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https://github.com/meilisearch/MeiliSearch
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Merge #4938
4938: Remove default embedder r=ManyTheFish a=dureuill # Pull Request ## Related issue Fixes #4738 ## What does this PR do? [See public usage](https://meilisearch.notion.site/v1-11-AI-search-changes-0e37727193884a70999f254fa953ce6e#1044b06b651f80edb9d4ef6dc367bad0) - Remove `hybrid.embedder` boolean from analytics because embedder is now mandatory and so the boolean would always be `true` - Rework search kind so that a search without query but with vector is a vector search regardless of (non-zero) semantic ratio Co-authored-by: Louis Dureuil <louis@meilisearch.com>
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meili-bors[bot]
GitHub
commit
5f474a640d
@ -646,8 +646,6 @@ pub struct SearchAggregator {
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max_vector_size: usize,
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// Whether the semantic ratio passed to a hybrid search equals the default ratio.
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semantic_ratio: bool,
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// Whether a non-default embedder was specified
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embedder: bool,
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hybrid: bool,
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retrieve_vectors: bool,
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@ -795,7 +793,6 @@ impl SearchAggregator {
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if let Some(hybrid) = hybrid {
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ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
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ret.embedder = hybrid.embedder.is_some();
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ret.hybrid = true;
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}
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@ -863,7 +860,6 @@ impl SearchAggregator {
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show_ranking_score,
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show_ranking_score_details,
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semantic_ratio,
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embedder,
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hybrid,
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total_degraded,
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total_used_negative_operator,
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@ -923,7 +919,6 @@ impl SearchAggregator {
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self.retrieve_vectors |= retrieve_vectors;
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self.semantic_ratio |= semantic_ratio;
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self.hybrid |= hybrid;
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self.embedder |= embedder;
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// pagination
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self.max_limit = self.max_limit.max(max_limit);
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@ -999,7 +994,6 @@ impl SearchAggregator {
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show_ranking_score,
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show_ranking_score_details,
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semantic_ratio,
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embedder,
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hybrid,
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total_degraded,
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total_used_negative_operator,
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@ -1051,7 +1045,6 @@ impl SearchAggregator {
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"hybrid": {
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"enabled": hybrid,
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"semantic_ratio": semantic_ratio,
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"embedder": embedder,
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},
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"pagination": {
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"max_limit": max_limit,
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@ -1782,7 +1775,6 @@ pub struct SimilarAggregator {
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used_syntax: HashMap<String, usize>,
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// Whether a non-default embedder was specified
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embedder: bool,
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retrieve_vectors: bool,
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// pagination
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@ -1803,7 +1795,7 @@ impl SimilarAggregator {
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pub fn from_query(query: &SimilarQuery, request: &HttpRequest) -> Self {
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let SimilarQuery {
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id: _,
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embedder,
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embedder: _,
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offset,
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limit,
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attributes_to_retrieve: _,
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@ -1851,7 +1843,6 @@ impl SimilarAggregator {
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ret.show_ranking_score_details = *show_ranking_score_details;
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ret.ranking_score_threshold = ranking_score_threshold.is_some();
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ret.embedder = embedder.is_some();
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ret.retrieve_vectors = *retrieve_vectors;
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ret
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@ -1883,7 +1874,6 @@ impl SimilarAggregator {
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max_attributes_to_retrieve,
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show_ranking_score,
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show_ranking_score_details,
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embedder,
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ranking_score_threshold,
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retrieve_vectors,
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} = other;
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@ -1914,7 +1904,6 @@ impl SimilarAggregator {
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*used_syntax = used_syntax.saturating_add(value);
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}
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self.embedder |= embedder;
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self.retrieve_vectors |= retrieve_vectors;
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// pagination
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@ -1948,7 +1937,6 @@ impl SimilarAggregator {
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max_attributes_to_retrieve,
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show_ranking_score,
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show_ranking_score_details,
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embedder,
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ranking_score_threshold,
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retrieve_vectors,
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} = self;
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@ -1980,9 +1968,6 @@ impl SimilarAggregator {
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"vector": {
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"retrieve_vectors": retrieve_vectors,
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},
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"hybrid": {
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"embedder": embedder,
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},
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"pagination": {
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"max_limit": max_limit,
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"max_offset": max_offset,
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@ -72,7 +72,7 @@ pub enum MeilisearchHttpError {
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DocumentFormat(#[from] DocumentFormatError),
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#[error(transparent)]
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Join(#[from] JoinError),
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#[error("Invalid request: missing `hybrid` parameter when both `q` and `vector` are present.")]
