Popular GitHub Repositories for Hackable

A full-featured, hackable Next.js AI chatbot built by Vercel

Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackable.

kani (カニ) is a highly hackable microframework for chat-based language models with tool use/function calling. (NLP-OSS @ EMNLP 2023)

A transparent, minimal, and hackable agent framework. ~300 lines of readable code. Full control, no magic.

Your Self-Hosted, Hackable Research Agent Inspired by AutoGPT

A simple, hackable text-to-speech system in PyTorch and MLX

Cold Compress is a hackable, lightweight, and open-source toolkit for creating and benchmarking cache compression methods built on top of GPT-Fast, a simple, PyTorch-native generation codebase.

Delightful AI coding mentor | Open-source, local, hackable | ? Star if it sparks delight!

? Hackable UI Generator with LLMs. Build quick MVP UIs with HTML, Tailwind, Font Awesome, Placehold.co and Groq for superfast generation?

A Hackable speech recognition library.

Build your own JARVIS: An AI voice interface that enables you to talk with an AI model, creating a conversational experience. It offers a modern alternative to traditional virtual assistants. Highly customizable, leveraging Picovoice; powerful, backed by Nano Bots compatible with OpenAI ChatGPT and Google Gemini; and hackable, supporting Nano Apps.

A hackable library for running and fine-tuning modern transformer models on commodity and alternative GPUs, powered by tinygrad.

Chatnificent: LLM chat app framework – Minimally complete. Maximally hackable.

Zeno is a lightweight, plugin-first Markdown blog framework built with JavaScript. It's designed to be simple, hackable, and extendable.

?⚡ Lightweight, hackable multi-agent orchestration lab. YAML configs, CLI + Python API, 10 presets, transcripts, checkpoints. Perfect for LLM experiments!

A minimal, hackable Vision-Language Model built on Karpathy’s nanochat — add image understanding and multimodal chat for under $200 in compute.

Hackable, simple, llm evals on preference datasets