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+# Multi-Agent Travel Planning Workflow Evaluation
+
+This sample demonstrates evaluating a multi-agent workflow using Azure AI's built-in evaluators. The workflow processes travel planning requests through seven specialized agents in a fan-out/fan-in pattern: travel request handler, hotel/flight/activity search agents, booking aggregator, booking confirmation, and payment processing.
+
+## Evaluation Metrics
+
+The evaluation uses four Azure AI built-in evaluators:
+
+- **Relevance** - How well responses address the user query
+- **Groundedness** - Whether responses are grounded in available context
+- **Tool Call Accuracy** - Correct tool selection and parameter usage
+- **Tool Output Utilization** - Effective use of tool outputs in responses
+
+## Setup
+
+Create a `.env` file with configuration as in the `.env.example` file in this folder.
+
+## Running the Evaluation
+
+Execute the complete workflow and evaluation:
+
+```bash
+python run_evaluation.py
+```
+
+The script will:
+1. Execute the multi-agent travel planning workflow
+2. Display response summary for each agent
+3. Create and run evaluation on hotel, flight, and activity search agents
+4. Monitor progress and display the evaluation report URL