Update app.py

app.py

@@ -103,28 +103,31 @@ def extract_text(file):
             # Add the text from each page to the text string
             text += page.extract_text()
 
-        return text, os.path.basename(file.name)
+        return text
   
-  
-def ask_ai_upload(doc, question):
-  
-  text, file_name = extract_text(doc)
-  index = construct_index([Document(text)])
-  index2 = index
-  index2.storage_context.persist(f'{file_name}')
-  storage_context2 = StorageContext.from_defaults(persist_dir=f'{file_name}')
-
-  # Load index
-  index2 = load_index_from_storage(storage_context2)
-  
-  # Save index to Azure blob storage
-  index.storage_context.persist(f'gpt/storage_demo/{file_name}', fs=fs)
-
-  # Rebuild storage context
-  storage_context = StorageContext.from_defaults(persist_dir=f'gpt/storage_demo/{file_name}', fs=fs)
+def extract_name(file):
 
-  # Load index
-  index = load_index_from_storage(storage_context)
+    return  os.path.basename(file.name)
+        
+def ask_ai_upload(doc, question):
+  file_name = extract_name(doc)
+  try:
+      storage_context = StorageContext.from_defaults(persist_dir=f'gpt/storage_demo/{file_name}', fs=fs)
+      # Load index
+      index = load_index_from_storage(storage_context)
+  except:
+      text = extract_text(doc)
+      index = construct_index([Document(text)])
+    
+      
+      # Save index to Azure blob storage
+      index.storage_context.persist(f'gpt/storage_demo/{file_name}', fs=fs)
+    
+      # Rebuild storage context
+      storage_context = StorageContext.from_defaults(persist_dir=f'gpt/storage_demo/{file_name}', fs=fs)
+    
+      # Load index
+      index = load_index_from_storage(storage_context)
   
   # Define the query & the querying method
   query_engine = index.as_query_engine(optimizer=SentenceEmbeddingOptimizer(percentile_cutoff=0.8))