Skip to main content

Quick Start

Spin up FleetLM locally, register an agent webhook, and send your first message.

1. Run the stack​

Checkout the repository

git clone https://github.com/cpluss/fleetlm.git
cd fleetlm

Run the test stack using docker

docker compose up

The API and WebSocket endpoints are available at http://localhost:4000 and ws://localhost:4000/socket.

2. Register an agent​

Tell FleetLM where your agent lives.

curl -X POST http://localhost:4000/api/agents \
  -H "Content-Type: application/json" \
  -d '{
    "agent": {
      "id": "demo-agent",
      "name": "Demo Agent",
      "origin_url": "http://localhost:3000",
      "webhook_path": "/webhook",
      "message_history_mode": "tail",
      "message_history_limit": 10,
      "timeout_ms": 30000,
      "status": "enabled"
    }
  }'

Your webhook will receive the session id, agent id, user id, and the most recent messages. See Agent Webhooks for the exact format.

3. Create a session​

Every session need to be created upfront so we know what agent to connect it to.

curl -X POST http://localhost:4000/api/sessions \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "alice",
    "agent_id": "demo-agent"
  }'

Save the id from the response. All future REST and WebSocket calls reference it.

4. Send a message​

Sending a message using the REST API is easy, and follows a flexible format that mirror many popular platforms (e.g. OpenAI) today.

curl -X POST http://localhost:4000/api/sessions/{session_id}/messages \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "alice",
    "kind": "text",
    "content": {"text": "Hello!"}
  }'

FleetLM stores the user message, invokes your agent webhook, and streams each JSONL line your agent returns into the session.

5. Read the conversation​

curl http://localhost:4000/api/sessions/{session_id}/messages

You should see the user message and any responses produced by your agent. For real-time streaming or cursor management, continue with Clients.