WIP multi embedders

fixed template bugs

index-scheduler/src/lib.rs

@@ -1361,7 +1361,6 @@ impl IndexScheduler {
                 let embedder = Arc::new(
                     Embedder::new(embedder_options.clone())
                         .map_err(meilisearch_types::milli::vector::Error::from)
-                        .map_err(meilisearch_types::milli::UserError::from)
                         .map_err(meilisearch_types::milli::Error::from)?,
                 );
                 {

meilisearch-types/src/error.rs

@@ -222,6 +222,8 @@ InvalidVectorsType                    , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentId                     , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentLimit                  , InvalidRequest       , BAD_REQUEST ;
 InvalidDocumentOffset                 , InvalidRequest       , BAD_REQUEST ;
+InvalidEmbedder                       , InvalidRequest       , BAD_REQUEST ;
+InvalidHybridQuery                    , InvalidRequest       , BAD_REQUEST ;
 InvalidIndexLimit                     , InvalidRequest       , BAD_REQUEST ;
 InvalidIndexOffset                    , InvalidRequest       , BAD_REQUEST ;
 InvalidIndexPrimaryKey                , InvalidRequest       , BAD_REQUEST ;
@@ -233,6 +235,7 @@ InvalidSearchAttributesToRetrieve     , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchCropLength               , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchCropMarker               , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchFacets                   , InvalidRequest       , BAD_REQUEST ;
+InvalidSemanticRatio                  , InvalidRequest       , BAD_REQUEST ;
 InvalidFacetSearchFacetName           , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchFilter                   , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchHighlightPostTag         , InvalidRequest       , BAD_REQUEST ;
@@ -340,6 +343,7 @@ impl ErrorCode for milli::Error {
                     }
                     UserError::MissingDocumentField(_) => Code::InvalidDocumentFields,
                     UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
+                    UserError::TooManyEmbedders(_) => Code::InvalidSettingsEmbedders,
                     UserError::InvalidPromptForEmbeddings(..) => Code::InvalidSettingsEmbedders,
                     UserError::NoPrimaryKeyCandidateFound => Code::IndexPrimaryKeyNoCandidateFound,
                     UserError::MultiplePrimaryKeyCandidatesFound { .. } => {
@@ -363,6 +367,7 @@ impl ErrorCode for milli::Error {
                     UserError::InvalidMinTypoWordLenSetting(_, _) => {
                         Code::InvalidSettingsTypoTolerance
                     }
+                    UserError::InvalidEmbedder(_) => Code::InvalidEmbedder,
                     UserError::VectorEmbeddingError(_) => Code::VectorEmbeddingError,
                 }
             }

meilisearch/src/analytics/segment_analytics.rs

@@ -36,7 +36,7 @@ use crate::routes::{create_all_stats, Stats};
 use crate::search::{
     FacetSearchResult, MatchingStrategy, SearchQuery, SearchQueryWithIndex, SearchResult,
     DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
+    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
 };
 use crate::Opt;
 
@@ -586,6 +586,11 @@ pub struct SearchAggregator {
     // vector
     // The maximum number of floats in a vector request
     max_vector_size: usize,
+    // Whether the semantic ratio passed to a hybrid search equals the default ratio.
+    semantic_ratio: bool,
+    // Whether a non-default embedder was specified
+    embedder: bool,
+    hybrid: bool,
 
     // every time a search is done, we increment the counter linked to the used settings
     matching_strategy: HashMap<String, usize>,
@@ -639,6 +644,7 @@ impl SearchAggregator {
             crop_marker,
             matching_strategy,
             attributes_to_search_on,
+            hybrid,
         } = query;
 
         let mut ret = Self::default();
@@ -712,6 +718,12 @@ impl SearchAggregator {
         ret.show_ranking_score = *show_ranking_score;
         ret.show_ranking_score_details = *show_ranking_score_details;
 
+        if let Some(hybrid) = hybrid {
+            ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
+            ret.embedder = hybrid.embedder.is_some();
+            ret.hybrid = true;
+        }
+
         ret
     }
 
@@ -765,6 +777,9 @@ impl SearchAggregator {
             facets_total_number_of_facets,
             show_ranking_score,
             show_ranking_score_details,
+            semantic_ratio,
+            embedder,
+            hybrid,
         } = other;
 
         if self.timestamp.is_none() {
@@ -810,6 +825,9 @@ impl SearchAggregator {
 
         // vector
         self.max_vector_size = self.max_vector_size.max(max_vector_size);
+        self.semantic_ratio |= semantic_ratio;
+        self.hybrid |= hybrid;
+        self.embedder |= embedder;
 