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#[error("Invalid request: missing `hybrid` parameter when `vector` is present.")]
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MissingSearchHybrid,
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}
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@ -128,8 +128,10 @@ impl std::ops::Deref for SemanticRatioGet {
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}
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}
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impl From<SearchQueryGet> for SearchQuery {
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fn from(other: SearchQueryGet) -> Self {
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impl TryFrom<SearchQueryGet> for SearchQuery {
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type Error = ResponseError;
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fn try_from(other: SearchQueryGet) -> Result<Self, Self::Error> {
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let filter = match other.filter {
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Some(f) => match serde_json::from_str(&f) {
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Ok(v) => Some(v),
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@ -140,19 +142,28 @@ impl From<SearchQueryGet> for SearchQuery {
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let hybrid = match (other.hybrid_embedder, other.hybrid_semantic_ratio) {
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(None, None) => None,
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(None, Some(semantic_ratio)) => {
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Some(HybridQuery { semantic_ratio: *semantic_ratio, embedder: None })
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(None, Some(_)) => {
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return Err(ResponseError::from_msg(
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"`hybridEmbedder` is mandatory when `hybridSemanticRatio` is present".into(),
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meilisearch_types::error::Code::InvalidHybridQuery,
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));
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}
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(Some(embedder), None) => {
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Some(HybridQuery { semantic_ratio: DEFAULT_SEMANTIC_RATIO(), embedder })
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}
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(Some(embedder), None) => Some(HybridQuery {
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semantic_ratio: DEFAULT_SEMANTIC_RATIO(),
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embedder: Some(embedder),
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}),
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(Some(embedder), Some(semantic_ratio)) => {
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Some(HybridQuery { semantic_ratio: *semantic_ratio, embedder: Some(embedder) })
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Some(HybridQuery { semantic_ratio: *semantic_ratio, embedder })
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}
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};
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Self {
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if other.vector.is_some() && hybrid.is_none() {
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return Err(ResponseError::from_msg(
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"`hybridEmbedder` is mandatory when `vector` is present".into(),
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meilisearch_types::error::Code::MissingSearchHybrid,
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));
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}
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Ok(Self {
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q: other.q,
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vector: other.vector.map(CS::into_inner),
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offset: other.offset.0,
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@ -179,7 +190,7 @@ impl From<SearchQueryGet> for SearchQuery {
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hybrid,
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ranking_score_threshold: other.ranking_score_threshold.map(|o| o.0),
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locales: other.locales.map(|o| o.into_iter().collect()),
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}
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})
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}
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}
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@ -219,7 +230,7 @@ pub async fn search_with_url_query(
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debug!(parameters = ?params, "Search get");
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let index_uid = IndexUid::try_from(index_uid.into_inner())?;
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let mut query: SearchQuery = params.into_inner().into();
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let mut query: SearchQuery = params.into_inner().try_into()?;
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// Tenant token search_rules.
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if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
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@ -312,44 +323,36 @@ pub fn search_kind(
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features.check_vector("Passing `hybrid` as a parameter")?;
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}
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// regardless of anything, always do a keyword search when we don't have a vector and the query is whitespace or missing
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if query.vector.is_none() {
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match &query.q {
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Some(q) if q.trim().is_empty() => return Ok(SearchKind::KeywordOnly),
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None => return Ok(SearchKind::KeywordOnly),
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_ => {}
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// handle with care, the order of cases matters, the semantics is subtle
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match (query.q.as_deref(), &query.hybrid, query.vector.as_deref()) {
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// empty query, no vector => placeholder search
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(Some(q), _, None) if q.trim().is_empty() => Ok(SearchKind::KeywordOnly),
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// no query, no vector => placeholder search
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(None, _, None) => Ok(SearchKind::KeywordOnly),
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// hybrid.semantic_ratio == 1.0 => vector
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(_, Some(HybridQuery { semantic_ratio, embedder }), v) if **semantic_ratio == 1.0 => {
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SearchKind::semantic(index_scheduler, index, embedder, v.map(|v| v.len()))
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}
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}
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match &query.hybrid {
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Some(HybridQuery { semantic_ratio, embedder }) if **semantic_ratio == 1.0 => {
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Ok(SearchKind::semantic(
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index_scheduler,
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index,
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embedder.as_deref(),
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query.vector.as_ref().map(Vec::len),
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)?)
