app.py

import numpy as np
import gradio as gr
import joblib
from pytorch_tabnet.tab_model import TabNetClassifier

# Load model, scaler, and encoder
model = TabNetClassifier()
model.load_model('tabnet_model.zip')  # Must be .zip file
scaler = joblib.load('scaler.save')
encoder = joblib.load('encoder.save')

# Full form trait mapping
trait_prefixes = {
    'Extraversion': 'EXT',
    'Emotional Stability': 'EST',
    'Agreeableness': 'AGR',
    'Conscientiousness': 'CSN',
    'Openness': 'OPN'
}

# Example IPIP-FFM questionnaire questions (replace with actual questions)
questions = [
    "I am the life of the party.", "I feel comfortable around people.", "I often feel blue.", "I am easily disturbed.", 
    "I enjoy trying new things.", "I am talkative.", "I don't mind being the center of attention.", "I often get upset.", 
    "I am interested in abstract ideas.", "I am full of energy.", "I would rather sit at home than go out.", 
    "I don't like to draw attention to myself.", "I am sometimes easily angered.", "I have frequent mood swings.", 
    "I like to travel to new places.", "I like to meet new people.", "I enjoy having a wide variety of friends.", 
    "I am good at handling stress.", "I often feel like I’m not in control of my emotions.", "I prefer variety to routine.", 
    "I am a very anxious person.", "I prefer to stick to one activity at a time.", "I enjoy being active in social settings.", 
    "I don’t like to take risks.", "I get along with most people.", "I get bored easily.", "I tend to be impulsive.", 
    "I like being organized.", "I feel uncomfortable around strangers.", "I avoid conflict with others.", "I have a lot of energy.", 
    "I find it difficult to express my emotions.", "I often feel lonely.", "I like to keep my thoughts and feelings to myself.", 
    "I find it difficult to relax.", "I am always prepared.", "I sometimes feel down.", "I find it difficult to focus on one task.", 
    "I enjoy the company of others.", "I like to talk about my feelings.", "I can’t stand being interrupted.", 
    "I often forget to do things.", "I am good at understanding other people’s feelings.", "I enjoy taking on challenges.", 
    "I often feel overwhelmed.", "I like to take my time making decisions.", "I enjoy being in charge.", "I am easily distracted.", 
    "I get along well with others.", "I enjoy being the center of attention."
]

# Create sliders with questions
inputs = [gr.Slider(1.0, 5.0, value=3.0, label=q) for q in questions]
output = gr.Textbox(label="Prediction")

# Inference function
def predict_personality(*inputs):
    input_array = np.array(inputs).reshape(1, -1)
    scaled_input = scaler.transform(input_array)
    pred = model.predict(scaled_input)
    personality = encoder.inverse_transform(pred)[0]
    return f"Predicted Personality: **{personality}**"

# Gradio UI with 50 sliders and full question labels
demo = gr.Interface(
    fn=predict_personality,
    inputs=inputs,
    outputs=output,
    title="Personality Type Classifier (Introvert vs. Extrovert)",
    description="Provide scores (1–5) for 50 questions from the IPIP-FFM questionnaire. The model will predict whether the person is an Introvert or an Extrovert."
)

demo.launch()