Update src/main.py

src/main.py

@@ -4,19 +4,29 @@ from NLP_Spacy_base_translator import NlpSpacyBaseTranslator
 from flask import Flask, render_template, Response, request
 from transformers import pipeline
 import torch
+import os
 
 app = Flask(__name__)
 app.config['TITLE'] = 'ASL Translator'
 
+# Set cache directory
+os.environ['TRANSFORMERS_CACHE'] = '/tmp/transformers_cache'
+os.makedirs('/tmp/transformers_cache', exist_ok=True)
+
 # Force CPU usage
 device = torch.device('cpu')
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", device=device)
+os.environ['CUDA_VISIBLE_DEVICES'] = ''
+
+# Initialize translator with local cache
+translator = pipeline("translation", 
+                     model="Helsinki-NLP/opus-mt-ko-en", 
+                     device=device,
+                     model_kwargs={"cache_dir": "/tmp/transformers_cache"})
 
 nlp, dict_docs_spacy = sp.load_spacy_values()
 dataset, list_2000_tokens = dg.load_data()
 
 def translate_korean_to_english(text):
-    # Check if input is Korean using Unicode range
     if any('\u3131' <= char <= '\u318F' or '\uAC00' <= char <= '\uD7A3' for char in text):
         translation = translator(text)[0]['translation_text']
         return translation