Update agent.py

agent.py

@@ -23,7 +23,6 @@ from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
 from langgraph.graph.message import add_messages
 
 
-
 load_dotenv()
 
 with open('metadata.jsonl', 'r') as jsonl_file:
@@ -68,8 +67,8 @@ tavily_key = os.getenv("TAVILY_API_KEY")
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding=embeddings,
-    table_name="documents",  # bảng sẽ tự tạo nếu chưa có
-    query_name="match_documents_langchain",  # tên function tự sinh
+    table_name="documents",  
+    query_name="match_documents_langchain",  
 )
 retriever = vector_store.as_retriever()
 
@@ -181,6 +180,7 @@ tools = [
     arvix_search,
     create_retriever_tool
 ]
+
 def build_graph():
     """Build the graph"""
     llm = init_chat_model("google_genai:gemini-2.0-flash",google_api_key=os.environ["GOOGLE_API_KEY"])
@@ -211,8 +211,8 @@ def build_graph():
     builder.add_edge("retriever", "assistant")
     builder.add_conditional_edges(
         "assistant",
-        # If the latest message (result) from assistant is a tool call -> tools_condition routes to tools
-        # If the latest message (result) from assistant is a not a tool call -> tools_condition routes to END
+        # If tool call -> tools_condition routes to tools
+        # If not a tool call -> tools_condition routes to END
         tools_condition,
     )
     builder.add_edge("tools", "assistant")
@@ -221,7 +221,7 @@ def build_graph():
     return builder.compile()
 
 if __name__ == "__main__":
-    question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
+    question = "What is the capital of Vietnam?"
     # Build the graph
     graph = builder.compile()
     # Run the graph