Large Language Models GitHub Repositories (2026) · Open Source Tools

Build and run agents you can see, understand and trust.

Observal is self-hosted registry for your coding agent extensions with a built in insight engine. Setup Observal, define the scope and share your Skills, MCPs and Agents with your peers.

Ultrafast serverless GPU inference, sandboxes, and background jobs

[NeurIPS 2025 Spotlight] Reasoning Environments for Reinforcement Learning with Verifiable Rewards

🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.

A practical lab for building, testing, and evaluating apps with Apple's Foundation Models framework.

Ingest files for retrieval augmented generation (RAG) with open-source Large Language Models (LLMs), all without 3rd parties or sensitive data leaving your network.

🏗️ Fine-tune, build, and deploy open-source LLMs easily!

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

Setup and run a local LLM and Chatbot using consumer grade hardware.

Open Source AI Tracing Framework built on Opentelemetry for AI Applications and Frameworks

Scalable data pre processing and curation toolkit for LLMs

LLM agents: curated papers on planning, memory, tool use, multi-agent systems, evaluation, and safety.

Laplace's Scissors: protected readout rotations for open LLMs. Diagnose weak output directions, repair answers, preserve successful generations, and analyze scaling deviations with Rust and Triton on CUDA/HIP.