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Contributing to effGen

Thank you for your interest in contributing to effGen! This guide will help you get started.

Development Setup

Prerequisites

  • Python 3.9+
  • CUDA-compatible GPU (for integration tests)
  • Git

Installation

# Clone the repository
git clone https://github.com/ctrl-gaurav/effGen.git
cd effGen

# Create a virtual environment
conda create -n effgen python=3.11 -y
conda activate effgen

# Install in development mode
pip install -e ".[dev]"

# Install pre-commit hooks
pip install pre-commit
pre-commit install

Running Tests

# Unit tests (no GPU required)
pytest tests/unit/ -v --no-cov

# Integration tests (requires GPU)
CUDA_VISIBLE_DEVICES=0 pytest tests/integration/ -v -m gpu --no-cov

# Performance benchmarks
pytest tests/benchmarks/ -v --no-cov

# All tests with coverage
pytest tests/ -v

Code Style

We use the following tools to maintain code quality:

  • Black for code formatting (line length: 100)
  • isort for import sorting (profile: black)
  • flake8 for linting
  • mypy for type checking
  • bandit for security linting

All these run automatically via pre-commit hooks. You can also run them manually:

black effgen/
isort effgen/
flake8 effgen/
mypy effgen/ --ignore-missing-imports

Pull Request Process

  1. Fork the repository and create a feature branch from main
  2. Write tests for your changes (unit tests at minimum, integration tests if GPU-dependent)
  3. Update CHANGELOG.md with a summary of your changes
  4. Ensure all tests pass: pytest tests/unit/ -v --no-cov
  5. Submit your PR with a clear description of the changes

PR Checklist

  • Tests added/updated
  • CHANGELOG.md updated
  • Code passes black --check and isort --check
  • No new TODO/FIXME without a tracking issue
  • Documentation updated if public API changed

Issue Reporting

When reporting bugs, please include:

  • Python version (python --version)
  • effGen version (python -c "import effgen; print(effgen.__version__)")
  • GPU info (if relevant): nvidia-smi
  • Full error traceback
  • Steps to reproduce

Architecture Overview

effgen/
├── core/           # Agent, AgentConfig, ReAct loop
├── models/         # Model backends (vLLM, Transformers, API adapters)
├── tools/          # Built-in tools and protocols (MCP, A2A, ACP)
├── memory/         # Short-term, long-term, vector memory
├── prompts/        # Template management and optimization
├── config/         # Configuration loading and validation
├── execution/      # Code execution sandboxing
├── gpu/            # GPU allocation and monitoring
└── utils/          # Logging, metrics, validators, health checks

Key Design Principles

  • Open Source First: All features must work without paid APIs
  • SLM-Optimized: Prompts and tools designed for 1B-7B parameter models
  • Tools extend BaseTool with async _execute() method
  • Agent uses ReAct loop: Thought → Action → Observation → repeat

License

By contributing, you agree that your contributions will be licensed under the Apache License 2.0.