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Installation Guide

This guide provides detailed instructions for installing Amega AI and its dependencies.

System Requirements

  • Operating System: Linux, macOS, or Windows
  • Python Version: 3.8 or higher
  • RAM: Minimum 8GB (16GB recommended)
  • Storage: At least 2GB free space
  • GPU: Optional but recommended for training large models

Installation Methods

pip install amega-ai

2. From Source

  1. Clone the Repository 

    git clone https://github.com/yourusername/amega-ai.git
cd amega-ai

  2. Create Virtual Environment 

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

  3. Install Dependencies 

    pip install -r requirements.txt

  4. Install in Development Mode 

    pip install -e .

GPU Support

For GPU support, install the CUDA version compatible with your GPU:

pip install amega-ai[gpu]

This will install additional dependencies including: - CUDA Toolkit - cuDNN - GPU-enabled TensorFlow and PyTorch

Verification

Verify the installation:

import amega_ai

# Check version
print(amega_ai.__version__)

# Verify GPU support
print(amega_ai.gpu_available())

Common Issues

1. CUDA Installation Problems

If you encounter CUDA-related issues: 1. Verify CUDA toolkit installation 2. Check GPU compatibility 3. Update graphics drivers

2. Dependencies Conflicts

If you encounter dependency conflicts: 1. Create a fresh virtual environment 2. Install dependencies one by one 3. Check for version compatibility

Next Steps

  1. Follow our Getting Started Guide
  2. Configure your Environment
  3. Run the Example Projects