Update app.py

app.py

@@ -60,7 +60,13 @@ def generate_paraphrase(text: str, style: str = "standard", num_variations: int
         
         # Tokenize the input text
         input_ids = tokenizer.encode(text, return_tensors="pt").to(device)
-        
+
+        # Determine beam groups
+        beam_groups = min(num_variations, 4) if num_variations > 1 else 1
+
+        # If using diverse beam search, disable sampling
+        do_sample = False if beam_groups > 1 else True
+
         # Generate paraphrases
         with torch.no_grad():
             outputs = model.generate(
@@ -71,16 +77,16 @@ def generate_paraphrase(text: str, style: str = "standard", num_variations: int
                 temperature=params["temperature"],
                 top_k=params["top_k"],
                 diversity_penalty=params["diversity_penalty"],
-                num_beam_groups=min(num_variations, 4) if num_variations > 1 else 1,
-                do_sample=True
+                num_beam_groups=beam_groups,
+                do_sample=do_sample  # <-- Fix applied here
             )
-        
+
         # Decode the generated outputs
         paraphrases = [
             tokenizer.decode(output, skip_special_tokens=True) 
             for output in outputs
         ]
-        
+
         return paraphrases
 
     except Exception as e: