value and ai_model_id issues, handle None in content list
- Fix ollama _chat_client: remove .value on string literals
- Fix ollama _chat_client: rename ai_model_id to model_id
- Fix _parse_content_list: skip None values gracefully
* Fix A2AAgent type signature to include Content
* Fix Role/FinishReason NewType dict annotations and improve test coverage to 95%
* Fix mypy errors for Role/FinishReason NewType usage
* Fix Role.TOOL and Role.ASSISTANT usage in _orchestrator_helpers.py
* Fix Role NewType usage in durabletask _models.py
180 lines
6.6 KiB
Python
180 lines
6.6 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from collections.abc import Awaitable, Callable
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from random import randint
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from typing import Annotated
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from agent_framework import (
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AgentMiddleware,
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AgentResponse,
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AgentRunContext,
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ChatMessage,
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tool,
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)
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from agent_framework.azure import AzureAIAgentClient
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from azure.identity.aio import AzureCliCredential
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from pydantic import Field
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"""
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Middleware Termination Example
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This sample demonstrates how middleware can terminate execution using the `context.terminate` flag.
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The example includes:
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- PreTerminationMiddleware: Terminates execution before calling next() to prevent agent processing
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- PostTerminationMiddleware: Allows processing to complete but terminates further execution
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This is useful for implementing security checks, rate limiting, or early exit conditions.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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class PreTerminationMiddleware(AgentMiddleware):
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"""Middleware that terminates execution before calling the agent."""
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def __init__(self, blocked_words: list[str]):
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self.blocked_words = [word.lower() for word in blocked_words]
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async def process(
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self,
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context: AgentRunContext,
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next: Callable[[AgentRunContext], Awaitable[None]],
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) -> None:
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# Check if the user message contains any blocked words
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last_message = context.messages[-1] if context.messages else None
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if last_message and last_message.text:
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query = last_message.text.lower()
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for blocked_word in self.blocked_words:
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if blocked_word in query:
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print(f"[PreTerminationMiddleware] Blocked word '{blocked_word}' detected. Terminating request.")
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# Set a custom response
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context.result = AgentResponse(
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messages=[
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ChatMessage(
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role="assistant",
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text=(
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f"Sorry, I cannot process requests containing '{blocked_word}'. "
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"Please rephrase your question."
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),
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)
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]
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)
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# Set terminate flag to prevent further processing
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context.terminate = True
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break
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await next(context)
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class PostTerminationMiddleware(AgentMiddleware):
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"""Middleware that allows processing but terminates after reaching max responses across multiple runs."""
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def __init__(self, max_responses: int = 1):
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self.max_responses = max_responses
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self.response_count = 0
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async def process(
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self,
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context: AgentRunContext,
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next: Callable[[AgentRunContext], Awaitable[None]],
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) -> None:
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print(f"[PostTerminationMiddleware] Processing request (response count: {self.response_count})")
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# Check if we should terminate before processing
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if self.response_count >= self.max_responses:
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print(
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f"[PostTerminationMiddleware] Maximum responses ({self.max_responses}) reached. "
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"Terminating further processing."
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)
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context.terminate = True
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# Allow the agent to process normally
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await next(context)
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# Increment response count after processing
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self.response_count += 1
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async def pre_termination_middleware() -> None:
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"""Demonstrate pre-termination middleware that blocks requests with certain words."""
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print("\n--- Example 1: Pre-termination Middleware ---")
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="WeatherAgent",
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instructions="You are a helpful weather assistant.",
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tools=get_weather,
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middleware=[PreTerminationMiddleware(blocked_words=["bad", "inappropriate"])],
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) as agent,
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):
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# Test with normal query
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print("\n1. Normal query:")
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query = "What's the weather like in Seattle?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text}")
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# Test with blocked word
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print("\n2. Query with blocked word:")
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query = "What's the bad weather in New York?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text}")
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async def post_termination_middleware() -> None:
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"""Demonstrate post-termination middleware that limits responses across multiple runs."""
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print("\n--- Example 2: Post-termination Middleware ---")
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="WeatherAgent",
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instructions="You are a helpful weather assistant.",
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tools=get_weather,
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middleware=[PostTerminationMiddleware(max_responses=1)],
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) as agent,
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):
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# First run (should work)
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print("\n1. First run:")
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query = "What's the weather in Paris?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text}")
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# Second run (should be terminated by middleware)
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print("\n2. Second run (should be terminated):")
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query = "What about the weather in London?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text if result.text else 'No response (terminated)'}")
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# Third run (should also be terminated)
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print("\n3. Third run (should also be terminated):")
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query = "And New York?"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result.text if result.text else 'No response (terminated)'}")
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async def main() -> None:
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"""Example demonstrating middleware termination functionality."""
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print("=== Middleware Termination Example ===")
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await pre_termination_middleware()
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await post_termination_middleware()
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if __name__ == "__main__":
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asyncio.run(main())
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