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Browse Source 
5232: Stabilize vector store feature r=Kerollmops a=dureuill

# Pull Request

## Related issue
Fixes #4733 

## What does this PR do?
- `vectorStore` feature can no longer be set or get from `/experimental-features`
- That feature has been removed, and there is no longer any check for its activation
- Always display `embedders` in the settings, even if empty
- Always hide `_vectors` in documents, unless `retrieveVectors: true`
- Make error codes consistent with the usual nomenclature
- Update tests as needed


Co-authored-by: Louis Dureuil <louis@meilisearch.com>
This commit is contained in:
meili-bors[bot]
2025-01-16 11:50:21 +00:00
committed by GitHub
parent 8f006eeaf3 89a4ac92eb
commit c85146524b
32 changed files with 214 additions and 1010 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
crates/dump/src/lib.rs
View File

@@ -458,7 +458,7 @@ pub(crate) mod test {
}
fn create_test_features() -> RuntimeTogglableFeatures {
RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
RuntimeTogglableFeatures::default()
}
#[test]

10
crates/dump/src/reader/mod.rs
View File

@@ -327,10 +327,7 @@ pub(crate) mod test {
}
}
assert_eq!(
dump.features().unwrap().unwrap(),
RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
);
assert_eq!(dump.features().unwrap().unwrap(), RuntimeTogglableFeatures::default());
}
#[test]
@@ -373,10 +370,7 @@ pub(crate) mod test {
assert_eq!(test.documents().unwrap().count(), 1);
assert_eq!(
dump.features().unwrap().unwrap(),
RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
);
assert_eq!(dump.features().unwrap().unwrap(), RuntimeTogglableFeatures::default());
}
#[test]

13
crates/index-scheduler/src/features.rs
View File

@@ -56,19 +56,6 @@ impl RoFeatures {
}
}
pub fn check_vector(&self, disabled_action: &'static str) -> Result<()> {
if self.runtime.vector_store {
Ok(())
} else {
Err(FeatureNotEnabledError {
disabled_action,
feature: "vector store",
issue_link: "https://github.com/meilisearch/product/discussions/677",
}
.into())
}
}
pub fn check_edit_documents_by_function(&self, disabled_action: &'static str) -> Result<()> {
if self.runtime.edit_documents_by_function {
Ok(())

8
crates/meilisearch-types/src/error.rs
View File

@@ -243,8 +243,9 @@ InvalidVectorsType , InvalidRequest , BAD_REQUEST ;
InvalidDocumentId , InvalidRequest , BAD_REQUEST ;
InvalidDocumentLimit , InvalidRequest , BAD_REQUEST ;
InvalidDocumentOffset , InvalidRequest , BAD_REQUEST ;
InvalidEmbedder , InvalidRequest , BAD_REQUEST ;
InvalidHybridQuery , InvalidRequest , BAD_REQUEST ;
InvalidSearchEmbedder , InvalidRequest , BAD_REQUEST ;
InvalidSimilarEmbedder , InvalidRequest , BAD_REQUEST ;
InvalidSearchHybridQuery , InvalidRequest , BAD_REQUEST ;
InvalidIndexLimit , InvalidRequest , BAD_REQUEST ;
InvalidIndexOffset , InvalidRequest , BAD_REQUEST ;
InvalidIndexPrimaryKey , InvalidRequest , BAD_REQUEST ;
@@ -443,7 +444,8 @@ impl ErrorCode for milli::Error {
UserError::InvalidMinTypoWordLenSetting(_, _) => {
Code::InvalidSettingsTypoTolerance
}
UserError::InvalidEmbedder(_) => Code::InvalidEmbedder,
UserError::InvalidSearchEmbedder(_) => Code::InvalidSearchEmbedder,
UserError::InvalidSimilarEmbedder(_) => Code::InvalidSimilarEmbedder,
UserError::VectorEmbeddingError(_) | UserError::DocumentEmbeddingError(_) => {
Code::VectorEmbeddingError
}

1
crates/meilisearch-types/src/features.rs
View File

@@ -3,7 +3,6 @@ use serde::{Deserialize, Serialize};
#[derive(Serialize, Deserialize, Debug, Clone, Copy, Default, PartialEq, Eq)]
#[serde(rename_all = "camelCase", default)]
pub struct RuntimeTogglableFeatures {
pub vector_store: bool,
pub metrics: bool,
pub logs_route: bool,
pub edit_documents_by_function: bool,

2
crates/meilisearch-types/src/settings.rs
View File

@@ -866,7 +866,7 @@ pub fn settings(
(name, SettingEmbeddingSettings { inner: Setting::Set(config.into()) })
})
.collect();
let embedders = if embedders.is_empty() { Setting::NotSet } else { Setting::Set(embedders) };
let embedders = Setting::Set(embedders);
let search_cutoff_ms = index.search_cutoff(rtxn)?;

5
crates/meilisearch/src/analytics/segment_analytics.rs
View File

@@ -177,13 +177,12 @@ impl SegmentAnalytics {
/// This structure represent the `infos` field we send in the analytics.
/// It's quite close to the `Opt` structure except all sensitive informations
/// have been simplified to a boolean.
/// It's send as-is in amplitude thus you should never update a name of the
/// It's sent as-is in amplitude thus you should never update a name of the
/// struct without the approval of the PM.
#[derive(Debug, Clone, Serialize)]
struct Infos {
env: String,
experimental_contains_filter: bool,
experimental_vector_store: bool,
experimental_enable_metrics: bool,
experimental_edit_documents_by_function: bool,
experimental_search_queue_size: usize,
@@ -280,7 +279,6 @@ impl Infos {
indexer_options;
let RuntimeTogglableFeatures {
vector_store,
metrics,
logs_route,
edit_documents_by_function,
@@ -292,7 +290,6 @@ impl Infos {
Self {
env,
experimental_contains_filter: experimental_contains_filter | contains_filter,
experimental_vector_store: vector_store,
experimental_edit_documents_by_function: edit_documents_by_function,
experimental_enable_metrics: experimental_enable_metrics | metrics,
experimental_search_queue_size,

