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Eduard van Valkenburg 5e056b672e 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>
5e056b672e · 2026-03-25 09:56:29 +00:00
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Purview Policy Enforcement Sample (Python)

This getting-started sample shows how to attach Microsoft Purview policy evaluation to an Agent Framework Agent using the middleware approach.

What this sample demonstrates:

  1. Configure an Azure OpenAI chat client
  2. Add Purview policy enforcement middleware (PurviewPolicyMiddleware)
  3. Add Purview policy enforcement at the chat client level (PurviewChatPolicyMiddleware)
  4. Implement a custom cache provider for advanced caching scenarios
  5. Run conversations and observe prompt / response blocking behavior

Note: Caching is automatic and enabled by default with sensible defaults (30-minute TTL, 200MB max size).


1. Setup

Required Environment Variables

Variable Required Purpose
AZURE_OPENAI_ENDPOINT Yes Azure OpenAI endpoint (https://.openai.azure.com)
AZURE_OPENAI_DEPLOYMENT_NAME Optional Model deployment name (defaults inside SDK if omitted)
PURVIEW_CLIENT_APP_ID Yes* Client (application) ID used for Purview authentication
PURVIEW_USE_CERT_AUTH Optional (true/false) Switch between certificate and interactive auth
PURVIEW_TENANT_ID Yes (when cert auth on) Tenant ID for certificate authentication
PURVIEW_CERT_PATH Yes (when cert auth on) Path to your .pfx certificate
PURVIEW_CERT_PASSWORD Optional Password for encrypted certs

2. Auth Modes Supported

A. Interactive Browser Authentication (default)

Opens a browser on first run to sign in.

$env:AZURE_OPENAI_ENDPOINT = "https://your-openai-instance.openai.azure.com"
$env:PURVIEW_CLIENT_APP_ID = "00000000-0000-0000-0000-000000000000"

B. Certificate Authentication

For headless / CI scenarios.

$env:PURVIEW_USE_CERT_AUTH = "true"
$env:PURVIEW_TENANT_ID = "<tenant-guid>"
$env:PURVIEW_CERT_PATH = "C:\path\to\cert.pfx"
$env:PURVIEW_CERT_PASSWORD = "optional-password"

Certificate steps (summary): create / register entra app, generate certificate, upload public key, export .pfx with private key, grant required Graph / Purview permissions.


3. Run the Sample

From repo root:

cd python/samples/05-end-to-end/purview_agent
python sample_purview_agent.py

If interactive auth is used, a browser window will appear the first time.


4. How It Works

The sample demonstrates three different scenarios:

A. Agent Middleware (run_with_agent_middleware)

  1. Builds an Azure OpenAI chat client (using the environment endpoint / deployment)
  2. Chooses credential mode (certificate vs interactive)
  3. Creates PurviewPolicyMiddleware with PurviewSettings
  4. Injects middleware into the agent at construction
  5. Sends two user messages sequentially
  6. Prints results (or policy block messages)
  7. Uses default caching automatically

B. Chat Client Middleware (run_with_chat_middleware)

  1. Creates a chat client with PurviewChatPolicyMiddleware attached directly
  2. Policy evaluation happens at the chat client level rather than agent level
  3. Demonstrates an alternative integration point for Purview policies
  4. Uses default caching automatically

C. Custom Cache Provider (run_with_custom_cache_provider)

  1. Implements the CacheProvider protocol with a custom class (SimpleDictCacheProvider)
  2. Shows how to add custom logging and metrics to cache operations
  3. The custom provider must implement three async methods:
    • async def get(self, key: str) -> Any | None
    • async def set(self, key: str, value: Any, ttl_seconds: int | None = None) -> None
    • async def remove(self, key: str) -> None

Policy Behavior: Prompt blocks set a system-level message: Prompt blocked by policy and terminate the run early. Response blocks rewrite the output to Response blocked by policy.


5. Code Snippets

Agent Middleware Injection

agent = Agent(
	client=client,
	instructions="You are good at telling jokes.",
	name="Joker",
	middleware=[
		PurviewPolicyMiddleware(credential, PurviewSettings(app_name="Sample App"))
	],
)

Custom Cache Provider Implementation

This is only needed if you want to integrate with external caching systems.

class SimpleDictCacheProvider:
    """Custom cache provider that implements the CacheProvider protocol."""

    def __init__(self) -> None:
        self._cache: dict[str, Any] = {}

    async def get(self, key: str) -> Any | None:
        """Get a value from the cache."""
        return self._cache.get(key)

    async def set(self, key: str, value: Any, ttl_seconds: int | None = None) -> None:
        """Set a value in the cache."""
        self._cache[key] = value

    async def remove(self, key: str) -> None:
        """Remove a value from the cache."""
        self._cache.pop(key, None)

# Use the custom cache provider
custom_cache = SimpleDictCacheProvider()
middleware = PurviewPolicyMiddleware(
    credential,
    PurviewSettings(app_name="Sample App"),
    cache_provider=custom_cache,
)