Research Paper Summarizer

Overview

The Research Paper Summarizer is a web application designed to help users quickly fetch and summarize the latest research papers from arXiv. This tool is ideal for researchers, students, and anyone interested in staying updated with the latest scientific advancements. Simply enter a research topic, specify the number of papers to fetch, and let the application handle the rest!

Features

Fetch Latest Research Papers: Retrieve the most recent papers from arXiv by entering a topic.
Summarize Papers: Generate concise summaries for individual research papers.
Download PDFs: Download the full text of the research papers in PDF format directly from the application.
Clean and Professional UI: Enjoy a user-friendly interface with a modern design.

Technologies Used

Backend: Python, Flask
Frontend: HTML, CSS, JavaScript
APIs: OpenAI GPT-4 (for summarization), arXiv API (for fetching papers)
Libraries: requests, PyPDF2, nltk, langchain

Installation

1. Create a virtual environment:

python3 -m venv venv
source venv/bin/activate

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

Create a .env file in the root directory.
Add your OpenAI API key:

OPENAI_API_KEY=your-openai-api-key

4. Run the application:

python app.py

5. Access the application:

Open your web browser and navigate to http://127.0.0.1:5001/.

Usage

Homepage:

The homepage welcomes you with a brief overview of the tool. Enter your desired research topic and the number of papers you wish to retrieve.

Fetch Papers:

After submitting the topic, the application fetches the most recent papers from arXiv and displays them on a results page.

Summarize:

For each paper, click the "Summarize" button to generate a concise summary of the paper.

Download PDF:

You can also download the full text of the research papers in PDF format using the "Download PDF" button.

Screenshots

Homepage

Results Page

Customization

You can customize the application by modifying the style.css file for styling or updating the backend logic in app.py for different summarization models or additional features.

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes. For major changes, please open an issue first to discuss what you would like to change.

Contact

If you have any questions, feel free to contact me here.

sankalpsaoji98/Research-Paper-Summarizer