29
crates/meilisearch/src/routes/features.rs
View File

@@ -46,7 +46,6 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
security(("Bearer" = ["experimental_features.get", "experimental_features.*", "*"])),
responses(
(status = OK, description = "Experimental features are returned", body = RuntimeTogglableFeatures, content_type = "application/json", example = json!(RuntimeTogglableFeatures {
vector_store: Some(true),
metrics: Some(true),
logs_route: Some(false),
edit_documents_by_function: Some(false),
@@ -71,6 +70,7 @@ async fn get_features(
let features = index_scheduler.features();
let features = features.runtime_features();
let features: RuntimeTogglableFeatures = features.into();
debug!(returns = ?features, "Get features");
HttpResponse::Ok().json(features)
}
@@ -80,8 +80,6 @@ async fn get_features(
#[serde(rename_all = "camelCase")]
#[schema(rename_all = "camelCase")]
pub struct RuntimeTogglableFeatures {
#[deserr(default)]
pub vector_store: Option<bool>,
#[deserr(default)]
pub metrics: Option<bool>,
#[deserr(default)]
@@ -92,9 +90,26 @@ pub struct RuntimeTogglableFeatures {
pub contains_filter: Option<bool>,
}
impl From<meilisearch_types::features::RuntimeTogglableFeatures> for RuntimeTogglableFeatures {
fn from(value: meilisearch_types::features::RuntimeTogglableFeatures) -> Self {
let meilisearch_types::features::RuntimeTogglableFeatures {
metrics,
logs_route,
edit_documents_by_function,
contains_filter,
} = value;
Self {
metrics: Some(metrics),
logs_route: Some(logs_route),
edit_documents_by_function: Some(edit_documents_by_function),
contains_filter: Some(contains_filter),
}
}
}
#[derive(Serialize)]
pub struct PatchExperimentalFeatureAnalytics {
vector_store: bool,
metrics: bool,
logs_route: bool,
edit_documents_by_function: bool,
@@ -108,7 +123,6 @@ impl Aggregate for PatchExperimentalFeatureAnalytics {
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
vector_store: new.vector_store,
metrics: new.metrics,
logs_route: new.logs_route,
edit_documents_by_function: new.edit_documents_by_function,
@@ -131,7 +145,6 @@ impl Aggregate for PatchExperimentalFeatureAnalytics {
security(("Bearer" = ["experimental_features.update", "experimental_features.*", "*"])),
responses(
(status = OK, description = "Experimental features are returned", body = RuntimeTogglableFeatures, content_type = "application/json", example = json!(RuntimeTogglableFeatures {
vector_store: Some(true),
metrics: Some(true),
logs_route: Some(false),
edit_documents_by_function: Some(false),
@@ -161,7 +174,6 @@ async fn patch_features(
let old_features = features.runtime_features();
let new_features = meilisearch_types::features::RuntimeTogglableFeatures {
vector_store: new_features.0.vector_store.unwrap_or(old_features.vector_store),
metrics: new_features.0.metrics.unwrap_or(old_features.metrics),
logs_route: new_features.0.logs_route.unwrap_or(old_features.logs_route),
edit_documents_by_function: new_features
@@ -175,7 +187,6 @@ async fn patch_features(
// the it renames to camelCase, which we don't want for analytics.
// **Do not** ignore fields with `..` or `_` here, because we want to add them in the future.
let meilisearch_types::features::RuntimeTogglableFeatures {
vector_store,
metrics,
logs_route,
edit_documents_by_function,
@@ -184,7 +195,6 @@ async fn patch_features(
analytics.publish(
PatchExperimentalFeatureAnalytics {
vector_store,
metrics,
logs_route,
edit_documents_by_function,
@@ -193,6 +203,7 @@ async fn patch_features(
&req,
);
index_scheduler.put_runtime_features(new_features)?;
let new_features: RuntimeTogglableFeatures = new_features.into();
debug!(returns = ?new_features, "Patch features");
Ok(HttpResponse::Ok().json(new_features))
}

7
crates/meilisearch/src/routes/indexes/documents.rs
View File

@@ -257,8 +257,7 @@ pub async fn get_document(
let GetDocument { fields, retrieve_vectors: param_retrieve_vectors } = params.into_inner();
let attributes_to_retrieve = fields.merge_star_and_none();
let features = index_scheduler.features();
let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0, features)?;
let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0);
analytics.publish(
DocumentsFetchAggregator::<DocumentsGET> {
@@ -593,8 +592,7 @@ fn documents_by_query(
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let BrowseQuery { offset, limit, fields, retrieve_vectors, filter } = query;
let features = index_scheduler.features();
let retrieve_vectors = RetrieveVectors::new(retrieve_vectors, features)?;
let retrieve_vectors = RetrieveVectors::new(retrieve_vectors);
let index = index_scheduler.index(&index_uid)?;
let (total, documents) = retrieve_documents(
@@ -1420,7 +1418,6 @@ fn some_documents<'a, 't: 'a>(
ret.map_err(ResponseError::from).and_then(|(key, document)| -> Result<_, ResponseError> {
let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
match retrieve_vectors {
RetrieveVectors::Ignore => {}
RetrieveVectors::Hide => {
document.remove("_vectors");
}

6
crates/meilisearch/src/routes/indexes/facet_search.rs
View File

@@ -56,7 +56,7 @@ pub struct FacetSearchQuery {
pub q: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSearchVector>)]
pub vector: Option<Vec<f32>>,
#[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
#[deserr(default, error = DeserrJsonError<InvalidSearchHybridQuery>)]
pub hybrid: Option<HybridQuery>,
#[deserr(default, error = DeserrJsonError<InvalidSearchFilter>)]
pub filter: Option<Value>,
@@ -252,9 +252,7 @@ pub async fn search(
}
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
let search_kind =
search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index, features)?;
let search_kind = search_kind(&search_query, &index_scheduler, index_uid.to_string(), &index)?;
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_facet_search(

