README.en.md

DeepSite

English | Indonesian

This project is a modified version of enzostvs/deepsite.

DeepSite is an application generation tool based on various large language models, allowing users to quickly generate various web applications through simple descriptions. The project is built using modern web technology stack, including React, TypeScript, Vite, and Express.

Features

• Generate complete web applications based on natural language descriptions
• Built-in Vue, various components, and tool library templates
• Integrated code editor with real-time preview and editing
• English and Indonesian language support
• Responsive design, adapting to various devices

Requirements

• Node.js 18.x or higher
• npm or yarn package manager
• Docker and Docker Compose (for containerized deployment)

Vercel Deployment

You can deploy to Vercel with one click using the button below:

Configure Vercel Environment Variables

During Vercel deployment, you need to configure the following environment variables:

Any API provider that conforms to the OpenAI request and response format can be used. If not configured in the environment variables, you will need to configure it in the page settings.

Environment Variable	Description	Example
OPENAI_API_KEY	OpenAI or DeepSeek API key	sk-xxxxxxxxxxxxxxxx
OPENAI_MODEL	Model name to use	deepseek-chat/DeepSeek-V3-0324 or gpt-4o
OPENAI_BASE_URL	API base URL	https://api.deepseek.com/v1 or https://api.openai.com/v1
IP_RATE_LIMIT	Maximum requests per hour per IP	100

Note: If IP_RATE_LIMIT is not set or set to a value less than or equal to 0, IP rate limiting will not be enabled.

Note: In Vercel deployment, due to the default timeout of 10s for the free version of Vercel, you need to configure Function Max Duration in the project's Settings. The maximum setting for the free version is 60s.

Build Commands

In your Vercel project settings, ensure you set the correct build commands:

• Build Command: npm run build
• Output Directory: dist

Local Development

Environment Setup

1. Clone the repository:

git clone https://github.com/yourusername/deepsite.git
cd deepsite

2. Create an environment variable file:

cp .env.example .env

3. Edit the .env file and fill in the necessary API keys and configurations:

APP_PORT=3000
OPENAI_API_KEY=your_openai_api_key_here
OPENAI_MODEL=gpt-4o
OPENAI_BASE_URL=https://api.openai.com/v1
IP_RATE_LIMIT=100  # Max requests per hour per IP, set to 0 or omit to disable rate limiting

Install Dependencies

npm install

Run in Development Mode

npm run start:dev

The development server will run at http://localhost:5173

Run in Production Mode

npm run build && npm run start

The production server runs by default at http://localhost:3000; the port can be configured via the APP_PORT variable in the .env file.

Docker Deployment

Using Docker Compose

Docker image is available: docker pull 195658/deepsite:latest

1. Make sure Docker and Docker Compose are installed
2. Edit the docker-compose.yml file, setting the necessary environment variables:

version: '3.8'

services:
  web:
    image: 195658/deepsite:latest
    ports:
      - "30002:3000"
    environment:
      - OPENAI_API_KEY=your_openai_api_key_here
      - OPENAI_MODEL=gpt-4o
      - OPENAI_BASE_URL=https://api.openai.com/v1
      - APP_PORT=3000
      - IP_RATE_LIMIT=100  # Max requests per hour per IP, set to 0 to disable limiting
    restart: unless-stopped

3. Build and start the container:

docker-compose up -d

The application will run at http://localhost:30002.

Direct Docker Build

1. Build the Docker image:

docker build -t deepsite .

2. Run the container:

docker run -d -p 30002:3000 --name deepsite \
  -e OPENAI_API_KEY=your_openai_api_key_here \
  -e OPENAI_MODEL=gpt-4o \
  -e OPENAI_BASE_URL=https://api.openai.com/v1 \
  -e APP_PORT=3000 \
  -e IP_RATE_LIMIT=100 \
  deepsite

Hugging Face Spaces Deployment

This project is configured to be deployed on Hugging Face Spaces. For configuration details, please refer to: https://huggingface.co/docs/hub/spaces-config-reference

Contribution Guidelines

Feel free to submit Issues and Pull Requests to help improve this project. Before submitting code, please ensure:

1. Follow existing code style
2. Add appropriate tests
3. Update relevant documentation

License

MIT