Update app.py

app.py

@@ -128,26 +128,26 @@ def call_model_transformer(sources, direction_trans):
         ct_model_path = "myen_ctranslate2/"
         sp_source_model_path = "myen_ctranslate2/source.model"
         sp_target_model_path = "myen_ctranslate2/target.model"
-            if sources == "" :
-                gr.Warning("Please Enter Myanmar Text")
-            else:
-                sp_source_model = sp.load(sp_source_model_path)
-                sp_target_model = sp.load(sp_target_model_path)
-                #translator = ctranslate2.Translator(ct_model_path)    
-                sources_seg = write_to_file_myanmar(sources)
-                #Subword the source sentences
-                source_sents_subworded = sp.encode_as_pieces([sources_seg])
-
-                # Translate the source sentences
-                translator = ctranslate2.Translator(ct_model_path, device="cpu")  # or "cuda" for GPU
-                translations = translator.translate_batch(source_sents_subworded, batch_type="tokens", max_batch_size=4096)
-                translations = [translation.hypotheses[0] for translation in translations]
-
-                # Load the target SentecePiece model
-                sp.load(sp_target_model_path)
-
-                # Desubword the target sentences
-                translations_desubword = sp.decode(translations)      
+        if sources == "" :
+            gr.Warning("Please Enter Myanmar Text")
+        else:
+            sp_source_model = sp.load(sp_source_model_path)
+            sp_target_model = sp.load(sp_target_model_path)
+            #translator = ctranslate2.Translator(ct_model_path)    
+            sources_seg = write_to_file_myanmar(sources)
+            #Subword the source sentences
+            source_sents_subworded = sp.encode_as_pieces([sources_seg])
+
+            # Translate the source sentences
+            translator = ctranslate2.Translator(ct_model_path, device="cpu")  # or "cuda" for GPU
+            translations = translator.translate_batch(source_sents_subworded, batch_type="tokens", max_batch_size=4096)
+            translations = [translation.hypotheses[0] for translation in translations]
+
+            # Load the target SentecePiece model
+            sp.load(sp_target_model_path)
+
+            # Desubword the target sentences
+            translations_desubword = sp.decode(translations)      
 
     else: gr.Warning("Please Select Language Direction")