         // pagination
         self.max_limit = self.max_limit.max(max_limit);
@@ -878,6 +896,9 @@ impl SearchAggregator {
             facets_total_number_of_facets,
             show_ranking_score,
             show_ranking_score_details,
+            semantic_ratio,
+            embedder,
+            hybrid,
         } = self;
 
         if total_received == 0 {
@@ -917,6 +938,11 @@ impl SearchAggregator {
                 "vector": {
                     "max_vector_size": max_vector_size,
                 },
+                "hybrid": {
+                    "enabled": hybrid,
+                    "semantic_ratio": semantic_ratio,
+                    "embedder": embedder,
+                },
                 "pagination": {
                    "max_limit": max_limit,
                    "max_offset": max_offset,
@@ -1012,6 +1038,7 @@ impl MultiSearchAggregator {
                     crop_marker: _,
                     matching_strategy: _,
                     attributes_to_search_on: _,
+                    hybrid: _,
                 } = query;
 
                 index_uid.as_str()
@@ -1158,6 +1185,7 @@ impl FacetSearchAggregator {
             filter,
             matching_strategy,
             attributes_to_search_on,
+            hybrid,
         } = query;
 
         let mut ret = Self::default();
@@ -1171,7 +1199,8 @@ impl FacetSearchAggregator {
             || vector.is_some()
             || filter.is_some()
             || *matching_strategy != MatchingStrategy::default()
-            || attributes_to_search_on.is_some();
+            || attributes_to_search_on.is_some()
+            || hybrid.is_some();
 
         ret
     }

meilisearch/src/routes/indexes/facet_search.rs

@@ -14,9 +14,9 @@ use crate::analytics::{Analytics, FacetSearchAggregator};
 use crate::extractors::authentication::policies::*;
 use crate::extractors::authentication::GuardedData;
 use crate::search::{
-    add_search_rules, perform_facet_search, MatchingStrategy, SearchQuery, DEFAULT_CROP_LENGTH,
+    add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, SearchQuery,
-    DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
+    DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
+    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
 };
 
 pub fn configure(cfg: &mut web::ServiceConfig) {
@@ -37,6 +37,8 @@ pub struct FacetSearchQuery {
     pub q: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchVector>)]
     pub vector: Option<Vec<f32>>,
+    #[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
+    pub hybrid: Option<HybridQuery>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchFilter>)]
     pub filter: Option<Value>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchMatchingStrategy>, default)]
@@ -96,6 +98,7 @@ impl From<FacetSearchQuery> for SearchQuery {
             filter,
             matching_strategy,
             attributes_to_search_on,
+            hybrid,
         } = value;
 
         SearchQuery {
@@ -120,6 +123,7 @@ impl From<FacetSearchQuery> for SearchQuery {
             matching_strategy,
             vector: vector.map(VectorQuery::Vector),
             attributes_to_search_on,
+            hybrid,
         }
     }
 }

meilisearch/src/routes/indexes/search.rs

@@ -8,7 +8,7 @@ use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
 use meilisearch_types::error::deserr_codes::*;
 use meilisearch_types::error::ResponseError;
 use meilisearch_types::index_uid::IndexUid;
-use meilisearch_types::milli::VectorQuery;
+use meilisearch_types::milli::{self, VectorQuery};
 use meilisearch_types::serde_cs::vec::CS;
 use serde_json::Value;
 
@@ -17,9 +17,9 @@ use crate::extractors::authentication::policies::*;
 use crate::extractors::authentication::GuardedData;
 use crate::extractors::sequential_extractor::SeqHandler;
 use crate::search::{
-    add_search_rules, perform_search, MatchingStrategy, SearchQuery, DEFAULT_CROP_LENGTH,
+    add_search_rules, perform_search, HybridQuery, MatchingStrategy, SearchQuery,
-    DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
+    DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
-    DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
+    DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
 };
 
 pub fn configure(cfg: &mut web::ServiceConfig) {
@@ -75,6 +75,10 @@ pub struct SearchQueryGet {
     matching_strategy: MatchingStrategy,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToSearchOn>)]
     pub attributes_to_search_on: Option<CS<String>>,
+    #[deserr(default, error = DeserrQueryParamError<InvalidHybridQuery>)]
+    pub hybrid_embedder: Option<String>,
+    #[deserr(default, error = DeserrQueryParamError<InvalidHybridQuery>)]
+    pub hybrid_semantic_ratio: Option<f32>,
 }
 
 impl From<SearchQueryGet> for SearchQuery {
@@ -87,6 +91,18 @@ impl From<SearchQueryGet> for SearchQuery {
             None => None,
         };
 
+        let hybrid = match (other.hybrid_embedder, other.hybrid_semantic_ratio) {
+            (None, None) => None,
+            (None, Some(semantic_ratio)) => Some(HybridQuery { semantic_ratio, embedder: None }),
+            (Some(embedder), None) => Some(HybridQuery {
+                semantic_ratio: DEFAULT_SEMANTIC_RATIO(),
+                embedder: Some(embedder),
+            }),
+            (Some(embedder), Some(semantic_ratio)) => {
+                Some(HybridQuery { semantic_ratio, embedder: Some(embedder) })
+            }
+        };
+
         Self {
             q: other.q,
             vector: other.vector.map(CS::into_inner).map(VectorQuery::Vector),
@@ -109,6 +125,7 @@ impl From<SearchQueryGet> for SearchQuery {
             crop_marker: other.crop_marker,
             matching_strategy: other.matching_strategy,
             attributes_to_search_on: other.attributes_to_search_on.map(|o| o.into_iter().collect()),
+            hybrid,
         }
     }
 }
@@ -159,6 +176,9 @@ pub async fn search_with_url_query(
 
     let index = index_scheduler.index(&index_uid)?;
     let features = index_scheduler.features();
+
+    embed(&mut query, index_scheduler.get_ref(), &index).await?;
+
     let search_result =
         tokio::task::spawn_blocking(move || perform_search(&index, query, features)).await?;
     if let Ok(ref search_result) = search_result {
@@ -213,22 +233,31 @@ pub async fn search_with_post(
 pub async fn embed(
     query: &mut SearchQuery,
     index_scheduler: &IndexScheduler,
-    index: &meilisearch_types::milli::Index,
+    index: &milli::Index,
 ) -> Result<(), ResponseError> {
     if let Some(VectorQuery::String(prompt)) = query.vector.take() {
         let embedder_configs = index.embedding_configs(&index.read_txn()?)?;
         let embedder = index_scheduler.embedders(embedder_configs)?;
 
