searchengines-web/MeiliSearch
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Code Issues Releases Wiki Activity

WIP

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- manual embedder
- multi embedders OK
- clippy + tests OK
This commit is contained in:
Louis Dureuil 2023-12-12 23:39:01 +01:00
parent 922a640188
commit 12940d79a9
No known key found for this signature in database
13 changed files with 292 additions and 140 deletions
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60
meilisearch/src/routes/indexes/search.rs
View file

@ -235,38 +235,42 @@ pub async fn embed(
index_scheduler: &IndexScheduler,
index: &milli::Index,
) -> Result<(), ResponseError> {
if let Some(VectorQuery::String(prompt)) = query.vector.take() {
let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
let embedder = index_scheduler.embedders(embedder_configs)?;
match query.vector.take() {
Some(VectorQuery::String(prompt)) => {
let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
let embedder = index_scheduler.embedders(embedder_configs)?;
let embedder_name = if let Some(HybridQuery {
semantic_ratio: _,
embedder: Some(embedder),
}) = &query.hybrid
{
embedder
} else {
"default"
};
let embedder_name =
if let Some(HybridQuery { semantic_ratio: _, embedder: Some(embedder) }) =
&query.hybrid
{
embedder
} else {
"default"
};
let embeddings = embedder
.get(embedder_name)
.ok_or(milli::UserError::InvalidEmbedder(embedder_name.to_owned()))
.map_err(milli::Error::from)?
.0
.embed(vec![prompt])
.await
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?
.pop()
.expect("No vector returned from embedding");
let embeddings = embedder
.get(embedder_name)
.ok_or(milli::UserError::InvalidEmbedder(embedder_name.to_owned()))
.map_err(milli::Error::from)?
.0
.embed(vec![prompt])
.await
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?
.pop()
.expect("No vector returned from embedding");
if embeddings.iter().nth(1).is_some() {
warn!("Ignoring embeddings past the first one in long search query");
query.vector = Some(VectorQuery::Vector(embeddings.iter().next().unwrap().to_vec()));
} else {
query.vector = Some(VectorQuery::Vector(embeddings.into_inner()));
if embeddings.iter().nth(1).is_some() {
warn!("Ignoring embeddings past the first one in long search query");
query.vector =
Some(VectorQuery::Vector(embeddings.iter().next().unwrap().to_vec()));
} else {
query.vector = Some(VectorQuery::Vector(embeddings.into_inner()));
}
}
Some(vector) => query.vector = Some(vector),
None => {}
};
Ok(())
}

21
meilisearch/src/search.rs
View file

@ -13,7 +13,7 @@ use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::deserr_codes::*;
use meilisearch_types::heed::RoTxn;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
use meilisearch_types::milli::score_details::{self, ScoreDetails, ScoringStrategy};
use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, VectorQuery};
use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
use meilisearch_types::{milli, Document};
@ -562,8 +562,17 @@ pub fn perform_search(
insert_geo_distance(sort, &mut document);
}
/// FIXME: remove this or set to value from the score details
let semantic_score = None;
let mut semantic_score = None;
for details in &score {
if let ScoreDetails::Vector(score_details::Vector {
target_vector: _,
value_similarity: Some((_matching_vector, similarity)),
}) = details
{
semantic_score = Some(*similarity);
break;
}
}
let ranking_score =
query.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
@ -648,8 +657,10 @@ pub fn perform_search(
hits: documents,
hits_info,
query: query.q.unwrap_or_default(),
// FIXME: display input vector
vector: None,
vector: match query.vector {
Some(VectorQuery::Vector(vector)) => Some(vector),
_ => None,
},
processing_time_ms: before_search.elapsed().as_millis(),
facet_distribution,
facet_stats,