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>
This commit is contained in:
Eduard van Valkenburg
2026-03-25 09:56:29 +00:00
committed by GitHub
co-authored by Copilot
parent 4b533608b6
commit 5e056b672e
485 changed files with 9784 additions and 12084 deletions
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# Azure Provider Samples
This folder contains Azure OpenAI chat completion samples for Agent Framework.
## Azure OpenAI ChatCompletionClient Samples
| File | Description |
|------|-------------|
| [`openai_chat_completion_client_azure_basic.py`](openai_chat_completion_client_azure_basic.py) | Azure OpenAI Chat Client Basic Example |
| [`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 |
| [`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 |
| [`openai_chat_completion_client_azure_with_session.py`](openai_chat_completion_client_azure_with_session.py) | Azure OpenAI Chat Client with Session Management Example |
@@ -0,0 +1,85 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from random import randint
from typing import Annotated
from agent_framework import Agent, tool
from agent_framework.openai import OpenAIChatCompletionClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from pydantic import Field
# Load environment variables from .env file
load_dotenv()
"""
Azure OpenAI Chat Client Basic Example
This sample demonstrates basic usage of OpenAIChatCompletionClient for direct chat-based
interactions, showing both streaming and non-streaming responses.
"""
# 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."
async def non_streaming_example() -> None:
"""Example of non-streaming response (get the complete result at once)."""
print("=== Non-streaming Response Example ===")
# Create agent with Azure Chat Client
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful weather agent.",
tools=get_weather,
)
query = "What's the weather like in Seattle?"
print(f"User: {query}")
result = await agent.run(query)
print(f"Result: {result}\n")
async def streaming_example() -> None:
"""Example of streaming response (get results as they are generated)."""
print("=== Streaming Response Example ===")
# Create agent with Azure Chat Client
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful weather agent.",
tools=get_weather,
)
query = "What's the weather like in Portland?"
print(f"User: {query}")
print("Agent: ", end="", flush=True)
async for chunk in agent.run(query, stream=True):
if chunk.text:
print(chunk.text, end="", flush=True)
print("\n")
async def main() -> None:
print("=== Basic Azure Chat Client Agent Example ===")
await non_streaming_example()
await streaming_example()
if __name__ == "__main__":
asyncio.run(main())
@@ -0,0 +1,58 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import os
from random import randint
from typing import Annotated
from agent_framework import Agent, tool
from agent_framework.openai import OpenAIChatCompletionClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from pydantic import Field
# Load environment variables from .env file
load_dotenv()
"""
Azure OpenAI Chat Client with Explicit Settings Example
This sample demonstrates creating Azure OpenAI Chat Client with explicit configuration
settings rather than relying on environment variable defaults.
"""
# 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."
async def main() -> None:
print("=== Azure Chat Client with Explicit Settings ===")
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
_client = OpenAIChatCompletionClient(
model=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
credential=AzureCliCredential(),
)
agent = Agent(
client=_client,
instructions="You are a helpful weather agent.",
tools=[get_weather],
)
result = await agent.run("What's the weather like in New York?")
print(f"Result: {result}\n")
if __name__ == "__main__":
asyncio.run(main())
@@ -0,0 +1,143 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from datetime import datetime, timezone
from random import randint
from typing import Annotated
from agent_framework import Agent, tool
from agent_framework.openai import OpenAIChatCompletionClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from pydantic import Field
# Load environment variables from .env file
load_dotenv()
"""
Azure OpenAI Chat Client with Function Tools Example
This sample demonstrates function tool integration with Azure OpenAI Chat Client,
showing both agent-level and query-level tool configuration patterns.
"""
# 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."
@tool(approval_mode="never_require")
def get_time() -> str:
"""Get the current UTC time."""
current_time = datetime.now(timezone.utc)
return f"The current UTC time is {current_time.strftime('%Y-%m-%d %H:%M:%S')}."
async def tools_on_agent_level() -> None:
"""Example showing tools defined when creating the agent."""
print("=== Tools Defined on Agent Level ===")
# Tools are provided when creating the agent
# The agent can use these tools for any query during its lifetime
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful assistant that can provide weather and time information.",
tools=[get_weather, get_time], # Tools defined at agent creation
)
# First query - agent can use weather tool
query1 = "What's the weather like in New York?"
print(f"User: {query1}")
result1 = await agent.run(query1)
print(f"Agent: {result1}\n")
# Second query - agent can use time tool
query2 = "What's the current UTC time?"