-        /// FIXME: add error if no embedder, remove unwrap, support multiple embedders
+        let embedder_name = if let Some(HybridQuery {
+            semantic_ratio: _,
+            embedder: Some(embedder),
+        }) = &query.hybrid
+        {
+            embedder
+        } else {
+            "default"
+        };
+
         let embeddings = embedder
-            .get("default")
+            .get(embedder_name)
-            .unwrap()
+            .ok_or(milli::UserError::InvalidEmbedder(embedder_name.to_owned()))
+            .map_err(milli::Error::from)?
             .0
             .embed(vec![prompt])
             .await
-            .map_err(meilisearch_types::milli::vector::Error::from)
+            .map_err(milli::vector::Error::from)
-            .map_err(meilisearch_types::milli::UserError::from)
+            .map_err(milli::Error::from)?
-            .map_err(meilisearch_types::milli::Error::from)?
             .pop()
             .expect("No vector returned from embedding");
 

meilisearch/src/search.rs

@@ -36,6 +36,7 @@ pub const DEFAULT_CROP_LENGTH: fn() -> usize = || 10;
 pub const DEFAULT_CROP_MARKER: fn() -> String = || "…".to_string();
 pub const DEFAULT_HIGHLIGHT_PRE_TAG: fn() -> String = || "<em>".to_string();
 pub const DEFAULT_HIGHLIGHT_POST_TAG: fn() -> String = || "</em>".to_string();
+pub const DEFAULT_SEMANTIC_RATIO: fn() -> f32 = || 0.5;
 
 #[derive(Debug, Clone, Default, PartialEq, Deserr)]
 #[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
@@ -44,6 +45,8 @@ pub struct SearchQuery {
     pub q: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchVector>)]
     pub vector: Option<milli::VectorQuery>,
+    #[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
+    pub hybrid: Option<HybridQuery>,
     #[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSearchOffset>)]
     pub offset: usize,
     #[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSearchLimit>)]
@@ -84,6 +87,15 @@ pub struct SearchQuery {
     pub attributes_to_search_on: Option<Vec<String>>,
 }
 
+#[derive(Debug, Clone, Default, PartialEq, Deserr)]
+#[deserr(error = DeserrJsonError<InvalidHybridQuery>, rename_all = camelCase, deny_unknown_fields)]
+pub struct HybridQuery {
+    #[deserr(default, error = DeserrJsonError<InvalidSemanticRatio>, default = DEFAULT_SEMANTIC_RATIO())]
+    pub semantic_ratio: f32,
+    #[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
+    pub embedder: Option<String>,
+}
+
 impl SearchQuery {
     pub fn is_finite_pagination(&self) -> bool {
         self.page.or(self.hits_per_page).is_some()
@@ -103,6 +115,8 @@ pub struct SearchQueryWithIndex {
     pub q: Option<String>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchQ>)]
     pub vector: Option<VectorQuery>,
+    #[deserr(default, error = DeserrJsonError<InvalidHybridQuery>)]
+    pub hybrid: Option<HybridQuery>,
     #[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSearchOffset>)]
     pub offset: usize,
     #[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSearchLimit>)]
@@ -168,6 +182,7 @@ impl SearchQueryWithIndex {
             crop_marker,
             matching_strategy,
             attributes_to_search_on,
+            hybrid,
         } = self;
         (
             index_uid,
@@ -193,6 +208,7 @@ impl SearchQueryWithIndex {
                 crop_marker,
                 matching_strategy,
                 attributes_to_search_on,
+                hybrid,
                 // do not use ..Default::default() here,
                 // rather add any missing field from `SearchQuery` to `SearchQueryWithIndex`
             },

milli/src/error.rs

@@ -63,6 +63,8 @@ pub enum InternalError {
     InvalidMatchingWords,
     #[error(transparent)]
     ArroyError(#[from] arroy::Error),
+    #[error(transparent)]
+    VectorEmbeddingError(#[from] crate::vector::Error),
 }
 
 #[derive(Error, Debug)]
@@ -188,8 +190,23 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
     MissingDocumentField(#[from] crate::prompt::error::RenderPromptError),
     #[error(transparent)]
     InvalidPrompt(#[from] crate::prompt::error::NewPromptError),
-    #[error("Invalid prompt in for embeddings with name '{0}': {1}")]
+    #[error("Invalid prompt in for embeddings with name '{0}': {1}.")]
     InvalidPromptForEmbeddings(String, crate::prompt::error::NewPromptError),
+    #[error("Too many embedders in the configuration. Found {0}, but limited to 256.")]
+    TooManyEmbedders(usize),
+    #[error("Cannot find embedder with name {0}.")]
+    InvalidEmbedder(String),
+}
+
+impl From<crate::vector::Error> for Error {
+    fn from(value: crate::vector::Error) -> Self {
+        match value.fault() {
+            FaultSource::User => Error::UserError(value.into()),
+            FaultSource::Runtime => Error::InternalError(value.into()),
+            FaultSource::Bug => Error::InternalError(value.into()),
+            FaultSource::Undecided => Error::InternalError(value.into()),
+        }
+    }
 }
 
 impl From<arroy::Error> for Error {

milli/src/prompt/mod.rs

@@ -110,7 +110,6 @@ impl Prompt {
         };
 
