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Contributing to KVTC

Thanks for your interest in contributing! Here's how to get started.

Setup

git clone https://github.com/OnlyTerp/kvtc.git
cd kvtc
pip install -e ".[dev]"
pytest src/test_kvtc.py  # all 38 tests should pass

What We Need Help With

  • GPU-accelerated entropy coding — Replace zlib with nvCOMP or custom CUDA kernels
  • Triton kernels — Fused PCA transform + quantize kernel for inference speed
  • More model benchmarks — Test on Llama-3, Qwen, Gemma, etc.
  • vLLM integration — KV cache manager plugin for production serving
  • Pipelined decompression — Layer-by-layer decompress overlapped with attention

Pull Request Process

  1. Fork the repo and create a feature branch
  2. Make sure all existing tests pass: pytest src/test_kvtc.py
  3. Add tests for any new functionality
  4. Update docs if you change the public API
  5. Open a PR with a clear description

Code Style

  • Type annotations on all public functions
  • Docstrings on all public APIs
  • Pure PyTorch — avoid unnecessary dependencies
  • Tests go in src/test_kvtc.py

Reporting Issues

Open a GitHub issue with:

  • What you expected vs what happened
  • Minimal reproduction code
  • Your environment (Python version, PyTorch version, OS)