update tool calling

agent.py

@@ -59,6 +59,26 @@ def read_message(state: AgentState) -> AgentState:
     # Just pass the messages through to the next node
     return {"messages": messages}
 
+# def tool_message(state: AgentState) -> AgentState:
+#     messages = state["messages"]
+#     prompt = f"""
+#     You are a GAIA question answering expert. 
+#     Your task is to decide whether to use a tool or not.
+#     If you need to use a tool, answer ONLY:
+#         CALL_TOOL: <your tool name>
+#     If you do not need to use a tool, answer ONLY:
+#         NO_TOOL
+#     Here is the question:
+#     {messages}
+#     """
+#     return {"messages": messages}
+#     response = model_with_tools.invoke(prompt)
+#     return {"messages": messages + [response]}
+
+# Augment the LLM with tools
+tools = [web_search]
+tools_by_name = {tool.name: tool for tool in tools}
+model_with_tools = model.bind_tools(tools)
 
 def answer_message(state: AgentState) -> AgentState:
     messages = state["messages"]
@@ -69,6 +89,10 @@ def answer_message(state: AgentState) -> AgentState:
     Do not include any thought process before answering the question, and only response exactly what was being asked of you.
     If you are not able to provide an answer, please state the limitation that you're facing instead.
 
+    You can optionally use a web search tool.
+    if you need web information, answer ONLY:
+        CALL_WEB_SEARCH: <your search query>
+
     Example question: How many hours are there in a day?
     Response: 24
 
@@ -76,11 +100,12 @@ def answer_message(state: AgentState) -> AgentState:
     {messages}
     
     """
-    response = model.invoke(prompt)
+    response = model_with_tools.invoke(prompt)
     # Append the model's answer to the messages list
     return {"messages": messages + [response]}
 
 
+
 def build_graph():
     agent_graph = StateGraph(AgentState)