Update app.py

app.py

@@ -72,6 +72,10 @@ def predict(message, model_type):
 	q = Queue()
 	job_done = object()
 
+    # load existing index
+	vectorsearch = Pinecone.from_existing_index(index_name, embeddings)
+	retriever = vectorsearch.as_retriever()
+    
 	# create retrieval tool
 	tool = create_retriever_tool(
 		retriever, 
@@ -79,10 +83,6 @@ def predict(message, model_type):
 		"Searches and returns information about the MarkStrat simulation program."
 	)
 	tools = [tool]
-
-    # load existing index
-	vectorsearch = Pinecone.from_existing_index(index_name, embeddings)
-	retriever = vectorsearch.as_retriever()
     
 	# conversational retrieval agent component construction - memory, prompt template, agent, agent executor
 	# specifying LLM to use