Awesome Opensource Ai

RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

"RAG-Anything: All-in-One RAG Framework"

Unified framework for building enterprise RAG pipelines with small, specialized models

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

Agent S: an open agentic framework that uses computers like a human

Retrieval and Retrieval-augmented LLMs

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

AutoRAG: Now your agent can find anything in your computer. It gets smarter if you are using it frequently.

Harness LLMs with Multi-Agent Programming

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

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

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

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL