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πŸš€ Unlock the power of learning with this app! πŸ’‘ Explore video courses, chat with virtual assistants πŸ’¬, and access FAQs – all in one seamless edtech experience. πŸ“š Elevate your knowledge today! πŸŽ“

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padh.ai - now, you can β€œtalk” to videos.

Table of Contents

Introduction

padh.ai is An edtech app with courses, videos, chat, and FAQ.

What padh.ai aims at solving:

  • Limited 1-on-1 interaction in online lectures
  • Students getting distracted while looking up topics they need help with.
  • Making doubt-solving more convenient and fast, feeding curiosity instantly.

Thus, enhancing overall academic performance and confidence of students

Features

  • Browse and watch video courses
  • Ask questions related to the video content or slides content using a chat interface
  • View relevant materials like articles for each video

Screenshots

Screenshot 1
SignUp Screen
Screenshot 2
Login Screen
Screenshot 3
Dashboard 1
Screenshot 4
Dashboard 2
Screenshot 5
Topic Review
Screenshot 6
AV Summary Video Player
Screenshot 7
What is SOAP? 1
Screenshot 8
What is SOAP? 2
Screenshot 9
Context Aware LLM Answer
Screenshot 10
Context
Screenshot 11
Who is the Curator of Slides ?
Screenshot 12
Server Side Logs
Screenshot 13
More RAG Testing 1
Screenshot 14
More RAG Testing 2

How It Works!

padh.AI is built using Flutter for the frontend, FastAPI for the backend, OpenAI's CPT-3.5 turbo for querying, FAISS (Facebook AI Similarity Search) library in python for RAG (Retrieval Augmented Generation) and Firebase for authentication. Here's how it works:

  1. User Authentication:

    • Users can sign up or log in using their email and password via Firebase authentication, or can utilize Google OAuth to login/sign in.
  2. Courses Dashboard

    • Upon logging in, users are presented with a scrollable carousel of different courses and different Units under each course: A prospective redesign of the courses dashboard of the PESU App.
    • The User can select the topic that he wants to study. Each topic has a summary video along with relevant course content/slides.
  3. Context-Aware Chatbot

    • The chatbot utilizes video and slide transcriptions stored in a vector database, providing accurate and context-specific answers to student queries.
    • A separate backend service converts each topic's summary video (audio to text using deepgram), and slides into vector embeddings. It stores them in a .faiss file so the chatbot is context-aware of that specific topic.
  4. Advanced Query Processing

    • Using OpenAI’s GPT-3.5 turbo, student questions are matched with relevant content through FAISS, minimizing errors and enhancing the learning experience.

Tech-Used

  • Frontend: Flutter - An open source cross-platform UI framework, using which the beautiful screens of bh.AI were built
  • Backend: FastAPI - Backend for the app, uses Python, performs RAG embeddings on content as well as queries the LLM using system and user prompts
  • langchain: Framework to integrate LLMs customized for different use Cases
  • FAISS(Facebook AI Similarity Search): A library for efficient similarity search and clustering of dense vectors.
  • OpenAI Embeddings: Used to created an information-dense representation of the semantic meaning of a piece of text.
  • deepgram: Audio to Text ML model
  • AI Querying: GPT 3.5 - The most popular LLM today.
  • Authentication: Firebase - Backend as a Service software used to manage user authentication.
  • Ngrok: Helps developers expose their local development server to the internet.

About

πŸš€ Unlock the power of learning with this app! πŸ’‘ Explore video courses, chat with virtual assistants πŸ’¬, and access FAQs – all in one seamless edtech experience. πŸ“š Elevate your knowledge today! πŸŽ“

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