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}
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Some(HybridQuery { semantic_ratio, embedder: _ }) if **semantic_ratio == 0.0 => {
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// hybrid.semantic_ratio == 0.0 => keyword
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(_, Some(HybridQuery { semantic_ratio, embedder: _ }), _) if **semantic_ratio == 0.0 => {
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Ok(SearchKind::KeywordOnly)
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}
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Some(HybridQuery { semantic_ratio, embedder }) => Ok(SearchKind::hybrid(
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// no query, hybrid, vector => semantic
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(None, Some(HybridQuery { semantic_ratio: _, embedder }), Some(v)) => {
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SearchKind::semantic(index_scheduler, index, embedder, Some(v.len()))
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}
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// query, no hybrid, no vector => keyword
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(Some(_), None, None) => Ok(SearchKind::KeywordOnly),
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// query, hybrid, maybe vector => hybrid
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(Some(_), Some(HybridQuery { semantic_ratio, embedder }), v) => SearchKind::hybrid(
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index_scheduler,
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index,
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embedder.as_deref(),
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embedder,
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**semantic_ratio,
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query.vector.as_ref().map(Vec::len),
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)?),
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None => match (query.q.as_deref(), query.vector.as_deref()) {
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(_query, None) => Ok(SearchKind::KeywordOnly),
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(None, Some(_vector)) => Ok(SearchKind::semantic(
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index_scheduler,
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index,
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None,
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query.vector.as_ref().map(Vec::len),
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)?),
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(Some(_), Some(_)) => Err(MeilisearchHttpError::MissingSearchHybrid.into()),
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},
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v.map(|v| v.len()),
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),
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(_, None, Some(_)) => Err(MeilisearchHttpError::MissingSearchHybrid.into()),
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}
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}
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@ -103,7 +103,7 @@ async fn similar(
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let index = index_scheduler.index(&index_uid)?;
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let (embedder_name, embedder) =
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SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
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SearchKind::embedder(&index_scheduler, &index, &query.embedder, None)?;
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tokio::task::spawn_blocking(move || {
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perform_similar(
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@ -139,8 +139,8 @@ pub struct SimilarQueryGet {
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show_ranking_score_details: Param<bool>,
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#[deserr(default, error = DeserrQueryParamError<InvalidSimilarRankingScoreThreshold>, default)]
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pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
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#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
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pub embedder: Option<String>,
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#[deserr(error = DeserrQueryParamError<InvalidEmbedder>)]
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pub embedder: String,
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}
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#[derive(Debug, Clone, Copy, PartialEq, deserr::Deserr)]
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@ -267,8 +267,8 @@ impl fmt::Debug for SearchQuery {
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pub struct HybridQuery {
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#[deserr(default, error = DeserrJsonError<InvalidSearchSemanticRatio>, default)]
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pub semantic_ratio: SemanticRatio,
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#[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
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pub embedder: Option<String>,
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#[deserr(error = DeserrJsonError<InvalidEmbedder>)]
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pub embedder: String,
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}
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#[derive(Clone)]
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@ -282,7 +282,7 @@ impl SearchKind {
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pub(crate) fn semantic(
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index_scheduler: &index_scheduler::IndexScheduler,
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index: &Index,
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embedder_name: Option<&str>,
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embedder_name: &str,
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vector_len: Option<usize>,
