Update agent.py

agent.py

@@ -56,25 +56,33 @@ def build_agent():
     
     tools = [use_wikipedia_tool, use_search_tool]
 
-    system_template = (
+    # system_template = (
+    #     "You are a helpful, friendly, and respectful AI assistant. "
+    #     "Always address the user politely and answer their questions in a positive manner.\n"
+    #     "When reasoning, always use the following format:\n"
+    #     "Thought: [your reasoning here]\n"
+    #     "Action: [the action to take, should be one of [{tool_names}]]\n"
+    #     "Action Input: [the input to the action]\n"
+    #     "If you know the answer without using a tool, respond with:\n"
+    #     "Thought: [your reasoning here]\n"
+    #     "Final Answer: [your answer here]\n"
+    #     "Always ensure your responses are polite, accurate, and helpful."
+    # )
+    # system_prompt = SystemMessage(content=system_template.format(
+    #     tool_names=", ".join([tool.name for tool in tools])
+    # ))
+
+     system_template = (
         "You are a helpful, friendly, and respectful AI assistant. "
         "Always address the user politely and answer their questions in a positive manner.\n"
-        "When reasoning, always use the following format:\n"
-        "Thought: [your reasoning here]\n"
-        "Action: [the action to take, should be one of [{tool_names}]]\n"
-        "Action Input: [the input to the action]\n"
-        "If you know the answer without using a tool, respond with:\n"
-        "Thought: [your reasoning here]\n"
+        "If you know the answer then respond with:\n"
         "Final Answer: [your answer here]\n"
         "Always ensure your responses are polite, accurate, and helpful."
     )
-    system_prompt = SystemMessage(content=system_template.format(
-        tool_names=", ".join([tool.name for tool in tools])
-    ))
 
     def call_model(state: MessagesState):
         """Call the LLM with the given state."""
-        messages = state["messages"]
+        messages = system_template + state["messages"]
         response = llm.invoke(messages)
         return {"messages" : response}