mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-22 18:17:39 +08:00
Change retrieveVectors
behavior:
- when the feature is disabled, documents are never modified - when the feature is enabled and `retrieveVectors` is disabled, `_vectors` is removed from documents - when the feature is enabled and `retrieveVectors` is enabled, vectors from the vectors DB are merged with `_vectors` in documents Additionally `_vectors` is never displayed when the `displayedAttributes` list does not contain either `*` or `_vectors` - fixed an issue where `_vectors` was not injected when all vectors in the dataset where always generated
This commit is contained in:
parent
e35ef31738
commit
b9b938c902
@ -40,7 +40,7 @@ use crate::extractors::sequential_extractor::SeqHandler;
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use crate::routes::{
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get_task_id, is_dry_run, PaginationView, SummarizedTaskView, PAGINATION_DEFAULT_LIMIT,
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};
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use crate::search::parse_filter;
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use crate::search::{parse_filter, RetrieveVectors};
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use crate::Opt;
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static ACCEPTED_CONTENT_TYPE: Lazy<Vec<String>> = Lazy::new(|| {
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@ -110,21 +110,20 @@ pub async fn get_document(
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debug!(parameters = ?params, "Get document");
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let index_uid = IndexUid::try_from(index_uid)?;
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let GetDocument { fields, retrieve_vectors } = params.into_inner();
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let GetDocument { fields, retrieve_vectors: param_retrieve_vectors } = params.into_inner();
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let attributes_to_retrieve = fields.merge_star_and_none();
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let features = index_scheduler.features();
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if retrieve_vectors.0 {
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features.check_vector("Passing `retrieveVectors` as a parameter")?;
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}
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let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0, features)?;
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analytics.get_fetch_documents(
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&DocumentFetchKind::PerDocumentId { retrieve_vectors: retrieve_vectors.0 },
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&DocumentFetchKind::PerDocumentId { retrieve_vectors: param_retrieve_vectors.0 },
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&req,
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);
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let index = index_scheduler.index(&index_uid)?;
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let document =
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retrieve_document(&index, &document_id, attributes_to_retrieve, retrieve_vectors.0)?;
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retrieve_document(&index, &document_id, attributes_to_retrieve, retrieve_vectors)?;
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debug!(returns = ?document, "Get document");
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Ok(HttpResponse::Ok().json(document))
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}
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@ -195,11 +194,6 @@ pub async fn documents_by_query_post(
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let body = body.into_inner();
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debug!(parameters = ?body, "Get documents POST");
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let features = index_scheduler.features();
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if body.retrieve_vectors {
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features.check_vector("Passing `retrieveVectors` as a parameter")?;
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}
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analytics.post_fetch_documents(
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&DocumentFetchKind::Normal {
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with_filter: body.filter.is_some(),
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@ -224,11 +218,6 @@ pub async fn get_documents(
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let BrowseQueryGet { limit, offset, fields, retrieve_vectors, filter } = params.into_inner();
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let features = index_scheduler.features();
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if retrieve_vectors.0 {
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features.check_vector("Passing `retrieveVectors` as a parameter")?;
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}
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let filter = match 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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@ -266,6 +255,9 @@ fn documents_by_query(
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let index_uid = IndexUid::try_from(index_uid.into_inner())?;
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let BrowseQuery { offset, limit, fields, retrieve_vectors, filter } = query;
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let features = index_scheduler.features();
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let retrieve_vectors = RetrieveVectors::new(retrieve_vectors, features)?;
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let index = index_scheduler.index(&index_uid)?;
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let (total, documents) =
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retrieve_documents(&index, offset, limit, filter, fields, retrieve_vectors)?;
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@ -608,7 +600,7 @@ fn some_documents<'a, 't: 'a>(
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index: &'a Index,
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rtxn: &'t RoTxn,
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doc_ids: impl IntoIterator<Item = DocumentId> + 'a,
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retrieve_vectors: bool,
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retrieve_vectors: RetrieveVectors,
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) -> Result<impl Iterator<Item = Result<Document, ResponseError>> + 'a, ResponseError> {
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let fields_ids_map = index.fields_ids_map(rtxn)?;
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let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
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@ -617,9 +609,16 @@ fn some_documents<'a, 't: 'a>(
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Ok(index.iter_documents(rtxn, doc_ids)?.map(move |ret| {
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ret.map_err(ResponseError::from).and_then(|(key, document)| -> Result<_, ResponseError> {
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let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
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if retrieve_vectors {
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let mut vectors = serde_json::Map::new();
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match retrieve_vectors {
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RetrieveVectors::Ignore => {}
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RetrieveVectors::Hide => {
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document.remove("_vectors");
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}
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RetrieveVectors::Retrieve => {
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let mut vectors = match document.remove("_vectors") {
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Some(Value::Object(map)) => map,
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_ => Default::default(),
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};
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for (name, vector) in index.embeddings(rtxn, key)? {
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let user_provided = embedding_configs
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.iter()
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@ -636,6 +635,7 @@ fn some_documents<'a, 't: 'a>(
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}
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document.insert("_vectors".into(), vectors.into());
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}
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}
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Ok(document)
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})
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@ -648,7 +648,7 @@ fn retrieve_documents<S: AsRef<str>>(
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limit: usize,
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filter: Option<Value>,
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attributes_to_retrieve: Option<Vec<S>>,
