improved prompt and added llm_nam customization for arg parse

Author: codinglabsong

src/any_chatbot/agent.py

@@ -51,6 +51,12 @@ def parse_args() -> argparse.Namespace:
         default=BASE / "data" / "generated_db" / "csv_excel_to_db.duckdb",
         help="Path to database dir where the sql version of CSV/EXCEL files are stored.",
     )
+    p.add_argument(
+        "--llm_name",
+        type=str,
+        default="gemini-2.5-flash",
+        help="LLM to use for the current session. More capable models perform better. Choose from models provided by 'google_genai'",
+    )
     return p.parse_args()
 
 
@@ -64,7 +70,7 @@ def main() -> None:
     )
 
     # BUILD LLM
-    llm = init_chat_model("gemini-2.0-flash", model_provider="google_genai")
+    llm = init_chat_model(cfg.llm_name, model_provider="google_genai")
 
     # LOAD TOOLS
     retrieve_tool = initialize_retrieve_tool(vector_store)

src/any_chatbot/prompts.py

@@ -1,14 +1,14 @@
 system_message = """
-You are a helpful and intelligent agent designed to conduct semantic search on the uploaded user documents 
-and/or also interact with a SQL database. Your purpose is to answer the user's questions ACCURATELY and HONESTLY.
+You are a agent designed to conduct semantic search on the uploaded user documents 
+and/or also interact with a SQL database.
 
 Whether you know or don't know what files the user is talking about, 
-always first use the 'retrieve' functional call to retrieve what data is available to you across all tags with a prompt that best matches the user's inquiry.
+ALWAYS FIRST use the 'retrieve' functional call to retrieve what data is available to you across all tags.
 If you didn't find sufficient information, rewrite the query and try again
 until you can resonably determine that the needed data is simply not available.
-Base your answers ONLY on the retrieved information thorugh the functional calls you have.
+Base your answers only on the retrieved information thorugh the functional calls you have when answering user questions about the uploaded documents.
 
-If you think the user's prompt could be better answered through SQL querying, 
+Only after doing semantic search, if you think the user's prompt could be better answered through SQL querying, 
 create a syntactically correct {dialect} query to run,
 then look at the results of the query and return the answer. Unless the user
 specifies a specific number of examples they wish to obtain, always limit your