         // render template with special object that's OK with `doc.*` and `fields.*`
-        /// FIXME: doesn't work for nested objects e.g. `doc.a.b`
         this.template
             .render(&template_checker::TemplateChecker)
             .map_err(NewPromptError::invalid_fields_in_template)?;
@@ -142,3 +141,80 @@ pub enum PromptFallbackStrategy {
     #[default]
     Error,
 }
+
+#[cfg(test)]
+mod test {
+    use super::Prompt;
+    use crate::error::FaultSource;
+    use crate::prompt::error::{NewPromptError, NewPromptErrorKind};
+
+    #[test]
+    fn default_template() {
+        // does not panic
+        Prompt::default();
+    }
+
+    #[test]
+    fn empty_template() {
+        Prompt::new("".into(), None, None).unwrap();
+    }
+
+    #[test]
+    fn template_ok() {
+        Prompt::new("{{doc.title}}: {{doc.overview}}".into(), None, None).unwrap();
+    }
+
+    #[test]
+    fn template_syntax() {
+        assert!(matches!(
+            Prompt::new("{{doc.title: {{doc.overview}}".into(), None, None),
+            Err(NewPromptError {
+                kind: NewPromptErrorKind::CannotParseTemplate(_),
+                fault: FaultSource::User
+            })
+        ));
+    }
+
+    #[test]
+    fn template_missing_doc() {
+        assert!(matches!(
+            Prompt::new("{{title}}: {{overview}}".into(), None, None),
+            Err(NewPromptError {
+                kind: NewPromptErrorKind::InvalidFieldsInTemplate(_),
+                fault: FaultSource::User
+            })
+        ));
+    }
+
+    #[test]
+    fn template_nested_doc() {
+        Prompt::new("{{doc.actor.firstName}}: {{doc.actor.lastName}}".into(), None, None).unwrap();
+    }
+
+    #[test]
+    fn template_fields() {
+        Prompt::new("{% for field in fields %}{{field}}{% endfor %}".into(), None, None).unwrap();
+    }
+
+    #[test]
+    fn template_fields_ok() {
+        Prompt::new(
+            "{% for field in fields %}{{field.name}}: {{field.value}}{% endfor %}".into(),
+            None,
+            None,
+        )
+        .unwrap();
+    }
+
+    #[test]
+    fn template_fields_invalid() {
+        assert!(matches!(
+            // intentionally garbled field
+            Prompt::new("{% for field in fields %}{{field.vaelu}} {% endfor %}".into(), None, None),
+            Err(NewPromptError {
+                kind: NewPromptErrorKind::InvalidFieldsInTemplate(_),
+                fault: FaultSource::User
+            })
+        ));
+    }
+}

milli/src/prompt/template_checker.rs

@@ -1,7 +1,7 @@
 use liquid::model::{
     ArrayView, DisplayCow, KStringCow, ObjectRender, ObjectSource, State, Value as LiquidValue,
 };
-use liquid::{ObjectView, ValueView};
+use liquid::{Object, ObjectView, ValueView};
 
 #[derive(Debug)]
 pub struct TemplateChecker;
@@ -31,11 +31,11 @@ impl ObjectView for DummyField {
     }
 
     fn values<'k>(&'k self) -> Box<dyn Iterator<Item = &'k dyn ValueView> + 'k> {
-        Box::new(std::iter::empty())
+        Box::new(vec![DUMMY_VALUE.as_view(), DUMMY_VALUE.as_view()].into_iter())
     }
 
     fn iter<'k>(&'k self) -> Box<dyn Iterator<Item = (KStringCow<'k>, &'k dyn ValueView)> + 'k> {
-        Box::new(std::iter::empty())
+        Box::new(self.keys().zip(self.values()))
     }
 
     fn contains_key(&self, index: &str) -> bool {
@@ -69,7 +69,12 @@ impl ValueView for DummyField {
     }
 
     fn query_state(&self, state: State) -> bool {
-        DUMMY_VALUE.query_state(state)
+        match state {
+            State::Truthy => true,
+            State::DefaultValue => false,
+            State::Empty => false,
+            State::Blank => false,
+        }
     }
 
     fn to_kstr(&self) -> KStringCow<'_> {
@@ -77,7 +82,10 @@ impl ValueView for DummyField {
     }
 
     fn to_value(&self) -> LiquidValue {
-        LiquidValue::Nil
+        let mut this = Object::new();
+        this.insert("name".into(), LiquidValue::Nil);
+        this.insert("value".into(), LiquidValue::Nil);
+        LiquidValue::Object(this)
     }
 
     fn as_object(&self) -> Option<&dyn ObjectView> {
@@ -103,7 +111,12 @@ impl ValueView for DummyFields {
     }
 
     fn query_state(&self, state: State) -> bool {
-        DUMMY_VALUE.query_state(state)
+        match state {
+            State::Truthy => true,
+            State::DefaultValue => false,
+            State::Empty => false,
+            State::Blank => false,
+        }
     }
 
     fn to_kstr(&self) -> KStringCow<'_> {
@@ -111,7 +124,7 @@ impl ValueView for DummyFields {
     }
 
     fn to_value(&self) -> LiquidValue {
-        LiquidValue::Nil
+        LiquidValue::Array(vec![DummyField.to_value()])
     }
 
     fn as_array(&self) -> Option<&dyn ArrayView> {
@@ -125,15 +138,15 @@ impl ArrayView for DummyFields {
     }
 
     fn size(&self) -> i64 {
-        i64::MAX
+        u16::MAX as i64
     }
 
     fn values<'k>(&'k self) -> Box<dyn Iterator<Item = &'k dyn ValueView> + 'k> {
-        Box::new(std::iter::empty())
+        Box::new(std::iter::once(DummyField.as_value()))
     }
 