25
crates/meilisearch/src/routes/indexes/search.rs
View File

@@ -1,7 +1,7 @@
use actix_web::web::Data;
use actix_web::{web, HttpRequest, HttpResponse};
use deserr::actix_web::{AwebJson, AwebQueryParameter};
use index_scheduler::{IndexScheduler, RoFeatures};
use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::query_params::Param;
use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
use meilisearch_types::error::deserr_codes::*;
@@ -121,7 +121,7 @@ pub struct SearchQueryGet {
#[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToSearchOn>)]
#[param(value_type = Vec<String>, explode = false)]
pub attributes_to_search_on: Option<CS<String>>,
#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
#[deserr(default, error = DeserrQueryParamError<InvalidSearchEmbedder>)]
pub hybrid_embedder: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchSemanticRatio>)]
#[param(value_type = f32)]
@@ -185,7 +185,7 @@ impl TryFrom<SearchQueryGet> for SearchQuery {
(None, Some(_)) => {
return Err(ResponseError::from_msg(
"`hybridEmbedder` is mandatory when `hybridSemanticRatio` is present".into(),
meilisearch_types::error::Code::InvalidHybridQuery,
meilisearch_types::error::Code::InvalidSearchHybridQuery,
));
}
(Some(embedder), None) => {
@@ -336,11 +336,10 @@ pub async fn search_with_url_query(
let mut aggregate = SearchAggregator::<SearchGET>::from_query(&query);
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
let search_kind =
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors);
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(
@@ -444,11 +443,9 @@ pub async fn search_with_post(
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
let search_kind =
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index, features)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
search_kind(&query, index_scheduler.get_ref(), index_uid.to_string(), &index)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors);
let permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
@@ -483,15 +480,7 @@ pub fn search_kind(
index_scheduler: &IndexScheduler,
index_uid: String,
index: &milli::Index,
features: RoFeatures,
) -> Result<SearchKind, ResponseError> {
if query.vector.is_some() {
features.check_vector("Passing `vector` as a parameter")?;
}
if query.hybrid.is_some() {
features.check_vector("Passing `hybrid` as a parameter")?;
}
// handle with care, the order of cases matters, the semantics is subtle
match (query.q.as_deref(), &query.hybrid, query.vector.as_deref()) {
// empty query, no vector => placeholder search

6
crates/meilisearch/src/routes/indexes/settings.rs
View File

@@ -5,7 +5,6 @@ use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::ResponseError;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::update::Setting;
use meilisearch_types::settings::{
settings, SecretPolicy, SettingEmbeddingSettings, Settings, Unchecked,
};
@@ -711,10 +710,7 @@ pub async fn delete_all(
fn validate_settings(
settings: Settings<Unchecked>,
index_scheduler: &IndexScheduler,
_index_scheduler: &IndexScheduler,
) -> Result<Settings<Unchecked>, ResponseError> {
if matches!(settings.embedders, Setting::Set(_)) {
index_scheduler.features().check_vector("Passing `embedders` in settings")?
}
Ok(settings.validate()?)
}

13
crates/meilisearch/src/routes/indexes/similar.rs
View File

@@ -19,8 +19,8 @@ use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::routes::indexes::similar_analytics::{SimilarAggregator, SimilarGET, SimilarPOST};
use crate::search::{
add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, SearchKind,
SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, Route,
SearchKind, SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
};
#[derive(OpenApi)]
@@ -216,11 +216,7 @@ async fn similar(
index_uid: IndexUid,
mut query: SimilarQuery,
) -> Result<SimilarResult, ResponseError> {
let features = index_scheduler.features();
features.check_vector("Using the similar API")?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors);
// Tenant token search_rules.
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
@@ -235,6 +231,7 @@ async fn similar(
&index,
&query.embedder,
None,
Route::Similar,
)?;
tokio::task::spawn_blocking(move || {
@@ -281,7 +278,7 @@ pub struct SimilarQueryGet {
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarRankingScoreThreshold>, default)]
#[param(value_type = Option<f32>)]
pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
#[deserr(error = DeserrQueryParamError<InvalidEmbedder>)]
#[deserr(error = DeserrQueryParamError<InvalidSimilarEmbedder>)]
pub embedder: String,
}

6
crates/meilisearch/src/routes/multi_search.rs
View File

@@ -106,7 +106,7 @@ pub struct SearchResults {
{
"id": 42,
"title": "Batman returns",
"overview": "The overview of batman returns",
"overview": "The overview of batman returns",
"_federation": {
"indexUid": "movies",
"queriesPosition": 0
@@ -240,11 +240,9 @@ pub async fn multi_search_with_post(
index_scheduler.get_ref(),
index_uid_str.clone(),
&index,
features,
)
.with_index(query_index)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)
.with_index(query_index)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors);
let search_result = tokio::task::spawn_blocking(move || {
perform_search(

4
crates/meilisearch/src/search/federated.rs
View File

@@ -569,7 +569,7 @@ pub fn perform_federated_search(
let res: Result<(), ResponseError> = (|| {
let search_kind =
search_kind(&query, index_scheduler, index_uid.to_string(), &index, features)?;
search_kind(&query, index_scheduler, index_uid.to_string(), &index)?;
let canonicalization_kind = match (&search_kind, &query.q) {
(SearchKind::SemanticOnly { .. }, _) => {
@@ -631,7 +631,7 @@ pub fn perform_federated_search(
_ => semantic_hit_count = Some(0),
}
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors);
let time_budget = match cutoff {
Some(cutoff) => TimeBudget::new(Duration::from_millis(cutoff)),

