Awesome Opensource Ai

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own persistent autonomous agent on top!

The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.

🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines

AdalFlow: The library to build & auto-optimize LLM applications.

A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.

Official repository for the Boltz biomolecular interaction models

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.

Harness LLMs with Multi-Agent Programming

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

OpenAgents - AI Agent Networks for Open Collaboration

A system for agentic LLM-powered data processing and ETL

A retargetable MLIR-based machine learning compiler and runtime toolkit.

VILA is a family of state-of-the-art vision language models (VLMs) for diverse multimodal AI tasks across the edge, data center, and cloud.

A flexible, high-performance 3D simulator for Embodied AI research.

Open-source security automation platform for teams and AI agents

Superfast AI decision making and intelligent processing of multi-modal data.

A library for mechanistic interpretability of GPT-style language models

Quickly and accurately render even the largest data.

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

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

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

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

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.

The Security Toolkit for LLM Interactions

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

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

RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

llama.cpp fork with additional SOTA quants and improved performance

Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali

Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai

PentestAgent is an AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends

SDG is a specialized framework designed to generate high-quality structured tabular data.

Data Contracts engine for the modern data stack. https://www.soda.io

Inspect: A framework for large language model evaluations

Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app