From 6ebb6b55a64b266bfad68b8a76ee5ce00435b2d0 Mon Sep 17 00:00:00 2001 From: Louis Dureuil Date: Thu, 28 Mar 2024 11:50:53 +0100 Subject: [PATCH] Lazily embed, don't fail hybrid search on embedding failure --- .../src/routes/indexes/facet_search.rs | 4 +- meilisearch/src/routes/indexes/search.rs | 119 ++++++--------- meilisearch/src/routes/multi_search.rs | 8 +- meilisearch/src/search.rs | 141 +++++++++++++----- milli/src/index.rs | 8 - milli/src/lib.rs | 2 +- milli/src/search/facet/search.rs | 12 +- milli/src/search/hybrid.rs | 37 +++-- milli/src/search/mod.rs | 93 +++++------- milli/src/search/new/mod.rs | 10 +- milli/src/search/new/vector_sort.rs | 6 +- 11 files changed, 237 insertions(+), 203 deletions(-) diff --git a/meilisearch/src/routes/indexes/facet_search.rs b/meilisearch/src/routes/indexes/facet_search.rs index 272b8156f..56880a472 100644 --- a/meilisearch/src/routes/indexes/facet_search.rs +++ b/meilisearch/src/routes/indexes/facet_search.rs @@ -12,6 +12,7 @@ use tracing::debug; use crate::analytics::{Analytics, FacetSearchAggregator}; use crate::extractors::authentication::policies::*; use crate::extractors::authentication::GuardedData; +use crate::routes::indexes::search::search_kind; use crate::search::{ add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, SearchQuery, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, @@ -73,9 +74,10 @@ pub async fn search( let index = index_scheduler.index(&index_uid)?; let features = index_scheduler.features(); + let search_kind = search_kind(&search_query, &index_scheduler, &index)?; let _permit = search_queue.try_get_search_permit().await?; let search_result = tokio::task::spawn_blocking(move || { - perform_facet_search(&index, search_query, facet_query, facet_name, features) + perform_facet_search(&index, search_query, facet_query, facet_name, features, search_kind) }) .await?; diff --git a/meilisearch/src/routes/indexes/search.rs b/meilisearch/src/routes/indexes/search.rs index f16a6c4df..a5fe3c5d6 100644 --- a/meilisearch/src/routes/indexes/search.rs +++ b/meilisearch/src/routes/indexes/search.rs @@ -8,19 +8,19 @@ use meilisearch_types::error::deserr_codes::*; use meilisearch_types::error::ResponseError; use meilisearch_types::index_uid::IndexUid; use meilisearch_types::milli; -use meilisearch_types::milli::vector::DistributionShift; use meilisearch_types::serde_cs::vec::CS; use serde_json::Value; -use tracing::{debug, warn}; +use tracing::debug; use crate::analytics::{Analytics, SearchAggregator}; +use crate::error::MeilisearchHttpError; use crate::extractors::authentication::policies::*; use crate::extractors::authentication::GuardedData; use crate::extractors::sequential_extractor::SeqHandler; use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS; use crate::search::{ - add_search_rules, perform_search, HybridQuery, MatchingStrategy, SearchQuery, SemanticRatio, - DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, + add_search_rules, perform_search, HybridQuery, MatchingStrategy, SearchKind, SearchQuery, + SemanticRatio, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO, }; use crate::search_queue::SearchQueue; @@ -204,11 +204,11 @@ pub async fn search_with_url_query( let index = index_scheduler.index(&index_uid)?; let features = index_scheduler.features(); - let distribution = embed(&mut query, index_scheduler.get_ref(), &index)?; + let search_kind = search_kind(&query, index_scheduler.get_ref(), &index)?; let _permit = search_queue.try_get_search_permit().await?; let search_result = - tokio::task::spawn_blocking(move || perform_search(&index, query, features, distribution)) + tokio::task::spawn_blocking(move || perform_search(&index, query, features, search_kind)) .await?; if let Ok(ref search_result) = search_result { aggregate.succeed(search_result); @@ -245,11 +245,11 @@ pub async fn search_with_post( let features = index_scheduler.features(); - let distribution = embed(&mut