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2c0f535bab
* FEATURE: HyDE-powered semantic search. It relies on the new outlet added on discourse/discourse#23390 to display semantic search results in an unobtrusive way. We'll use a HyDE-backed approach for semantic search, which consists on generating an hypothetical document from a given keywords, which gets transformed into a vector and used in a asymmetric similarity topic search. This PR also reorganizes the internals to have less moving parts, maintaining one hierarchy of DAOish classes for vector-related operations like transformations and querying. Completions and vectors created by HyDE will remain cached on Redis for now, but we could later use Postgres instead. * Missing translation and rate limiting --------- Co-authored-by: Roman Rizzi <rizziromanalejandro@gmail.com>
35 lines
878 B
Ruby
35 lines
878 B
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Embeddings
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module HydeGenerators
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class Llama2 < DiscourseAi::Embeddings::HydeGenerators::Base
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def prompt(search_term)
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<<~TEXT
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[INST] <<SYS>>
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You are a helpful bot
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You create forum posts about a given topic
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<</SYS>>
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Topic: #{search_term}
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[/INST]
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Here is a forum post about the above topic:
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TEXT
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end
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def models
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["Llama2-*-chat-hf"]
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end
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def hypothetical_post_from(query)
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::DiscourseAi::Inference::HuggingFaceTextGeneration.perform!(
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prompt(query),
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SiteSetting.ai_embeddings_semantic_search_hyde_model,
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token_limit: 400,
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).dig(:generated_text)
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end
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end
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end
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end
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end
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