Update app.py

app.py

@@ -5,6 +5,7 @@ import bophono
 
 from pydub import AudioSegment
 from botok import WordTokenizer
+from mlotsawa.translator import Translator
 from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
 from transformers import MBart50TokenizerFast, MBartForConditionalGeneration
 
@@ -360,15 +361,17 @@ def run_task(text, language, task):
                 # Load Monlam AI Tibetan→English model
                 #tib_tokenizer = AutoTokenizer.from_pretrained("monlam-ai/mt-bod-eng", token=HF_TOKEN)
                 #tib_model = AutoModelForSeq2SeqLM.from_pretrained("monlam-ai/mt-bod-eng", token=HF_TOKEN)
-                tib_tokenizer = AutoTokenizer.from_pretrained("billingsmoore/prototype-tibetan-to-english-translation-v1")
-                tib_model = AutoModelForSeq2SeqLM.from_pretrained("billingsmoore/prototype-tibetan-to-english-translation-v1")
+                #tib_tokenizer = AutoTokenizer.from_pretrained("billingsmoore/prototype-tibetan-to-english-translation-v1")
+                #tib_model = AutoModelForSeq2SeqLM.from_pretrained("billingsmoore/prototype-tibetan-to-english-translation-v1")
         
                 # Encode Tibetan input
-                inputs = tib_tokenizer(text, return_tensors="pt")
+                #inputs = tib_tokenizer(text, return_tensors="pt")
         
                 # Generate translation
-                outputs = tib_model.generate(**inputs, max_new_tokens=256)
-                translated = tib_tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
+                #outputs = tib_model.generate(**inputs, max_new_tokens=256)
+                #translated = tib_tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
+                translator = Translator()
+                translated = translator.translate(text)
         
                 # Handle nonsense or empty outputs
                 if not translated or translated.isspace():