query, index_scheduler.get_ref(), &index)?; + let search_kind = search_kind(&query, index_scheduler.get_ref(), &index)?; let _permit = search_queue.try_get_search_permit().await?; let search_result = - tokio::task::spawn_blocking(move || perform_search(&index, query, features, distribution)) + tokio::task::spawn_blocking(move || perform_search(&index, query, features, search_kind)) .await?; if let Ok(ref search_result) = search_result { aggregate.succeed(search_result); @@ -265,76 +265,49 @@ pub async fn search_with_post( Ok(HttpResponse::Ok().json(search_result)) } -pub fn embed( - query: &mut SearchQuery, +pub fn search_kind( + query: &SearchQuery, index_scheduler: &IndexScheduler, index: &milli::Index, -) -> Result, ResponseError> { - match (&query.hybrid, &query.vector, &query.q) { - (Some(HybridQuery { semantic_ratio: _, embedder }), None, Some(q)) - if !q.trim().is_empty() => - { - let embedder_configs = index.embedding_configs(&index.read_txn()?)?; - let embedders = index_scheduler.embedders(embedder_configs)?; - - let embedder = if let Some(embedder_name) = embedder { - embedders.get(embedder_name) - } else { - embedders.get_default() - }; - - let embedder = embedder - .ok_or(milli::UserError::InvalidEmbedder("default".to_owned())) - .map_err(milli::Error::from)? - .0; - - let distribution = embedder.distribution(); - - let embeddings = embedder - .embed(vec![q.to_owned()]) - .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(embeddings.iter().next().unwrap().to_vec()); - } else { - query.vector = Some(embeddings.into_inner()); - } - Ok(distribution) +) -> Result { + // regardless of anything, always do a semantic search when we don't have a vector and the query is whitespace or missing + if query.vector.is_none() { + match &query.q { + Some(q) if q.trim().is_empty() => return Ok(SearchKind::KeywordOnly), + None => return Ok(SearchKind::KeywordOnly), + _ => {} } - (Some(hybrid), vector, _) => { - let embedder_configs = index.embedding_configs(&index.read_txn()?)?; - let embedders = index_scheduler.embedders(embedder_configs)?; + } - let embedder = if let Some(embedder_name) = &hybrid.embedder { - embedders.get(embedder_name) - } else { - embedders.get_default() - }; - - let embedder = embedder - .ok_or(milli::UserError::InvalidEmbedder("default".to_owned())) - .map_err(milli::Error::from)? - .0; - - if let Some(vector) = vector { - if vector.len() != embedder.dimensions() { - return Err(meilisearch_types::milli::Error::UserError( - meilisearch_types::milli::UserError::InvalidVectorDimensions { - expected: embedder.dimensions(), - found: vector.len(), - }, - ) - .into()); - } - } - - Ok(embedder.distribution()) + match &query.hybrid { + Some(HybridQuery { semantic_ratio, embedder }) if **semantic_ratio == 1.0 => { + Ok(SearchKind::semantic( + index_scheduler, + index, + embedder.as_deref(), + query.vector.as_ref().map(Vec::len), + )?) } - _ => Ok(None), + Some(HybridQuery { semantic_ratio, embedder: _ }) if **semantic_ratio == 0.0 => { + Ok(SearchKind::KeywordOnly) + } + Some(HybridQuery { semantic_ratio, embedder }) => Ok(SearchKind::hybrid( + index_scheduler, + index, + embedder.as_deref(), + **semantic_ratio, + query.vector.as_ref().map(Vec::len), + )?), + None => match (query.q.as_deref(), query.vector.as_deref()) { + (_query, None) => Ok(SearchKind::KeywordOnly), + (None, Some(_vector)) => Ok(SearchKind::semantic( + index_scheduler, + index, + None, + query.vector.as_ref().map(Vec::len), + )?), + (Some(_), Some(_)) => Err(MeilisearchHttpError::MissingSearchHybrid.into()), + }, } } diff --git a/meilisearch/src/routes/multi_search.rs b/meilisearch/src/routes/multi_search.rs index b2055fb07..04cd3f637 100644 --- a/meilisearch/src/routes/multi_search.rs +++ b/meilisearch/src/routes/multi_search.rs @@ -13,7 +13,7 @@ use crate::analytics::{Analytics, MultiSearchAggregator}; use crate::extractors::authentication::policies::ActionPolicy; use