https://github.com/mangoresoham/text-summarization-and-keyword-extraction
A text summarization project which uses groq for faster inference and also extracts important keywords from the text
https://github.com/mangoresoham/text-summarization-and-keyword-extraction
document-summarization groq keyword-extraction keywords llama3 llm summarization text-summarization
Last synced: about 1 month ago
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A text summarization project which uses groq for faster inference and also extracts important keywords from the text
- Host: GitHub
- URL: https://github.com/mangoresoham/text-summarization-and-keyword-extraction
- Owner: mangoresoham
- Created: 2024-12-20T18:37:42.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-20T18:43:01.000Z (over 1 year ago)
- Last Synced: 2025-02-13T21:37:21.122Z (over 1 year ago)
- Topics: document-summarization, groq, keyword-extraction, keywords, llama3, llm, summarization, text-summarization
- Language: Python
- Homepage: https://huggingface.co/spaces/mangoresoham/Summarizer
- Size: 4.88 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Summarization and Keyword Extraction Tool
This project is a web-based application for summarizing text, identifying its domain, and extracting domain-specific keywords. The application is built using **Streamlit** and utilizes the **Groq API** for text processing. It is deployed on **Hugging Face Spaces** for easy access and usage.
## Features
- Upload a text file or input text directly.
- Generate a concise summary of the text.
- Identify the domain of the text (e.g., Technology, Healthcare, etc.).
- Extract domain-specific keywords.
- Easy-to-use interface with streamlined processing.
## How It Works
1. **Input Options**: Users can either upload a `.txt` file or paste the text directly into the provided text area.
2. **API Integration**: The application uses the Groq API to process the input and generate results.
3. **Output**: Results include a summary, domain identification, and a list of keywords displayed directly on the app.
## Deployed Platform
The application is deployed on **Hugging Face Spaces**, leveraging the simplicity and scalability of Streamlit for rapid prototyping.
[Visit the App on Hugging Face Spaces](https://huggingface.co/spaces/mangoresoham/Summarizer)
## Installation and Usage (Local Deployment)
To run the application locally, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/your-username/summarization-keyword-extraction.git
cd summarization-keyword-extraction
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the application:
```bash
streamlit run app.py
```
4. Open your browser and navigate to `http://localhost:8501`.
## Configuration
- The app requires a valid **GROQ API Key** for functionality.
- Enter the API key in the sidebar under the "Configuration" section.
## File Structure
- `app.py`: Main application file.
- `requirements.txt`: Contains the list of Python dependencies.
- `README.md`: Documentation for the project.
## Requirements
- Python 3.7+
- Streamlit
- Groq API
## Example Usage
### Input
- **Uploaded file**: Upload a `.txt` file containing your document.
- **Text area**: Paste or type text directly into the app.
### Output
- **Summary**: A brief overview of the document.
- **Domain**: The primary domain of the text.
- **Keywords**: A list of extracted domain-specific keywords.