https://github.com/CllsPy/sag
A faster way to summarizer your papers
https://github.com/CllsPy/sag
gemini-ai generative-ai-tools papers python summarization
Last synced: 5 months ago
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A faster way to summarizer your papers
- Host: GitHub
- URL: https://github.com/CllsPy/sag
- Owner: CllsPy
- License: mit
- Created: 2024-11-16T01:33:04.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-12-12T20:53:41.000Z (over 1 year ago)
- Last Synced: 2024-12-12T21:31:37.230Z (over 1 year ago)
- Topics: gemini-ai, generative-ai-tools, papers, python, summarization
- Language: Python
- Homepage: https://gemsum.streamlit.app/
- Size: 1.86 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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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:
```bash
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:
```plaintext
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:
```bash
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