Scholar Paper RAG

Scholar Paper Fetcher is a simple application that retrieves recent research papers from Google Scholar, generates their descriptions using a locally running LLM, and displays them either in the terminal or in a minimalistic GUI interface. The app runs automatically every time you unlock your computer, utilizing Hammerspoon and a Lua script.

Features

• Paper Retrieval: Fetches recent papers from Google Scholar.
• Viewing Modes:
  • Terminal-based version: Displays paper titles and descriptions directly in the terminal.
  • GUI-based version: A user-friendly PyQt6 GUI with buttons to navigate between papers.
• Retrieval-Augmented Generation (RAG): Enhances the descriptions of the papers using a RAG system.
• Automatic Fetching: Automatically retrieves and displays papers upon unlocking the computer via Hammerspoon.

Setup and Installation

1. Prerequisites

• Python 3.x

• Install the required Python packages:

  pip3 install tqdm requests beautifulsoup4 PyQt6 langchain FAISS transformers

2. Getting Google Scholar Cookies

1. Open Google Chrome and navigate to Google Scholar.

2. Right-click anywhere on the page and select "Inspect."

3. Go to the "Application" tab, then find "Cookies" under the "Storage" section.

4. Copy the cookie data and save it in a JSON file (e.g., cookies.json) on your local machine. The file should look like this:

   {
       "GSP": "",
       "NID": "",
       "HSID": "",
       "SSID": "",
       "APISID": "",
       "SAPISID": "",
       "SID": ""
   }

3. Installing Ollama for Running LLMs Locally

1. Download Ollama either using the command line or manually from the website:

   curl -fsSL https://ollama.com/install.sh | sh

2. Pull a Large Language Model (the available models are listed here):

   ollama pull llama3.2

4. Building the Terminal-Based Version

The terminal-based version fetches papers and displays their titles and descriptions directly in the terminal.

1. Use a Python script to handle fetching papers, generating descriptions, and displaying them in the terminal:

   python3 main.py

5. Building the GUI Version

The GUI version uses PyQt6 to provide a more user-friendly interface where users can swipe between paper descriptions.

1. Use a Python script to fetch papers, generate descriptions, and display them in a PyQt6 window with "Next" and "Previous" buttons:

   python3 main_gui.py

6. Automating Paper Fetching with Hammerspoon

You can configure the app to run automatically whenever you unlock your computer using Hammerspoon, a macOS automation tool.

1. Install Hammerspoon from its official website.
2. Create a Lua script to trigger the app whenever the screen is unlocked. An example is provided in ./lua/init.lua.
3. Place the script in the following directory: ~/.hammerspoon/init.lua.
4. Save and reload the Hammerspoon configuration.

---

With this setup, every time you unlock your computer, the script will automatically run and fetch the latest papers from Google Scholar.