🤖 RAG Application

< The only FREE TO USE RAG Application > This is a RAG application made on the following technologies

• Gemini API
• Docker
• Python
• Streamlit
• Langchain
• A PDF :>

🪜Usage

Any amount of PDF can be stored inside a list and then their vector data will automatically be feeded to the Google Gemini Free Version using the 'embed-model-001' by Google.

💪Requirement

• Google API Key need to be provided n the .env or You can directly upload in the Streamlit
• Also add "main.pdf" in the root directory, or you can change the name as well of this file.

📂Project Structure

• app.py: Main application script.
• .env: file which will contain your environment variable.
• requirements.txt: Python packages required for working of the app.
• README.md: Project documentation.

🐍Python Dependencies

• Streamlit
• google.generativeai
• dotenv
• langchain
• PyPDF2

🤖Running Guide

• Either Upload on Streamlit to run it
• or in the root directory open CMD and type "streamlit app.py"

📒Developer Notes

• This is right now hosted on Streamlit, but soon a Flask variant will be launched as well.
• Vercel / Netlify cannot support right now because of Langchain-Community module
• For any personal queries you can contact at mostuselessboy@gmail.com or https://www.linkedin.com/in/devhamzarizvi/