Refine answer_message function in agent.py to improve response generation. Updated prompt structure to guide the model in providing concise answers without thought processes, ensuring clarity in responses.

agent.py

@@ -32,10 +32,23 @@ def read_message(state: AgentState) -> AgentState:
 
 def answer_message(state: AgentState) -> AgentState:
     messages = state["messages"]
-    # Invoke the chat model with the conversation so far
-    response = model.invoke(messages)
+    prompt = f"""
+    You are a GAIA question answering expert. 
+    Your task is to provide an answer to a question. 
+    Think carefully before answering the question. 
+    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.
+
+    Example question: How many hours are there in a day?
+    Response: 24
+
+    Here is the question:
+    {messages}
+    
+    """
+    response = model.invoke(prompt)
     # Append the model's answer to the messages list
-    return {"messages": messages + [response]}
+    return {"messages": prompt + [response]}
 
 
 def build_graph():