README

Project Overview

This project provides a streamlined method for summarizing scientific articles using advanced natural language processing capabilities. By leveraging Google Generative AI and fine-tuned prompt engineering, the application generates structured summaries of uploaded scientific articles.

Features

• Automatic Summarization: Converts uploaded articles into structured summaries.
• Detailed Outputs: Includes key findings, objectives, methods, results, conclusions, and key concepts.
• User-Friendly Input: Users can upload files for seamless summarization.
• Powered by Generative AI: Utilizes Google's Gemini AI model for content generation.

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8 or higher
• pip (Python package manager)

Dependencies

Install the required libraries using:

pip install streamlit python-dotenv google-generativeai PyPDF2

Usage

Setting Up API Key

1. Create a .env file in the project directory.
2. Add your Google Generative AI API key to the file:

   API_KEY=your_api_key_here
   

Running the Application

1. Save the code in a Python script file (e.g., app.py).
2. Run the script:

   python app.py

Workflow

1. Upload a scientific article file (PDF or text format).
2. The program will process the file and generate a structured summary.

Example Prompt

The summarization prompt used in the application ensures a consistent structure:

# Structured Summary

# Key Findings

# Objectives

# Methods

# Results

# Conclusions

# Key Concepts

Code Explanation

Environment Variables

The .env file is used to securely load the API key.

Functions

• summarize(file): Generates the summary using the Google Generative AI model.
• main(): Entry point of the application.

Contributing

Contributions are welcome. Please fork the repository and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

To-do

• translate text - ptbr
• add copy button
• add tutorial
• add loading bar