app/confidence_analysis.py

from transformers import BertTokenizer, BertForSequenceClassification
import torch



model = BertForSequenceClassification.from_pretrained('./confidence_model')
tokenizer = BertTokenizer.from_pretrained('./confidence_tokenizer')

def predict_confidence(question, answer):
    inputs = tokenizer(question, answer, return_tensors="pt", padding=True, truncation=True)
    model.eval()

    with torch.no_grad():
        outputs = model(**inputs)
        logits = outputs.logits
        predictions = torch.argmax(logits, dim=-1)
        return "Confident" if predictions.item() == 1 else "Not Confident"

# Example
question = "What is your experience with Python?"
answer = "I dont have any experience in Python"
print(predict_confidence(question, answer))