Update gradio_app.py

gradio_app.py

@@ -5,16 +5,16 @@ import gradio as gr
 import psutil
 
 # Initing things                
-print("! DOWNLOADING TOKENIZER AND SETTING ALL UP !")
-translator_tokenizer = M2M100Tokenizer.from_pretrained(            # tokenizer for translator
-    "facebook/m2m100_418M", cache_dir="translator/"
-)
-print("! DOWNLOADING MODEL AND SETTING ALL UP !")
-translator_model = M2M100ForConditionalGeneration.from_pretrained( # translator model
-    "facebook/m2m100_418M", cache_dir="translator/"
-)
-print("! SETTING MODEL IN EVALUATION MODE !")
-translator_model.eval()
+#print("! DOWNLOADING TOKENIZER AND SETTING ALL UP !")
+#translator_tokenizer = M2M100Tokenizer.from_pretrained(            # tokenizer for translator
+#    "facebook/m2m100_418M", cache_dir="translator/"
+#)
+#print("! DOWNLOADING MODEL AND SETTING ALL UP !")
+#translator_model = M2M100ForConditionalGeneration.from_pretrained( # translator model
+#    "facebook/m2m100_418M", cache_dir="translator/"
+#)
+#print("! SETTING MODEL IN EVALUATION MODE !")
+#translator_model.eval()
 print("! INITING LLAMA MODEL !")
 llm = Llama(model_path="./model.bin")                              # LLaMa model
 llama_model_name = "TheBloke/Llama-2-13B-chat-GGUF" 
@@ -56,15 +56,15 @@ def generate_answer(request: str, max_tokens: int = 256, language: str = "en", c
         text = output["choices"][0]["text"]
         # i allowed only certain languages (its not discrimination, its just other popular language on my opinion!!!):
         # russian (ru), ukranian (uk), chinese (zh)
-        if language in ["ru", "uk", "zh"]:
-            encoded_input = translator_tokenizer(output, return_tensors="pt")
-            generated_tokens = translator_model.generate(
-                **encoded_input, forced_bos_token_id=translator_tokenizer.get_lang_id(language)
-            )
-            translated_text = translator_tokenizer.batch_decode(
-                generated_tokens, skip_special_tokens=True
-            )[0]
-            return translated_text
+        #if language in ["ru", "uk", "zh"]:
+            #encoded_input = translator_tokenizer(output, return_tensors="pt")
+            #generated_tokens = translator_model.generate(
+            #    **encoded_input, forced_bos_token_id=translator_tokenizer.get_lang_id(language)
+            #)
+            #translated_text = translator_tokenizer.batch_decode(
+            #    generated_tokens, skip_special_tokens=True
+            #)[0]
+            #return translated_text
         return text
     except Exception as e:
         print(e)