Update app.py

app.py

@@ -26,9 +26,9 @@ SERVICE_ACCOUNT_FILE = r"C:\Users\bhagy\AI\credentials.json"
 csv_file_path = r"C:\Users\bhagy\OneDrive\Desktop\INFOSYS PROJECT\900_products_dataset.csv"
 
 
-storage_path = "chromadb_storage"
-if not os.path.exists(storage_path):
-    os.makedirs(storage_path)
+# storage_path = "chromadb_storage"
+# if not os.path.exists(storage_path):
+#     os.makedirs(storage_path)
 
 # Define Custom Embedding Function
 class CustomEmbeddingFunction:
@@ -47,22 +47,33 @@ class CustomEmbeddingFunction:
 sentiment_pipeline = pipeline("sentiment-analysis")
 
 # Ensure no corrupted ChromaDB storage
+storage_path = r"C:\Users\bhagy\OneDrive\Desktop\INFOSYS PROJECT\chromadb_storage" # Replace with the correct path
+
 try:
+    # Initialize ChromaDB Client
     chroma_client = Client(Settings(persist_directory=storage_path))
-except ValueError:
-    print("ChromaDB storage may be corrupted. Resetting storage...")
+except ValueError as e:
+    print(f"Error: {str(e)}")
+    print("ChromaDB storage may be corrupted or the tenant might be missing. Resetting storage...")
+    
+    # Remove the existing storage path and recreate it
     shutil.rmtree(storage_path, ignore_errors=True)
     os.makedirs(storage_path)
+    
+    # Try reconnecting to ChromaDB after reset
     chroma_client = Client(Settings(persist_directory=storage_path))
 
 # Initialize Embedding Function
 embedding_fn = CustomEmbeddingFunction()
+
+# Define collection name
 collection_name = "crm_data"
 
 # Try fetching collection; create if missing
 try:
     collection = chroma_client.get_collection(collection_name)
-except Exception:
+except Exception as e:
+    print(f"Error fetching collection: {str(e)}. Creating new collection...")
     collection = chroma_client.create_collection(collection_name)
 
 def get_google_sheets_service():