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+FROM python:3.9
+
+WORKDIR /app
+
+COPY . /app
+
+RUN pip install --no-cache-dir flask gunicorn tensorflow-cpu numpy joblib scikit-learn
+
+CMD ["gunicorn", "--bind", "0.0.0.0:7860", "app:app"]

app.py

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+from flask import Flask, render_template, request, session, redirect, url_for
+import joblib
+import numpy as np
+import tensorflow as tf
+
+app = Flask(__name__)
+app.secret_key = "verysecretkey"
+
+# Load model & preprocessors
+scaler = joblib.load('preprocessing/scaler.joblib')
+le_gender = joblib.load('preprocessing/le_gender.joblib')
+le_edu = joblib.load('preprocessing/le_edu.joblib')
+le_interest = joblib.load('preprocessing/le_interest.joblib')
+le_personality = joblib.load('preprocessing/le_personality.joblib')
+deep_model = tf.keras.models.load_model('model/deep_mbti_model.h5')
+
+mbti_descriptions = {
+    'ENTJ': 'The Commander: Strategic leaders, motivated to organize change',
+    'INTJ': 'The Mastermind: Analytical problem-solvers, eager to improve systems and processes',
+    'ENTP': 'The Visionary: Inspired innovators, seeking new solutions to challenging problems',
+    'INTP': 'The Architect: Philosophical innovators, fascinated by logical analysis',
+    'ENFJ': 'The Teacher: Idealist organizers, driven to do what is best for humanity',
+    'INFJ': 'The Counselor: Creative nurturers, driven by a strong sense of personal integrity',
+    'ENFP': 'The Champion: People-centered creators, motivated by possibilities and potential',
+    'INFP': 'The Healer: Imaginative idealists, guided by their own values and beliefs',
+    'ESTJ': 'The Supervisor: Hardworking traditionalists, taking charge to get things done',
+    'ISTJ': 'The Inspector: Responsible organizers, driven to create order out of chaos',
+    'ESFJ': 'The Provider: Conscientious helpers, dedicated to their duties to others',
+    'ISFJ': 'The Protector: Industrious caretakers, loyal to traditions and institutions',
+    'ESTP': 'The Dynamo: Energetic thrillseekers, ready to push boundaries and dive into action',
+    'ISTP': 'The Craftsperson: Observant troubleshooters, solving practical problems',
+    'ESFP': 'The Entertainer: Vivacious entertainers, loving life and charming those around them',
+    'ISFP': 'The Composer: Gentle caretakers, enjoying the moment with low-key enthusiasm'
+}
+
+# Mapping for MCQ answers (A/B/C/D) to numeric scores (customize as needed)
+MCQ_MAP = {'A': 10, 'B': 7, 'C': 4, 'D': 1}
+
+# MCQ config: 4 MBTI traits, 5 Qs each
+TRAITS = [
+    ('extroversion', "Extroversion (E/I)", [
+        "Are you comfortable with public speaking?",
+        "Do you enjoy being the center of attention?",
+        "Do you thrive in group settings?",
+        "Do you make friends easily at new places?",
+        "Do group activities energize you more than being alone?"
+    ]),
+    ('sensing', "Sensing vs Intuition (S/N)", [
+        "Do you focus more on immediate details than the big picture?",
+        "Do you trust experience over theories?",
+        "Do you prefer practical applications over abstract concepts?",
+        "Do you rely on your five senses rather than gut feelings?",
+        "Do you prefer dealing with practical facts rather than imaginative ideas?"
+    ]),
+    ('thinking', "Thinking vs Feeling (T/F)", [
+        "Do you prioritize logic over emotions when deciding?",
+        "Do you value objective truth over social harmony?",
+        "Are you comfortable giving critical feedback?",
+        "Do you analyze problems objectively rather than considering people's feelings first?",
+        "Is it more important for you to be fair than to be compassionate?"
+    ]),
+    ('judging', "Judging vs Perceiving (J/P)", [
+        "Do you prefer planned activities over spontaneous ones?",
+        "Do you enjoy making schedules and to-do lists?",
+        "Are you uncomfortable with last-minute changes?",
+        "Do you prefer closure and completion over keeping options open?",
+        "Do you prefer having a structured plan rather than keeping options open?"
+    ])
+]
+
+# Step 0: Demographics collection
+@app.route('/', methods=['GET', 'POST'])
+def demographics():
+    if request.method == 'POST':
+        session['demographics'] = {
+            'age': request.form['age'],
+            'gender': request.form['gender'],
+            'education': request.form['education'],
+            'interest': request.form['interest']
+        }
+        return redirect(url_for('mcq', step=1))
+    return render_template('index.html',
+                           gender_classes=le_gender.classes_,
+                           edu_classes=le_edu.classes_,
+                           interest_classes=le_interest.classes_)
+
+# Step 1-N: MCQ stepper for MBTI traits
+@app.route('/mcq/<int:step>', methods=['GET', 'POST'])
+def mcq(step):
+    total_steps = len(TRAITS)
+    if request.method == 'POST' and step > 1:
+        prev_trait_key = TRAITS[step - 2][0]
+        session[prev_trait_key] = [
+            request.form.get(f'{prev_trait_key}_q{i}', None) for i in range(1, 6)
+        ]
+    if step > total_steps:
+        return redirect(url_for('results'))
+    trait_key, trait_label, questions = TRAITS[step - 1]
+    return render_template('mcq_step.html',
+                          trait_key=trait_key,
+                          trait_label=trait_label,
+                          questions=questions,
+                          step=step,
+                          total_steps=total_steps)
+
+# Final: Results calculation and personality prediction
+@app.route('/results')
+def results():
+    try:
+        data = session.get('demographics', {})
+        age = float(data.get('age', 25))
+        gender = le_gender.transform([data.get('gender', le_gender.classes_[0])])[0]
+        education = le_edu.transform([data.get('education', le_edu.classes_[0])])[0]
+        interest = le_interest.transform([data.get('interest', le_interest.classes_[0])])[0]
+
+        # Collect trait scores, average each over 5 MCQs
+        trait_keys = ['extroversion', 'sensing', 'thinking', 'judging']
+        trait_scores = []
+        for trait_key in trait_keys:
+            answers = session.get(trait_key, ['C'] * 5)  # default 5 'C'
+            numeric_scores = [MCQ_MAP.get(ans, 4) for ans in answers]
+            trait_scores.append(float(sum(numeric_scores)) / 5)
+
+        # Features: [age, gender, education, extroversion, sensing, thinking, judging, interest]
+        features = np.array([[age, gender, education] + trait_scores + [interest]])
+        features_scaled = scaler.transform(features)
+        pred_proba = deep_model.predict(features_scaled)
+        pred_class = np.argmax(pred_proba)
+        mbti_pred = le_personality.inverse_transform([pred_class])[0]
+        class_probs = dict(zip(le_personality.classes_, pred_proba[0].round(3)))
+        description = mbti_descriptions.get(mbti_pred, '')
+    except Exception as e:
+        mbti_pred, class_probs, description = None, None, f"Error: {e}"
+    session.clear()
+    return render_template('results.html',
+                          mbti_pred=mbti_pred,
+                          class_probs=class_probs,
+                          description=description)
+
+if __name__ == '__main__':
+    app.run(debug=True)

requirements.txt

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+Flask==3.0.0
+numpy==1.26.2
+pandas==2.1.2
+joblib==1.3.2
+scikit-learn==1.3.2
+tensorflow==2.15.0
+gunicorn==21.2.0
+Werkzeug==3.0.1
+setuptools>=68.0.0
+wheel>=0.42.0