Update app.py

app.py

@@ -19,6 +19,21 @@ from llama_index.indices.vector_store.base import GPTVectorStoreIndex
 from adlfs import AzureBlobFileSystem
 import time 
 
+# Blob storage parameters
+account_name = 'apeazdlkini07s'
+account_key = os.environ['account_key']
+file_system_name = "gpt"
+service_client = DataLakeServiceClient(account_url=f"https://{account_name}.dfs.core.windows.net", credential=account_key)
+file_system_client = service_client.get_file_system_client(file_system_name)
+
+AZURE_ACCOUNT_NAME = account_name
+AZURE_ACCOUNT_KEY = account_key
+
+assert AZURE_ACCOUNT_NAME is not None and AZURE_ACCOUNT_NAME != ""
+
+fs = AzureBlobFileSystem(account_name=AZURE_ACCOUNT_NAME, account_key=AZURE_ACCOUNT_KEY)
+
+
 def construct_index(doc):
 
   ## Define the prompt helper
@@ -51,7 +66,6 @@ def construct_index(doc):
 
   # save index to disk
   index.set_index_id("vector_index")
-  index.storage_context.persist('/gpttest')
 
   return index
 
@@ -77,10 +91,10 @@ def ask_ai(doc, question):
   index = construct_index([Document(text)])
   
   # Save index to Azure blob storage
-  index.storage_context.persist(f'gpttest/{file_name}', fs=fs)
+  index.storage_context.persist(f'gpt/storage_demo/{file_name}', fs=fs)
 
   # Rebuild storage context
-  storage_context = StorageContext.from_defaults(persist_dir=f'gpttest/{file_name}')
+  storage_context = StorageContext.from_defaults(persist_dir=f'gpt/storage_demo/{file_name}', fs=fs)
 
   # Load index
   index = load_index_from_storage(storage_context)