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# Multi-Agent
This sample demonstrates how to host multiple AI agents with different tools in a single worker-client setup using the Durable Task Scheduler.
## Key Concepts Demonstrated
- Hosting multiple agents (WeatherAgent and MathAgent) in a single worker process.
- Each agent with its own specialized tools and instructions.
- Interacting with different agents using separate conversation sessions.
- Worker-client architecture for multi-agent systems.
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup, you can run the sample using the combined approach or separate worker and client processes:
**Option 1: Combined (Recommended for Testing)**
```bash
cd samples/04-hosting/durabletask/02_multi_agent
python sample.py
```
**Option 2: Separate Processes**
Start the worker in one terminal:
```bash
python worker.py
```
In a new terminal, run the client:
```bash
python client.py
```
The client will interact with both agents:
```
Starting Durable Task Multi-Agent Client...
Using taskhub: default
Using endpoint: http://localhost:8080
================================================================================
Testing WeatherAgent
================================================================================
Created weather conversation session: <guid>
User: What is the weather in Seattle?
🔧 [TOOL CALLED] get_weather(location=Seattle)
✓ [TOOL RESULT] {'location': 'Seattle', 'temperature': 72, 'conditions': 'Sunny', 'humidity': 45}
WeatherAgent: The current weather in Seattle is sunny with a temperature of 72°F and 45% humidity.
================================================================================
Testing MathAgent
================================================================================
Created math conversation session: <guid>
User: Calculate a 20% tip on a $50 bill
🔧 [TOOL CALLED] calculate_tip(bill_amount=50.0, tip_percentage=20.0)
✓ [TOOL RESULT] {'bill_amount': 50.0, 'tip_percentage': 20.0, 'tip_amount': 10.0, 'total': 60.0}
MathAgent: For a $50 bill with a 20% tip, the tip amount is $10.00 and the total is $60.00.
```
## Viewing Agent State
You can view the state of both agents in the Durable Task Scheduler dashboard:
1. Open your browser and navigate to `http://localhost:8082`
2. In the dashboard, you can view:
- The state of both WeatherAgent and MathAgent entities (dafx-WeatherAgent, dafx-MathAgent)
- Each agent's conversation state across multiple interactions