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AI Demo Platform

A comprehensive Python-based platform for demonstrating various AI model capabilities across different providers.

Features

  • 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

Getting Started

Prerequisites

  • Python 3.9+
  • pip

Installation

# 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

Environment Setup

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

Running the API Server

python -m aidemo.src.api.server

The API will be available at http://localhost:8000.

Project Structure

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

Usage Examples

See the examples/ directory for detailed usage examples of each model provider.

License

MIT

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