Update app.py

app.py

@@ -10,6 +10,7 @@ models = ["Helsinki-NLP", "t5-base", "t5-small", "t5-large", "facebook/nllb-200-
 def translate_text(input_text, sselected_language, tselected_language, model_name):
     sl = langs[sselected_language][0]
     tl = langs[tselected_language][0]
+    message_text = f'Translated from {sselected_language} to {tselected_language} with {model_name}'
     if model_name == "Helsinki-NLP":
         try:
             model_name_full = f"Helsinki-NLP/opus-mt-{sl}-{tl}"
@@ -21,13 +22,13 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
                 tokenizer = AutoTokenizer.from_pretrained(model_name_full)
                 model = AutoModelForSeq2SeqLM.from_pretrained(model_name_full)
             except EnvironmentError as error:
-                return f"Error finding required model! Try other available language combination. Error: {error}"
+                return f"Error finding model: {model_name_full}! Try other available language combination.", error
     elif model_name.startswith('facebook/nllb'):
         tokenizer = AutoTokenizer.from_pretrained(model_name)
         model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
         translator = pipeline('translation', model=model, tokenizer=tokenizer, src_lang=langs[sselected_language][1], tgt_lang=langs[tselected_language][1])
         translated_text = translator(input_text, max_length=512)
-        return translated_text[0]['translation_text']
+        return translated_text[0]['translation_text'], message_text
     else:
         tokenizer = T5Tokenizer.from_pretrained(model_name)
         model = T5ForConditionalGeneration.from_pretrained(model_name, device_map="auto")
@@ -40,7 +41,7 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
     input_ids = tokenizer.encode(prompt, return_tensors="pt")
     output_ids = model.generate(input_ids, max_length=512)
     translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-    message_text = f'Translated from {sselected_language} to {tselected_language} with {model_name}'
+    
     print(f'Translating from {sselected_language} to {tselected_language} with {model_name}:', f'{input_text} =  {translated_text}', sep='\n')
     return translated_text, message_text