-    fn contains_key(&self, _index: i64) -> bool {
+    fn contains_key(&self, index: i64) -> bool {
-        true
+        index < self.size()
     }
 
     fn get(&self, _index: i64) -> Option<&dyn ValueView> {
@@ -167,7 +180,8 @@ impl ObjectView for DummyDoc {
     }
 
     fn get<'s>(&'s self, _index: &str) -> Option<&'s dyn ValueView> {
-        Some(DUMMY_VALUE.as_view())
+        // Recursively sends itself
+        Some(self)
     }
 }
 
@@ -189,7 +203,12 @@ impl ValueView for DummyDoc {
     }
 
     fn query_state(&self, state: State) -> bool {
-        DUMMY_VALUE.query_state(state)
+        match state {
+            State::Truthy => true,
+            State::DefaultValue => false,
+            State::Empty => false,
+            State::Blank => false,
+        }
     }
 
     fn to_kstr(&self) -> KStringCow<'_> {

milli/src/search/new/mod.rs

@@ -516,7 +516,7 @@ pub fn execute_vector_search(
 ) -> Result<PartialSearchResult> {
     check_sort_criteria(ctx, sort_criteria.as_ref())?;
 
-    /// FIXME: input universe = universe & documents_with_vectors
+    // FIXME: input universe = universe & documents_with_vectors
     // for now if we're computing embeddings for ALL documents, we can assume that this is just universe
     let ranking_rules = get_ranking_rules_for_vector(
         ctx,

milli/src/update/index_documents/extract/extract_vector_points.rs

@@ -71,8 +71,8 @@ impl VectorStateDelta {
 pub fn extract_vector_points<R: io::Read + io::Seek>(
     obkv_documents: grenad::Reader<R>,
     indexer: GrenadParameters,
-    field_id_map: FieldsIdsMap,
+    field_id_map: &FieldsIdsMap,
-    prompt: Option<&Prompt>,
+    prompt: &Prompt,
 ) -> Result<ExtractedVectorPoints> {
     puffin::profile_function!();
 
@@ -142,14 +142,11 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
                         .any(|deladd| deladd.get(DelAdd::Addition).is_some());
                     if document_is_kept {
                         // becomes autogenerated
-                        match prompt {
+                        VectorStateDelta::NowGenerated(prompt.render(
-                            Some(prompt) => VectorStateDelta::NowGenerated(prompt.render(
+                            obkv,
-                                obkv,
+                            DelAdd::Addition,
-                                DelAdd::Addition,
+                            field_id_map,
-                                &field_id_map,
+                        )?)
-                            )?),
-                            None => VectorStateDelta::NowRemoved,
-                        }
                     } else {
                         VectorStateDelta::NowRemoved
                     }
@@ -162,26 +159,18 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
                         .any(|deladd| deladd.get(DelAdd::Addition).is_some());
 
                     if document_is_kept {
-                        match prompt {
+                        // Don't give up if the old prompt was failing
-                            Some(prompt) => {
+                        let old_prompt =
-                                // Don't give up if the old prompt was failing
+                            prompt.render(obkv, DelAdd::Deletion, field_id_map).unwrap_or_default();
-                                let old_prompt = prompt
+                        let new_prompt = prompt.render(obkv, DelAdd::Addition, field_id_map)?;
-                                    .render(obkv, DelAdd::Deletion, &field_id_map)
+                        if old_prompt != new_prompt {
-                                    .unwrap_or_default();
+                            log::trace!(
-                                let new_prompt =
+                                "🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
-                                    prompt.render(obkv, DelAdd::Addition, &field_id_map)?;
+                            );
-                                if old_prompt != new_prompt {
+                            VectorStateDelta::NowGenerated(new_prompt)
-                                    log::trace!(
+                        } else {
-                                        "🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
+                            log::trace!("⏭️ Prompt unmodified, skipping");
-                                    );
+                            VectorStateDelta::NoChange
-                                    VectorStateDelta::NowGenerated(new_prompt)
-                                } else {
-                                    log::trace!("⏭️ Prompt unmodified, skipping");
-                                    VectorStateDelta::NoChange
-                                }
-                            }
-                            // We no longer have a prompt, so we need to remove any existing vector
-                            None => VectorStateDelta::NowRemoved,
                         }
                     } else {
                         VectorStateDelta::NowRemoved
@@ -196,24 +185,16 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
                 .any(|deladd| deladd.get(DelAdd::Addition).is_some());
 