crate::extractors::authentication::{AuthenticationError, GuardedData}; use crate::extractors::sequential_extractor::SeqHandler; -use crate::routes::indexes::search::embed; +use crate::routes::indexes::search::search_kind; use crate::search::{ add_search_rules, perform_search, SearchQueryWithIndex, SearchResultWithIndex, }; @@ -81,11 +81,11 @@ pub async fn multi_search_with_post( }) .with_index(query_index)?; - let distribution = - embed(&mut query, index_scheduler.get_ref(), &index).with_index(query_index)?; + let search_kind = + search_kind(&query, index_scheduler.get_ref(), &index).with_index(query_index)?; let search_result = tokio::task::spawn_blocking(move || { - perform_search(&index, query, features, distribution) + perform_search(&index, query, features, search_kind) }) .await .with_index(query_index)?; diff --git a/meilisearch/src/search.rs b/meilisearch/src/search.rs index a1aa37779..2a22cb2ce 100644 --- a/meilisearch/src/search.rs +++ b/meilisearch/src/search.rs @@ -1,6 +1,7 @@ use std::cmp::min; use std::collections::{BTreeMap, BTreeSet, HashSet}; use std::str::FromStr; +use std::sync::Arc; use std::time::{Duration, Instant}; use deserr::Deserr; @@ -10,10 +11,11 @@ use indexmap::IndexMap; use meilisearch_auth::IndexSearchRules; use meilisearch_types::deserr::DeserrJsonError; use meilisearch_types::error::deserr_codes::*; +use meilisearch_types::error::ResponseError; use meilisearch_types::heed::RoTxn; use meilisearch_types::index_uid::IndexUid; use meilisearch_types::milli::score_details::{self, ScoreDetails, ScoringStrategy}; -use meilisearch_types::milli::vector::DistributionShift; +use meilisearch_types::milli::vector::Embedder; use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, TimeBudget}; use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS; use meilisearch_types::{milli, Document}; @@ -90,13 +92,75 @@ pub struct SearchQuery { #[derive(Debug, Clone, Default, PartialEq, Deserr)] #[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)] pub struct HybridQuery { - /// TODO validate that sementic ratio is between 0.0 and 1,0 #[deserr(default, error = DeserrJsonError, default)] pub semantic_ratio: SemanticRatio, #[deserr(default, error = DeserrJsonError, default)] pub embedder: Option, } +pub enum SearchKind { + KeywordOnly, + SemanticOnly { embedder_name: String, embedder: Arc }, + Hybrid { embedder_name: String, embedder: Arc, semantic_ratio: f32 }, +} +impl SearchKind { + pub(crate) fn semantic( + index_scheduler: &index_scheduler::IndexScheduler, + index: &Index, + embedder_name: Option<&str>, + vector_len: Option, + ) -> Result { + let (embedder_name, embedder) = + Self::embedder(index_scheduler, index, embedder_name, vector_len)?; + Ok(Self::SemanticOnly { embedder_name, embedder }) + } + + pub(crate) fn hybrid( + index_scheduler: &index_scheduler::IndexScheduler, + index: &Index, + embedder_name: Option<&str>, + semantic_ratio: f32, + vector_len: Option, + ) -> Result { + let (embedder_name, embedder) = + Self::embedder(index_scheduler, index, embedder_name, vector_len)?; + Ok(Self::Hybrid { embedder_name, embedder, semantic_ratio }) + } + + fn embedder( + index_scheduler: &index_scheduler::IndexScheduler, + index: &Index, + embedder_name: Option<&str>, + vector_len: Option, + ) -> Result<(String, Arc), ResponseError> { + let embedder_configs = index.embedding_configs(&index.read_txn()?)?; + let embedders = index_scheduler.embedders(embedder_configs)?; + + let embedder_name = embedder_name.unwrap_or_else(|| embedders.get_default_embedder_name()); + + let embedder = embedders.get(embedder_name); + + let embedder = embedder + .ok_or(milli::UserError::InvalidEmbedder(embedder_name.to_owned())) + .map_err(milli::Error::from)? + .0; + + if let Some(vector_len) = vector_len { + if vector_len != embedder.dimensions() { + return Err(meilisearch_types::milli::Error::UserError( + meilisearch_types::milli::UserError::InvalidVectorDimensions { + expected: embedder.dimensions(), + found: