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Search PDFs semantically

Project description

semantic-pdf-search

A semantic PDF searching application, written in Python.

By Jordan Zedeck and Jonathan Louis

Overview

This application utilizes a machine learning embedding model to encode both a PDF document and a user's queries. This process enables the application to find near-matches to the query within the document, much like an internet search engine would for web-pages. The page number results are displayed as buttons which can be clicked to open the PDF directly to the page in your default web browser.

Features

  • Semantic Search: Finds near-matches and related concepts, not just exact keywords.
  • Offline Operability: Once semantic-pdf-search is installed and used once, it can be used completely offline.
  • Cross-Platform: Supports Linux, Windows and macOS.

Example

Query:

alt text

Result:

alt text

Installation

Prerequisites

This package requires Tkinter. If you run the command python -m tkinter and a new window does not appear, you will need to install it manually.

  • Windows: Re-run the Python installer and ensure the tcl/tk checkbox is ticked.
  • macOS: Install Tkinter using Homebrew with the following command:
    brew install python-tk
    
  • Linux: Varies depending on package manager:
    • Debian:
      sudo apt install python3-tk
      
    • Fedora:
      sudo dnf install python3-tkinter
      
    • Arch: (note that pip installing packages on Arch requires using a venv):
      sudo pacman -S tk
      

From PyPI

The easiest way to install the package is using pip.

pip install semantic-pdf-search

From Source

To install from the GitHub repository, follow these steps:

cd semantic-pdf-search
python -m build
pip install dist/semantic_pdf_search-0.8.0-py3-none-any.whl

Launching semantic-pdf-search

Once installed, run the application from your command line:

semantic-pdf-search

Basic Usage Guide

  1. Browse for a PDF: Click on "Browse for PDF" to browse for a PDF file.
  2. Select and Open: Navigate to your PDF, select it, and click "Open".
  3. Wait for Embeddings: The application will process the document and create embeddings. This may take a moment, especially for large files.
  4. Enter a Query: Once the document is loaded, type your query into the search bar and press Enter.
  5. View Results: The application will display a list of page numbers that contain near-matches to your query.
  6. Open the Page: Click on any of the result buttons to open the PDF directly to that page in your default web browser.

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