Awesome Opensource Ai

OpenAgents - AI Agent Networks for Open Collaboration

A library for mechanistic interpretability of GPT-style language models

Synthetic data generation for tabular data

Evaluation and Tracking for LLM Experiments and AI Agents

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

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

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

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.

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

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

Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models

XAI - An eXplainability toolbox for machine learning

Weave is a toolkit for developing AI-powered applications, built by Weights & Biases.