Tags: knowledge retrieval with RAG framework

Comprehensive Introduction NodeRAG is an open source Retrieval Augmented Generation (RAG) system hosted on GitHub and developed by Terry-Xu-666. It optimizes information retrieval and generation through heterogeneous graph structures, significantly improving retrieval accuracy and contextual relevance.NodeRAG supports local deployment and provides user-friendly...

Comprehensive Introduction Yuxi-Know is an open source intelligent Q&A platform that combines knowledge graph and RAG (Retrieval Augmented Generation) technology to help users quickly get accurate answers. It is based on Neo4j to store the knowledge graph , using FastAPI and VueJS to build the back-end and front-end , supports a variety of large models such as Op...

Comprehensive Introduction Recall is an artificial intelligence tool that enhances your browsing experience by quickly summarizing and depositing web pages, videos, PDFs and more into your personal knowledge base. The core function is to help you display relevant information in real time while browsing, and organize fragmented content into an organized knowledge network. It was developed by Paul and Mission...

General Introduction Morphik Core is an open source project developed by the morphik-org team and hosted on GitHub. It used to be called DataBridge Core, but is now renamed Morphik Core.This tool is a database designed for AI applications that can handle text, images, PDFs, videos, and other various...

KBLaM is an open source project developed by Microsoft, the full name is "Knowledge Base augmented Language Model" (Knowledge Base Augmented Language Model). It transforms external knowledge into vectors and embedded in a large model of the attention layer , so that the model can directly use this knowledge to answer questions or ...

General Introduction Rankify is an open source Python toolkit developed by the Data Science Group at the University of Innsbruck, Austria. It focuses on information retrieval, reordering and retrieval augmentation generation (RAG), providing a unified framework. The toolkit comes with 40 built-in pre-retrieved benchmark datasets and supports 7 retrieval techniques...

General Introduction Fast.io is an AI workbench for teams focused on turning large-scale data into practical insights. It quickly analyzes thousands of files, including documents, images, and videos, generating summaries and answering questions. The website was built by the founders of MediaFire with the goal of helping SMBs...

General Introduction Oliva is an open source multi-intelligence assistant tool developed by Deluxer on GitHub. It helps users search for product information in the Qdrant database through the collaboration of multiple AI intelligences. The main features are voice support, combined with LangChain and Superlinked technology...

Second Me is an open source project developed by the Mindverse team that lets you create an AI on your computer that acts like a "digital doppelganger", learning your speech and habits through your words and memories, and turning it into a smart assistant that understands you. Its best feature is that all the numbers...

The GraphRAG project aims to extend the range of questions that AI systems can answer on private datasets by exploiting implicit relationships in unstructured text. A key advantage of GraphRAG over traditional vector RAG (or "semantic search") is its ability to answer global queries over entire datasets, such as...

General Introduction HippoRAG is an open source framework developed by the OSU-NLP group at The Ohio State University, inspired by human long term memory mechanisms. It combines Retrieval Augmented Generation (RAG), Knowledge Graph, and Personalized PageRank techniques to help Large Language Models (LLMs) continuously integrate knowledge from external documents...

Comprehensive Introduction RLAMA is a document intelligent Q&A RAG (Retrieval Augmentation Generation) system developed open-source by DonTizi and hosted on GitHub, with the core feature of functionality through command line operations. Users can connect to the local Ollama model through concise terminal commands, and connect the folder of...

Comprehensive Introduction LettuceDetect is a lightweight open source tool developed by KRLabsOrg that specializes in detecting hallucinatory content generated in Retrieval Augmented Generation (RAG) systems. It helps developers enhance RAG by comparing context, questions, and answers, and identifying parts of the answer that are not supported by the context ...

General Introduction Onyx (formerly known as Danswer) is an open source AI chat platform developed by the onyx-dot-app team to help organizations integrate and manage documents, applications and employee data. It provides rich chat functionality with support for connecting to any Large Language Model (LLM) and through more than 40 connectors (e.g. Go...

General Introduction ReSearch is an open-source research tool developed by the Agent-RL team to improve the search and inference capabilities of Large Language Models (LLMs) through Reinforcement Learning (RL). The project is inspired by Deepseek-R1-Zero and OpenAI's Deep ...

Comprehensive Introduction Flying Book Knowledge Q&A is an AI-driven knowledge management and Q&A tool launched by Flying Book, which deeply integrates DeepSeek R1 big model technology. It supports real-time networking search, multi-format file parsing (including documents, images, etc.), and can seamlessly interface with the enterprise knowledge base to help users quickly build a smart...

Comprehensive Introduction Large Model Knowledge Engine (LKE for short) is a smart application building platform for enterprise users launched by Tencent Cloud. It combines powerful big language modeling technology with enterprise proprietary data to help users quickly build knowledge quizzes, RAG (Retrieval Augmented Generation) applications, Agent intelligences and work...

General Introduction DeepSeek-RAG-Chatbot is an open source chatbot project built on the DeepSeek R1 model, hosted on GitHub and created by developer SaiAkhil066. It combines Retrieval Augmented Generation (RAG) technology with support for users to upload documents (e.g. PDF, DOCX or TXT ...

Comprehensive Introduction dsRAG is a high-performance retrieval engine designed to handle complex queries on unstructured data. It performs particularly well in handling challenging queries in dense text such as financial reports, legal documents, and academic papers. dsRAG employs three key approaches to improve performance: semantic segmentation,...