Update app.py

app.py

@@ -13,7 +13,7 @@ tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B")
 model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_1.2B").to(device)
 model.eval()
 
-l1="Afrikaans"
+
 class Language:
     def __init__(self, name, code):
         self.name = name
@@ -141,21 +141,9 @@ def trans_page(input,trg):
         translated_text=input
         pass
 
+     
         
-    if trg_lang != src_lang:
-        new_lang = []
-        tokenizer.src_lang = src_lang
-        for langs in lang_id:
-            with torch.no_grad():
-                encoded_input = tokenizer(langs.name, return_tensors="pt").to(device)
-                generated_tokens = model.generate(**encoded_input, forced_bos_token_id=tokenizer.get_lang_id(trg_lang))
-                trans_langs = tokenizer.batch_decode(generated_tokens, skip_special_tokens=False)[0]
-            new_lang.append(trans_langs)
-    else:
-        new_lang=lang_id
-        pass
-        
-    return translated_text,gr.Dropdown.update(choices=[l.name for l in new_lang]),gr.Dropdown.update(choices=[l.name for l in new_lang])
+    return translated_text
 
 def trans_to(input,src,trg):
     for lang in lang_id:
@@ -208,7 +196,7 @@ with gr.Blocks() as transbot:
                     message = gr.Textbox(label="Prompt",placeholder="Enter Prompt",lines=4)
                     translated = gr.Textbox(label="Translated",lines=4,interactive=False)
         gr.Column()
-    t_submit.click(trans_page,[md,t_space],[md,lang_from,lang_to])
+    t_submit.click(trans_page,[md,t_space],[md])
     
     submit.click(trans_to, inputs=[message,lang_from,lang_to], outputs=[translated])
 transbot.queue(concurrency_count=20)