61
crates/meilisearch/src/search/mod.rs
View File

@@ -63,7 +63,7 @@ pub struct SearchQuery {
pub q: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSearchVector>)]
pub vector: Option<Vec<f32>>,
#[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
#[deserr(default, error = DeserrJsonError<InvalidSearchHybridQuery>)]
pub hybrid: Option<HybridQuery>,
#[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSearchOffset>)]
#[schema(default = DEFAULT_SEARCH_OFFSET)]
@@ -276,12 +276,12 @@ impl fmt::Debug for SearchQuery {
}
#[derive(Debug, Clone, Default, PartialEq, Deserr, ToSchema)]
#[deserr(error = DeserrJsonError<InvalidHybridQuery>, rename_all = camelCase, deny_unknown_fields)]
#[deserr(error = DeserrJsonError<InvalidSearchHybridQuery>, rename_all = camelCase, deny_unknown_fields)]
pub struct HybridQuery {
#[deserr(default, error = DeserrJsonError<InvalidSearchSemanticRatio>, default)]
#[schema(value_type = f32, default)]
pub semantic_ratio: SemanticRatio,
#[deserr(error = DeserrJsonError<InvalidEmbedder>)]
#[deserr(error = DeserrJsonError<InvalidSearchEmbedder>)]
pub embedder: String,
}
@@ -300,8 +300,14 @@ impl SearchKind {
embedder_name: &str,
vector_len: Option<usize>,
) -> Result<Self, ResponseError> {
let (embedder_name, embedder, quantized) =
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
let (embedder_name, embedder, quantized) = Self::embedder(
index_scheduler,
index_uid,
index,
embedder_name,
vector_len,
Route::Search,
)?;
Ok(Self::SemanticOnly { embedder_name, embedder, quantized })
}
@@ -313,8 +319,14 @@ impl SearchKind {
semantic_ratio: f32,
vector_len: Option<usize>,
) -> Result<Self, ResponseError> {
let (embedder_name, embedder, quantized) =
Self::embedder(index_scheduler, index_uid, index, embedder_name, vector_len)?;
let (embedder_name, embedder, quantized) = Self::embedder(
index_scheduler,
index_uid,
index,
embedder_name,
vector_len,
Route::Search,
)?;
Ok(Self::Hybrid { embedder_name, embedder, quantized, semantic_ratio })
}
@@ -324,13 +336,21 @@ impl SearchKind {
index: &Index,
embedder_name: &str,
vector_len: Option<usize>,
route: Route,
) -> Result<(String, Arc<Embedder>, bool), ResponseError> {
let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
let embedders = index_scheduler.embedders(index_uid, embedder_configs)?;
let (embedder, _, quantized) = embedders
.get(embedder_name)
.ok_or(milli::UserError::InvalidEmbedder(embedder_name.to_owned()))
.ok_or(match route {
Route::Search | Route::MultiSearch => {
milli::UserError::InvalidSearchEmbedder(embedder_name.to_owned())
}
Route::Similar => {
milli::UserError::InvalidSimilarEmbedder(embedder_name.to_owned())
}
})
.map_err(milli::Error::from)?;
if let Some(vector_len) = vector_len {
@@ -401,7 +421,7 @@ pub struct SearchQueryWithIndex {
pub q: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSearchQ>)]
pub vector: Option<Vec<f32>>,
#[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
#[deserr(default, error = DeserrJsonError<InvalidSearchHybridQuery>)]
pub hybrid: Option<HybridQuery>,
#[deserr(default, error = DeserrJsonError<InvalidSearchOffset>)]
pub offset: Option<usize>,
@@ -553,7 +573,7 @@ pub struct SimilarQuery {
pub limit: usize,
#[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
pub filter: Option<Value>,
#[deserr(error = DeserrJsonError<InvalidEmbedder>)]
#[deserr(error = DeserrJsonError<InvalidSimilarEmbedder>)]
pub embedder: String,
#[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
pub attributes_to_retrieve: Option<BTreeSet<String>>,
@@ -1048,9 +1068,10 @@ pub struct ComputedFacets {
pub stats: BTreeMap<String, FacetStats>,
}
enum Route {
pub enum Route {
Search,
MultiSearch,
Similar,
}
fn compute_facet_distribution_stats<S: AsRef<str>>(
@@ -1141,10 +1162,6 @@ struct AttributesFormat {
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum RetrieveVectors {
/// Do not touch the `_vectors` field
///
/// this is the behavior when the vectorStore feature is disabled
Ignore,
/// Remove the `_vectors` field
///
/// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `false`
@@ -1156,15 +1173,11 @@ pub enum RetrieveVectors {
}
impl RetrieveVectors {
pub fn new(
retrieve_vector: bool,
features: index_scheduler::RoFeatures,
) -> Result<Self, index_scheduler::Error> {
match (retrieve_vector, features.check_vector("Passing `retrieveVectors` as a parameter")) {
(true, Ok(())) => Ok(Self::Retrieve),
(true, Err(error)) => Err(error),
(false, Ok(())) => Ok(Self::Hide),
(false, Err(_)) => Ok(Self::Ignore),
pub fn new(retrieve_vector: bool) -> Self {
if retrieve_vector {
Self::Retrieve
} else {
Self::Hide
}
}
}

27
crates/meilisearch/tests/documents/errors.rs
View File

@@ -760,15 +760,6 @@ async fn retrieve_vectors() {
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_all_documents_raw("?retrieveVectors=true").await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
// FETCH ALL DOCUMENTS BY POST
let (response, _code) =
@@ -781,15 +772,6 @@ async fn retrieve_vectors() {
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_document_by_filter(json!({ "retrieveVectors": true })).await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
// GET A SINGLE DOCUMENT
let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": "tamo"}))).await;
@@ -801,13 +783,4 @@ async fn retrieve_vectors() {
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": true}))).await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
}

11
crates/meilisearch/tests/documents/get_documents.rs
View File

@@ -518,17 +518,6 @@ async fn get_document_by_filter() {
async fn get_document_with_vectors() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({

