Salman Hameed

Data Science | Machine Learning | Deep Learning | Generative AI

Generative AI

Books To Life: Intelligent RAG System

From the early days of building Retrieval-Augmented Generation (RAG) applications, I’ve explored various vector databases such as Chroma, Faiss, and Pinecone, I also build with MySQL as well. However, I wasn’t fully satisfied with the scalability for production environments. This challenge inspired me to create a hybrid approach, resulting in the development of PDFGenie.

Here’s what it offers:

  • Easily upload and manage multiple PDFs.
  • Engage in meaningful conversations with any of your uploaded PDFs.
  • Switch between books effortlessly, with the app remembering your last interaction with each document.
  • If you don’t understand an answer, simply ask for clarification, or request a summary of your conversation so far.
  • Get informed if a query is unrelated to the content.
  • Clear your conversation history with any book and start a new whenever you want.
  • Read the book directly in the app or generate concise summaries of books with a single click.
  • PDFGenie keeps track of your questions, avoiding duplicated queries to improve efficiency over time.

Potential Benefits:

PDFGenie is perfect for students, researchers, or anyone who works extensively with PDF documents. It saves time, enhances productivity, and provides an intuitive way to interact with digital texts.

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Books To Life: Intelligent RAG System

I created PDFGenie, a scalable and user-friendly app for uploading and engaging with PDFs. It tracks interactions, remembers where you left off, provides contextual answers and summaries, and improves efficiency over time.

Skills Used in Project

Python
Flask
Embeddings
Bootstrap
LLM
LangChain
SQL
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