             if document_is_kept {
-                match prompt {
+                // Don't give up if the old prompt was failing
-                    Some(prompt) => {
+                let old_prompt =
-                        // Don't give up if the old prompt was failing
+                    prompt.render(obkv, DelAdd::Deletion, field_id_map).unwrap_or_default();
-                        let old_prompt = prompt
+                let new_prompt = prompt.render(obkv, DelAdd::Addition, field_id_map)?;
-                            .render(obkv, DelAdd::Deletion, &field_id_map)
+                if old_prompt != new_prompt {
-                            .unwrap_or_default();
+                    log::trace!("🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}");
-                        let new_prompt = prompt.render(obkv, DelAdd::Addition, &field_id_map)?;
+                    VectorStateDelta::NowGenerated(new_prompt)
-                        if old_prompt != new_prompt {
+                } else {
-                            log::trace!(
+                    log::trace!("⏭️ Prompt unmodified, skipping");
-                                "🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
+                    VectorStateDelta::NoChange
-                            );
-                            VectorStateDelta::NowGenerated(new_prompt)
-                        } else {
-                            log::trace!("⏭️ Prompt unmodified, skipping");
-                            VectorStateDelta::NoChange
-                        }
-                    }
-                    None => VectorStateDelta::NowRemoved,
                 }
             } else {
                 VectorStateDelta::NowRemoved
@@ -322,7 +303,7 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
     prompt_reader: grenad::Reader<R>,
     indexer: GrenadParameters,
     embedder: Arc<Embedder>,
-) -> Result<(grenad::Reader<BufReader<File>>, Option<usize>)> {
+) -> Result<grenad::Reader<BufReader<File>>> {
     let rt = tokio::runtime::Builder::new_current_thread().enable_io().enable_time().build()?;
 
     let n_chunks = embedder.chunk_count_hint(); // chunk level parellelism
@@ -341,8 +322,6 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
     let mut chunks_ids = Vec::with_capacity(n_chunks);
     let mut cursor = prompt_reader.into_cursor()?;
 
-    let mut expected_dimension = None;
-
     while let Some((key, value)) = cursor.move_on_next()? {
         let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
         // SAFETY: precondition, the grenad value was saved from a string
@@ -367,7 +346,6 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
                         .embed_chunks(std::mem::replace(&mut chunks, Vec::with_capacity(n_chunks))),
                 )
                 .map_err(crate::vector::Error::from)
-                .map_err(crate::UserError::from)
                 .map_err(crate::Error::from)?;
 
             for (docid, embeddings) in chunks_ids
@@ -376,7 +354,6 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
                 .zip(chunked_embeds.iter().flat_map(|embeds| embeds.iter()))
             {
                 state_writer.insert(docid.to_be_bytes(), cast_slice(embeddings.as_inner()))?;
-                expected_dimension = Some(embeddings.dimension());
             }
             chunks_ids.clear();
         }
@@ -387,7 +364,6 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
         let chunked_embeds = rt
             .block_on(embedder.embed_chunks(std::mem::take(&mut chunks)))
             .map_err(crate::vector::Error::from)
-            .map_err(crate::UserError::from)
             .map_err(crate::Error::from)?;
         for (docid, embeddings) in chunks_ids
             .iter()
@@ -395,7 +371,6 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
             .zip(chunked_embeds.iter().flat_map(|embeds| embeds.iter()))
         {
             state_writer.insert(docid.to_be_bytes(), cast_slice(embeddings.as_inner()))?;
-            expected_dimension = Some(embeddings.dimension());
         }
     }
 
@@ -403,14 +378,12 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
         let embeds = rt
             .block_on(embedder.embed(std::mem::take(&mut current_chunk)))
             .map_err(crate::vector::Error::from)
-            .map_err(crate::UserError::from)
             .map_err(crate::Error::from)?;
 
         for (docid, embeddings) in current_chunk_ids.iter().zip(embeds.iter()) {
             state_writer.insert(docid.to_be_bytes(), cast_slice(embeddings.as_inner()))?;
-            expected_dimension = Some(embeddings.dimension());
         }
     }
 
-    Ok((writer_into_reader(state_writer)?, expected_dimension))
+    writer_into_reader(state_writer)
 }

milli/src/update/index_documents/extract/mod.rs

@@ -292,43 +292,42 @@ fn send_original_documents_data(
     let documents_chunk_cloned = original_documents_chunk.clone();
     let lmdb_writer_sx_cloned = lmdb_writer_sx.clone();
     rayon::spawn(move || {
-        let (embedder, prompt) = embedders.get("default").cloned().unzip();
+        for (name, (embedder, prompt)) in embedders {
-        let result =
+            let result = extract_vector_points(
-            extract_vector_points(documents_chunk_cloned, indexer, field_id_map, prompt.as_deref());
+                documents_chunk_cloned.clone(),
-        match result {
+                indexer,
-            Ok(ExtractedVectorPoints { manual_vectors, remove_vectors, prompts }) => {
+                &field_id_map,
-                /// FIXME: support multiple embedders
+                &prompt,
-                let results = embedder.and_then(|embedder| {
+            );
-                    match extract_embeddings(prompts, indexer, embedder.clone()) {
+            match result {
+                Ok(ExtractedVectorPoints { manual_vectors, remove_vectors, prompts }) => {
+                    let embeddings = match extract_embeddings(prompts, indexer, embedder.clone()) {
                         Ok(results) => Some(results),
                         Err(error) => {
                             let _ = lmdb_writer_sx_cloned.send(Err(error));
                             None
                         }
-                    }
+                    };
-                });
+
-                let (embeddings, expected_dimension) = results.unzip();
+                    if !(remove_vectors.is_empty()
-                let expected_dimension = expected_dimension.flatten();
+                        && manual_vectors.is_empty()
-                if !(remove_vectors.is_empty()
+                        && embeddings.as_ref().map_or(true, |e| e.is_empty()))
-                    && manual_vectors.is_empty()
+                    {
-                    && embeddings.as_ref().map_or(true, |e| e.is_empty()))
-                {
-                    /// FIXME FIXME FIXME
-                    if expected_dimension.is_some() {
                         let _ = lmdb_writer_sx_cloned.send(Ok(TypedChunk::VectorPoints {
                             remove_vectors,
                             embeddings,
-                            /// FIXME: compute an expected dimension from the manual vectors if any
+                            expected_dimension: embedder.dimensions(),
-                            expected_dimension: expected_dimension.unwrap(),
                             manual_vectors,
+                            embedder_name: name,
                         }));
                     }
                 }
+
+                Err(error) => {
+                    let _ = lmdb_writer_sx_cloned.send(Err(error));
+                }
             }
-            Err(error) => {
+        }
-                let _ = lmdb_writer_sx_cloned.send(Err(error));
-            }
-        };
     });
 
