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app.py

@@ -264,15 +264,15 @@ try:
     from transformers import pipeline
     
     # Initialize the zero-shot classification pipeline
-    classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
-    print("Using facebook/bart-large-mnli for classification")
+    classifier = pipeline("zero-shot-classification", model="facebook/bart-base-mnli")
+    print("Using facebook/bart-base-mnli for classification")
     
-    # 2. Load MPNet model for semantic search
+    # 2. Load MiniLM model for semantic search
     from sentence_transformers import SentenceTransformer, util
     
     # Load the sentence transformer model
-    sentence_model = SentenceTransformer('sentence-transformers/all-mpnet-base-v2')
-    print("Using sentence-transformers/all-mpnet-base-v2 for semantic search")
+    sentence_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+    print("Using sentence-transformers/all-MiniLM-L6-v2 for semantic search")
     
     # Pre-compute embeddings for category descriptions
     category_texts = list(category_descriptions.values())
@@ -378,17 +378,48 @@ def load_deals_from_file():
 # Global variable to store deals data
 deals_cache = None
 
-# Load deals from file on startup
-try:
+# Function to load deals data lazily
+def get_deals_cache():
+    """
+    Load deals data lazily to avoid startup timeout
+    """
+    global deals_cache
+    
+    # If deals are already loaded, return them
+    if deals_cache is not None:
+        return deals_cache
+    
     # Try to load from file
-    deals_cache = load_deals_from_file()
+    try:
+        deals_cache = load_deals_from_file()
+        
+        # If file doesn't exist or is empty, use sample data
+        if deals_cache is None or len(deals_cache) == 0:
+            print("No deals found in local file. Using sample data...")
+            deals_cache = process_deals_data(SAMPLE_DEALS)
+            
+        print(f"Loaded {len(deals_cache) if deals_cache else 0} deals")
+    except Exception as e:
+        print(f"Error loading deals cache: {str(e)}")
+        # Fall back to sample data
+        deals_cache = process_deals_data(SAMPLE_DEALS)
+        print(f"Loaded {len(deals_cache)} sample deals")
     
-    # If file doesn't exist or is empty, use sample data
-    if deals_cache is None or len(deals_cache) == 0:
-        print("No deals found in local file. Using sample data...")
+    return deals_cache
+
+# Load a small subset of deals on startup to avoid timeout
+try:
+    # Load just the first 1000 deals for fast startup
+    if os.path.exists(DEALS_DATA_PATH):
+        with open(DEALS_DATA_PATH, "r") as f:
+            all_deals = json.load(f)
+            # Take just the first 1000 deals for initial loading
+            deals_cache = all_deals[:1000]
+        print(f"Initialized with {len(deals_cache)} deals (subset of {len(all_deals)} total deals)")
+    else:
+        # Fall back to sample data
         deals_cache = process_deals_data(SAMPLE_DEALS)
-        
-    print(f"Initialized with {len(deals_cache) if deals_cache else 0} deals")
+        print(f"Initialized with {len(deals_cache)} sample deals")
 except Exception as e:
     print(f"Error initializing deals cache: {str(e)}")
     # Fall back to sample data