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) -> Result<Self, ResponseError> {
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let (embedder_name, embedder) =
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@ -293,7 +293,7 @@ impl SearchKind {
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pub(crate) fn hybrid(
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index_scheduler: &index_scheduler::IndexScheduler,
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index: &Index,
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embedder_name: Option<&str>,
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embedder_name: &str,
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semantic_ratio: f32,
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vector_len: Option<usize>,
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) -> Result<Self, ResponseError> {
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@ -305,14 +305,12 @@ impl SearchKind {
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pub(crate) fn embedder(
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index_scheduler: &index_scheduler::IndexScheduler,
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index: &Index,
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embedder_name: Option<&str>,
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embedder_name: &str,
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vector_len: Option<usize>,
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) -> Result<(String, Arc<Embedder>), ResponseError> {
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let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
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let embedders = index_scheduler.embedders(embedder_configs)?;
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let embedder_name = embedder_name.unwrap_or_else(|| embedders.get_default_embedder_name());
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let embedder = embedders.get(embedder_name);
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let embedder = embedder
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@ -538,8 +536,8 @@ pub struct SimilarQuery {
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pub limit: usize,
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#[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
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pub filter: Option<Value>,
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#[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
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pub embedder: Option<String>,
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#[deserr(error = DeserrJsonError<InvalidEmbedder>)]
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pub embedder: String,
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#[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
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pub attributes_to_retrieve: Option<BTreeSet<String>>,
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#[deserr(default, error = DeserrJsonError<InvalidSimilarRetrieveVectors>)]
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@ -128,7 +128,7 @@ async fn simple_search() {
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let (response, code) = index
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.search_post(
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2, "embedder": "default"}, "retrieveVectors": true}),
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)
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.await;
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snapshot!(code, @"200 OK");
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@ -137,7 +137,7 @@ async fn simple_search() {
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let (response, code) = index
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.search_post(
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true, "retrieveVectors": true}),
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5, "embedder": "default"}, "showRankingScore": true, "retrieveVectors": true}),
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)
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.await;
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snapshot!(code, @"200 OK");
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@ -146,7 +146,7 @@ async fn simple_search() {
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let (response, code) = index
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.search_post(
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true, "retrieveVectors": true}),
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8, "embedder": "default"}, "showRankingScore": true, "retrieveVectors": true}),
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)
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.await;
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snapshot!(code, @"200 OK");
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@ -161,7 +161,7 @@ async fn limit_offset() {
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let (response, code) = index
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.search_post(
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true, "offset": 1, "limit": 1}),
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2, "embedder": "default"}, "retrieveVectors": true, "offset": 1, "limit": 1}),
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)
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.await;
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snapshot!(code, @"200 OK");
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@ -174,7 +174,7 @@ async fn limit_offset() {
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let (response, code) = index
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.search_post(
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.9}, "retrieveVectors": true, "offset": 1, "limit": 1}),
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json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.9, "embedder": "default"}, "retrieveVectors": true, "offset": 1, "limit": 1}),
