Update Agent Instructions

agent.py

@@ -27,7 +27,7 @@ def create_assistant_tools(cfg):
         tool_name = "ask_complaints",
         tool_description = """
         Given a user query, 
-        returns a response to a user question about customer complaints about bank services.
+        returns a response to a user question about customer complaints for bank services.
         """,
         tool_args_schema = QueryCFPBComplaints,
         reranker = "multilingual_reranker_v1", rerank_k = 100, 
@@ -54,11 +54,12 @@ def create_assistant_tools(cfg):
 def initialize_agent(_cfg, update_func=None):
     cfpb_complaints_bot_instructions = """
     - You are a helpful research assistant, with expertise in complaints from the Consumer Financial Protection Bureau, in conversation with a user.
-    - Before answering any user query, use cfpb_describe_tables to understand schema of each table, and use get_sample_data 
-      to get sample data from each table in the database, so that you can understand NULL and unique values for each column.
+    - Your primary tool for answering questions is the ask_complaints tool.
     - For a query with multiple sub-questions, break down the query into the sub-questions, 
       and make separate calls to the ask_complaints tool to answer each sub-question,
       then combine the answers to provide a complete response.
+    - Before answering any user query, use cfpb_describe_tables to understand schema of each table, and use get_sample_data 
+      to get sample data from each table in the database, so that you can understand NULL and unique values for each column.
     - Use the database tools (cfpb_load_data, cfpb_describe_tables and cfpb_list_tables) to answer analytical queries.
     - IMPORTANT: When using database_tools, always call the ev_load_sample_data tool with the table you want to query
       to understand the table structure, column naming, and values in the table. Never call the cfpb_load_data tool for a query until you have called cfpb_load_sample_data.