update app.py

app.py

@@ -1,28 +1,21 @@
+import os
 from flask import Flask, request, render_template, jsonify
 import re
-import os
 import nltk
 import torch
 from pathlib import Path
-
-# Define the device if using GPU
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-from transformers import pipeline
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
 from nltk.tokenize import word_tokenize
 from nltk.stem import WordNetLemmatizer
 
-# nltk.download('punkt')
-# nltk.download('wordnet')
-# # Ensure NLTK data is downloaded
-# nltk.download('punkt', download_dir=Path('/app/nltk_data'))
-# nltk.download('wordnet', download_dir=Path('/app/nltk_data'))
 # Ensure NLTK uses the correct data path
 nltk.data.path.append(os.getenv('NLTK_DATA'))
 
 app = Flask(__name__)
 
+# Ensure the Transformers cache directory is set correctly
+os.environ['TRANSFORMERS_CACHE'] = os.getenv('TRANSFORMERS_CACHE')
+
 tokenizer = AutoTokenizer.from_pretrained(Path("summary/tokenizer"))
 model_name = "summary/pegasus-samsum-model"
 
@@ -86,5 +79,4 @@ def index():
     return render_template('index.html')
 
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', debug=True, port=7860) # This is Host Port
-
+    app.run(host='0.0.0.0', debug=True, port=7860)