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In ConveraationalRetrievalQAChain, click the Additional Parameters, from there you can select stuff, map reduce type |
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Random Thought: I guess this process of iterating over each part of a document would be similar to the creation hypothetical document embeddings as well in that the LLM must interact with all available data, but not within the same completion. |
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oh got it, you are trying to use summarization chain with map-reduce, instead of a conversational retrieval qa chain? for now we still haven't integrated into flowise yet, but might be a good addition - https://js.langchain.com/docs/modules/chains/popular/summarize |
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@djpecot Do you solved this question? |
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Howdy! Looking to start using this tool in addition to Langchain for quick prototyping :)
What would be the best practice to implement a map-reduce style summarization of an entire document (like in Langchain)? Is there a best practice or way to perform any kind of custom summarization task on a document that exceeds the token limit for a single prompt? I browsed the docs, checked the UI, and checked issues and discussions here without finding anything.
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