feedback.py

from flask import Flask, render_template, request
from transformers import GPT2LMHeadModel, GPT2Tokenizer

app = Flask(__name__)

# Load the fine-tuned model and tokenizer
model = GPT2LMHeadModel.from_pretrained("./fine_tuned_model")
tokenizer = GPT2Tokenizer.from_pretrained("./fine_tuned_model")

# Function to generate feedback
def generate_feedback(user_input):
    inputs = tokenizer(user_input, return_tensors="pt", truncation=True, padding=True, max_length=512)
    outputs = model.generate(inputs["input_ids"], max_length=150, num_return_sequences=1)
    feedback = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return feedback

@app.route('/')
def index():
    return render_template('behavioral.html')

@app.route('/submit_answer', methods=['POST'])
def submit_answer():
    # Get the user input from the form
    user_input = request.form['answer']  # Assuming the form uses 'answer' as input field name
    
    # Generate feedback using the fine-tuned model
    feedback = generate_feedback(user_input)
    
    # Return the feedback to the user and render it in behavioral.html
    return render_template('behavioral.html', feedback=feedback)

if __name__ == '__main__':
    app.run(debug=True)