     // TODO: create a custom internal error

milli/src/update/index_documents/mod.rs

@@ -435,7 +435,7 @@ where
         let mut word_docids = None;
         let mut exact_word_docids = None;
 
-        let mut dimension = None;
+        let mut dimension = HashMap::new();
 
         for result in lmdb_writer_rx {
             if (self.should_abort)() {
@@ -471,13 +471,15 @@ where
                     remove_vectors,
                     embeddings,
                     manual_vectors,
+                    embedder_name,
                 } => {
-                    dimension = Some(expected_dimension);
+                    dimension.insert(embedder_name.clone(), expected_dimension);
                     TypedChunk::VectorPoints {
                         remove_vectors,
                         embeddings,
                         expected_dimension,
                         manual_vectors,
+                        embedder_name,
                     }
                 }
                 otherwise => otherwise,
@@ -513,14 +515,22 @@ where
         self.index.put_primary_key(self.wtxn, &primary_key)?;
         let number_of_documents = self.index.number_of_documents(self.wtxn)?;
 
-        if let Some(dimension) = dimension {
+        for (embedder_name, dimension) in dimension {
             let wtxn = &mut *self.wtxn;
             let vector_arroy = self.index.vector_arroy;
+            /// FIXME: unwrap
+            let embedder_index =
+                self.index.embedder_category_id.get(wtxn, &embedder_name)?.unwrap();
             pool.install(|| {
-                /// FIXME: do for each embedder
+                let writer_index = (embedder_index as u16) << 8;
                 let mut rng = rand::rngs::StdRng::from_entropy();
                 for k in 0..=u8::MAX {
-                    let writer = arroy::Writer::prepare(wtxn, vector_arroy, k.into(), dimension)?;
+                    let writer = arroy::Writer::prepare(
+                        wtxn,
+                        vector_arroy,
+                        writer_index | (k as u16),
+                        dimension,
+                    )?;
                     if writer.is_empty(wtxn)? {
                         break;
                     }

milli/src/update/index_documents/typed_chunk.rs

@@ -47,6 +47,7 @@ pub(crate) enum TypedChunk {
         embeddings: Option<grenad::Reader<BufReader<File>>>,
         expected_dimension: usize,
         manual_vectors: grenad::Reader<BufReader<File>>,
+        embedder_name: String,
     },
     ScriptLanguageDocids(HashMap<(Script, Language), (RoaringBitmap, RoaringBitmap)>),
 }
@@ -100,8 +101,8 @@ impl TypedChunk {
             TypedChunk::GeoPoints(grenad) => {
                 format!("GeoPoints {{ number_of_entries: {} }}", grenad.len())
             }
-            TypedChunk::VectorPoints{ remove_vectors, manual_vectors, embeddings, expected_dimension } => {
+            TypedChunk::VectorPoints{ remove_vectors, manual_vectors, embeddings, expected_dimension, embedder_name } => {
-                format!("VectorPoints {{ remove_vectors: {}, manual_vectors: {}, embeddings: {}, dimension: {} }}", remove_vectors.len(), manual_vectors.len(), embeddings.as_ref().map(|e| e.len()).unwrap_or_default(), expected_dimension)
+                format!("VectorPoints {{ remove_vectors: {}, manual_vectors: {}, embeddings: {}, dimension: {}, embedder_name: {} }}", remove_vectors.len(), manual_vectors.len(), embeddings.as_ref().map(|e| e.len()).unwrap_or_default(), expected_dimension, embedder_name)
             }
             TypedChunk::ScriptLanguageDocids(sl_map) => {
                 format!("ScriptLanguageDocids {{ number_of_entries: {} }}", sl_map.len())
@@ -360,12 +361,20 @@ pub(crate) fn write_typed_chunk_into_index(
             manual_vectors,
             embeddings,
             expected_dimension,
+            embedder_name,
         } => {
-            /// FIXME: allow customizing distance
+            /// FIXME: unwrap
+            let embedder_index = index.embedder_category_id.get(wtxn, &embedder_name)?.unwrap();
+            let writer_index = (embedder_index as u16) << 8;
+            // FIXME: allow customizing distance
             let writers: std::result::Result<Vec<_>, _> = (0..=u8::MAX)
                 .map(|k| {
-                    /// FIXME: allow customizing index and then do index << 8 + k
+                    arroy::Writer::prepare(
-                    arroy::Writer::prepare(wtxn, index.vector_arroy, k.into(), expected_dimension)
+                        wtxn,
+                        index.vector_arroy,
+                        writer_index | (k as u16),
+                        expected_dimension,
+                    )
                 })
                 .collect();
             let writers = writers?;
@@ -456,7 +465,7 @@ pub(crate) fn write_typed_chunk_into_index(
                 }
             }
 