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retrieve_vectors: bool,
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retrieve_vectors: RetrieveVectors,
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) -> Result<(u64, Vec<Document>), ResponseError> {
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let rtxn = index.read_txn()?;
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let filter = &filter;
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@ -688,10 +688,9 @@ fn retrieve_documents<S: AsRef<str>>(
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Ok(match &attributes_to_retrieve {
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Some(attributes_to_retrieve) => permissive_json_pointer::select_values(
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&document?,
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attributes_to_retrieve
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.iter()
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.map(|s| s.as_ref())
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.chain(retrieve_vectors.then_some("_vectors")),
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attributes_to_retrieve.iter().map(|s| s.as_ref()).chain(
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(retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors"),
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),
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),
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None => document?,
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})
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@ -705,7 +704,7 @@ fn retrieve_document<S: AsRef<str>>(
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index: &Index,
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doc_id: &str,
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attributes_to_retrieve: Option<Vec<S>>,
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retrieve_vectors: bool,
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retrieve_vectors: RetrieveVectors,
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) -> Result<Document, ResponseError> {
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let txn = index.read_txn()?;
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@ -724,7 +723,7 @@ fn retrieve_document<S: AsRef<str>>(
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attributes_to_retrieve
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.iter()
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.map(|s| s.as_ref())
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.chain(retrieve_vectors.then_some("_vectors")),
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.chain((retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors")),
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),
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None => document,
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};
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@ -20,9 +20,9 @@ use crate::extractors::sequential_extractor::SeqHandler;
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use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
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use crate::search::{
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add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
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SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
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DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
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DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
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RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,
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DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
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DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
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};
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use crate::search_queue::SearchQueue;
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@ -225,10 +225,12 @@ pub async fn search_with_url_query(
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let features = index_scheduler.features();
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let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
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let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
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let _permit = search_queue.try_get_search_permit().await?;
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let search_result =
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tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
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let search_result = tokio::task::spawn_blocking(move || {
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perform_search(&index, query, search_kind, retrieve_vector)
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})
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.await?;
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if let Ok(ref search_result) = search_result {
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aggregate.succeed(search_result);
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}
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@ -265,10 +267,13 @@ pub async fn search_with_post(
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let features = index_scheduler.features();
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let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
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let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
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let _permit = search_queue.try_get_search_permit().await?;
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let search_result =
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tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
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let search_result = tokio::task::spawn_blocking(move || {
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perform_search(&index, query, search_kind, retrieve_vectors)
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})
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.await?;
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if let Ok(ref search_result) = search_result {
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aggregate.succeed(search_result);
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if search_result.degraded {
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@ -295,9 +300,6 @@ pub fn search_kind(
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if query.hybrid.is_some() {
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features.check_vector("Passing `hybrid` as a parameter")?;
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}
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if query.retrieve_vectors {
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features.check_vector("Passing `retrieveVectors` 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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@ -17,8 +17,8 @@ use crate::analytics::{Analytics, SimilarAggregator};
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use crate::extractors::authentication::GuardedData;
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use crate::extractors::sequential_extractor::SeqHandler;
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use crate::search::{
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add_search_rules, perform_similar, RankingScoreThresholdSimilar, SearchKind, SimilarQuery,
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SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
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add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, SearchKind,
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SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
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};
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pub fn configure(cfg: &mut web::ServiceConfig) {
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@ -93,6 +93,8 @@ async fn similar(
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features.check_vector("Using the similar API")?;
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let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
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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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add_search_rules(&mut query.filter, search_rules);
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@ -103,7 +105,9 @@ async fn similar(
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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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tokio::task::spawn_blocking(move || perform_similar(&index, query, embedder_name, embedder))
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tokio::task::spawn_blocking(move || {
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perform_similar(&index, query, embedder_name, embedder, retrieve_vectors)
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})
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.await?
