a2a-langgraph-boilerplate

# A2A LangGraph Boilerplate This project is a boilerplate for developers who want to start building an AI agent cluster faster and more efficiently. ## Features * Create & manage AI crews * Create & manage AI agents * Create & manage MCP servers * Create & manage Tools * Integrate MCP servers for tool usage * Monitor activity logs * Create & manage conversations with AI crews / AI agents * Expose Swagger API Docs for frontend integration instructions ## Getting Started ### Prerequisites * Python 3.11+ * PostgreSQL ### Installation 1. **Clone the repository:** ```bash git clone https://github.com/your-username/a2a-langgraph-boilerplate.git cd a2a-langgraph-boilerplate ``` 2. **Create and activate a virtual environment:** ```bash python3 -m venv venv source venv/bin/activate ``` 3. **Install the dependencies:** ```bash pip install -r requirements.txt ``` 4. **Set up the database:** * Ensure your PostgreSQL server is running. * Create a new database named `a2a-langgraph-boilerplate`. You can use the following command: ```bash createdb "a2a-langgraph-boilerplate" ``` * Copy the `.env.example` file to `.env`: ```bash cp .env.example .env ``` * Update the `DATABASE_URL` in the `.env` file with your PostgreSQL credentials. 5. **Create the database tables:** ```bash python create_tables.py ``` ### Running the Application To start the application, run the following command: ```bash uvicorn app.main:app --reload ``` The application will be available at `http://127.0.0.1:8000`. ## API Documentation The API documentation is automatically generated by FastAPI and is available at the following URLs: * **Swagger UI:** [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs) * **ReDoc:** [http://127.0.0.1:8000/redoc](http://127.0.0.1:8000/redoc)