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Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)

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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>
This commit is contained in:
Eduard van Valkenburg
2026-03-25 10:56:29 +01:00
committed by GitHub
Unverified
parent 4b533608b6
commit 5e056b672e
485 changed files with 9784 additions and 12084 deletions
Download Patch File Download Diff File Expand all files Collapse all files
python/samples/02-agents/context_providers/redis/azure_redis_conversation.py
+10 -10
View File
@@ -17,23 +17,22 @@ Requirements:
Environment Variables:
- AZURE_REDIS_HOST: Your Azure Managed Redis host (e.g., myredis.redis.cache.windows.net)
- AZURE_AI_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
- AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: Azure OpenAI Responses deployment name
- FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
- FOUNDRY_MODEL: Azure OpenAI Responses deployment name
- AZURE_USER_OBJECT_ID: Your Azure AD User Object ID for authentication
"""
import asyncio
import os
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from agent_framework.redis import RedisHistoryProvider
from azure.identity import AzureCliCredential
from azure.identity.aio import AzureCliCredential as AsyncAzureCliCredential
from dotenv import load_dotenv
from redis.credentials import CredentialProvider
# Load environment variables from .env file
load_dotenv()
# Copyright (c) Microsoft. All rights reserved.
class AzureCredentialProvider(CredentialProvider):
@@ -81,14 +80,15 @@ async def main() -> None:
)
# 3. Create chat client
client = AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
# 4. Create agent with Azure Redis history provider
agent = client.as_agent(
agent = Agent(
client=client,
name="AzureRedisAssistant",
instructions="You are a helpful assistant.",
context_providers=[history_provider],
python/samples/02-agents/context_providers/redis/redis_basics.py
+11 -9
View File
@@ -30,8 +30,8 @@ Run:
import asyncio
import os
from agent_framework import Message, tool
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework import Agent, Message, tool
from agent_framework.foundry import FoundryChatClient
from agent_framework.redis import RedisContextProvider
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
@@ -99,11 +99,11 @@ def search_flights(origin_airport_code: str, destination_airport_code: str, deta
)
def create_chat_client() -> AzureOpenAIResponsesClient:
def create_chat_client() -> FoundryChatClient:
"""Create an Azure OpenAI Responses client using a Foundry project endpoint."""
return AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
return FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
@@ -121,7 +121,7 @@ async def main() -> None:
# Create a provider with partition scope and OpenAI embeddings
# Please set OPENAI_API_KEY to use the OpenAI vectorizer.
# For chat responses, also set AZURE_AI_PROJECT_ENDPOINT and AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
# For chat responses, also set FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL.
# We attach an embedding vectorizer so the provider can perform hybrid (text + vector)
# retrieval. If you prefer text-only retrieval, instantiate RedisContextProvider without the
@@ -206,7 +206,8 @@ async def main() -> None:
client = create_chat_client()
# Create agent wired to the Redis context provider. The provider automatically
# persists conversational details and surfaces relevant context on each turn.
agent = client.as_agent(
agent = Agent(
client=client,
name="MemoryEnhancedAssistant",
instructions=(
"You are a helpful assistant. Personalize replies using provided context. "
@@ -249,7 +250,8 @@ async def main() -> None:
# Create agent exposing the flight search tool. Tool outputs are captured by the
# provider and become retrievable context for later turns.
client = create_chat_client()
agent = client.as_agent(
agent = Agent(
client=client,
name="MemoryEnhancedAssistant",
instructions=(
"You are a helpful assistant. Personalize replies using provided context. "
python/samples/02-agents/context_providers/redis/redis_conversation.py
+9 -8
View File
@@ -21,15 +21,15 @@ Run:
import asyncio
import os
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from agent_framework.redis import RedisContextProvider
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from redisvl.extensions.cache.embeddings import EmbeddingsCache
from redisvl.utils.vectorize import OpenAITextVectorizer
# Load environment variables from .env file
load_dotenv()
# Copyright (c) Microsoft. All rights reserved.
# Default Redis URL for local Redis Stack.
# Override via the REDIS_URL environment variable for remote or authenticated instances.
@@ -64,14 +64,15 @@ async def main() -> None:
)
# Create chat client for the agent
client = AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
# Create agent wired to the Redis context provider. The provider automatically
# persists conversational details and surfaces relevant context on each turn.
agent = client.as_agent(
agent = Agent(
client=client,
name="MemoryEnhancedAssistant",
instructions=(
"You are a helpful assistant. Personalize replies using provided context. "
python/samples/02-agents/context_providers/redis/redis_sessions.py
+17 -13
View File
@@ -29,15 +29,15 @@ Run:
import asyncio
import os
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from agent_framework.redis import RedisContextProvider
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
from redisvl.extensions.cache.embeddings import EmbeddingsCache
from redisvl.utils.vectorize import OpenAITextVectorizer
# Load environment variables from .env file
load_dotenv()
# Copyright (c) Microsoft. All rights reserved.
# Default Redis URL for local Redis Stack.
# Override via the REDIS_URL environment variable for remote or authenticated instances.
@@ -45,12 +45,12 @@ REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379")
# Please set OPENAI_API_KEY to use the OpenAI vectorizer.
# For chat responses, also set AZURE_AI_PROJECT_ENDPOINT and AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
def create_chat_client() -> AzureOpenAIResponsesClient:
# For chat responses, also set FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL.
def create_chat_client() -> FoundryChatClient:
"""Create an Azure OpenAI Responses client using a Foundry project endpoint."""
return AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
return FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
@@ -71,7 +71,8 @@ async def example_global_thread_scope() -> None:
user_id="threads_demo_user",
)
agent = client.as_agent(
agent = Agent(
client=client,
name="GlobalMemoryAssistant",
instructions=(
"You are a helpful assistant. Personalize replies using provided context. "
@@ -128,7 +129,8 @@ async def example_per_operation_thread_scope() -> None:
vector_distance_metric="cosine",
)
agent = client.as_agent(
agent = Agent(
client=client,
name="ScopedMemoryAssistant",
instructions="You are an assistant with thread-scoped memory.",
context_providers=[provider],
@@ -191,7 +193,8 @@ async def example_multiple_agents() -> None:
vector_distance_metric="cosine",
)
personal_agent = client.as_agent(
personal_agent = Agent(
client=client,
name="PersonalAssistant",
instructions="You are a personal assistant that helps with personal tasks.",
context_providers=[personal_provider],
@@ -210,7 +213,8 @@ async def example_multiple_agents() -> None:
vector_distance_metric="cosine",
)
work_agent = client.as_agent(
work_agent = Agent(
client=client,
name="WorkAssistant",
instructions="You are a work assistant that helps with professional tasks.",
context_providers=[work_provider],