26
crates/meilisearch/tests/dumps/mod.rs
View File

@@ -78,6 +78,7 @@ async fn import_dump_v1_movie_raw() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -243,6 +244,7 @@ async fn import_dump_v1_movie_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -394,6 +396,7 @@ async fn import_dump_v1_rubygems_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -531,6 +534,7 @@ async fn import_dump_v2_movie_raw() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -680,6 +684,7 @@ async fn import_dump_v2_movie_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -828,6 +833,7 @@ async fn import_dump_v2_rubygems_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -965,6 +971,7 @@ async fn import_dump_v3_movie_raw() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1114,6 +1121,7 @@ async fn import_dump_v3_movie_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1262,6 +1270,7 @@ async fn import_dump_v3_rubygems_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1399,6 +1408,7 @@ async fn import_dump_v4_movie_raw() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1548,6 +1558,7 @@ async fn import_dump_v4_movie_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1696,6 +1707,7 @@ async fn import_dump_v4_rubygems_with_settings() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1893,7 +1905,6 @@ async fn import_dump_v6_containing_experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": false,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
@@ -1945,6 +1956,7 @@ async fn import_dump_v6_containing_experimental_features() {
"pagination": {
"maxTotalHits": 1000
},
"embedders": {},
"searchCutoffMs": null,
"localizedAttributes": null,
"facetSearch": true,
@@ -1988,16 +2000,7 @@ async fn generate_and_import_dump_containing_vectors() {
let temp = tempfile::tempdir().unwrap();
let mut opt = default_settings(temp.path());
let server = Server::new_with_options(opt.clone()).await.unwrap();
let (code, _) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let index = server.index("pets");
let (response, code) = index
.update_settings(json!(
@@ -2063,7 +2066,6 @@ async fn generate_and_import_dump_containing_vectors() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,

22
crates/meilisearch/tests/features/mod.rs
View File

@@ -7,7 +7,7 @@ use crate::json;
/// Feature name to test against.
/// This will have to be changed by a different one when that feature is stabilized.
/// All tests that need to set a feature can make use of this constant.
const FEATURE_NAME: &str = "vectorStore";
const FEATURE_NAME: &str = "metrics";
#[actix_rt::test]
async fn experimental_features() {
@@ -18,7 +18,6 @@ async fn experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": false,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
@@ -31,8 +30,7 @@ async fn experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"metrics": true,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
@@ -44,8 +42,7 @@ async fn experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"metrics": true,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
@@ -58,8 +55,7 @@ async fn experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"metrics": true,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
@@ -72,8 +68,7 @@ async fn experimental_features() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"metrics": true,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
@@ -93,7 +88,6 @@ async fn experimental_feature_metrics() {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": false,
"metrics": true,
"logsRoute": false,
"editDocumentsByFunction": false,
@@ -152,7 +146,7 @@ async fn errors() {
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`, `editDocumentsByFunction`, `containsFilter`",
"message": "Unknown field `NotAFeature`: expected one of `metrics`, `logsRoute`, `editDocumentsByFunction`, `containsFilter`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
@@ -165,7 +159,7 @@ async fn errors() {
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Invalid value type at `.vectorStore`: expected a boolean, but found a positive integer: `42`",
"message": "Invalid value type at `.metrics`: expected a boolean, but found a positive integer: `42`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
@@ -178,7 +172,7 @@ async fn errors() {
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Invalid value type at `.vectorStore`: expected a boolean, but found a string: `\"true\"`",
"message": "Invalid value type at `.metrics`: expected a boolean, but found a string: `\"true\"`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"

26
crates/meilisearch/tests/search/hybrid.rs
View File

@@ -11,19 +11,6 @@ async fn index_with_documents_user_provided<'a>(
) -> Index<'a> {
let index = server.index("test");
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({ "embedders": {"default": {
"source": "userProvided",
@@ -41,19 +28,6 @@ async fn index_with_documents_user_provided<'a>(
async fn index_with_documents_hf<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
let index = server.index("test");
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({ "embedders": {"default": {
"source": "huggingFace",

234
crates/meilisearch/tests/search/mod.rs
View File

@@ -818,13 +818,6 @@ async fn test_score_details() {
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
},
"_rankingScoreDetails": {
"words": {
"order": 0,
@@ -1159,206 +1152,6 @@ async fn test_degraded_score_details() {
.await;
}
#[actix_rt::test]
async fn experimental_feature_vector_store() {
let server = Server::new().await;
let index = server.index("test");
let documents = DOCUMENTS.clone();
let (task, _status_code) = index.add_documents(json!(documents), None).await;
index.wait_task(task.uid()).await.succeeded();
let (response, code) = index
.search_post(json!({
"vector": [1.0, 2.0, 3.0],
"hybrid": {
"embedder": "manual",
},
"showRankingScore": true
}))
.await;
{
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Passing `vector` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
}
index
.search(json!({
"retrieveVectors": true,
"showRankingScore": true
}), |response, code|{
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Passing `retrieveVectors` as a parameter requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
})
.await;
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(response["vectorStore"], @"true");
let (response, code) = index
.update_settings(json!({"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
}}))
.await;
meili_snap::snapshot!(response, @r###"
{
"taskUid": 1,
"indexUid": "test",
"status": "enqueued",
"type": "settingsUpdate",
"enqueuedAt": "[date]"
}
"###);
meili_snap::snapshot!(code, @"202 Accepted");
let response = index.wait_task(response.uid()).await;
meili_snap::snapshot!(meili_snap::json_string!(response["status"]), @"\"succeeded\"");
let (response, code) = index
.search_post(json!({
"vector": [1.0, 2.0, 3.0],
"hybrid": {
"embedder": "manual",
},
"showRankingScore": true,
"retrieveVectors": true,
}))
.await;
meili_snap::snapshot!(code, @"200 OK");
// vector search returns all documents that don't have vectors in the last bucket, like all sorts
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Shazam!",
"id": "287947",
"color": [
"green",
"blue"
],
"_vectors": {
"manual": {
"embeddings": [
[
1.0,
2.0,
3.0
]
],
"regenerate": false
}
},
"_rankingScore": 1.0
},
{
"title": "Captain Marvel",
"id": "299537",
"color": [
"yellow",
"blue"
],
"_vectors": {
"manual": {
"embeddings": [
[
1.0,
2.0,
54.0
]
],
"regenerate": false
}
},
"_rankingScore": 0.9129111766815186
},
{
"title": "Gläss",
"id": "450465",
"color": [
"blue",
"red"
],
"_vectors": {
"manual": {
"embeddings": [
[
-100.0,
340.0,
90.0
]
],
"regenerate": false
}
},
"_rankingScore": 0.8106412887573242
},
{
"title": "How to Train Your Dragon: The Hidden World",
"id": "166428",
"color": [
"green",
"red"
],
"_vectors": {
"manual": {
"embeddings": [
[
-100.0,
231.0,
32.0
]
],
"regenerate": false
}
},
"_rankingScore": 0.7412010431289673
},
{
"title": "Escape Room",
"id": "522681",
"color": [
"yellow",
"red"
],
"_vectors": {
"manual": {
"embeddings": [
[
10.0,
-23.0,
32.0
]
],
"regenerate": false
}
},
"_rankingScore": 0.6972063183784485
}
]
"###);
}
#[cfg(feature = "default")]
#[actix_rt::test]
async fn camelcased_words() {
@@ -1611,14 +1404,7 @@ async fn simple_search_with_strange_synonyms() {
"color": [
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
}
]
}
]
"###);
@@ -1636,14 +1422,7 @@ async fn simple_search_with_strange_synonyms() {
"color": [
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
}
]
}
]
"###);
@@ -1661,14 +1440,7 @@ async fn simple_search_with_strange_synonyms() {
"color": [
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
}
]
}
]
"###);

