Help with router query engine

[SarahSohana27]

I want to implement a router query engine in my code. I have written the code so far. But it's throwing the following errors:

ValueError during initialization: Expected one required input key
Error in generating result: 'NoneType' object has no attribute 'achat'

How to fix it?

def initialize_chat_engine():
    vector_query_engine = create_general_component()
    generic_chain = QP(chain=[InputComponent(), vector_query_engine], verbose=True)

    # handles sql generation
    vn_component = create_vn_component()
    # handles final response
    response_component = create_response_component()

    # Set up Query Pipeline as a sequential chain
    vn_chain = QP(
        chain=[InputComponent(), vn_component, response_component],
        verbose=True
    )
    print('vn_chain', vn_chain)

    # vn_chain = QP(
    #     modules={
    #         "input": InputComponent(),
    #         "vn_component": vn_component,
    #         "response_component": response_component,
    #     },
    #     verbose=True,
    # )

    # vn_chain.add_link("input", "vn_component", dest_key="input_str")
    # vn_chain.add_link("vn_component", "response_component", dest_key="response")


    # Step 3: Define Router and Pipelines
    selector = LLMSingleSelector.from_defaults()
    router_component = RouterComponent(
        selector=selector,
        choices = [
            "This tool answers specific questions about the document (not questions that can be answered from the SQL tables)",
            "This tool answers questions from SQL tables by forming a SQL query (not specific questions about the document)",
        ],
        components=[generic_chain, vn_chain],
        verbose=True,
    )

    # Step 4: Create Query Pipeline
    qp = QP(chain=[router_component], verbose=True)
    print('qp', qp)

    # TO-DO: memory
    chat_store = SimpleChatStore()
    memory = ChatMemoryBuffer.from_defaults(
        token_limit=8000, chat_store=chat_store, chat_store_key=uuid.uuid4().hex
    )

    chat_engine = CustomChatEngine(qp, memory)
    print("chat_engine", chat_engine)

    if chat_engine:
        st.session_state.chat_engine = chat_engine
        st.session_state.chat_engine_status = True
    else:
        print("Chat engine not created! Check for errors!")


def custom_query_pipeline():
    if "chat_engine_status" not in st.session_state:
        st.session_state.chat_engine_status = False

    if not st.session_state.chat_engine_status:
        initialize_chat_engine()

this is my custom chat engine class:

class CustomChatEngine(BaseChatEngine):
    def __init__(self, query_pipeline, memory: BaseMemory, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.query_pipeline = query_pipeline
        self._memory = memory
        print(query_pipeline)

    def chat(self, message, chat_history):
        try:
            # Retrieve chat history
            chat_history = self._memory.get()
            # Add the new message to the chat history
            chat_history.append(ChatMessage(role="user", content=message))
            # Process the message with the query pipeline
            response = self.query_pipeline.run(query=message)
            # Add the response to the chat history
            chat_history.append(ChatMessage(role="assistant", content=response))
            # Update the memory with the new chat history
            self._memory.chat_store.set_messages(
                self._memory.chat_store_key, chat_history
            )
            print(response)
            return response
        except Exception as e:
            return "An error occurred while processing your query: {}".format(e)

    def reset(self) -> None:
        # Reset conversation state if applicable
        self._memory.chat_store.set_messages(self._memory.chat_store_key, [])

    async def achat(
        self, message: str, chat_history: Optional[List[ChatMessage]] = None
    ):
        try:
            # Retrieve chat history
            chat_history = self._memory.get()
            # Add the new message to the chat history
            chat_history.append(ChatMessage(role="user", content=message))
            # Process the message with the query pipeline
            chat_response = await self.query_pipeline.arun(query=message)
            # Add the response to the chat history
            chat_history.append(ChatMessage(role="assistant", content=chat_response))
            # Update the memory with the new chat history
            self._memory.chat_store.set_messages(
                self._memory.chat_store_key, chat_history
            )
            print(chat_response)
            return chat_response
        except Exception as e:
            return "An error occurred while processing your query: {}".format(e)

[dosubot[bot]]

To address the errors you're encountering, let's break down the issues and potential solutions:

1. ValueError during initialization: Expected one required input key:

   • This error suggests that one of the components in your query pipeline is missing a required input key. Ensure that each component in your QP chains is correctly configured with the necessary input keys. Check the create_general_component, create_vn_component, and create_response_component functions to ensure they are returning components with the expected input keys.

