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>

python/samples/03-workflows/orchestrations/magentic_checkpoint.py

@@ -15,7 +15,7 @@ from agent_framework import (
     WorkflowEvent,
     WorkflowRunState,
 )
-from agent_framework.azure import AzureOpenAIResponsesClient
+from agent_framework.foundry import FoundryChatClient
 from agent_framework.orchestrations import MagenticBuilder, MagenticPlanReviewRequest
 from azure.identity import AzureCliCredential
 from dotenv import load_dotenv
@@ -39,8 +39,8 @@ Concepts highlighted here:
    `responses` mapping so we can inject the stored human reply during restoration.
 
 Prerequisites:
-- AZURE_AI_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
-- Azure OpenAI configured for AzureOpenAIResponsesClient with required environment variables.
+- FOUNDRY_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
+- Azure OpenAI configured for FoundryChatClient with required environment variables.
 - Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
 """
 
@@ -64,9 +64,9 @@ def build_workflow(checkpoint_storage: FileCheckpointStorage):
         name="ResearcherAgent",
         description="Collects background facts and references for the project.",
         instructions=("You are the research lead. Gather crisp bullet points the team should know."),
-        client=AzureOpenAIResponsesClient(
-            project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
-            deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        client=FoundryChatClient(
+            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+            model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             credential=AzureCliCredential(),
         ),
     )
@@ -75,9 +75,9 @@ def build_workflow(checkpoint_storage: FileCheckpointStorage):
         name="WriterAgent",
         description="Synthesizes the final brief for stakeholders.",
         instructions=("You convert the research notes into a structured brief with milestones and risks."),
-        client=AzureOpenAIResponsesClient(
-            project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
-            deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        client=FoundryChatClient(
+            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+            model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             credential=AzureCliCredential(),
         ),
     )
@@ -87,9 +87,9 @@ def build_workflow(checkpoint_storage: FileCheckpointStorage):
         name="MagenticManager",
         description="Orchestrator that coordinates the research and writing workflow",
         instructions="You coordinate a team to complete complex tasks efficiently.",
-        client=AzureOpenAIResponsesClient(
-            project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
-            deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        client=FoundryChatClient(
+            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+            model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             credential=AzureCliCredential(),
         ),
     )