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)
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.await;
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snapshot!(code, @"200 OK");
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@ -188,8 +188,11 @@ async fn simple_search_hf() {
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let server = Server::new().await;
|
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let index = index_with_documents_hf(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
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|
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let (response, code) =
|
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index.search_post(json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}})).await;
|
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let (response, code) = index
|
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.search_post(
|
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json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2, "embedder": "default"}}),
|
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)
|
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.await;
|
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snapshot!(code, @"200 OK");
|
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snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"}]"###);
|
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snapshot!(response["semanticHitCount"], @"0");
|
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@ -197,7 +200,7 @@ async fn simple_search_hf() {
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let (response, code) = index
|
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.search_post(
|
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// disable ranking score as the vectors between architectures are not equal
|
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json!({"q": "Captain", "hybrid": {"semanticRatio": 0.55}, "showRankingScore": false}),
|
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json!({"q": "Captain", "hybrid": {"embedder": "default", "semanticRatio": 0.55}, "showRankingScore": false}),
|
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)
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.await;
|
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snapshot!(code, @"200 OK");
|
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@ -206,7 +209,7 @@ async fn simple_search_hf() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.8}, "showRankingScore": false}),
|
||||
json!({"q": "Captain", "hybrid": {"embedder": "default", "semanticRatio": 0.8}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -215,7 +218,7 @@ async fn simple_search_hf() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Movie World", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
json!({"q": "Movie World", "hybrid": {"embedder": "default", "semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -224,7 +227,7 @@ async fn simple_search_hf() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Wonder replacement", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
json!({"q": "Wonder replacement", "hybrid": {"embedder": "default", "semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -237,7 +240,7 @@ async fn distribution_shift() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
|
||||
let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}, "retrieveVectors": true});
|
||||
let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"embedder": "default", "semanticRatio": 1.0}, "retrieveVectors": true});
|
||||
let (response, code) = index.search_post(search.clone()).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
|
||||
@ -271,7 +274,7 @@ async fn highlighter() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
|
||||
"hybrid": {"semanticRatio": 0.2},
|
||||
"hybrid": {"embedder": "default", "semanticRatio": 0.2},
|
||||
"retrieveVectors": true,
|
||||
"attributesToHighlight": [
|
||||
"desc",
|
||||
@ -287,7 +290,7 @@ async fn highlighter() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
|
||||
"hybrid": {"semanticRatio": 0.8},
|
||||
"hybrid": {"embedder": "default", "semanticRatio": 0.8},
|
||||
"retrieveVectors": true,
|
||||
"showRankingScore": true,
|
||||
"attributesToHighlight": [
|
||||
@ -304,7 +307,7 @@ async fn highlighter() {
|
||||
// no highlighting on full semantic
|
||||
let (response, code) = index
|
||||
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
|
||||
"hybrid": {"semanticRatio": 1.0},
|
||||
"hybrid": {"embedder": "default", "semanticRatio": 1.0},
|
||||
"retrieveVectors": true,
|
||||
"showRankingScore": true,
|
||||
"attributesToHighlight": [
|
||||
@ -326,7 +329,7 @@ async fn invalid_semantic_ratio() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 1.2}}),
|
||||
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"embedder": "default", "semanticRatio": 1.2}}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
@ -341,7 +344,7 @@ async fn invalid_semantic_ratio() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": -0.8}}),
|
||||
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"embedder": "default", "semanticRatio": -0.8}}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
@ -357,7 +360,7 @@ async fn invalid_semantic_ratio() {
|
||||
let (response, code) = index
|
||||
.search_get(
|
||||
&yaup::to_string(
|
||||
&json!({"q": "Captain", "vector": [1.0, 1.0], "hybridSemanticRatio": 1.2}),
|
||||
&json!({"q": "Captain", "vector": [1.0, 1.0], "hybridEmbedder": "default", "hybridSemanticRatio": 1.2}),
|
||||
)
|
||||
.unwrap(),
|
||||
)
|
||||
@ -375,7 +378,7 @@ async fn invalid_semantic_ratio() {
|
||||
let (response, code) = index
|
||||
.search_get(
|
||||
&yaup::to_string(
|
||||
&json!({"q": "Captain", "vector": [1.0, 1.0], "hybridSemanticRatio": -0.2}),
|
||||
&json!({"q": "Captain", "vector": [1.0, 1.0], "hybridEmbedder": "default", "hybridSemanticRatio": -0.2}),
|
||||
)
|
||||
.unwrap(),
|
||||
)
|
||||
@ -398,7 +401,7 @@ async fn single_document() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0, "embedder": "default"}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
)
|
||||
.await;
|
||||
|
||||
@ -414,7 +417,7 @@ async fn query_combination() {
|
||||
|
||||
