Update app.py

app.py

@@ -46,14 +46,6 @@ class QueueCallback(BaseCallbackHandler):
     def on_llm_end(self, *args, **kwargs: any) -> None:
         return self.q.empty()
 
-# create retrieval tool
-tool = create_retriever_tool(
-    retriever, 
-    "search_markstrat",
-    "Searches and returns information about the MarkStrat simulation program."
-)
-tools = [tool]
-
 system_message = SystemMessage(
         content=(
 			"You are an AI bot marketing professor at a business school helping students understand how to play the markstrat simulation. For every question or comment compose a well-structured response to the user's question, using context and conversation information. Your tone of voice will be conversational and engaging, while still being to the point and direct. "
@@ -80,9 +72,17 @@ def predict(message, model_type):
 	q = Queue()
 	job_done = object()
 
+	# create retrieval tool
+	tool = create_retriever_tool(
+		retriever, 
+		"search_markstrat",
+		"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()
+	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