367
crates/meilisearch/tests/search/multi.rs
View File

@@ -110,14 +110,7 @@ async fn simple_search_single_index() {
"color": [
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
}
]
}
],
"query": "glass",
@@ -135,14 +128,7 @@ async fn simple_search_single_index() {
"color": [
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
}
]
}
],
"query": "captain",
@@ -180,13 +166,6 @@ async fn federation_single_search_single_index() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 0,
@@ -303,13 +282,6 @@ async fn federation_two_search_single_index() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 0,
@@ -323,13 +295,6 @@ async fn federation_two_search_single_index() {
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 1,
@@ -477,14 +442,7 @@ async fn simple_search_two_indexes() {
"color": [
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
}
]
}
],
"query": "glass",
@@ -510,14 +468,7 @@ async fn simple_search_two_indexes() {
"age": 4
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
}
"cattos": "pésti"
},
{
"id": 654,
@@ -532,14 +483,7 @@ async fn simple_search_two_indexes() {
"cattos": [
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
}
]
}
],
"query": "pésti",
@@ -583,13 +527,6 @@ async fn federation_two_search_two_indexes() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 0,
@@ -611,13 +548,6 @@ async fn federation_two_search_two_indexes() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -638,13 +568,6 @@ async fn federation_two_search_two_indexes() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -705,13 +628,6 @@ async fn federation_multiple_search_multiple_indexes() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 0,
@@ -733,13 +649,6 @@ async fn federation_multiple_search_multiple_indexes() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 2,
@@ -771,13 +680,6 @@ async fn federation_multiple_search_multiple_indexes() {
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 1,
@@ -791,13 +693,6 @@ async fn federation_multiple_search_multiple_indexes() {
"yellow",
"red"
],
"_vectors": {
"manual": [
10,
-23,
32
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 3,
@@ -822,13 +717,6 @@ async fn federation_multiple_search_multiple_indexes() {
"moumoute",
"gomez"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 4,
@@ -867,13 +755,6 @@ async fn federation_multiple_search_multiple_indexes() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 2,
@@ -896,13 +777,6 @@ async fn federation_multiple_search_multiple_indexes() {
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
},
"_federation": {
"indexUid": "test",
"queriesPosition": 6,
@@ -1391,13 +1265,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1412,13 +1279,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
"cattos": [
"enigma"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1440,13 +1300,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1472,13 +1325,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
"moumoute",
"gomez"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1520,13 +1366,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1548,13 +1387,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1580,13 +1412,6 @@ async fn federation_sort_same_indexes_same_criterion_same_direction() {
"moumoute",
"gomez"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -1714,13 +1539,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -1746,13 +1564,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
"moumoute",
"gomez"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -1767,13 +1578,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
"cattos": [
"enigma"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1795,13 +1599,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -1843,13 +1640,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
"simba",
"pestiféré"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1872,13 +1662,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
}
],
"cattos": "pésti",
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 0,
@@ -1904,13 +1687,6 @@ async fn federation_sort_same_indexes_different_criterion_same_direction() {
"moumoute",
"gomez"
],
"_vectors": {
"manual": [
10,
23,
32
]
},
"_federation": {
"indexUid": "nested",
"queriesPosition": 1,
@@ -2101,13 +1877,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2122,13 +1891,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"yellow",
"red"
],
"_vectors": {
"manual": [
10,
-23,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2143,13 +1905,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2164,13 +1919,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2185,13 +1933,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"green",
"blue"
],
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2226,13 +1967,6 @@ async fn federation_sort_different_indexes_same_criterion_same_direction() {
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 1,
@@ -2413,13 +2147,6 @@ async fn federation_sort_different_ranking_rules() {
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2434,13 +2161,6 @@ async fn federation_sort_different_ranking_rules() {
"yellow",
"red"
],
"_vectors": {
"manual": [
10,
-23,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2455,13 +2175,6 @@ async fn federation_sort_different_ranking_rules() {
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2476,13 +2189,6 @@ async fn federation_sort_different_ranking_rules() {
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2497,13 +2203,6 @@ async fn federation_sort_different_ranking_rules() {
"green",
"blue"
],
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2714,13 +2413,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2755,13 +2447,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"yellow",
"red"
],
"_vectors": {
"manual": [
10,
-23,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2776,13 +2461,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"blue",
"red"
],
"_vectors": {
"manual": [
-100,
340,
90
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2797,13 +2475,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"green",
"red"
],
"_vectors": {
"manual": [
-100,
231,
32
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2818,13 +2489,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"green",
"blue"
],
"_vectors": {
"manual": [
1,
2,
3
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 0,
@@ -2879,13 +2543,6 @@ async fn federation_sort_different_indexes_different_criterion_same_direction()
"yellow",
"blue"
],
"_vectors": {
"manual": [
1,
2,
54
]
},
"_federation": {
"indexUid": "movies",
"queriesPosition": 1,
@@ -4094,13 +3751,6 @@ async fn federation_non_federated_contains_federation_option() {
#[actix_rt::test]
async fn federation_vector_single_index() {
let server = Server::new().await;
let (_, code) = server
.set_features(json!({
"vectorStore": true
}))
.await;
snapshot!(code, @"200 OK");
let index = server.index("vectors");
@@ -4302,13 +3952,6 @@ async fn federation_vector_single_index() {
#[actix_rt::test]
async fn federation_vector_two_indexes() {
let server = Server::new().await;
let (_, code) = server
.set_features(json!({
"vectorStore": true
}))
.await;
snapshot!(code, @"200 OK");
let index = server.index("vectors-animal");

