Update app.py

app.py

@@ -406,12 +406,9 @@ class Translators:
         model = SeamlessM4TModel.from_pretrained(self.model_name)
         src_lang = iso1toall.get(self.sl)[2] # 'deu', 'ron', 'eng', 'fra'        
         tgt_lang = iso1toall.get(self.tl)[2]
-        print(src_lang, tgt_lang)
         text_inputs = processor(text = self.input_text, src_lang=src_lang, return_tensors="pt")
-        output_tokens = model.generate(**text_inputs, tgt_lang=tgt_lang, generate_speech=False)
-        translated_text = processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True) 
-        print(f"{tgt_lang}: {text_inputs} {translated_text}")
-        return translated_text 
+        output_tokens = model.generate(**text_inputs, tgt_lang=tgt_lang, generate_speech=False) 
+        return processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True)
         
     def seamlessm4t2(self):
         from transformers import AutoProcessor, SeamlessM4Tv2ForTextToText
@@ -419,12 +416,9 @@ class Translators:
         model = SeamlessM4Tv2ForTextToText.from_pretrained(self.model_name)
         src_lang = iso1toall.get(self.sl)[2] # 'deu', 'ron', 'eng', 'fra'        
         tgt_lang = iso1toall.get(self.tl)[2]
-        print(src_lang, tgt_lang)
         text_inputs = processor(text=self.input_text, src_lang=src_lang, return_tensors="pt")
         decoder_input_ids = model.generate(**text_inputs, tgt_lang=tgt_lang)[0].tolist()
-        translated_text = processor.decode(decoder_input_ids, skip_special_tokens=True)
-        print(f"{tgt_lang}: {text_inputs} {translated_text}")
-        return translated_text
+        return processor.decode(decoder_input_ids, skip_special_tokens=True)
     
     def wingpt(self):
         model = AutoModelForCausalLM.from_pretrained(
@@ -613,10 +607,10 @@ def translate_text(input_text: str, s_language: str, t_language: str, model_name
             translated_text = Translators(model_name, s_language, t_language, input_text).mbart_many_to_one()
           
         elif model_name ==  "facebook/seamless-m4t-v2-large":
-            translated_text = Translators(model_name, s_language, t_language, input_text).seamlessm4t2()
+            translated_text = Translators(model_name, sl, tl, input_text).seamlessm4t2()
           
         elif "m4t-medium" in model_name or "m4t-large" in model_name:
-            translated_text = Translators(model_name, s_language, t_language, input_text).seamlessm4t1()
+            translated_text = Translators(model_name, sl, tl, input_text).seamlessm4t1()
         
         elif model_name == "utter-project/EuroLLM-1.7B-Instruct":
             translated_text = Translators(model_name, s_language, t_language, input_text).eurollm_instruct()