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# paraphraser.py
from model_loader import paraphraser_model
import time
def paraphrase_comment(comment):
"""
Paraphrase a given comment using the fine-tuned Granite 3.2-2B-Instruct model to make it non-toxic, empathetic, and professional while retaining the original intent.
Returns the paraphrased comment.
"""
try:
start_time = time.time()
print("Starting paraphrasing...")
# Access the model and tokenizer
model = paraphraser_model.model
tokenizer = paraphraser_model.tokenizer
# Define the prompt for paraphrasing
prompt = (
f"You are a content moderator tasked with paraphrasing a comment to make it non-toxic, empathetic, and professional while retaining the original intent. "
f"The original comment is: \"{comment}\". "
f"Guidelines: "
f"- Remove any hate speech, offensive language, or toxic elements. "
f"- Use a neutral or positive tone. "
f"- Ensure the paraphrased comment is concise and clear. "
f"- Maintain the core message or intent of the original comment. "
f"Provide the paraphrased comment only, without additional explanation."
)
# Tokenize the prompt
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True, max_length=512)
# Generate the paraphrased comment
outputs = model.generate(
inputs["input_ids"],
max_length=512,
num_beams=5,
no_repeat_ngram_size=2,
early_stopping=True
)
# Decode the output
paraphrased_comment = tokenizer.decode(outputs[0], skip_special_tokens=True)
# Clean up the output (remove the prompt and any extra text)
if prompt in paraphrased_comment:
paraphrased_comment = paraphrased_comment.replace(prompt, "").strip()
paraphrased_comment = paraphrased_comment.strip()
print(f"Paraphrasing completed in {time.time() - start_time:.2f} seconds")
return paraphrased_comment if paraphrased_comment else "Error: Unable to generate paraphrase."
except Exception as e:
print(f"Error during paraphrasing: {str(e)}")
return "Error: Unable to generate paraphrase." |