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infiniflow/ragflow

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

Go89K10K

#ai#ai-agents#context-engine#llm-apps#rag

HKUDS/LightRAG

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

Python39K5.5K

#knowledge-graph#large-language-models#retrieval-augmented-generation#genai#graphrag

VectifyAI/PageIndex

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

Python35K3.1K

#agentic-ai#agents#ai#ai-agents#context-engineering

NirDiamant/RAG_Techniques

Sponsor Star NirDiamant / RAG_Techniques This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

Jupyter Notebook29K3.6K

#rag#tutorials#langchain#llama-index#llms

HKUDS/RAG-Anything

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

Python23K2.7K

#multi-modal-rag#retrieval-augmented-generation

memvid/memvid

Star memvid / memvid Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

Rust16K1.4K

#ai#context#embedded#faiss#knowledge-base

LearningCircuit/local-deep-research

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

Python9K792

#academia#arxiv#brave#deep-research#local