print(f"User: {query2}")
result2 = await agent.run(query2)
print(f"Agent: {result2}\n")
# Third query - agent can use both tools if needed
query3 = "What's the weather in London and what's the current UTC time?"
print(f"User: {query3}")
result3 = await agent.run(query3)
print(f"Agent: {result3}\n")
async def tools_on_run_level() -> None:
"""Example showing tools passed to the run method."""
print("=== Tools Passed to Run Method ===")
# Agent created without tools
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful assistant.",
# No tools defined here
)
# First query with weather tool
query1 = "What's the weather like in Seattle?"
print(f"User: {query1}")
result1 = await agent.run(query1, tools=[get_weather]) # Tool passed to run method
print(f"Agent: {result1}\n")
# Second query with time tool
query2 = "What's the current UTC time?"
print(f"User: {query2}")
result2 = await agent.run(query2, tools=[get_time]) # Different tool for this query
print(f"Agent: {result2}\n")
# Third query with multiple tools
query3 = "What's the weather in Chicago and what's the current UTC time?"
print(f"User: {query3}")
result3 = await agent.run(query3, tools=[get_weather, get_time]) # Multiple tools
print(f"Agent: {result3}\n")
async def mixed_tools_example() -> None:
"""Example showing both agent-level tools and run-method tools."""
print("=== Mixed Tools Example (Agent + Run Method) ===")
# Agent created with some base tools
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a comprehensive assistant that can help with various information requests.",
tools=[get_weather], # Base tool available for all queries
)
# Query using both agent tool and additional run-method tools
query = "What's the weather in Denver and what's the current UTC time?"
print(f"User: {query}")
# Agent has access to get_weather (from creation) + additional tools from run method
result = await agent.run(
query,
tools=[get_time], # Additional tools for this specific query
)
print(f"Agent: {result}\n")
async def main() -> None:
print("=== Azure Chat Client Agent with Function Tools Examples ===\n")
await tools_on_agent_level()
await tools_on_run_level()
await mixed_tools_example()
if __name__ == "__main__":
asyncio.run(main())
@@ -0,0 +1,161 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from random import randint
from typing import Annotated
from agent_framework import Agent, AgentSession, InMemoryHistoryProvider, tool
from agent_framework.openai import OpenAIChatCompletionClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from pydantic import Field
# Load environment variables from .env file
load_dotenv()
"""
Azure OpenAI Chat Client with Session Management Example
This sample demonstrates session management with Azure OpenAI Chat Client, comparing
automatic session creation with explicit session management for persistent context.
"""
# 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."
async def example_with_automatic_session_creation() -> None:
"""Example showing automatic session creation (service-managed session)."""
print("=== Automatic Session Creation Example ===")
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful weather agent.",
tools=get_weather,
)
# First conversation - no session provided, will be created automatically
query1 = "What's the weather like in Seattle?"
print(f"User: {query1}")
result1 = await agent.run(query1)
print(f"Agent: {result1.text}")
# Second conversation - still no session provided, will create another new session
query2 = "What was the last city I asked about?"
print(f"\nUser: {query2}")
result2 = await agent.run(query2)
print(f"Agent: {result2.text}")
print("Note: Each call creates a separate session, so the agent doesn't remember previous context.\n")
async def example_with_session_persistence() -> None:
"""Example showing session persistence across multiple conversations."""
print("=== Session Persistence Example ===")
print("Using the same session across multiple conversations to maintain context.\n")
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# authentication option.
agent = Agent(
client=OpenAIChatCompletionClient(credential=AzureCliCredential()),
instructions="You are a helpful weather agent.",
tools=get_weather,
)
# Create a new session that will be reused
session = agent.create_session()
# First conversation
query1 = "What's the weather like in Tokyo?"
print(f"User: {query1}")
result1 = await agent.run(query1, session=session)
print(f"Agent: {result1.text}")
# Second conversation using the same session - maintains context
query2 = "How about London?"
print(f"\nUser: {query2}")
result2 = await agent.run(query2, session=session)
print(f"Agent: {result2.text}")
# Third conversation - agent should remember both previous cities
query3 = "Which of the cities I asked about has better weather?"
print(f"\nUser: {query3}")
result3 = await agent.run(query3, session=session)
print(f"Agent: {result3.text}")
print("Note: The agent remembers context from previous messages in the same session.\n")
async def example_with_existing_session_messages() -> None:
"""Example showing how to work with existing session messages for Azure."""
print("=== Existing Session Messages Example ===")
# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
# 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())