Text Summarizer Flask Application

This Flask application allows users to input text, generate summaries using a BART-based model, and save the inputs and summaries to a SQLite database. It also includes functionality to fine-tune the summarization model with user-provided data.

Features

• Text Summarization: Users can input text, which is then summarized using a fine-tuned BART model.
• Database Storage: User inputs and generated summaries are stored in a SQLite database.
• Model Fine-Tuning: Optionally fine-tune the summarization model with data from the database.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/text-summarizer.git
   cd text-summarizer

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

4. Download the model and tokenizer (if not pre-downloaded):

   from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
   model = AutoModelForSeq2SeqLM.from_pretrained('facebook/bart-large-cnn')
   tokenizer = AutoTokenizer.from_pretrained('facebook/bart-large-cnn')

Usage

1. Run the Flask application:

   python app.py

2. Open your web browser and navigate to http://127.0.0.1:5000/.

3. Enter text in the provided form to get a summary. The summarized text will be displayed and saved in the database.

4. Model Fine-Tuning: To fine-tune the model with user data, you can call the fine_tune_model function with data retrieved from the database.

Project Structure

text-summarizer/

• app.py # Main Flask application script
• requirements.txt # List of dependencies
• fine_tuned_model/ # Directory for saving fine-tuned models
• generation_config/ # Directory for saving generation configuration
• README.md # This file

Dependencies

• Flask
• transformers
• sqlite3
• torch
• re
• os

License

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

Contributing

If you have suggestions or improvements, please fork the repository and create a pull request. For major changes, please open an issue first to discuss what you would like to change.

Contact

For any questions or feedback, please reach out to vishnuvardhanv046@example.com

To install these dependencies, use the requirements.txt file:

Flask==2.2.3
transformers==4.27.1
torch==2.0.0