Personality Prediction Web Application

This project is a web application that predicts personality types using the K-Nearest Neighbors (KNN) algorithm. The application is built with FastAPI for the backend and Streamlit for the frontend, providing an interactive and user-friendly personality test.

Project Description

The Personality Prediction Web Application allows users to take a personality test and receive predictions based on their responses. Users can choose between two test lengths: a comprehensive 60-question test or a shorter 20-question version. Both versions classify users into one of 16 personality types. While the 60-question test provides a more detailed analysis, the 20-question version offers a quicker way to get an overview of their personality type. Each personality type is described with specific characteristics to help users understand their results better.

How To Run The Project

This project requires three terminals to run the backend and frontend services. Follow the steps below:

Terminal 1: Start MySQL and Create the Database First of all, you need to configure the DB_URL variable from sql_app/database.py file with your own database credentials. Here is the format:

DB_URL = "mysql+pymysql://username:password@host:port/persons" (database named persons)

1. Start MySQL service:

$ brew services start mysql

2. Access MySQL with the root user:

$ mysql -u root -p

3. Create the persons database:

$ CREATE DATABASE persons;

$ EXIT;

Terminal 2: Start the FastAPI Application

1. Navigate to the project directory.
2. Start the FastAPI application using Uvicorn:

$ uvicorn app.main:app --reload

Terminal 3: Start the Streamlit Frontend

1. Navigate to the project directory.
2. Start the Streamlit application:

$ streamlit run frontend/app.py

Website:

Prediction: