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rag-llm

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x0-GPT is an advanced AI-powered tool that enables you to interact seamlessly with any website or document (including PDFs) using natural language. Whether you're looking to extract specific data, automate tasks, or gain insights, x0-GPT makes it possible with ease. Best of all, it's free and accessible to everyone.

  • Updated Jan 4, 2025
  • TypeScript

Paste any public website URL, ingest its content into Upstash Vector & Jina, and chat with grounded answers via a multi-provider LLM fallback chain (Gemini, Groq, OpenRouter free models, Hugging Face). Built with Next.js 16, React 19, & TypeScript, with live token streaming & Jina (SPA JS-heavy page ingestion), Redis-backed session history

  • Updated Aug 30, 2026
  • TypeScript

This project implements a Retrieval-Augmented Generation (RAG) based chatbot designed to handle university-related queries using natural language understanding. It combines semantic search with generative AI to provide precise, context-aware answers to students, faculty, and visitors.

  • Updated Feb 26, 2026
  • Jupyter Notebook

An intelligent GraphRAG system that transforms any database into a knowledge graph using Neo4j, combines pgvector semantic search with graph reasoning, and enables natural language question answering over structured data.

  • Updated Aug 8, 2026
  • Python

This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.

  • Updated Feb 4, 2025
  • Python

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