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Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* 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>
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# Azure Provider Samples
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This folder contains Azure OpenAI chat completion samples for Agent Framework.
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## Azure OpenAI ChatCompletionClient Samples
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| File | Description |
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|------|-------------|
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| [`openai_chat_completion_client_azure_basic.py`](openai_chat_completion_client_azure_basic.py) | Azure OpenAI Chat Client Basic Example |
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| [`openai_chat_completion_client_azure_with_explicit_settings.py`](openai_chat_completion_client_azure_with_explicit_settings.py) | Azure OpenAI Chat Client with Explicit Settings Example |
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| [`openai_chat_completion_client_azure_with_function_tools.py`](openai_chat_completion_client_azure_with_function_tools.py) | Azure OpenAI Chat Client with Function Tools Example |
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| [`openai_chat_completion_client_azure_with_session.py`](openai_chat_completion_client_azure_with_session.py) | Azure OpenAI Chat Client with Session Management Example |
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import Agent, tool
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from agent_framework.openai import OpenAIChatCompletionClient
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from azure.identity 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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Azure OpenAI Chat Client Basic Example
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This sample demonstrates basic usage of OpenAIChatCompletionClient for direct chat-based
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interactions, showing both streaming and non-streaming responses.
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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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async def non_streaming_example() -> None:
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"""Example of non-streaming response (get the complete result at once)."""
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print("=== Non-streaming Response Example ===")
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# Create agent with Azure Chat Client
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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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"Result: {result}\n")
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async def streaming_example() -> None:
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"""Example of streaming response (get results as they are generated)."""
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print("=== Streaming Response Example ===")
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# Create agent with Azure Chat Client
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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query = "What's the weather like in Portland?"
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print(f"User: {query}")
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print("Agent: ", end="", flush=True)
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async for chunk in agent.run(query, stream=True):
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if chunk.text:
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print(chunk.text, end="", flush=True)
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print("\n")
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async def main() -> None:
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print("=== Basic Azure Chat Client Agent Example ===")
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await non_streaming_example()
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await streaming_example()
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import os
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from random import randint
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from typing import Annotated
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from agent_framework import Agent, tool
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from agent_framework.openai import OpenAIChatCompletionClient
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from azure.identity 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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Azure OpenAI Chat Client with Explicit Settings Example
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This sample demonstrates creating Azure OpenAI Chat Client with explicit configuration
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settings rather than relying on environment variable defaults.
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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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async def main() -> None:
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print("=== Azure Chat Client with Explicit Settings ===")
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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_client = OpenAIChatCompletionClient(
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model=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
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endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
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credential=AzureCliCredential(),
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)
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agent = Agent(
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client=_client,
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instructions="You are a helpful weather agent.",
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tools=[get_weather],
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)
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result = await agent.run("What's the weather like in New York?")
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print(f"Result: {result}\n")
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from datetime import datetime, timezone
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from random import randint
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from typing import Annotated
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from agent_framework import Agent, tool
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from agent_framework.openai import OpenAIChatCompletionClient
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from azure.identity 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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Azure OpenAI Chat Client with Function Tools Example
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This sample demonstrates function tool integration with Azure OpenAI Chat Client,
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showing both agent-level and query-level tool configuration patterns.
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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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@tool(approval_mode="never_require")
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def get_time() -> str:
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"""Get the current UTC time."""
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current_time = datetime.now(timezone.utc)
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return f"The current UTC time is {current_time.strftime('%Y-%m-%d %H:%M:%S')}."
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async def tools_on_agent_level() -> None:
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"""Example showing tools defined when creating the agent."""
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print("=== Tools Defined on Agent Level ===")
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# Tools are provided when creating the agent
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# The agent can use these tools for any query during its lifetime
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful assistant that can provide weather and time information.",
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tools=[get_weather, get_time], # Tools defined at agent creation
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)
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# First query - agent can use weather tool
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query1 = "What's the weather like in New York?"
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print(f"User: {query1}")
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result1 = await agent.run(query1)
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print(f"Agent: {result1}\n")
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# Second query - agent can use time tool
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query2 = "What's the current UTC time?"
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print(f"User: {query2}")
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result2 = await agent.run(query2)
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print(f"Agent: {result2}\n")
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# Third query - agent can use both tools if needed
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query3 = "What's the weather in London and what's the current UTC time?"
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print(f"User: {query3}")
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result3 = await agent.run(query3)
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print(f"Agent: {result3}\n")
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async def tools_on_run_level() -> None:
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"""Example showing tools passed to the run method."""
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print("=== Tools Passed to Run Method ===")
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# Agent created without tools
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful assistant.",
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# No tools defined here
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)
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# First query with weather tool
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query1 = "What's the weather like in Seattle?"
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print(f"User: {query1}")
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result1 = await agent.run(query1, tools=[get_weather]) # Tool passed to run method
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print(f"Agent: {result1}\n")
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# Second query with time tool
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query2 = "What's the current UTC time?"
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print(f"User: {query2}")
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result2 = await agent.run(query2, tools=[get_time]) # Different tool for this query
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print(f"Agent: {result2}\n")
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# Third query with multiple tools
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query3 = "What's the weather in Chicago and what's the current UTC time?"
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print(f"User: {query3}")
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result3 = await agent.run(query3, tools=[get_weather, get_time]) # Multiple tools
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print(f"Agent: {result3}\n")
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async def mixed_tools_example() -> None:
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"""Example showing both agent-level tools and run-method tools."""