// search without query and vector, but with hybrid => still placeholder
|
||||
let (response, code) = index
|
||||
.search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"hybrid": {"embedder": "default", "semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -423,7 +426,7 @@ async fn query_combination() {
|
||||
|
||||
// same with a different semantic ratio
|
||||
let (response, code) = index
|
||||
.search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"hybrid": {"embedder": "default", "semanticRatio": 0.76}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -432,7 +435,7 @@ async fn query_combination() {
|
||||
|
||||
// wrong vector dimensions
|
||||
let (response, code) = index
|
||||
.search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"embedder": "default", "semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
@ -447,7 +450,7 @@ async fn query_combination() {
|
||||
|
||||
// full vector
|
||||
let (response, code) = index
|
||||
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"embedder": "default", "semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -456,7 +459,7 @@ async fn query_combination() {
|
||||
|
||||
// full keyword, without a query
|
||||
let (response, code) = index
|
||||
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"embedder": "default", "semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -465,7 +468,7 @@ async fn query_combination() {
|
||||
|
||||
// query + vector, full keyword => keyword
|
||||
let (response, code) = index
|
||||
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"embedder": "default", "semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -480,7 +483,7 @@ async fn query_combination() {
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Invalid request: missing `hybrid` parameter when both `q` and `vector` are present.",
|
||||
"message": "Invalid request: missing `hybrid` parameter when `vector` is present.",
|
||||
"code": "missing_search_hybrid",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#missing_search_hybrid"
|
||||
@ -490,7 +493,7 @@ async fn query_combination() {
|
||||
// full vector, without a vector => error
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0, "embedder": "default"}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
)
|
||||
.await;
|
||||
|
||||
@ -507,7 +510,7 @@ async fn query_combination() {
|
||||
// hybrid without a vector => full keyword
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99, "embedder": "default"}, "showRankingScore": true, "retrieveVectors": true}),
|
||||
)
|
||||
.await;
|
||||
|
||||
@ -523,7 +526,7 @@ async fn retrieve_vectors() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
|
||||
json!({"q": "Captain", "hybrid": {"embedder": "default", "semanticRatio": 0.2}, "retrieveVectors": true}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -573,7 +576,7 @@ async fn retrieve_vectors() {
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
|
||||
json!({"q": "Captain", "hybrid": {"embedder": "default", "semanticRatio": 0.2}, "retrieveVectors": true}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
|
||||
@ -1099,11 +1099,17 @@ async fn experimental_feature_vector_store() {
|
||||
index.add_documents(json!(documents), None).await;
|
||||
index.wait_task(0).await;
|
||||
|
||||
index
|
||||
.search(json!({
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"vector": [1.0, 2.0, 3.0],
|
||||
"hybrid": {
|
||||
"embedder": "manual",
|
||||
},
|
||||
"showRankingScore": true
|
||||
}), |response, code|{
|
||||
}))
|
||||
.await;
|
||||
|
||||
{
|
||||
meili_snap::snapshot!(code, @"400 Bad Request");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
|
||||
{
|
||||
@ -1113,8 +1119,8 @@ async fn experimental_feature_vector_store() {
|
||||
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
|
||||
}
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
index
|
||||
.search(json!({
|
||||
"retrieveVectors": true,
|
||||
@ -1162,6 +1168,9 @@ async fn experimental_feature_vector_store() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"vector": [1.0, 2.0, 3.0],
|
||||
"hybrid": {
|
||||
"embedder": "manual",
|
||||
},
|
||||
"showRankingScore": true,
|
||||
"retrieveVectors": true,
|
||||
}))
|
||||
|
||||
@ -18,7 +18,7 @@ async fn similar_unexisting_index() {
|
||||
});
|
||||
|
||||
index
|
||||
.similar(json!({"id": 287947}), |response, code| {
|
||||
.similar(json!({"id": 287947, "embedder": "manual"}), |response, code| {
|
||||
assert_eq!(code, 404);
|
||||
assert_eq!(response, expected_response);
|
||||
})
|
||||
@ -44,7 +44,7 @@ async fn similar_feature_not_enabled() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947})).await;
|
||||
let (response, code) = index.similar_post(json!({"id": 287947, "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -199,7 +199,8 @@ async fn similar_not_found_id() {
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": "definitely-doesnt-exist"})).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({"id": "definitely-doesnt-exist", "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -230,7 +231,8 @@ async fn similar_bad_offset() {
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947, "offset": "doggo"})).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({"id": 287947, "offset": "doggo", "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -241,7 +243,7 @@ async fn similar_bad_offset() {
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index.similar_get("?id=287947&offset=doggo").await;
|
||||
let (response, code) = index.similar_get("?id=287947&offset=doggo&embedder=manual").await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -272,7 +274,8 @@ async fn similar_bad_limit() {
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947, "limit": "doggo"})).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({"id": 287947, "limit": "doggo", "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -283,7 +286,7 @@ async fn similar_bad_limit() {
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index.similar_get("?id=287946&limit=doggo").await;
|
||||
let (response, code) = index.similar_get("?id=287946&limit=doggo&embedder=manual").await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -323,7 +326,8 @@ async fn similar_bad_filter() {
