A comprehensive Python-based platform for demonstrating various AI model capabilities across different providers.
- Multi-provider LLM integrations (OpenAI, Anthropic, Cohere, Mistral, etc.)
- Text generation, embeddings, and completions
- Image generation with Stable Diffusion and DALL-E
- Fine-tuning examples for various models
- API server for model serving
- Benchmarking tools for model performance comparison
- Python 3.9+
- pip
# Clone the repository
git clone https://github.com/your-username/aidemo.git
cd aidemo
# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate # On Windows, use: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
Create a .env
file in the project root with your API keys:
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
COHERE_API_KEY=your_cohere_api_key
HUGGINGFACE_API_KEY=your_huggingface_api_key
python -m aidemo.src.api.server
The API will be available at http://localhost:8000
.
aidemo/
├── src/
│ ├── models/ # AI model implementations
│ ├── api/ # FastAPI server
│ ├── utils/ # Helper utilities
│ ├── data/ # Data handling
│ └── config/ # Configuration management
├── tests/ # Unit and integration tests
├── examples/ # Example scripts showing usage
└── docs/ # Documentation
See the examples/
directory for detailed usage examples of each model provider.
MIT