Update app.py

app.py

@@ -24,14 +24,16 @@ from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
 translation_model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
 translation_tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
 
-def english_to_hindi(sentence):
+languages_list = [gu_IN, hi_IN ,bn_IN, ml_IN, mr_IN, ta_IN, te_IN]
+
+def english_to_indian(sentence):
     translation_tokenizer.src_lang = "en_xx"
     encoded_hi = translation_tokenizer(sentence, return_tensors="pt")
     generated_tokens = translation_model.generate(**encoded_hi, forced_bos_token_id=translation_tokenizer.lang_code_to_id["hi_IN"] )
     return (translation_tokenizer.batch_decode(generated_tokens, skip_special_tokens=True))
 
 
-def hindi_to_english(sentence):
+def indian_to_english(sentence):
     translation_tokenizer.src_lang = "hi_IN"
     encoded_hi = translation_tokenizer(sentence, return_tensors="pt")
     generated_tokens = translation_model.generate(**encoded_hi, forced_bos_token_id=translation_tokenizer.lang_code_to_id["en_XX"] )
@@ -264,7 +266,10 @@ def demo():
             llm_progress = gr.Textbox(value="None",label="QA chain initialization", visible=True)
         with gr.Row():
             qachain_btn = gr.Button("Initialize question-answering chain...")
-            
+
+        with gr.Row():
+            lang_btn = gr.Radio(languages_list, label="Languages", value = list_llm_simple[1], type="index", info="Choose your language")
+        
         chatbot = gr.Chatbot(height=300)
 
         with gr.Row():