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({ "id": 287947, "filter": true })).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({ "id": 287947, "filter": true, "embedder": "manual" })).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -361,7 +365,7 @@ async fn filter_invalid_syntax_object() {
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "title & Glass"}), |response, code| {
|
||||
.similar(json!({"id": 287947, "filter": "title & Glass", "embedder": "manual"}), |response, code| {
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `CONTAINS`, `NOT CONTAINS`, `STARTS WITH`, `NOT STARTS WITH`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
|
||||
@ -400,7 +404,7 @@ async fn filter_invalid_syntax_array() {
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["title & Glass"]}), |response, code| {
|
||||
.similar(json!({"id": 287947, "filter": ["title & Glass"], "embedder": "manual"}), |response, code| {
|
||||
snapshot!(response, @r###"
|
||||
{
|
||||
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `CONTAINS`, `NOT CONTAINS`, `STARTS WITH`, `NOT STARTS WITH`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
|
||||
@ -446,7 +450,7 @@ async fn filter_invalid_syntax_string() {
|
||||
});
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "title = Glass XOR title = Glass"}),
|
||||
json!({"id": 287947, "filter": "title = Glass XOR title = Glass", "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
@ -486,10 +490,13 @@ async fn filter_invalid_attribute_array() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["many = Glass"]}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": ["many = Glass"], "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -524,10 +531,13 @@ async fn filter_invalid_attribute_string() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "many = Glass"}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "many = Glass", "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -562,10 +572,13 @@ async fn filter_reserved_geo_attribute_array() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geo = Glass"]}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": ["_geo = Glass"], "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -600,10 +613,13 @@ async fn filter_reserved_geo_attribute_string() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geo = Glass"}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "_geo = Glass", "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -638,10 +654,13 @@ async fn filter_reserved_attribute_array() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geoDistance = Glass"]}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": ["_geoDistance = Glass"], "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -676,10 +695,13 @@ async fn filter_reserved_attribute_string() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geoDistance = Glass"}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "_geoDistance = Glass", "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -714,10 +736,13 @@ async fn filter_reserved_geo_point_array() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geoPoint = Glass"]}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": ["_geoPoint = Glass"], "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -752,10 +777,13 @@ async fn filter_reserved_geo_point_string() {
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geoPoint = Glass"}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "_geoPoint = Glass", "embedder": "manual"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -765,7 +793,8 @@ async fn similar_bad_retrieve_vectors() {
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
let index = server.index("test");
|
||||
|
||||
let (response, code) = index.similar_post(json!({"retrieveVectors": "doggo"})).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({"retrieveVectors": "doggo", "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
@ -776,7 +805,8 @@ async fn similar_bad_retrieve_vectors() {
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index.similar_post(json!({"retrieveVectors": [true]})).await;
|
||||
let (response, code) =
|
||||
index.similar_post(json!({"retrieveVectors": [true], "embedder": "manual"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
|
||||
@ -80,7 +80,9 @@ async fn basic() {
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 143, "retrieveVectors": true}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 143, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
@ -154,11 +156,14 @@ async fn basic() {
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": "299537", "retrieveVectors": true}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": "299537", "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
@ -232,7 +237,8 @@ async fn basic() {
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
@ -272,7 +278,7 @@ async fn ranking_score_threshold() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0, "retrieveVectors": true}),
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"4");
|
||||
@ -358,7 +364,7 @@ async fn ranking_score_threshold() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.2, "retrieveVectors": true}),
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.2, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"3");
|
||||
@ -426,7 +432,7 @@ async fn ranking_score_threshold() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.3, "retrieveVectors": true}),
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.3, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"2");
|
||||
@ -476,7 +482,7 @@ async fn ranking_score_threshold() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.6, "retrieveVectors": true}),
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.6, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"1");
|
||||
@ -508,7 +514,7 @@ async fn ranking_score_threshold() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.9, "retrieveVectors": true}),
|
||||
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.9, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @"[]");
|
||||
@ -553,7 +559,7 @@ async fn filter() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 522681, "filter": "release_year = 2019", "retrieveVectors": true}),
|
||||
json!({"id": 522681, "filter": "release_year = 2019", "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