2. Error in generating result: 'NoneType' object has no attribute 'achat':

   • This error indicates that the achat method is being called on a NoneType object, which means that the chat_engine might not be properly initialized. Ensure that the initialize_chat_engine function successfully creates a CustomChatEngine instance and assigns it to st.session_state.chat_engine. Double-check the logic that sets st.session_state.chat_engine_status to ensure it reflects the actual initialization status of the chat engine.

Here are some steps to help resolve these issues:

• Verify Component Initialization: Ensure that all components (generic_chain, vn_chain, etc.) are correctly initialized with the required input keys. You might need to inspect the create_general_component, create_vn_component, and create_response_component functions to confirm they are returning valid components.

• Check Query Pipeline Configuration: Make sure that the RouterComponent and QP are correctly set up with the necessary components and that the selector is functioning as expected. The choices and components lists should align, with each choice corresponding to a component.

• Debugging Initialization: Add print statements or logging to verify that each step in the initialize_chat_engine function is executed as expected. Ensure that the chat_engine is not None before assigning it to st.session_state.chat_engine.

• Ensure Asynchronous Method Availability: If you're using the achat method, ensure that the CustomChatEngine instance is correctly initialized and that the query_pipeline supports asynchronous execution.

By following these steps, you should be able to identify and resolve the issues causing the errors in your implementation.

To continue talking to Dosu, mention @dosu.

[dosubot[bot]]

The error you're encountering indicates that an attempt is being made to instantiate the BasePromptTemplate class directly. This class is abstract and requires the implementation of several methods: format, format_messages, get_template, and partial_format ^[1].

To resolve this error, ensure that you are using a concrete subclass of BasePromptTemplate that implements these abstract methods. Some existing implementations you can reference include PromptTemplate, ChatPromptTemplate, and SelectorPromptTemplate ^[2]. These classes provide the necessary implementations for the abstract methods and can be used in place of BasePromptTemplate.

To continue talking to Dosu, mention @dosu.

[SarahSohana27]

@dosu I am getting the error 'QueryPipeline' object has no attribute 'query'

    # top-level pipeline

    # qp = QP(chain=[InputComponent(), router_c, router_response()], verbose=True)
    qp = QP(
        modules={
            "router_input": InputComponent(),
            "router_component": router_c,
            "response_component": router_response()
        },
        verbose=True,
    )

    qp.add_link("router_input", "router_component", dest_key="input_str")
    qp.add_link("router_component", "response_component", dest_key="response")

    # chat_engine = CustomChatEngine(qp, memory)
    chat_engine = CondenseQuestionChatEngine.from_defaults(query_engine=qp, memory=memory, verbose= True)
    print("chat_engine", chat_engine)

what should be the fix?

[dosubot[bot]]

To fix the error "'QueryPipeline' object has no attribute 'query'", you should use the run method instead of query. The QueryPipeline class does not have a query attribute. Here's how you can adjust your code:

# Use the run method to execute the query
response = qp.run(query_str="your query here")

Make sure to replace any incorrect usage of query with run in your code ^[1].

To continue talking to Dosu, mention @dosu.

[SarahSohana27]

@dosu how to convert AgentChatResponse(response=str(query_response), sources=[tool_output]) to string response?

[dosubot[bot]]

To convert AgentChatResponse(response=str(query_response), sources=[tool_output]) to a string response, you can use the str() function. The AgentChatResponse class has a __str__ method that returns the response attribute. Here's how you can do it:

agent_chat_response = AgentChatResponse(response=str(query_response), sources=[tool_output])
string_response = str(agent_chat_response)

This will give you the response as a string ^[1].

To continue talking to Dosu, mention @dosu.

[cgthunderstrike]

help