create-agent

A CLI tool to quickly scaffold LLM agent API projects with an OpenAI-compatible interface.

Features

• Create a new agent project with a single command
• Includes ready-to-use API endpoints compatible with OpenAI's chat completion API
• Built-in RAG (Retrieval Augmented Generation) capabilities using LangGraph
• Support for custom tool definitions
• Complete FastAPI application structure

Installation

pip install create-agent

Usage

Create a new agent project:

create-agent my-agent

This will create a new directory called my-agent with all the necessary files to run an agent API.

Options

• --template: Specify a template to use (default: "default")
• --output-dir: Specify the output directory (default: current directory)

create-agent my-agent --output-dir projects

Project Structure

The generated project follows a well-organized structure:

my-agent/
├── app/
│   ├── api/            # API definitions and models
│   ├── core/           # Core functionality
│   ├── rag/            # RAG implementation with LangGraph
│   ├── services/       # Business logic services
│   ├── utils/          # Utility functions
│   ├── config.py       # Application configuration
│   └── main.py         # FastAPI application
├── .env.example        # Environment variables template
├── .gitignore          # Git ignore file
├── README.md           # Project documentation
└── requirements.txt    # Dependencies

Next Steps After Creating a Project

1. Navigate to your new project directory:

   cd my-agent
   

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Set up your environment variables:

   cp .env.example .env
   

5. Edit the .env file with your API keys and configuration

6. Run the application:

   uvicorn app.main:app --reload
   

License

MIT