title: ColPali
app_file: app.py
sdk: gradio
sdk_version: 4.41.0
RAG-based PDF Search and Keyword Extraction using Qwen2VL
This repository contains an implementation of a RAG (Retrieval-Augmented Generation) based PDF search system using Copali's implementation of the Byaldi library and Qwen2VL for creating the RAG pipeline. Additionally, the repository includes a Gradio app that allows users to extract text from images and highlight searched keywords using Qwen2VL.
Table of Contents
Overview
RAG PDF Search
In copali-qwen.ipynb, you will find the complete implementation of the RAG-based PDF search. The pipeline is built using the Copali implementation of the Byaldi library, along with Qwen2VL. By default, the code indexes and searches through an image (image.png), but you can easily modify the path to a PDF file or any other desired document.
Gradio App for Keyword Extraction
The app.py file contains a Gradio app that utilizes only Qwen2VL to extract text from an image and highlight the keywords matching the user's search query. This app is an easy-to-use interface for real-time keyword extraction from images.
Installation
To run this project, you will need to install the following dependencies:
pip install transformers byaldi qwen-vl-utils gradio pillow torch