vector_len, + }, + ) + .into()); + } + } + + Ok((embedder_name.to_owned(), embedder)) + } +} + #[derive(Debug, Clone, Copy, PartialEq, Deserr)] #[deserr(try_from(f32) = TryFrom::try_from -> InvalidSearchSemanticRatio)] pub struct SemanticRatio(f32); @@ -385,7 +449,7 @@ fn prepare_search<'t>( rtxn: &'t RoTxn, query: &'t SearchQuery, features: RoFeatures, - distribution: Option, + search_kind: &SearchKind, time_budget: TimeBudget, ) -> Result<(milli::Search<'t>, bool, usize, usize), MeilisearchHttpError> { let mut search = index.search(rtxn); @@ -399,32 +463,30 @@ fn prepare_search<'t>( features.check_vector("Passing `hybrid` as a query parameter")?; } - if query.hybrid.is_none() && query.q.is_some() && query.vector.is_some() { - return Err(MeilisearchHttpError::MissingSearchHybrid); - } - - search.distribution_shift(distribution); - - if let Some(ref vector) = query.vector { - match &query.hybrid { - // If semantic ratio is 0.0, only the query search will impact the search results, - // skip the vector - Some(hybrid) if *hybrid.semantic_ratio == 0.0 => (), - _otherwise => { - search.vector(vector.clone()); - } - } - } - - if let Some(ref q) = query.q { - match &query.hybrid { - // If semantic ratio is 1.0, only the vector search will impact the search results, - // skip the query - Some(hybrid) if *hybrid.semantic_ratio == 1.0 => (), - _otherwise => { + match search_kind { + SearchKind::KeywordOnly => { + if let Some(q) = &query.q { search.query(q); } } + SearchKind::SemanticOnly { embedder_name, embedder } => { + let vector = match query.vector.clone() { + Some(vector) => vector, + None => embedder + .embed_one(query.q.clone().unwrap()) + .map_err(milli::vector::Error::from) + .map_err(milli::Error::from)?, + }; + + search.semantic(embedder_name.clone(), embedder.clone(), Some(vector)); + } + SearchKind::Hybrid { embedder_name, embedder, semantic_ratio: _ } => { + if let Some(q) = &query.q { + search.query(q); + } + // will be embedded in hybrid search if necessary + search.semantic(embedder_name.clone(), embedder.clone(), query.vector.clone()); + } } if let Some(ref searchable) = query.attributes_to_search_on { @@ -447,10 +509,6 @@ fn prepare_search<'t>( ScoringStrategy::Skip }); - if let Some(HybridQuery { embedder: Some(embedder), .. }) = &query.hybrid { - search.embedder_name(embedder); - } - // compute the offset on the limit depending on the pagination mode. let (offset, limit) = if is_finite_pagination { let limit = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT); @@ -494,7 +552,7 @@ pub fn perform_search( index: &Index, query: SearchQuery, features: RoFeatures, - distribution: Option, + search_kind: SearchKind, ) -> Result { let before_search = Instant::now(); let rtxn = index.read_txn()?; @@ -504,7 +562,7 @@ pub fn perform_search( }; let (search, is_finite_pagination, max_total_hits, offset) = - prepare_search(index, &rtxn, &query, features, distribution, time_budget)?; + prepare_search(index, &rtxn, &query, features, &search_kind, time_budget)?; let milli::SearchResult { documents_ids, @@ -514,12 +572,9 @@ pub fn perform_search( degraded, used_negative_operator, .. - } = match &query.hybrid { - Some(hybrid) => match *hybrid.semantic_ratio { - ratio if ratio == 0.0 || ratio == 1.0 => search.execute()?, - ratio => search.execute_hybrid(ratio)?, - }, - None => search.execute()?, + } = match &search_kind { + SearchKind::KeywordOnly | SearchKind::SemanticOnly { .. } => search.execute()?, + SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?, }; let fields_ids_map = index.fields_ids_map(&rtxn).unwrap(); @@ -726,6 +781,7 @@ pub fn perform_facet_search( facet_query: Option, facet_name: String, features: RoFeatures, + search_kind: SearchKind, ) -> Result { let before_search = Instant::now(); let rtxn = index.read_txn()?; @@ -735,9 +791,12 @@ pub fn perform_facet_search( }; let (search, _, _, _) = - prepare_search(index, &rtxn, &search_query, features, None, time_budget)?; - let mut facet_search = - SearchForFacetValues::new(facet_name, search, search_query.hybrid.is_some()); + prepare_search(index, &rtxn, &search_query, features, &search_kind, time_budget)?; + let mut facet_search = SearchForFacetValues::new( + facet_name, + search, + matches!