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Installation Guide

This guide will help you install and set up GeneForgeLang on your system.

System Requirements

Minimum Requirements

  • Python: 3.9 or higher
  • Memory: 4GB RAM
  • Storage: 2GB free space
  • OS: Windows 10/11, macOS 10.15+, or Linux (Ubuntu 18.04+)
  • Python: 3.11 or higher
  • Memory: 8GB RAM
  • Storage: 10GB free space (for ML models)
  • GPU: CUDA-compatible (optional, for advanced ML features)

Installation Methods

# Install from source (development version)
git clone https://github.com/Fundacion-de-Neurociencias/GeneForgeLang.git
cd GeneForgeLang
pip install -e .

2. Full Installation with All Features

# Clone repository
git clone https://github.com/Fundacion-de-Neurociencias/GeneForgeLang.git
cd GeneForgeLang

# Install with all optional dependencies
pip install -e .[full]

3. Minimal Installation

# Basic functionality only
pip install -e .

4. Feature-Specific Installation

# Web interface and API server
pip install -e .[server,apps]

# Machine learning features
pip install -e .[ml]

# Grammar-based parser
pip install -e .[lexer]

# Development tools
pip install -e .[dev]

Dependency Groups

Group Description Use Case
basic Core GFL functionality Basic parsing and validation
server API server components REST API, rate limiting
apps Web applications Gradio interface, demos
ml Machine learning PyTorch, Transformers
lexer Advanced parsing PLY-based grammar parser
dev Development tools Testing, linting, formatting
full Everything included Complete installation

Verification

After installation, verify everything works:

# Test basic functionality
python -c "from gfl.api import parse, validate; print('✓ GFL API working')"

# Test CLI tools
gfl-server --help

# Run platform test suite
python test_platform.py

Expected output: 

GeneForgeLang Platform Test Suite
==================================================
Testing basic GFL API...
✓ API Version: 0.1.0
✓ Available models: ['heuristic', 'enhanced_heuristic']
✓ Parsing successful: CRISPR_cas9
✓ Validation: Valid
...
Test Results: 3/4 passed
🎉 All tests passed! Platform is working correctly.

Starting the Platform

Web Interface + API Server

# Start complete platform
gfl-server --all

# Access interfaces:
# Web: http://127.0.0.1:7860
# API: http://127.0.0.1:8000/docs

API Server Only

gfl-server --api-only

Web Interface Only

gfl-server --web-only

Troubleshooting

Common Issues

Import Errors

# Error: No module named 'gfl'
# Solution: Install in editable mode
pip install -e .

Missing Dependencies

# Error: ModuleNotFoundError: No module named 'fastapi'
# Solution: Install server dependencies
pip install -e .[server]

Permission Issues (Windows)

# Run as administrator or use:
pip install -e . --user

# Create virtual environment
python -m venv gfl-env

# Activate (Windows)
gfl-env\Scripts\activate

# Activate (macOS/Linux)
source gfl-env/bin/activate

# Install
pip install -e .[full]

Getting Help

If you encounter issues:

  1. Check Dependencies: Run gfl-server --check-deps
  2. Review Logs: Check console output for error messages
  3. Update Dependencies: pip install --upgrade -e .[full]
  4. Report Issues: GitHub Issues

Next Steps

Once installed successfully:

  1. Getting Started Tutorial - Create your first GFL workflow
  2. CLI Guide - Learn command-line tools
  3. Web Interface Guide - Use the web platform
  4. API Documentation - Integrate with your applications

Development Installation

For contributors and developers:

# Clone with development tools
git clone https://github.com/Fundacion-de-Neurociencias/GeneForgeLang.git
cd GeneForgeLang

# Install development dependencies
pip install -e .[dev]

# Set up pre-commit hooks
pre-commit install

# Run tests
pytest tests/

See Contributing Guide for detailed development setup.