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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Updated
Nov 29, 2025 - JavaScript
Demystify RAG by building it from scratch. Local LLMs, no black boxes - real understanding of embeddings, vector search, retrieval, and context-augmented generation.
AI-powered document analysis platform built with Next.js, LangChain, PostgreSQL + pgvector. Upload, organize, and chat with documents. Includes predictive missing-document detection, role-based workflows, and page-level insight extraction.
Open-source, self-hosted alternative to NotebookLM. Chat with your documents, generate audio summaries, and ground AI in your own sources—built with Supabase and N8N on a React frontend.
One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.
A minimal Agentic RAG built with LangGraph — learn Retrieval-Augmented Agents in minutes.
Prototype SDK for RAG development.
pdfLLM is a completely open source, proof of concept RAG app.
Open-source, fully private and local alternative to NotebookLM. Chat with your documents, generate audio summaries, and ground AI in your own sources—built with Supabase, N8N on a React frontend using Ollama for local inference
AnythingLLM Embed widget submodule for the main AnythingLLM application
Agentic RAG for any scenario. Customize sources, depth, and width
A RAG agent using Google's ADK & Vertex AI that lets set up semantic search across documents in under 2 minutes. Features GCS integration and natural language querying
Open-source toolkit to extract structured knowledge graphs from documents and tables — power analytics, digital twins, and AI-driven assistants.
Template for AI chatbots & document management using Retrieval-Augmented Generation with vector search and FastAPI.
MediNotes: SOAP Note Generation through Ambient Listening, Large Language Model Fine-Tuning, and RAG
Supacrawler's ultralight engine for scraping and crawling the web. Written in go for maximum performance and concurrency.
Build and deploy a full-stack RAG app on AWS with Terraform, using free tier Gemini Pro, real-time web search using Remote MCP server and Streamlit UI with token based authentication.
A complete Retrieval-Augmented Generation (RAG) application that demonstrates modern AI capabilities for answering questions about Ultimate Frisbee rules and strategies. This project showcases how to build a production-ready RAG system using cutting-edge technologies.
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.
Crawl any website with Tavily, embed the content, and deploy the RAG on MongoDB Atlas vector search.
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