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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>
40 lines
812 B
SCSS
40 lines
812 B
SCSS
.semantic-search__container {
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background: var(--primary-very-low);
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margin: 1rem 0 1rem 0;
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.semantic-search__results {
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display: flex;
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flex-direction: column;
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align-items: baseline;
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.semantic-search {
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&__searching-text {
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display: inline-block;
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margin-left: 3px;
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}
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&__indicator-wave {
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flex: 0 0 auto;
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display: inline-flex;
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}
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&__indicator-dot {
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display: inline-block;
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animation: ai-summary__indicator-wave 1.8s linear infinite;
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&:nth-child(2) {
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animation-delay: -1.6s;
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}
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&:nth-child(3) {
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animation-delay: -1.4s;
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}
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}
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}
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.semantic-search__entries {
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margin-top: 10px;
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}
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.semantic-search__searching {
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margin-left: 5px;
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}
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}
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}
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