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AI Agent that handles engineering tasks end-to-end: integrates with developers’ tools, plans, executes, and iterates until it achieves a successful result.

Personal AI Notebooks. Organize files & webpages and generate notes from them. Open source, local & open data, open model choice (incl. local).

⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)

Synthetic data generation for tabular data

DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.

Evaluation and Tracking for LLM Experiments and AI Agents

Train, inspect, edit, automate, and export 3D Gaussian Splatting scenes from a single native application.

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

MTEB: State-of-the-art evaluation of embeddings across languages and modalities

II-Agent: a new open-source framework to build and deploy intelligent agents

A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.

Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

Build production-ready AI agents in both Python and Typescript.

JAX-based neural network library

🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.

Dead simple FLUX LoRA training UI with LOW VRAM support

Scalable and efficient data transformation framework - backwards compatible with dbt.

The Security Toolkit for LLM Interactions

A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.

Skywork-R1V is an advanced multimodal AI model series developed by Skywork AI, specializing in vision-language reasoning.

OneTrainer is a one-stop solution for all your Diffusion training needs.

Visualize and compare datasets, target values and associations, with one line of code.

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

(Crystal is now Nimbalyst) Run multiple Codex and Claude Code AI sessions in parallel git worktrees. Test, compare approaches & manage AI-assisted development workflows in one desktop app.

Postgres extension for vector search (DiskANN), complements pgvector for performance and scale. Postgres OSS licensed.