Update metrics.py

metrics.py

@@ -1,6 +1,6 @@
 # metrics.py
 import nltk
-from nltk.translate.bleu_score import sentence_bleu
+#from nltk.translate.bleu_score import sentence_bleu
 from rouge_score import rouge_scorer
 from model_loader import metrics_models
 
@@ -37,19 +37,6 @@ def compute_empathy_score(paraphrased):
         print(f"Error computing empathy score: {str(e)}")
         return None
 
-def compute_bleu_score(original, paraphrased):
-    """
-    Compute the BLEU score between the original and paraphrased comment.
-    Returns a score between 0 and 1.
-    """
-    try:
-        reference = [nltk.word_tokenize(original.lower())]
-        candidate = nltk.word_tokenize(paraphrased.lower())
-        score = sentence_bleu(reference, candidate, weights=(0.25, 0.25, 0.25, 0.25))
-        return round(score, 2)
-    except Exception as e:
-        print(f"Error computing BLEU score: {str(e)}")
-        return None
 
 def compute_rouge_score(original, paraphrased):
     """