Update app.py

app.py

@@ -145,8 +145,9 @@ class Translators:
         tokenizer = T5Tokenizer.from_pretrained(self.model_name)
         text = f"<2{self.tl}> {self.input_text}"
         # input_ids = tokenizer(text, return_tensors="pt").input_ids.to(model.device)
-        # outputs = model.generate(input_ids=input_ids)    
+        # outputs = model.generate(input_ids=input_ids, max_new_tokens=512)    
         # return tokenizer.decode(outputs[0], skip_special_tokens=True)
+        # return tokenizer.batch_decode(outputs, skip_special_tokens=True)
         # Use a pipeline as a high-level helper
         translator = pipeline('translation', model=model, tokenizer=tokenizer, src_lang=self.sl, tgt_lang=self.tl)
         translated_text = translator(text, max_length=512)
@@ -407,6 +408,9 @@ def translate_text(input_text: str, s_language: str, t_language: str, model_name
     sl = all_langs[s_language][0]
     tl = all_langs[t_language][0]
     message_text = f'Translated from {s_language} to {t_language} with {model_name}'
+    if sl = tl:
+        translated_text = "Source language identical to target language!"
+        return translated_text, message_text 
     translated_text = None
     try:    
         if "-mul" in model_name.lower() or "mul-" in model_name.lower() or "-roa" in model_name.lower():