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+# 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](../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`):
+
+```bash
+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:
+
+```bash
+cd samples/04-hosting/durabletask/08_workflow
+python worker.py
+```
+
+In a second terminal, run the client:
+
+```bash
+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: ..."`.