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print("=== Mixed Tools Example (Agent + Run Method) ===")
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# Agent created with some base tools
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a comprehensive assistant that can help with various information requests.",
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tools=[get_weather], # Base tool available for all queries
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)
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# Query using both agent tool and additional run-method tools
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query = "What's the weather in Denver and what's the current UTC time?"
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print(f"User: {query}")
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# Agent has access to get_weather (from creation) + additional tools from run method
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result = await agent.run(
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query,
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tools=[get_time], # Additional tools for this specific query
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)
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print(f"Agent: {result}\n")
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async def main() -> None:
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print("=== Azure Chat Client Agent with Function Tools Examples ===\n")
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await tools_on_agent_level()
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await tools_on_run_level()
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await mixed_tools_example()
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if __name__ == "__main__":
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asyncio.run(main())
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+161
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import Agent, AgentSession, InMemoryHistoryProvider, tool
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from agent_framework.openai import OpenAIChatCompletionClient
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from azure.identity 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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Azure OpenAI Chat Client with Session Management Example
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This sample demonstrates session management with Azure OpenAI Chat Client, comparing
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automatic session creation with explicit session management for persistent context.
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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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async def example_with_automatic_session_creation() -> None:
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"""Example showing automatic session creation (service-managed session)."""
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print("=== Automatic Session Creation Example ===")
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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# First conversation - no session provided, will be created automatically
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query1 = "What's the weather like in Seattle?"
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print(f"User: {query1}")
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result1 = await agent.run(query1)
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print(f"Agent: {result1.text}")
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# Second conversation - still no session provided, will create another new session
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query2 = "What was the last city I asked about?"
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print(f"\nUser: {query2}")
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result2 = await agent.run(query2)
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print(f"Agent: {result2.text}")
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print("Note: Each call creates a separate session, so the agent doesn't remember previous context.\n")
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async def example_with_session_persistence() -> None:
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"""Example showing session persistence across multiple conversations."""
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print("=== Session Persistence Example ===")
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print("Using the same session across multiple conversations to maintain context.\n")
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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agent = Agent(
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client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
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instructions="You are a helpful weather agent.",
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tools=get_weather,
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)
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# Create a new session that will be reused
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session = agent.create_session()
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# First conversation
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query1 = "What's the weather like in Tokyo?"
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print(f"User: {query1}")
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result1 = await agent.run(query1, session=session)
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print(f"Agent: {result1.text}")
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# Second conversation using the same session - maintains context
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query2 = "How about London?"
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print(f"\nUser: {query2}")
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result2 = await agent.run(query2, session=session)
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print(f"Agent: {result2.text}")
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# Third conversation - agent should remember both previous cities
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query3 = "Which of the cities I asked about has better weather?"
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print(f"\nUser: {query3}")
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result3 = await agent.run(query3, session=session)
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print(f"Agent: {result3.text}")
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print("Note: The agent remembers context from previous messages in the same session.\n")
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async def example_with_existing_session_messages() -> None:
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"""Example showing how to work with existing session messages for Azure."""
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print("=== Existing Session Messages Example ===")
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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||||
# authentication option.
|
||||
agent = Agent(
|
||||
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful weather agent.",
|
||||
tools=get_weather,
|
||||
)
|
||||
|
||||
# Start a conversation and build up message history
|
||||
session = agent.create_session()
|
||||
|
||||
query1 = "What's the weather in Paris?"
|
||||
print(f"User: {query1}")
|
||||
result1 = await agent.run(query1, session=session)
|
||||
print(f"Agent: {result1.text}")
|
||||
|
||||
# The session now contains the conversation history in state
|
||||
memory_state = session.state.get(InMemoryHistoryProvider.DEFAULT_SOURCE_ID, {})
|
||||
messages = memory_state.get("messages", [])
|
||||
if messages:
|
||||
print(f"Session contains {len(messages)} messages")
|
||||
|
||||
print("\n--- Continuing with the same session in a new agent instance ---")
|
||||
|
||||
# Create a new agent instance but use the existing session with its message history
|
||||
new_agent = Agent(
|
||||
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
|
||||
instructions="You are a helpful weather agent.",
|
||||
tools=get_weather,
|
||||
)
|
||||
|
||||
# Use the same session object which contains the conversation history
|
||||
query2 = "What was the last city I asked about?"
|
||||
print(f"User: {query2}")
|
||||
result2 = await new_agent.run(query2, session=session)
|
||||
print(f"Agent: {result2.text}")
|
||||
print("Note: The agent continues the conversation using the local message history.\n")
|
||||
|
||||
print("\n--- Alternative: Creating a new session from existing messages ---")
|
||||
|
||||
# You can also create a new session from existing messages
|
||||
new_session = AgentSession()
|
||||
|
||||
query3 = "How does the Paris weather compare to London?"
|
||||
print(f"User: {query3}")
|
||||
result3 = await new_agent.run(query3, session=new_session)
|
||||
print(f"Agent: {result3.text}")
|
||||
print("Note: This creates a new session with the same conversation history.\n")
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
print("=== Azure Chat Client Agent Session Management Examples ===\n")
|
||||
|
||||
await example_with_automatic_session_creation()
|
||||
await example_with_session_persistence()
|
||||
await example_with_existing_session_messages()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user