08_workflow

Workflow on a Standalone Durable Task Worker

This sample demonstrates running an agent-framework Workflow as a durable orchestration on a standalone Durable Task worker — no Azure Functions required. It is the durabletask counterpart to the Azure Functions workflow samples (samples/04-hosting/azure_functions/10_workflow_no_shared_state).

Key Concepts Demonstrated

• Hosting a MAF Workflow outside Azure Functions via DurableAIAgentWorker.configure_workflow(workflow), which auto-registers:
  • a durable entity for each agent executor,
  • a durable activity for each non-agent executor, and
  • the workflow orchestrator (registered as WORKFLOW_ORCHESTRATOR_NAME).
• Conditional routing with add_switch_case_edge_group (spam vs. legitimate email).
• Mixing AI agents with non-agent executors in one workflow graph.
• Starting the workflow from a client with DurableWorkflowClient.start_workflow(input=...) and reading its result with await_workflow_output(instance_id).

Environment Setup

See the README.md in the parent directory for environment setup.

This sample uses Azure AI Foundry credentials:

• FOUNDRY_PROJECT_ENDPOINT
• FOUNDRY_MODEL

It also needs a Durable Task Scheduler. For local development, start the emulator (defaults to http://localhost:8080):

docker run -d -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest

Running the Sample

Start the worker in one terminal:

cd samples/04-hosting/durabletask/08_workflow
python worker.py

In a second terminal, run the client:

python client.py

The client runs two cases:

• Legitimate email → SpamDetectionAgent → EmailAssistantAgent → email_sender → "Email sent: ...".
• Spam email → SpamDetectionAgent → spam_handler → "Email marked as spam: ...".