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}
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@ -15,7 +15,7 @@ use crate::extractors::authentication::{AuthenticationError, GuardedData};
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use crate::extractors::sequential_extractor::SeqHandler;
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use crate::routes::indexes::search::search_kind;
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use crate::search::{
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add_search_rules, perform_search, SearchQueryWithIndex, SearchResultWithIndex,
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add_search_rules, perform_search, RetrieveVectors, SearchQueryWithIndex, SearchResultWithIndex,
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};
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use crate::search_queue::SearchQueue;
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@ -83,9 +83,12 @@ pub async fn multi_search_with_post(
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let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)
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.with_index(query_index)?;
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let retrieve_vector =
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RetrieveVectors::new(query.retrieve_vectors, features).with_index(query_index)?;
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let search_result =
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tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind))
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let search_result = tokio::task::spawn_blocking(move || {
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perform_search(&index, query, search_kind, retrieve_vector)
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})
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.await
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.with_index(query_index)?;
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@ -823,6 +823,7 @@ pub fn perform_search(
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index: &Index,
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query: SearchQuery,
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search_kind: SearchKind,
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retrieve_vectors: RetrieveVectors,
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) -> Result<SearchResult, MeilisearchHttpError> {
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let before_search = Instant::now();
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let rtxn = index.read_txn()?;
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@ -860,7 +861,8 @@ pub fn perform_search(
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page,
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hits_per_page,
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attributes_to_retrieve,
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retrieve_vectors,
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// use the enum passed as parameter
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retrieve_vectors: _,
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attributes_to_crop,
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crop_length,
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attributes_to_highlight,
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@ -968,7 +970,7 @@ pub fn perform_search(
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struct AttributesFormat {
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attributes_to_retrieve: Option<BTreeSet<String>>,
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retrieve_vectors: bool,
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retrieve_vectors: RetrieveVectors,
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attributes_to_highlight: Option<HashSet<String>>,
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attributes_to_crop: Option<Vec<String>>,
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crop_length: usize,
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@ -981,6 +983,36 @@ struct AttributesFormat {
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show_ranking_score_details: bool,
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}
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#[derive(Debug, Clone, Copy, PartialEq, Eq)]
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pub enum RetrieveVectors {
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/// Do not touch the `_vectors` field
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///
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/// this is the behavior when the vectorStore feature is disabled
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Ignore,
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/// Remove the `_vectors` field
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///
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/// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `false`
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Hide,
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/// Retrieve vectors from the DB and merge them into the `_vectors` field
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///
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/// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `true`
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Retrieve,
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}
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impl RetrieveVectors {
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pub fn new(
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retrieve_vector: bool,
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features: index_scheduler::RoFeatures,
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) -> Result<Self, index_scheduler::Error> {
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match (retrieve_vector, features.check_vector("Passing `retrieveVectors` as a parameter")) {
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(true, Ok(())) => Ok(Self::Retrieve),
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(true, Err(error)) => Err(error),
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(false, Ok(())) => Ok(Self::Hide),
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(false, Err(_)) => Ok(Self::Ignore),
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}
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}
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}
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fn make_hits(
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index: &Index,
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rtxn: &RoTxn<'_>,
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@ -990,10 +1022,32 @@ fn make_hits(
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document_scores: Vec<Vec<ScoreDetails>>,
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) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
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let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
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let displayed_ids = index
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.displayed_fields_ids(rtxn)?
