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implement hyde

Open sandys opened this issue 2 years ago • 2 comments

https://twitter.com/darrenangle/status/1652014961806196745

https://wfhbrian.com/revolutionizing-search-how-hypothetical-document-embeddings-hyde-can-save-time-and-increase-productivity/

https://arxiv.org/pdf/2212.10496.pdf

Semantic search on embeddings is hard to get right. Embedding long documents is a challenge. User queries are a challenge, if a user provides an ambiguous query they’ll get ambiguous matches

LLMs just follow what was in the context and hallucinate answers as a result

I've had a lot of success using HyDE for the query problem.

Essentially, let an LLM generate the query, or even use the hallucinated answer as the query.

if chat, fold the response back into the chat step with a prompt along the lines of "thought: I can use this data to answer the user"

works really well

sandys avatar Apr 29 '23 06:04 sandys

Completed

Saatvik-droid avatar May 10 '23 13:05 Saatvik-droid

HyDE.py.md

Saatvik-droid avatar May 11 '23 05:05 Saatvik-droid