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* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
189 lines
6.8 KiB
Python
189 lines
6.8 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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Agent,
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AgentContext,
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AgentMiddleware,
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AgentResponse,
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Message,
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MiddlewareTermination,
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tool,
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)
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from agent_framework.foundry import FoundryChatClient
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from azure.identity.aio import AzureCliCredential
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from dotenv import load_dotenv
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from pydantic import Field
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# Load environment variables from .env file
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load_dotenv()
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"""
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MiddlewareTypes 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 call_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;
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# see samples/02-agents/tools/function_tool_with_approval.py
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# and samples/02-agents/tools/function_tool_with_approval_and_sessions.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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"""MiddlewareTypes 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: AgentContext,
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call_next: Callable[[], 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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Message(
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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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# Terminate to prevent further processing
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raise MiddlewareTermination(result=context.result)
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await call_next()
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class PostTerminationMiddleware(AgentMiddleware):
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"""MiddlewareTypes 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: AgentContext,
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call_next: Callable[[], 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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raise MiddlewareTermination
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# Allow the agent to process normally
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await call_next()
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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 MiddlewareTypes ---")
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async with (
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AzureCliCredential() as credential,
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Agent(
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client=FoundryChatClient(credential=credential),
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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 MiddlewareTypes ---")
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async with (
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AzureCliCredential() as credential,
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Agent(
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client=FoundryChatClient(credential=credential),
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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 and 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 and 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("=== MiddlewareTypes 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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