Awesome Opensource Ai

Next Generation Agentic Proxy for AI Agents and MCP servers

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.

Machine Learning Pipelines for Kubeflow

Official repository for the Boltz biomolecular interaction models

Harness LLMs with Multi-Agent Programming

OpenAgents - AI Agent Networks for Open Collaboration

Simple RL training for reasoning

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.

The official CLI and Python client for the Hugging Face Hub.

Framework for evaluating and improving agents

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

Open-source security automation platform for teams and AI agents

The best OSS video generation models, created by Genmo

Open-source multimodal retrieval engine (Morphik Core). By Morphik — AI back office for skilled nursing & senior living (morphik.ai).

Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

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

Synthetic data generation for tabular data

Evaluation and Tracking for LLM Experiments and AI Agents

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

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

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

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.

🔅 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.

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.

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.

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

A framework for prompt tuning using Intent-based Prompt Calibration

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

PyTorch native quantization for training and inference

Data manipulation and transformation for audio signal processing, powered by PyTorch

The pretty much "official" DSPy framework for Typescript

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

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Minimalistic large language model 3D-parallelism training

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

Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs.

An Open Standard for lineage metadata collection

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.

Inspect: A framework for large language model evaluations

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

Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.

Machine learning metrics for distributed, scalable PyTorch applications.

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