- Moved getting_started/durabletask to durable/console_apps - Moved getting_started/azure_functions to durable/azure_functions - Updated all paths in README files - Created durable/README.md with overview - Updated main samples README.md with new structure Co-authored-by: larohra <41490930+larohra@users.noreply.github.com>
Multi-Agent Sample
This sample demonstrates how to use the Durable Extension for Agent Framework to create an Azure Functions app that hosts multiple AI agents and provides direct HTTP API access for interactive conversations with each agent.
Key Concepts Demonstrated
- Using the Microsoft Agent Framework to define multiple AI agents with unique names and instructions.
- Registering multiple agents with the Function app and running them using HTTP.
- Conversation management (via thread IDs) for isolated interactions per agent.
- Two different methods for registering agents: list-based initialization and incremental addition.
Prerequisites
Complete the common environment preparation steps described in ../README.md, including installing Azure Functions Core Tools, starting Azurite, configuring Azure OpenAI settings, and installing this sample's requirements.
Running the Sample
With the environment setup and function app running, you can test the sample by sending HTTP requests to the different agent endpoints.
You can use the demo.http file to send messages to the agents, or a command line tool like curl as shown below:
Note: Each endpoint waits for the agent response by default. To receive an immediate HTTP 202 instead, set the
x-ms-wait-for-responseheader or include"wait_for_response": falsein the request body.
Test the Weather Agent
Bash (Linux/macOS/WSL): Weather agent request:
curl -X POST http://localhost:7071/api/agents/WeatherAgent/run \
-H "Content-Type: application/json" \
-d '{"message": "What is the weather in Seattle?"}'
Expected HTTP 202 payload:
{
"status": "accepted",
"response": "Agent request accepted",
"message": "What is the weather in Seattle?",
"thread_id": "<guid>",
"correlation_id": "<guid>"
}
Math agent request:
curl -X POST http://localhost:7071/api/agents/MathAgent/run \
-H "Content-Type: application/json" \
-d '{"message": "Calculate a 20% tip on a $50 bill"}'
Expected HTTP 202 payload:
{
"status": "accepted",
"response": "Agent request accepted",
"message": "Calculate a 20% tip on a $50 bill",
"thread_id": "<guid>",
"correlation_id": "<guid>"
}
Health check (optional):
curl http://localhost:7071/api/health
Expected response:
{
"status": "healthy",
"agents": [
{"name": "WeatherAgent", "type": "ChatAgent"},
{"name": "MathAgent", "type": "ChatAgent"}
],
"agent_count": 2
}
Code Structure
The sample demonstrates two ways to register multiple agents:
Option 1: Pass list of agents during initialization
app = AgentFunctionApp(agents=[weather_agent, math_agent])
Option 2: Add agents incrementally (commented in sample)
app = AgentFunctionApp()
app.add_agent(weather_agent)
app.add_agent(math_agent)
Each agent automatically gets:
POST /api/agents/{agent_name}/run- Send messages to the agent