AIOSRSE-UPM

Description

This repository contains deliverables related to Artificial Intelligence and Open Science in Research Software Engineering. Currently, it only contains IndividualAssessment, which is a Grobid client that extracts links, generates a word cloud from abstracts, and creates a figure-per-article graph from PDF papers.

Repository Structure

AIOSRSE-UPM/ IndividualAssessment/ # Main project folder data/ # Place your PDF files here main.py # Main execution script ... docs/ requirements.txt # Dependencies file

Requirements

• Python 3.9.13 or higher
• A running Grobid service (default: http://localhost:8070)
• Dependencies listed in docs/requirements.txt

Installation

Clone the repository: bash git clone https://github.com/AlRos14/AIOSRSE-UPM.git cd IndividualAssessment

Local Installation

Follow these instructions if you want to run the project with a Grobid instance on your local machine.

Create and activate a virtual environment (optional but recommended): bash python3 -m venv env source env/bin/activate # On Windows: env\Scripts\activate

Install the required dependencies: bash pip install -r docs/requirements.txt

Verify the installation: bash python main.py --help

Docker Installation

Follow these instructions if you prefer using Docker without worrying about dependencies or Grobid setup.

Build docker containers with Docker-Compose bash docker-compose up --build This will automatically: - Set up a Grobid instance - Install all required dependencies - Configure the project to work with the containerized Grobid

Execution

Local Execution

Requirements

It is mandatory to have a running Grobid instance, as this project is essentially a Grobid client. Additionally, Python dependencies must be installed from the requirements.txt file.

Before running the project

1. Ensure a Grobid instance is running (by default at http://localhost:8070)
2. Place your PDF files in the IndividualAssessment/data folder

Running the Project

To run the project, use the following command: bash python main.py

Docker Execution

Running the Project

If you've already built the containers, simply run: bash docker-compose up

Stopping the Project

The Docker containers will run in the background until you stop them: ```bash

Press CTRL+C in the terminal where docker-compose is running

docker-compose down ```

After running the project

After execution, an output folder will be created inside the IndividualAssessment directory, containing three files: - figures_per_article.png: A graph showing the number of figures per article - keyword_cloud.png: A word cloud generated from the abstracts - links.txt: A list of links extracted from the papers

Running Example(s)

This is a running example using ten AI-related articles:

python main.py       
2025-02-18 14:07:58,742 - INFO - Iniciando el anlisis de artculos...
2025-02-18 14:07:58,742 - INFO - Processing: 2305.04532v2.pdf
2025-02-18 14:08:32,068 - INFO - Processing: 2309.05519v3.pdf
2025-02-18 14:08:38,456 - INFO - Processing: 2403.09611v4.pdf
2025-02-18 14:08:44,838 - INFO - Processing: 2404.17605v1.pdf
2025-02-18 14:08:48,925 - INFO - Processing: 31664-Article Text-35728-1-2-20241016.pdf
2025-02-18 14:08:51,934 - INFO - Processing: 3649217.3653594.pdf
2025-02-18 14:08:55,379 - INFO - Processing: AIp2300031.pdf
2025-02-18 14:08:57,199 - INFO - Processing: GPT-4Vision_for_Robotics_Multimodal_Task_Planning_From_Human_Demonstration.pdf
2025-02-18 14:09:00,477 - INFO - Processing: GPT_Generative_Pre-Trained_Transformer_A_Comprehensive_Review_on_Enabling_Technologies_Potential_Applications_Emerging_Challenges_and.pdf
2025-02-18 14:09:10,667 - INFO - Processing: RTLCoder_Outperforming_GPT-3.5_in_Design_RTL_Generation_with_Our_Open-Source_Dataset_and_Lightweight_Solution.pdf
2025-02-18 14:09:15,003 - INFO - Anlisis completado. Resultados guardados en la carpeta output/

figuresperarticle.png: keyword_cloud.png: links.txt: links

Preferred Citation

A citation file is included in this repository. Please refer to the CITATION.cff file for proper citation format.