| 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](#overview) | |
| - [Installation](#installation) | |
| - [Usage](#usage) | |
| - [RAG PDF Search](#rag-pdf-search) | |
| - [Gradio App for Keyword Extraction](#gradio-app-for-keyword-extraction) | |
| - [License](#license) | |
| ## 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: | |
| ```bash | |
| pip install transformers byaldi qwen-vl-utils gradio pillow torch | |