Update paraphraser.py

paraphraser.py

@@ -18,15 +18,18 @@ def paraphrase_comment(comment):
             "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 conversational, suitable for a casual online platform.\n"
-            "- Ensure the rewritten comment retains the original intent but in a constructive tone, addressing the specific context of the comment (e.g., disagreement, frustration).\n\n"
+            "- Keep the response neutral and professional.\n"
+            "- Ensure the rewritten comment retains the original intent but in a constructive tone.\n"
+            "- Match the length and brevity of the original toxic comment whenever possible. Keep the response short and to the point.\n\n"
             "Examples:\n"
             "Toxic: \"You're so dumb! You never understand anything!\"\n"
-            "Neutral: \"I think there might be a misunderstanding here. Can we go over this again to clear things up?\"\n"
+            "Neutral: \"You might be misunderstanding this.\"\n"
             "Toxic: \"This is the worst idea ever. Only an idiot would suggest this.\"\n"
-            "Neutral: \"I’m not sure this idea works for me. Could we look at some other options instead?\"\n"
-            "Toxic: \"You are an idiot and should leave this platform.\"\n"
-            "Neutral: \"It seems like you might not be enjoying this platform. Maybe we can talk about what’s not working for you?\"\n\n"
+            "Neutral: \"I don’t think this idea works well.\"\n"
+            "Toxic: \"You’re useless.\"\n"
+            "Neutral: \"This isn’t helping much.\"\n"
+            "Toxic: \"Shut up.\"\n"
+            "Neutral: \"Let’s take a break from this.\"\n\n"
             f"Now, rewrite this comment: \"{comment}\""
         )
         inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True, max_length=512)