# paraphraser.py from model_loader import paraphraser_model def paraphrase_comment(comment): """ Paraphrase a toxic comment using the Granite 3.2-2B-Instruct model. Returns the paraphrased comment. """ if not comment: return None try: model = paraphraser_model.model tokenizer = paraphraser_model.tokenizer # Create a detailed prompt with guidelines and examples prompt = ( "You are a content moderator tasked with rewriting toxic comments into neutral and constructive ones while maintaining the original meaning. " "Follow these guidelines:\n" "- Remove explicit hate speech, personal attacks, or offensive language.\n" "- Keep the response neutral and professional.\n" "- Ensure the rewritten comment retains the original intent but in a constructive tone.\n\n" "Examples:\n" "Toxic: \"You're so dumb! You never understand anything!\"\n" "Neutral: \"I think there's some misunderstanding. Let's clarify things.\"\n" "Toxic: \"This is the worst idea ever. Only an idiot would suggest this.\"\n" "Neutral: \"I don't think this idea works well. Maybe we can explore other options.\"\n\n" f"Now, rewrite this comment: \"{comment}\"" ) inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True, max_length=512) # Generate the paraphrased comment outputs = model.generate( **inputs, max_length=512, num_return_sequences=1, temperature=0.7, top_p=0.9, do_sample=True ) paraphrased_comment = tokenizer.decode(outputs[0], skip_special_tokens=True) # Remove the prompt part from the output paraphrased_comment = paraphrased_comment.replace(prompt, "").strip() # Remove unwanted prefixes like "Neutral: " if paraphrased_comment.startswith("Neutral: "): paraphrased_comment = paraphrased_comment[len("Neutral: "):].strip() return paraphrased_comment except Exception as e: return f"Error paraphrasing comment: {str(e)}"