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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)
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