中文 | English

✨ Features

• Multi-Model Orchestration: Seamlessly combine multiple AI models in customizable workflows
• Role Management: Create AI roles with different personalities and skills
• Discussion Groups: Combine multiple roles to form discussion groups
• Multiple Discussion Modes:
  • General Discussion
  • Brainstorming
  • Debate
  • Role-playing
  • SWOT Analysis
  • Six Thinking Hats
• Provider Flexibility: Support for multiple AI providers:
  • DeepSeek
  • Claude
  • Gemini
  • Grok3
  • OpenAI
  • OneAPI
  • OpenRouter
  • Siliconflow
• OpenAI Compatible: Drop-in replacement for OpenAI’s API in existing applications
• Stream Support: Real-time streaming responses for better user experience
• Advanced Configuration: Fine-grained control over model parameters and system prompts
• Database Integration: SQLite-based configuration storage with Alembic migrations
• Web Management UI: Built-in interface for managing models and configurations
• Multi-language Support: English and Chinese interface

Preview

🚀 Quick Start

1. Installation

git clone https://github.com/sligter/DeepGemini.git
cd DeepGemini
uv sync

2. Configuration

cp .env.example .env

Required environment variables:

• ALLOW_API_KEY: Your API access key
• ALLOW_ORIGINS: Allowed CORS origins (comma-separated or “*”)

3. Run the Application

uv run uvicorn app.main:app --host 0.0.0.0 --port 8000

Visit http://localhost:8000/dashboard to access the web management interface.

🐳 Docker Deployment

Using Docker Compose (Recommended)

1. Create and configure your .env file:

cp .env.example .env
touch deepgemini.db
echo "" > deepgemini.db

2. Build and start the container:

docker-compose up -d

3. Access the web interface at http://localhost:8000/dashboard

Using Docker Directly

1. Pull the image:

docker pull bradleylzh/deepgemini:latest

2. Create necessary files:

For Linux/Mac:

# Create .env file
cp .env.example .env
touch deepgemini.db

For Windows PowerShell:

# Create .env file
cp .env.example .env
echo "" > deepgemini.db

3. Run the container:

For Linux/Mac:

docker run -d \
-p 8000:8000 \
-v $(pwd)/.env:/app/.env \
-v $(pwd)/deepgemini.db:/app/deepgemini.db \
--name deepgemini \
bradleylzh/deepgemini:latest

For Windows PowerShell:

docker run -d -p 8000:8000 `
-v ${PWD}\.env:/app/.env `
-v ${PWD}\deepgemini.db:/app/deepgemini.db `
--name deepgemini `
bradleylzh/deepgemini:latest

🔧 Model Configuration

DeepGemini supports various AI providers:

• DeepSeek: Advanced reasoning capabilities
• Claude: Refined text generation and thinking
• Gemini: Google’s AI model
• Grok3: Grok’s AI model
• Custom: Add your own provider integration

Each model can be configured with:

• API credentials
• Model parameters (temperature, top_p, tool, etc.)
• System prompts
• Usage type (reasoning/execution/both)

🔄 Relay Chain Configuration

Create custom Relay Chain by combining models:

1. Reasoning Step: Initial analysis and planning
2. Execution Step: Final response generation
3. Custom Steps: Add multiple steps as needed

👥 Multi-Role Discussion

Role Management: Create AI roles with different personalities and skills

• Discussion Groups: Combine multiple roles to form discussion groups
• Multiple Discussion Modes:
  • General Discussion
  • Brainstorming
  • Debate
  • Role-playing
  • SWOT Analysis
  • Six Thinking Hats

🛠 Tech Stack

• FastAPI: Modern web framework
• SQLAlchemy: Database ORM
• Alembic: Database migrations
• UV: Fast Python package installer
• aiohttp: Async HTTP client
• deepclaude

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📬 Contact

For questions and support, please open an issue on GitHub.