(search_kind, SearchKind::Hybrid { .. }), + ); if let Some(facet_query) = &facet_query { facet_search.query(facet_query); } diff --git a/milli/src/index.rs b/milli/src/index.rs index 80e524fb1..db31c953a 100644 --- a/milli/src/index.rs +++ b/milli/src/index.rs @@ -1499,14 +1499,6 @@ impl Index { .unwrap_or_default()) } - pub fn default_embedding_name(&self, rtxn: &RoTxn<'_>) -> Result { - let configs = self.embedding_configs(rtxn)?; - Ok(match configs.as_slice() { - [(ref first_name, _)] => first_name.clone(), - _ => "default".to_owned(), - }) - } - pub(crate) fn put_search_cutoff(&self, wtxn: &mut RwTxn<'_>, cutoff: u64) -> heed::Result<()> { self.main.remap_types::().put(wtxn, main_key::SEARCH_CUTOFF, &cutoff) } diff --git a/milli/src/lib.rs b/milli/src/lib.rs index df44ca127..22816787b 100644 --- a/milli/src/lib.rs +++ b/milli/src/lib.rs @@ -61,7 +61,7 @@ pub use self::index::Index; pub use self::search::facet::{FacetValueHit, SearchForFacetValues}; pub use self::search::{ FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy, - Search, SearchResult, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET, + Search, SearchResult, SemanticSearch, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET, }; pub type Result = std::result::Result; diff --git a/milli/src/search/facet/search.rs b/milli/src/search/facet/search.rs index 0251d6b8d..a6756a7af 100644 --- a/milli/src/search/facet/search.rs +++ b/milli/src/search/facet/search.rs @@ -92,9 +92,15 @@ impl<'a> SearchForFacetValues<'a> { None => return Ok(Vec::new()), }; - let search_candidates = self - .search_query - .execute_for_candidates(self.is_hybrid || self.search_query.vector.is_some())?; + let search_candidates = self.search_query.execute_for_candidates( + self.is_hybrid + || self + .search_query + .semantic + .as_ref() + .and_then(|semantic| semantic.vector.as_ref()) + .is_some(), + )?; let mut results = match index.sort_facet_values_by(rtxn)?.get(&self.facet) { OrderBy::Lexicographic => ValuesCollection::by_lexicographic(self.max_values), diff --git a/milli/src/search/hybrid.rs b/milli/src/search/hybrid.rs index 2a6d9f7a5..e45652206 100644 --- a/milli/src/search/hybrid.rs +++ b/milli/src/search/hybrid.rs @@ -4,6 +4,7 @@ use itertools::Itertools; use roaring::RoaringBitmap; use crate::score_details::{ScoreDetails, ScoreValue, ScoringStrategy}; +use crate::search::SemanticSearch; use crate::{MatchingWords, Result, Search, SearchResult}; struct ScoreWithRatioResult { @@ -126,7 +127,6 @@ impl<'a> Search<'a> { // create separate keyword and semantic searches let mut search = Search { query: self.query.clone(), - vector: self.vector.clone(), filter: self.filter.clone(), offset: 0, limit: self.limit + self.offset, @@ -139,26 +139,41 @@ impl<'a> Search<'a> { exhaustive_number_hits: self.exhaustive_number_hits, rtxn: self.rtxn, index: self.index, - distribution_shift: self.distribution_shift, - embedder_name: self.embedder_name.clone(), + semantic: self.semantic.clone(), time_budget: self.time_budget.clone(), }; - let vector_query = search.vector.take(); + let semantic = search.semantic.take(); let keyword_results = search.execute()?; - // skip semantic search if we don't have a vector query (placeholder search) - let Some(vector_query) = vector_query else { - return Ok(keyword_results); - }; - // completely skip semantic search if the results of the keyword search are good enough if self.results_good_enough(&keyword_results, semantic_ratio) { return Ok(keyword_results); } - search.vector = Some(vector_query); - search.query = None; + // no vector search against placeholder search + let Some(query) = search.query.take() else { return Ok(keyword_results) }; + // no embedder, no semantic search + let Some(SemanticSearch { vector, embedder_name, embedder }) = semantic else { + return Ok(keyword_results); + }; + + let vector_query = match vector { + Some(vector_query) => vector_query, + None => { + // attempt to embed the vector + match embedder.embed_one(query) { + Ok(embedding) => embedding, + Err(error) => { + tracing::error!