YT AnswerBot

A Retrieval-Augmented Generation (RAG) AI agent that answers questions using YouTube video transcripts.

Overview

• This project is an AI-powered Q&A system that lets users ask questions about YouTube videos. It combines:
  • Real-time video scraping (Bright Data)
  • Vector search (PGVector + OpenAI embeddings)
  • LLM-powered responses (Anthropic Claude 3)
  • Stateful agent workflows (LangChain + LangGraph)

Features

• YouTube Video Ingestion – Automatically fetches and stores transcripts.
• Conversational AI – Claude 3 generates natural, context-aware answers.
• React Frontend – Clean, interactive chat interface.

Tech Stack

• Backend - Node.js, Express.js, PostgreSQL (PGVector)
• AI/ML - LangChain(tools, retrieval), LangGraph (agent), Claude 3, OpenAI embeddings
• Data Pipeline - Bright Data (YouTube scraping)
• Frontend - React (TypeScript), CSS

Setup

• Prerequisites
  • Node.js (v18+)
  • PostgreSQL (with PGVector extension)
• API keys:
  • OpenAI (for embeddings)
  • Anthropic (Claude 3)
  • Bright Data (YouTube scraping)

Installation

• Clone the repo

   git clone https://github.com/yourusername/VidQuery_AI.git
   cd VidQuery_AI
  

• Set up environment variables

     DB_URL=postgresql://user:pass@localhost:5432/VidQuery_AI
     OPENAI_API_KEY=your_key
     ANTHROPIC_API_KEY=your_key
     BRIGHTDATA_API_KEY=your_key
  

• Run the backend

     cd server
     npm install
     npm start  # Starts Express server at http://localhost:3000
  

• Run the frontend

     cd client
     npm install
     npm run dev  # Starts React app at http://localhost:5173