17
crates/meilisearch/tests/settings/get_settings.rs
View File

@@ -152,7 +152,7 @@ test_setting_routes!(
{
setting: embedders,
update_verb: patch,
default_value: null
default_value: {}
},
{
setting: facet_search,
@@ -197,7 +197,7 @@ async fn get_settings() {
let (response, code) = index.settings().await;
assert_eq!(code, 200);
let settings = response.as_object().unwrap();
assert_eq!(settings.keys().len(), 19);
assert_eq!(settings.keys().len(), 20);
assert_eq!(settings["displayedAttributes"], json!(["*"]));
assert_eq!(settings["searchableAttributes"], json!(["*"]));
assert_eq!(settings["filterableAttributes"], json!([]));
@@ -230,23 +230,12 @@ async fn get_settings() {
assert_eq!(settings["searchCutoffMs"], json!(null));
assert_eq!(settings["prefixSearch"], json!("indexingTime"));
assert_eq!(settings["facetSearch"], json!(true));
assert_eq!(settings["embedders"], json!({}));
}
#[actix_rt::test]
async fn secrets_are_hidden_in_settings() {
let server = Server::new().await;
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let index = server.index("test");
let (response, _code) = index.create(None).await;

122
crates/meilisearch/tests/similar/errors.rs
View File

@@ -8,7 +8,6 @@ use crate::json;
async fn similar_unexisting_index() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let expected_response = json!({
"message": "Index `test` not found.",
@@ -29,7 +28,6 @@ async fn similar_unexisting_index() {
async fn similar_unexisting_parameter() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
index
.similar(json!({"id": 287947, "marin": "hello"}), |response, code| {
@@ -39,28 +37,10 @@ async fn similar_unexisting_parameter() {
.await;
}
#[actix_rt::test]
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, "embedder": "manual"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Using the similar API requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
"code": "feature_not_enabled",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
}
"###);
}
#[actix_rt::test]
async fn similar_bad_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -91,7 +71,6 @@ async fn similar_bad_id() {
async fn similar_bad_ranking_score_threshold() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -122,7 +101,6 @@ async fn similar_bad_ranking_score_threshold() {
async fn similar_invalid_ranking_score_threshold() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -153,7 +131,6 @@ async fn similar_invalid_ranking_score_threshold() {
async fn similar_invalid_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -184,7 +161,6 @@ async fn similar_invalid_id() {
async fn similar_not_found_id() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -216,7 +192,6 @@ async fn similar_not_found_id() {
async fn similar_bad_offset() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -259,7 +234,6 @@ async fn similar_bad_offset() {
async fn similar_bad_limit() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -304,7 +278,6 @@ async fn similar_bad_filter() {
// Thus the error message is not generated by deserr but written by us.
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -344,7 +317,6 @@ async fn similar_bad_filter() {
async fn filter_invalid_syntax_object() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -383,7 +355,6 @@ async fn filter_invalid_syntax_object() {
async fn filter_invalid_syntax_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -422,7 +393,6 @@ async fn filter_invalid_syntax_array() {
async fn filter_invalid_syntax_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -463,7 +433,6 @@ async fn filter_invalid_syntax_string() {
async fn filter_invalid_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -504,7 +473,6 @@ async fn filter_invalid_attribute_array() {
async fn filter_invalid_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -545,7 +513,6 @@ async fn filter_invalid_attribute_string() {
async fn filter_reserved_geo_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -586,7 +553,6 @@ async fn filter_reserved_geo_attribute_array() {
async fn filter_reserved_geo_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -627,7 +593,6 @@ async fn filter_reserved_geo_attribute_string() {
async fn filter_reserved_attribute_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -668,7 +633,6 @@ async fn filter_reserved_attribute_array() {
async fn filter_reserved_attribute_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -709,7 +673,6 @@ async fn filter_reserved_attribute_string() {
async fn filter_reserved_geo_point_array() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -750,7 +713,6 @@ async fn filter_reserved_geo_point_array() {
async fn filter_reserved_geo_point_string() {
let server = Server::new().await;
let index = server.index("test");
server.set_features(json!({"vectorStore": true})).await;
let (response, code) = index
.update_settings(json!({
@@ -790,7 +752,6 @@ async fn filter_reserved_geo_point_string() {
#[actix_rt::test]
async fn similar_bad_retrieve_vectors() {
let server = Server::new().await;
server.set_features(json!({"vectorStore": true})).await;
let index = server.index("test");
let (response, code) =
@@ -839,3 +800,86 @@ async fn similar_bad_retrieve_vectors() {
}
"###);
}
#[actix_rt::test]
async fn similar_bad_embedder() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index
.update_settings(json!({
"embedders": {
"manual": {
"source": "userProvided",
"dimensions": 3,
}
},
"filterableAttributes": ["title"]}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = DOCUMENTS.clone();
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
let expected_response = json!({
"message": "Cannot find embedder with name `auto`.",
"code": "invalid_similar_embedder",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_embedder"
});
index
.similar(json!({"id": 287947, "embedder": "auto"}), |response, code| {
assert_eq!(response, expected_response);
assert_eq!(code, 400);
})
.await;
let expected_response = json!({
"message": "Invalid value type at `.embedder`: expected a string, but found a positive integer: `42`",
"code": "invalid_similar_embedder",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_embedder"
});
let (response, code) = index.similar_post(json!({"id": 287947, "embedder": 42})).await;
assert_eq!(response, expected_response);
assert_eq!(code, 400);
let expected_response = json!({
"message": "Invalid value type at `.embedder`: expected a string, but found null",
"code": "invalid_similar_embedder",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_embedder"
});
let (response, code) = index.similar_post(json!({"id": 287947, "embedder": null})).await;
assert_eq!(response, expected_response);
assert_eq!(code, 400);
let expected_response = json!({
"message": "Missing field `embedder`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
});
let (response, code) = index.similar_post(json!({"id": 287947})).await;
assert_eq!(response, expected_response);
assert_eq!(code, 400);
let expected_response = json!({
"message": "Missing parameter `embedder`",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
});
let (response, code) = index.similar_get("?id=287947").await;
assert_eq!(response, expected_response);
assert_eq!(code, 400);
}