(error=%error, "Embedding failed"); + return Ok(keyword_results); + } + } + } + }; + + search.semantic = + Some(SemanticSearch { vector: Some(vector_query), embedder_name, embedder }); // TODO: would be better to have two distinct functions at this point let vector_results = search.execute()?; diff --git a/milli/src/search/mod.rs b/milli/src/search/mod.rs index 3c709a647..bab67e6bd 100644 --- a/milli/src/search/mod.rs +++ b/milli/src/search/mod.rs @@ -1,4 +1,5 @@ use std::fmt; +use std::sync::Arc; use levenshtein_automata::{LevenshteinAutomatonBuilder as LevBuilder, DFA}; use once_cell::sync::Lazy; @@ -8,7 +9,7 @@ pub use self::facet::{FacetDistribution, Filter, OrderBy, DEFAULT_VALUES_PER_FAC pub use self::new::matches::{FormatOptions, MatchBounds, MatcherBuilder, MatchingWords}; use self::new::{execute_vector_search, PartialSearchResult}; use crate::score_details::{ScoreDetails, ScoringStrategy}; -use crate::vector::DistributionShift; +use crate::vector::Embedder; use crate::{ execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, Index, Result, SearchContext, TimeBudget, @@ -24,9 +25,15 @@ mod fst_utils; pub mod hybrid; pub mod new; +#[derive(Debug, Clone)] +pub struct SemanticSearch { + vector: Option>, + embedder_name: String, + embedder: Arc, +} + pub struct Search<'a> { query: Option, - vector: Option>, // this should be linked to the String in the query filter: Option>, offset: usize, @@ -38,12 +45,9 @@ pub struct Search<'a> { scoring_strategy: ScoringStrategy, words_limit: usize, exhaustive_number_hits: bool, - /// TODO: Add semantic ratio or pass it directly to execute_hybrid() rtxn: &'a heed::RoTxn<'a>, index: &'a Index, - distribution_shift: Option, - embedder_name: Option, - + semantic: Option, time_budget: TimeBudget, } @@ -51,7 +55,6 @@ impl<'a> Search<'a> { pub fn new(rtxn: &'a heed::RoTxn, index: &'a Index) -> Search<'a> { Search { query: None, - vector: None, filter: None, offset: 0, limit: 20, @@ -64,8 +67,7 @@ impl<'a> Search<'a> { words_limit: 10, rtxn, index, - distribution_shift: None, - embedder_name: None, + semantic: None, time_budget: TimeBudget::max(), } } @@ -75,8 +77,13 @@ impl<'a> Search<'a> { self } - pub fn vector(&mut self, vector: Vec) -> &mut Search<'a> { - self.vector = Some(vector); + pub fn semantic( + &mut self, + embedder_name: String, + embedder: Arc, + vector: Option>, + ) -> &mut Search<'a> { + self.semantic = Some(SemanticSearch { embedder_name, embedder, vector }); self } @@ -133,19 +140,6 @@ impl<'a> Search<'a> { self } - pub fn distribution_shift( - &mut self, - distribution_shift: Option, - ) -> &mut Search<'a> { - self.distribution_shift = distribution_shift; - self - } - - pub fn embedder_name(&mut self, embedder_name: impl Into) -> &mut Search<'a> { - self.embedder_name = Some(embedder_name.into()); - self - } - pub fn time_budget(&mut self, time_budget: TimeBudget) -> &mut Search<'a> { self.time_budget = time_budget; self @@ -161,15 +155,6 @@ impl<'a> Search<'a> { } pub fn execute(&self) -> Result { - let embedder_name; - let embedder_name = match &self.embedder_name { - Some(embedder_name) => embedder_name, - None => { - embedder_name = self.index.default_embedding_name(self.rtxn)?; - &embedder_name - } - }; - let mut ctx = SearchContext::new(self.index, self.rtxn); if let Some(searchable_attributes) = self.searchable_attributes { @@ -184,21 +169,23 @@ impl<'a> Search<'a> { document_scores, degraded, used_negative_operator, - } = match self.vector.as_ref() { - Some(vector) => execute_vector_search( - &mut