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NirDiamant
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Explore the skillNirDiamant
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Swift package for on-device Retrieval-Augmented Generation (RAG)
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Official code of the ACL 2025 paper "SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation"
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A Retrieval-Augmented Generation (RAG) application for querying legal documents. It uses PostgreSQL, Elasticsearch, and LLM to provide summaries and suggestions based on…
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AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
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A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
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RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology.
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A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
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This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle…
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PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
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Demystify RAG by building it from scratch. Local LLMs, no black boxes - real understanding of embeddings, vector search, retrieval, and context-augmented generation.
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This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
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[ICLR 2026] Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning
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Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents.
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🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
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A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data