Personality Assessment Web App

This project is a web application built with Flask that assesses personality based on user responses to a set of questions. The application presents questions to the user, collects their responses, and generates a personality chart based on their answers.

Features

• User-friendly interface for answering personality assessment questions.
• Data visualization using Chart.js to display personality traits.
• Backend processing of user responses to generate personality insights.
• Integration with two K-means clustering models stored in the models directory for personality analysis.

Files and Folders

• app.py: Flask application file that defines routes and handles user interactions.
• Test.py: Python script containing functions for generating personality charts based on user responses.
• questions.csv: CSV file containing the questions for the personality assessment.
• css/: Folder containing CSS files for styling the web interface.
• templates/: Folder containing HTML templates for rendering the web pages.
• models/: Folder containing two K-means clustering models used for personality analysis.

Installation and Setup

1. Clone the repository:

   git clone https://github.com/pravincoder/personality_app.git

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Flask application:

   python app.py

4. Access the application in your web browser at http://localhost:5000.

Usage

1. Answer the questions presented on the web interface.
2. Submit your responses.
3. View the generated personality chart based on your responses.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/new-feature).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new feature').
5. Push to the branch (git push origin feature/new-feature).
6. Create a new Pull Request.

License

This project is licensed under the MIT License.

Acknowledgments

• This project was inspired by my friend in our Mini Project Mumbai university.
• Thanks to the Flask and Chart.js communities for providing excellent resources and documentation.
• Thanks to kaggle dataset (source)[!https://www.kaggle.com/datasets/tunguz/big-five-personality-test/data]