ctx, - vector, - self.scoring_strategy, - universe, - &self.sort_criteria, - self.geo_strategy, - self.offset, - self.limit, - self.distribution_shift, - embedder_name, - self.time_budget.clone(), - )?, - None => execute_search( + } = match self.semantic.as_ref() { + Some(SemanticSearch { vector: Some(vector), embedder_name, embedder }) => { + execute_vector_search( + &mut ctx, + vector, + self.scoring_strategy, + universe, + &self.sort_criteria, + self.geo_strategy, + self.offset, + self.limit, + embedder_name, + embedder, + self.time_budget.clone(), + )? + } + _ => execute_search( &mut ctx, self.query.as_deref(), self.terms_matching_strategy, @@ -237,7 +224,6 @@ impl fmt::Debug for Search<'_> { fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result { let Search { query, - vector: _, filter, offset, limit, @@ -250,8 +236,7 @@ impl fmt::Debug for Search<'_> { exhaustive_number_hits, rtxn: _, index: _, - distribution_shift, - embedder_name, + semantic, time_budget, } = self; f.debug_struct("Search") @@ -266,8 +251,10 @@ impl fmt::Debug for Search<'_> { .field("scoring_strategy", scoring_strategy) .field("exhaustive_number_hits", exhaustive_number_hits) .field("words_limit", words_limit) - .field("distribution_shift", distribution_shift) - .field("embedder_name", embedder_name) + .field( + "semantic.embedder_name", + &semantic.as_ref().map(|semantic| &semantic.embedder_name), + ) .field("time_budget", time_budget) .finish() } diff --git a/milli/src/search/new/mod.rs b/milli/src/search/new/mod.rs index 1f0ae7b29..617068ef8 100644 --- a/milli/src/search/new/mod.rs +++ b/milli/src/search/new/mod.rs @@ -52,7 +52,7 @@ use self::vector_sort::VectorSort; use crate::error::FieldIdMapMissingEntry; use crate::score_details::{ScoreDetails, ScoringStrategy}; use crate::search::new::distinct::apply_distinct_rule; -use crate::vector::DistributionShift; +use crate::vector::Embedder; use crate::{ AscDesc, DocumentId, FieldId, Filter, Index, Member, Result, TermsMatchingStrategy, TimeBudget, UserError, @@ -298,8 +298,8 @@ fn get_ranking_rules_for_vector<'ctx>( geo_strategy: geo_sort::Strategy, limit_plus_offset: usize, target: &[f32], - distribution_shift: Option, embedder_name: &str, + embedder: &Embedder, ) -> Result>> { // query graph search @@ -325,8 +325,8 @@ fn get_ranking_rules_for_vector<'ctx>( target.to_vec(), vector_candidates, limit_plus_offset, - distribution_shift, embedder_name, + embedder, )?; ranking_rules.push(Box::new(vector_sort)); vector = true; @@ -548,8 +548,8 @@ pub fn execute_vector_search( geo_strategy: geo_sort::Strategy, from: usize, length: usize, - distribution_shift: Option, embedder_name: &str, + embedder: &Embedder, time_budget: TimeBudget, ) -> Result { check_sort_criteria(ctx, sort_criteria.as_ref())?; @@ -562,8 +562,8 @@ pub fn execute_vector_search( geo_strategy, from + length, vector, - distribution_shift, embedder_name, + embedder, )?; let mut placeholder_search_logger = logger::DefaultSearchLogger; diff --git a/milli/src/search/new/vector_sort.rs b/milli/src/search/new/vector_sort.rs index 476477218..de272ed47 100644 --- a/milli/src/search/new/vector_sort.rs +++ b/milli/src/search/new/vector_sort.rs @@ -5,7 +5,7 @@ use roaring::RoaringBitmap; use super::ranking_rules::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait}; use crate::score_details::{self, ScoreDetails}; -use crate::vector::DistributionShift; +use crate::vector::{DistributionShift, Embedder}; use crate::{DocumentId, Result, SearchContext, SearchLogger}; pub struct VectorSort { @@ -24,8 +24,8 @@ impl VectorSort { target: Vec, vector_candidates: RoaringBitmap, limit: usize, - distribution_shift: Option, embedder_name: &str, + embedder: &Embedder, ) -> Result { let embedder_index = ctx .index @@ -39,7 +39,7 @@ impl VectorSort { vector_candidates, cached_sorted_docids: Default::default(), limit, - distribution_shift, + distribution_shift: embedder.distribution(), embedder_index, }) }