modify prompt

Alfred_Agent.py

@@ -62,26 +62,37 @@ tools = [
 chat_with_tools = llm.bind_tools(tools)
 
 #setting up prompt
-ai_message = SystemMessage(content="""You are a helpful assistant tasked with answering questions using a set of tools. 
-Now, I will ask you a question. Report your thoughts, and finish your answer with the following template: 
-FINAL ANSWER:
-[YOUR FINAL ANSWER]. 
-YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, Apply the rules above for each element (number or string), ensure there is exactly one space after each comma.
-Your answer should only start with "FINAL ANSWER: ", then follows with the answer. """)
+ai_message = SystemMessage(content="""You are a helpful assistant tasked with answering questions using a set of tools and reference materials. 
+You may be provided with a reference set of questions and their corresponding answers from a retriever. 
+If the current question is the same as or semantically equivalent to a question in the reference set, or if the reference answer clearly applies to the current question, use that answer as your final answer. 
+Otherwise, reason through the question as needed and report your thoughts before providing the final answer.
+
+Finish your answer with the following template: 
+FINAL ANSWER: [YOUR FINAL ANSWER].
+
+YOUR FINAL ANSWER should be:
+- A number without commas or units (unless explicitly requested),
+- Or a string without articles or abbreviations, with digits written in plain text unless specified otherwise,
+- Or a comma separated list, applying the above rules to each item and ensuring exactly one space after each comma.
+
+If the question is identical or functionally equivalent to a reference question, respond with:
+FINAL ANSWER: [the answer to the reference question].
+""")
+
 
 
 
 # Generate the AgentState and Agent graph
 from langgraph.graph import MessagesState #the same as AgentState
-class AgentState(TypedDict):
-    messages: Annotated[list[AnyMessage], add_messages]
+# class AgentState(TypedDict):
+#     messages: Annotated[list[AnyMessage], add_messages]
 
-def assistant(state: AgentState):
+def assistant(state: MessagesState):
     return {
         "messages": [chat_with_tools.invoke(state["messages"])],
     }
 
-def retriever(state: AgentState):
+def retriever(state: MessagesState):
     """Retriever node"""
     similar_question = vector_search(state["messages"][0].content)
 
@@ -89,13 +100,15 @@ def retriever(state: AgentState):
         example_msg = HumanMessage(
             content=f"Here I provide a similar question and answer for reference: \n\n{similar_question}",
         )
+        print(f"Similar question found: {similar_question}")
         return {"messages": [ai_message] + state["messages"] + [example_msg]}
     else:
         # Handle the case when no similar questions are found
+        print( "No similar question found.")
         return {"messages": [ai_message] + state["messages"]}
 
 ## The graph
-builder = StateGraph(AgentState)
+builder = StateGraph(MessagesState)
 
 
 # Define nodes: these do the work
@@ -115,8 +128,9 @@ builder.add_conditional_edges(
 builder.add_edge("tools", "assistant")
 alfred = builder.compile()
 
-# messages = [HumanMessage(content="Tell me about our guest named 'Dr. Nikola Tesla' and What's the weather in Bangkok.")]
-# response = alfred.invoke({"messages": messages})
+messages = [HumanMessage(content="When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?")]
+#messages = [HumanMessage(content="What the remainder of 30 divided by 7?")]
+response = alfred.invoke({"messages": messages})
+
 
-# print("🎩 Alfred's Response:")
-# print(response['messages'][-1].content)
+print(response['messages'][-1].content)