Simple NLP App with Flask Authentication

Overview

This project demonstrates the integration of natural language processing (NLP) functionality with a Flask-based login and registration system. The app fetches data from an external API, processes it using basic NLP techniques, and provides users with an interactive and secure platform.

Features

• User Authentication:
  • Secure user registration.
  • User login/logout functionality with session management.
• NLP Functionality:
  • Fetches data from an external API.
  • Processes and displays the data with basic NLP operations (e.g., sentiment analysis, keyword extraction, or summarization).
• Responsive UI:
  • Simple and clean interface for seamless user interaction.

Tech Stack

• Backend: Flask (Python)
• Frontend: HTML, CSS
• Database: Used JSON for DB
• API: External NLP or text-based API for data fetching

Installation

1. Clone the repository:

   git clone https://github.com/BensOmnitrix/NLPApp-using-Flask.git
   cd NLPApp-using-Flask

2. Set up a virtual environment:

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

3. Install dependencies:

   pip install -r requirements.txt

4. Configure the environment variables:

   • Create a .env file in the root directory.
   • Add the following variables:

     FLASK_APP=app.py
     FLASK_ENV=development
     SECRET_KEY=your_secret_key
     API_KEY=your_api_key

5. Run the application:

   flask run

6. Access the app: Open your browser and navigate to http://127.0.0.1:5000.

How It Works

1. User Registration and Login:

   • Users can register with a unique username and password.
   • Passwords are securely hashed using libraries like werkzeug.security.
   • Login credentials are verified, and users gain access to the NLP features upon successful login.

2. NLP Functionality:

   • Once logged in, users can interact with the NLP features.
   • Data is fetched from the external API (e.g. NLPCloud API).
   • The app processes the data and provides results such as:
     • Sentiment analysis.
     • NER (Named Entity Recognition)
     • Code Generation

Future Enhancements

• Add role-based access control.
• Integrate advanced NLP models like Hugging Face transformers.
• Implement OAuth for third-party login options (e.g., Google, GitHub).
• Improve the UI/UX with a frontend framework (e.g., React or Vue).

Contribution

Contributions are welcome! Feel free to fork the repository, make improvements, and submit a pull request.

---

Developed with passion and determination.