Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Retrieval-augmented generation, document Q&A, knowledge graphs and memory systems.
Signals: rag, retrieval-augmented-generation, llamaindex, knowledge-graph, question-answering, chat-with-documents, graphrag, memory
503 results
ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations [COLM 2025]
We introduce temporal working memory (TWM), which aims to enhance the temporal modeling capabilities of Multimodal foundation models (MFMs). This plug-and-play module can be easily integrated into existing MFMs. With our TWM, nine state-of-the-art models exhibit significant performance improvements across QA, captioning, and retrieval tasks.
One-stop data intelligence agent, providing insights from all mainstream data formats in a single dialogue box, including documents, databases, business systems, and images.一站式数据智能体，一个对话框提供所有主流格式数据的见解，包括文档、数据库、业务系统和图像。
Agent-native knowledge engine with MCP tools for document indexing, wiki organization, fast retrieval and deep reading across PDF/DOCX/PPTX/Markdown
OpenClaw Supermemory lets to have long-term memory and recall for your openclaw agent.
[ACL 2024] Official resources of "ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models".
Tuning and Evaluation of RAG pipeline. (Automated optimization to be added soon)
A RAG pipeline implementation built on the 'Epstein Files 20K' dataset from Hugging Face (Teyler).
A step by step implementation of a complex RAG pipeline to solve real world situations
git-like rag pipeline
A real production-worthy RAG Pipeline.
LightningRAG is a full-stack Vue + Gin starter with a decoupled frontend and backend, plus built-in, extensible RAG (retrieval-augmented generation): knowledge bases, vector search, and integrations with many LLM and vector-store providers
"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation" by Yifan Feng, Hao Hu, Shihui Ying, Xingliang Hou, Shiquan Liu, Mingyuan Yang, Junchang Li, Shaoyi Du, Nanning Zheng, Han Hu, and Yue Gao.
Official code for TOIS2026 "Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models"
A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.
✨✨[NeurIPS 2025] This is the official implementation of our paper "Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension"
This is an implementation of the paper: Searching for Best Practices in Retrieval-Augmented Generation (EMNLP2024)
This repository contains advanced LLM-based chatbots for Q&A using LLM agents, and Retrieval Augmented Generation (RAG) and with different databases. (VectorDB, GraphDB, SQLite, CSV, XLSX, etc.)
This repository is the source code for examples and illustrations discussed in the book - A Simple Introduction to Retrieval Augmented Generation
🚀 Retrieval Augmented Generation (RAG) with txtai. Combine search and LLMs to find insights with your own data.
A 3D interface for visualizing RAG (Retrieval-Augmented Generation) memory structures in real-time.
[EMNLP 2024: Demo Oral] RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
Repo for Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
Completed research on semantic retrieval augmented generation through novel semantic similarity graph traversal algorithms.
24,523 repositories in the index in total.
