* 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>
Sample Integration Tests
Integration tests that validate the Durable Agent Framework samples by running them against a Durable Task Scheduler (DTS) instance.
Setup
1. Create .env file
Copy .env.example to .env and fill in your Azure credentials:
cp .env.example .env
Required variables:
AZURE_OPENAI_ENDPOINTAZURE_OPENAI_DEPLOYMENT_NAMEAZURE_OPENAI_API_KEY(optional if using Azure CLI authentication)ENDPOINT(default: http://localhost:8080)TASKHUB(default: default)
Optional variables (for streaming tests):
REDIS_CONNECTION_STRING(default: redis://localhost:6379)REDIS_STREAM_TTL_MINUTES(default: 10)
2. Start required services
Durable Task Scheduler:
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest
- Port 8080: gRPC endpoint (used by tests)
- Port 8082: Web dashboard (optional, for monitoring)
Redis (for streaming tests):
docker run -d --name redis -p 6379:6379 redis:latest
- Port 6379: Redis server endpoint
Running Tests
The tests automatically start and stop worker processes for each sample.
Run all sample tests
uv run pytest packages/durabletask/tests/integration_tests -v
Run specific sample
uv run pytest packages/durabletask/tests/integration_tests/test_01_single_agent.py -v
Run with verbose output
uv run pytest packages/durabletask/tests/integration_tests -sv
How It Works
Each test file uses pytest markers to automatically configure and start the worker process:
pytestmark = [
pytest.mark.sample("03_single_agent_streaming"),
pytest.mark.integration_test,
pytest.mark.requires_azure_openai,
pytest.mark.requires_dts,
pytest.mark.requires_redis,
]
Troubleshooting
Tests are skipped:
Ensure the required environment variables (e.g., AZURE_OPENAI_ENDPOINT) are set in your .env file.
DTS connection failed:
Check that the DTS emulator container is running: docker ps | grep dts-emulator
Redis connection failed:
Check that Redis is running: docker ps | grep redis
Missing environment variables:
Ensure your .env file contains all required variables from .env.example.
Tests timeout: Check that Azure OpenAI credentials are valid and the service is accessible.
If you see "DTS emulator is not available":
- Ensure Docker container is running:
docker ps | grep dts-emulator - Check port 8080 is not in use by another process
- Restart the container if needed
Azure OpenAI Errors
If you see authentication or deployment errors:
- Verify your
AZURE_OPENAI_ENDPOINTis correct - Confirm
AZURE_OPENAI_DEPLOYMENT_NAMEmatches your deployment - If using API key, check
AZURE_OPENAI_API_KEYis valid - If using Azure CLI, ensure you're logged in:
az login
CI/CD
For automated testing in CI/CD pipelines:
- Use Docker Compose to start DTS emulator
- Set environment variables via CI/CD secrets
- Run tests with appropriate markers:
pytest -m integration_test