A FastAPI backend with a LangGraph-based multi-agent architecture using Claude's API and browser-use for web automation.
- Create a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate- Install dependencies:
pip install -r requirements.txt- Create a
.envfile in the root directory with your Anthropic API key:
ANTHROPIC_API_KEY=your_api_key_here
Start the server:
uvicorn main:app --reloadThe server will run on http://localhost:8000
Execute a task using the multi-agent system.
Request body:
{
"task": "Your task description",
"context": {
"any": "additional context"
}
}Response:
{
"result": "Task execution result",
"status": "success"
}The system uses:
- FastAPI for the web server
- LangGraph for the multi-agent architecture
- Claude's API for agent intelligence
- browser-use for web automation
The workflow consists of:
- Master Agent: Analyzes the task and creates a plan
- Execution Agent: Carries out the plan using available tools