[Question]: low-level response_synthesizer into chat_engine?

[sengiv]

Question Validation

• [X] I have searched both the documentation and discord for an answer.

Question

        response_synthesizer = get_response_synthesizer(response_mode="tree_summarize")

        user_question = kwargs["query"]

        # get response based on nodes as context
        response = response_synthesizer.synthesize(
            f"{user_question}, use only text in context, context is a person's life description",
            nodes=kwargs["input_documents"]
        )

instead use this response_synthesizer with nodes in chat engine?

thanks for any pointers....much appreciated 🙏

[dosubot[bot]]

Hey there, @sengiv! Great to see you back with another interesting question. Hope you're doing well! 🚀

Based on the context you've provided, it seems like you're trying to use the response_synthesizer with nodes in the chat engine. This is indeed possible, given the modular design of the LlamaIndex package.

The response_synthesizer module in the LlamaIndex package includes a variety of synthesizers such as Refine, SimpleSummarize, TreeSummarize, Generation, CompactAndRefine, and Accumulate. These are designed to process and synthesize responses in different ways.

To integrate a response_synthesizer with nodes in the chat engine, you would typically select the appropriate synthesizer class based on your requirements (e.g., summarization, refinement, generation) and instantiate it within the chat engine's processing pipeline where the nodes handle responses. This could involve modifying the chat engine to include a step where the selected synthesizer processes the node's output or responses before they are finalized or sent to the user.

Here's a simplified example of how you might do this:

from llama_index.core.response_synthesizers import get_response_synthesizer

# Instantiate the desired synthesizer
response_synthesizer = get_response_synthesizer(response_mode="tree_summarize")

# Within your chat engine's processing pipeline...
for node in chat_engine.nodes:
    # Process the node's output with the synthesizer
    synthesized_response = response_synthesizer.synthesize(node.output)
    # Use the synthesized response as needed...

Please note that this is a simplified example and the actual implementation may vary based on the specifics of your chat engine and the nodes you're working with.

As for the exact functionality of the response_synthesizer in the LlamaIndex codebase, I wasn't able to find a detailed explanation within the repository. However, based on the name and typical use of such modules, it's likely that the response_synthesizer is responsible for processing and formatting the responses generated by the LlamaIndex system.

I hope this helps! If you have any further questions or need more specific guidance, please don't hesitate to ask.

Sources

• llama-index-core/llama_index/core/response_synthesizers/init.py

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[logan-markewich]

I think I responded on discord, but I'll repeat the convo here

Logan M — Today at 8:38 AM
Chat engines only take strings as input
its meant to chat

vignes — Today at 8:39 AM
ah go it, thanks
it turns out the solution was a custom Retriever, where i can specifiy scored nodes