@ -617,7 +623,7 @@ async fn filter() {
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 522681, "filter": "release_year < 2000", "retrieveVectors": true}),
|
||||
json!({"id": 522681, "filter": "release_year < 2000", "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
@ -681,7 +687,9 @@ async fn limit_and_offset() {
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 143, "limit": 1, "retrieveVectors": true}), |response, code| {
|
||||
.similar(
|
||||
json!({"id": 143, "limit": 1, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
@ -704,12 +712,13 @@ async fn limit_and_offset() {
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
},
|
||||
)
|
||||
.await;
|
||||
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 143, "limit": 1, "offset": 1, "retrieveVectors": true}),
|
||||
json!({"id": 143, "limit": 1, "offset": 1, "retrieveVectors": true, "embedder": "manual"}),
|
||||
|response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
|
||||
@ -624,7 +624,8 @@ async fn clear_documents() {
|
||||
"###);
|
||||
|
||||
// Make sure the arroy DB has been cleared
|
||||
let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
|
||||
let (documents, _code) =
|
||||
index.search_post(json!({ "vector": [1, 1, 1], "hybrid": {"embedder": "manual"} })).await;
|
||||
snapshot!(documents, @r###"
|
||||
{
|
||||
"hits": [],
|
||||
@ -685,7 +686,11 @@ async fn add_remove_one_vector_4588() {
|
||||
let task = index.wait_task(value.uid()).await;
|
||||
snapshot!(task, name: "document-deleted");
|
||||
|
||||
let (documents, _code) = index.search_post(json!({"vector": [1, 1, 1] })).await;
|
||||
let (documents, _code) = index
|
||||
.search_post(
|
||||
json!({"vector": [1, 1, 1], "hybrid": {"semanticRatio": 1.0, "embedder": "manual"} }),
|
||||
)
|
||||
.await;
|
||||
snapshot!(documents, @r###"
|
||||
{
|
||||
"hits": [
|
||||
|
||||
@ -449,7 +449,7 @@ async fn it_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "chien de chasse",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"},
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -489,7 +489,7 @@ async fn it_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "petit chien",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -529,7 +529,7 @@ async fn it_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -616,7 +616,7 @@ async fn tokenize_long_text() {
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"showRankingScore": true,
|
||||
"attributesToRetrieve": ["id"],
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1064,7 +1064,7 @@ async fn smaller_dimensions() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "chien de chasse",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1104,7 +1104,7 @@ async fn smaller_dimensions() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "petit chien",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1144,7 +1144,7 @@ async fn smaller_dimensions() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1295,7 +1295,7 @@ async fn small_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "chien de chasse",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1335,7 +1335,7 @@ async fn small_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "petit chien",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1375,7 +1375,7 @@ async fn small_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1525,7 +1525,7 @@ async fn legacy_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "chien de chasse",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1565,7 +1565,7 @@ async fn legacy_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "petit chien",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1605,7 +1605,7 @@ async fn legacy_embedding_model() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1756,7 +1756,7 @@ async fn it_still_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "chien de chasse",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1796,7 +1796,7 @@ async fn it_still_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "petit chien",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
@ -1836,7 +1836,7 @@ async fn it_still_works() {
|
||||
let (response, code) = index
|
||||
.search_post(json!({
|
||||
"q": "grand chien de berger des montagnes",
|
||||
"hybrid": {"semanticRatio": 1.0}
|
||||
"hybrid": {"semanticRatio": 1.0, "embedder": "default"}
|
||||
}))
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
|
||||
@ -218,7 +218,8 @@ async fn reset_embedder_documents() {
|
||||
"###);
|
||||
|
||||
// Make sure the arroy DB has been cleared
|
||||
let (documents, _code) = index.search_post(json!({ "vector": [1, 1, 1] })).await;
|
||||
let (documents, _code) =
|
||||
index.search_post(json!({ "vector": [1, 1, 1], "hybrid": {"embedder": "default"} })).await;
|
||||
snapshot!(json_string!(documents), @r###"
|
||||
{
|
||||
"message": "Cannot find embedder with name `default`.",
|
||||
|
||||
@ -144,11 +144,6 @@ impl EmbeddingConfigs {
|
||||
self.0.get(name).cloned()
|
||||
}
|
||||
|
||||
/// Get the default embedder configuration, if any.
|
||||
pub fn get_default(&self) -> Option<(Arc<Embedder>, Arc<Prompt>)> {
|
||||
self.get(self.get_default_embedder_name())
|
||||
}
|
||||
|
||||
pub fn inner_as_ref(&self) -> &HashMap<String, (Arc<Embedder>, Arc<Prompt>)> {
|
||||
&self.0
|
||||
}
|
||||
@ -156,24 +151,6 @@ impl EmbeddingConfigs {
|
||||
pub fn into_inner(self) -> HashMap<String, (Arc<Embedder>, Arc<Prompt>)> {
|
||||
self.0
|
||||
}
|
||||
|
||||
/// Get the name of the default embedder configuration.
|
||||
///
|
||||
/// The default embedder is determined as follows:
|
||||
///
|
||||
/// - If there is only one embedder, it is always the default.
|
||||
/// - If there are multiple embedders and one of them is called `default`, then that one is the default embedder.
|
||||
/// - In all other cases, there is no default embedder.
|
||||
pub fn get_default_embedder_name(&self) -> &str {
|
||||
let mut it = self.0.keys();
|
||||
let first_name = it.next();
|
||||
let second_name = it.next();
|
||||
match (first_name, second_name) {
|
||||
(None, _) => "default",
|
||||
(Some(first), None) => first,
|
||||
(Some(_), Some(_)) => "default",
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl IntoIterator for EmbeddingConfigs {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user