44
crates/meilisearch/tests/similar/mod.rs
View File

@@ -49,17 +49,6 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
async fn basic() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -246,17 +235,6 @@ async fn basic() {
async fn ranking_score_threshold() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -527,17 +505,6 @@ async fn ranking_score_threshold() {
async fn filter() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -656,17 +623,6 @@ async fn filter() {
async fn limit_and_offset() {
let server = Server::new().await;
let index = server.index("test");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({

44
crates/meilisearch/tests/vector/binary_quantized.rs
View File

@@ -8,17 +8,6 @@ use crate::vector::generate_default_user_provided_documents;
async fn retrieve_binary_quantize_status_in_the_settings() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -78,17 +67,6 @@ async fn retrieve_binary_quantize_status_in_the_settings() {
async fn binary_quantize_before_sending_documents() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -163,17 +141,6 @@ async fn binary_quantize_before_sending_documents() {
async fn binary_quantize_after_sending_documents() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -261,17 +228,6 @@ async fn binary_quantize_after_sending_documents() {
async fn try_to_disable_binary_quantization() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({

47
crates/meilisearch/tests/vector/mod.rs
View File

@@ -13,36 +13,13 @@ use crate::common::{default_settings, GetAllDocumentsOptions, Server};
use crate::json;
async fn get_server_vector() -> Server {
let server = Server::new().await;
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
server
Server::new().await
}
#[actix_rt::test]
async fn add_remove_user_provided() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -187,17 +164,6 @@ async fn add_remove_user_provided() {
async fn generate_default_user_provided_documents(server: &Server) -> Index {
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -654,17 +620,6 @@ async fn add_remove_one_vector_4588() {
// https://github.com/meilisearch/meilisearch/issues/4588
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({

26
crates/meilisearch/tests/vector/settings.rs
View File

@@ -8,17 +8,6 @@ use crate::vector::generate_default_user_provided_documents;
async fn field_unavailable_for_source() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -55,17 +44,6 @@ async fn field_unavailable_for_source() {
async fn update_embedder() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
@@ -271,9 +249,9 @@ async fn reset_embedder_documents() {
snapshot!(json_string!(documents), @r###"
{
"message": "Cannot find embedder with name `default`.",
"code": "invalid_embedder",
"code": "invalid_search_embedder",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_embedder"
"link": "https://docs.meilisearch.com/errors#invalid_search_embedder"
}
"###);
}

4
crates/milli/src/error.rs
View File

@@ -222,7 +222,9 @@ and can not be more than 511 bytes.", .document_id.to_string()
#[error("Too many embedders in the configuration. Found {0}, but limited to 256.")]
TooManyEmbedders(usize),
#[error("Cannot find embedder with name `{0}`.")]
InvalidEmbedder(String),
InvalidSearchEmbedder(String),
#[error("Cannot find embedder with name `{0}`.")]
InvalidSimilarEmbedder(String),
#[error("Too many vectors for document with id {0}: found {1}, but limited to 256.")]
TooManyVectors(String, usize),
#[error("`.embedders.{embedder_name}`: Field `{field}` unavailable for source `{source_}` (only available for sources: {}). Available fields: {}",

2
crates/milli/src/search/new/vector_sort.rs
View File

@@ -32,7 +32,7 @@ impl<Q: RankingRuleQueryTrait> VectorSort<Q> {
.index
.embedder_category_id
.get(ctx.txn, embedder_name)?
.ok_or_else(|| crate::UserError::InvalidEmbedder(embedder_name.to_owned()))?;
.ok_or_else(|| crate::UserError::InvalidSearchEmbedder(embedder_name.to_owned()))?;
Ok(Self {
query: None,

7
crates/milli/src/search/similar.rs
View File

@@ -65,10 +65,9 @@ impl<'a> Similar<'a> {
let universe = universe;
let embedder_index =
self.index
.embedder_category_id
.get(self.rtxn, &self.embedder_name)?
.ok_or_else(|| crate::UserError::InvalidEmbedder(self.embedder_name.to_owned()))?;
self.index.embedder_category_id.get(self.rtxn, &self.embedder_name)?.ok_or_else(
|| crate::UserError::InvalidSimilarEmbedder(self.embedder_name.to_owned()),
)?;
let reader = ArroyWrapper::new(self.index.vector_arroy, embedder_index, self.quantized);
let results = reader.nns_by_item(