Update app.py

app.py

@@ -12,13 +12,22 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 # Function to generate speech from text
 def text_to_speech(urdu_text):
-    inputs = tokenizer(urdu_text, return_tensors="pt")
+    # Input Validation
+    if not urdu_text.strip():
+        raise ValueError("Input text is empty. Please enter valid Urdu text.")
     
-    # Ensure input_ids are LongTensor (Fix for error)
+    # Tokenize input text
+    inputs = tokenizer(urdu_text, return_tensors="pt", padding=True, truncation=True)
+    
+    # Check if input_ids is empty
+    if inputs["input_ids"].size(1) == 0:
+        raise ValueError("Tokenization resulted in empty input. Please check the input text.")
+    
+    # Ensure input_ids are LongTensor
     inputs["input_ids"] = inputs["input_ids"].to(torch.long)
 
     with torch.no_grad():
-        output = model(**inputs).waveform.numpy()
+        output = model(**inputs).waveform.squeeze().numpy()
 
     # Save audio as a temporary file
     temp_wav_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")