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.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
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.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
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let displayed_ids =
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index.displayed_fields_ids(rtxn)?.map(|fields| fields.into_iter().collect::<BTreeSet<_>>());
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let vectors_fid = fields_ids_map.id(milli::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME);
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let vectors_is_hidden = match (&displayed_ids, vectors_fid) {
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// displayed_ids is a wildcard, so `_vectors` can be displayed regardless of its fid
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(None, _) => false,
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// displayed_ids is a finite list, and `_vectors` cannot be part of it because it is not an existing field
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(Some(_), None) => true,
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// displayed_ids is a finit list, so hide if `_vectors` is not part of it
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(Some(map), Some(vectors_fid)) => map.contains(&vectors_fid),
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};
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let retrieve_vectors = if let RetrieveVectors::Retrieve = format.retrieve_vectors {
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if vectors_is_hidden {
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RetrieveVectors::Hide
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} else {
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RetrieveVectors::Retrieve
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}
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} else {
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format.retrieve_vectors
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};
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let displayed_ids =
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displayed_ids.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
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let fids = |attrs: &BTreeSet<String>| {
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let mut ids = BTreeSet::new();
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for attr in attrs {
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@ -1016,9 +1070,7 @@ fn make_hits(
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.intersection(&displayed_ids)
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.cloned()
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.collect();
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let is_vectors_displayed =
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fields_ids_map.id("_vectors").is_some_and(|fid| displayed_ids.contains(&fid));
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let retrieve_vectors = format.retrieve_vectors && is_vectors_displayed;
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let attr_to_highlight = format.attributes_to_highlight.unwrap_or_default();
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let attr_to_crop = format.attributes_to_crop.unwrap_or_default();
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let formatted_options = compute_formatted_options(
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@ -1058,15 +1110,30 @@ fn make_hits(
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// First generate a document with all the displayed fields
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let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
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let add_vectors_fid =
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vectors_fid.filter(|_fid| retrieve_vectors == RetrieveVectors::Retrieve);
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// select the attributes to retrieve
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let attributes_to_retrieve = to_retrieve_ids
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.iter()
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// skip the vectors_fid if RetrieveVectors::Hide
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.filter(|fid| match vectors_fid {
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Some(vectors_fid) => {
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!(retrieve_vectors == RetrieveVectors::Hide && **fid == vectors_fid)
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}
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None => true,
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})
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// need to retrieve the existing `_vectors` field if the `RetrieveVectors::Retrieve`
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.chain(add_vectors_fid.iter())
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.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
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let mut document =
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permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
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if retrieve_vectors {
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let mut vectors = serde_json::Map::new();
|
||||
if retrieve_vectors == RetrieveVectors::Retrieve {
|
||||
let mut vectors = match document.remove("_vectors") {
|
||||
Some(Value::Object(map)) => map,
|
||||
_ => Default::default(),
|
||||
};
|
||||
for (name, vector) in index.embeddings(rtxn, id)? {
|
||||
let user_provided = embedding_configs
|
||||
.iter()
|
||||
@ -1148,6 +1215,7 @@ pub fn perform_similar(
|
||||
query: SimilarQuery,
|
||||
embedder_name: String,
|
||||
embedder: Arc<Embedder>,
|
||||
retrieve_vectors: RetrieveVectors,
|
||||
) -> Result<SimilarResult, ResponseError> {
|
||||
let before_search = Instant::now();
|
||||
let rtxn = index.read_txn()?;
|
||||
@ -1159,7 +1227,7 @@ pub fn perform_similar(
|
||||
filter: _,
|
||||
embedder: _,
|
||||
attributes_to_retrieve,
|
||||
retrieve_vectors,
|
||||
retrieve_vectors: _,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
ranking_score_threshold,
|
||||
|
Loading…
Reference in New Issue
Block a user