🎥 Pragya - YouTube AI Assistant

A full-stack AI-powered application that summarizes and answers questions in many different languages from YouTube videos using Azure OpenAI, Whisper, and LangChain.

---

🚀 Getting Started

🔧 Backend Setup

1. Set environment variables
   Create a .env file or export manually with the following keys and get the Api keys from azure Openai:

   AZURE_OPENAI_API_KEY=
   AZURE_OPENAI_ENDPOINT=
   AZURE_DEPLOYMENT_NAME=
   AZURE_WHISPER_API_KEY=
   AZURE_WHISPER_ENDPOINT=
   AZURE_EMBEDDING_DEPLOYMENT_NAME=
   AZURE_EMBEDDING_DEPLOYMENT_VERSION=
   AZURE_INFERENCE_ENDPOINT=
   AZURE_EMBEDDING_API_KEY=
   AZURE_WHISPER_VERSION=
   AZURE_TTS_API_KEY=
   AZURE_TTS_ENDPOINT=

2. Run the backend locally

   python -m venv venv
   Set-ExecutionPolicy -Scope CurrentUser -ExecutionPolicy Unrestricted  # (PowerShell only)
   .\venv\Scripts\Activate.ps1                                           # (PowerShell)
   pip install -r requirements.txt
   python main.py

---

🌐 Frontend Setup

npm install
npm run dev

---

Demo

🛠️ Tech Stack

✅ Backend

• Flask + LangChain + Azure OpenAI + Whisper
  • Accepts YouTube links and user queries
  • Retrieves transcripts via YouTube Transcript API or Whisper
  • Uses GPT-4o-mini for summarization and question answering

✅ Vector Store

• FAISS + LangChain
  • Splits transcripts into chunks and embeds them
  • Stores embeddings for semantic search
  • Retrieves relevant chunks for QA

✅ Chat Memory

• LangChain Memory Modules
  • Maintains dialogue history
  • Supports contextual follow-up questions and coreference resolution

✅ Frontend

• React
  • UI for submitting YouTube links
  • Choose between Summary or QnA modes
  • Select language for response
  • Optionally listen to responses via Azure TTS

---

📦 Features

• Summarize or query any YouTube video
• Auto transcript via Whisper fallback
• Semantic retrieval with FAISS
• Memory-enabled multi-turn conversations
• Audio output with Azure TTS

---