📺 YouTube Summarizer & QnA using GenAI (RAG Pipeline)

A powerful GenAI application that summarizes YouTube videos and answers questions based on video content using LLMs, embeddings, and semantic search. Built using LangChain, Gemini Pro, ChromaDB, and deployed with Flask.

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🚀 Features

• 🔍 YouTube Transcript Extraction – Automatically pulls transcripts from any YouTube video.
• 🧠 RAG Pipeline (Retrieval-Augmented Generation) – Uses vector search + LLMs to provide accurate, context-aware answers.
• 🧾 Summarization + Q&A – Ask any question about the video or request a summary.
• 💾 Persistent Memory – Stores vectorized chunks in ChromaDB using unique hashes.
• 🌐 Flask REST API – Backend ready for integration into web apps or platforms.

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🧠 How It Works

1. Load Transcript from a YouTube video using YoutubeLoader.
2. Split Transcript into chunks using RecursiveCharacterTextSplitter.
3. Generate Embeddings using GoogleGenerativeAIEmbeddings.
4. Store & Search chunks using Chroma vector database.
5. Query through a RetrievalQA or RetrievalChain powered by Gemini Pro and LangChain.
6. Respond in a friendly tone customized for young learners using prompt templates.

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🧪 Example Usage

python app.py