-            log::debug!("There are 🤷‍♀️ entries in the arroy so far");
+            log::debug!("Finished vector chunk for {}", embedder_name);
         }
         TypedChunk::ScriptLanguageDocids(sl_map) => {
             for (key, (deletion, addition)) in sl_map {

milli/src/update/settings.rs

@@ -431,7 +431,6 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
                 let embedder = Arc::new(
                     Embedder::new(embedder_options.clone())
                         .map_err(crate::vector::Error::from)
-                        .map_err(crate::UserError::from)
                         .map_err(crate::Error::from)?,
                 );
                 Ok((name, (embedder, prompt)))
@@ -976,6 +975,19 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
                         Setting::NotSet => Some((name, EmbeddingSettings::default().into())),
                     })
                     .collect();
+
+                self.index.embedder_category_id.clear(self.wtxn)?;
+                for (index, (embedder_name, _)) in new_configs.iter().enumerate() {
+                    self.index.embedder_category_id.put_with_flags(
+                        self.wtxn,
+                        heed::PutFlags::APPEND,
+                        embedder_name,
+                        &index
+                            .try_into()
+                            .map_err(|_| UserError::TooManyEmbedders(new_configs.len()))?,
+                    )?;
+                }
+
                 if new_configs.is_empty() {
                     self.index.delete_embedding_configs(self.wtxn)?;
                 } else {
@@ -1062,7 +1074,7 @@ fn validate_prompt(
     match new {
         Setting::Set(EmbeddingSettings {
             embedder_options,
-            prompt:
+            document_template:
                 Setting::Set(PromptSettings { template: Setting::Set(template), strategy, fallback }),
         }) => {
             // validate
@@ -1072,7 +1084,7 @@ fn validate_prompt(
 
             Ok(Setting::Set(EmbeddingSettings {
                 embedder_options,
-                prompt: Setting::Set(PromptSettings {
+                document_template: Setting::Set(PromptSettings {
                     template: Setting::Set(template),
                     strategy,
                     fallback,

milli/src/vector/error.rs

@@ -65,6 +65,8 @@ pub enum EmbedErrorKind {
     OpenAiTooManyTokens(OpenAiError),
     #[error("received unhandled HTTP status code {0} from OpenAI")]
     OpenAiUnhandledStatusCode(u16),
+    #[error("attempt to embed the following text in a configuration where embeddings must be user provided: {0:?}")]
+    ManualEmbed(String),
 }
 
 impl EmbedError {
@@ -111,6 +113,10 @@ impl EmbedError {
     pub(crate) fn openai_unhandled_status_code(code: u16) -> EmbedError {
         Self { kind: EmbedErrorKind::OpenAiUnhandledStatusCode(code), fault: FaultSource::Bug }
     }
+
+    pub(crate) fn embed_on_manual_embedder(texts: String) -> EmbedError {
+        Self { kind: EmbedErrorKind::ManualEmbed(texts), fault: FaultSource::User }
+    }
 }
 
 #[derive(Debug, thiserror::Error)]
@@ -170,6 +176,13 @@ impl NewEmbedderError {
         Self { kind: NewEmbedderErrorKind::LoadModel(inner), fault: FaultSource::Runtime }
     }
 
+    pub fn hf_could_not_determine_dimension(inner: EmbedError) -> NewEmbedderError {
+        Self {
+            kind: NewEmbedderErrorKind::CouldNotDetermineDimension(inner),
+            fault: FaultSource::Runtime,
+        }
+    }
+
     pub fn openai_initialize_web_client(inner: reqwest::Error) -> Self {
         Self { kind: NewEmbedderErrorKind::InitWebClient(inner), fault: FaultSource::Runtime }
     }
@@ -219,6 +232,8 @@ pub enum NewEmbedderErrorKind {
     NewApiFail(ApiError),
     #[error("fetching file from HG_HUB failed: {0}")]
     ApiGet(ApiError),
+    #[error("could not determine model dimensions: test embedding failed with {0}")]
+    CouldNotDetermineDimension(EmbedError),
     #[error("loading model failed: {0}")]
     LoadModel(candle_core::Error),
     // openai

milli/src/vector/hf.rs

@@ -62,6 +62,7 @@ pub struct Embedder {
     model: BertModel,
     tokenizer: Tokenizer,
     options: EmbedderOptions,
+    dimensions: usize,
 }
 
 impl std::fmt::Debug for Embedder {
@@ -126,10 +127,17 @@ impl Embedder {
             tokenizer.with_padding(Some(pp));
         }
 
-        Ok(Self { model, tokenizer, options })
+        let mut this = Self { model, tokenizer, options, dimensions: 0 };
+
+        let embeddings = this
+            .embed(vec!["test".into()])
+            .map_err(NewEmbedderError::hf_could_not_determine_dimension)?;
+        this.dimensions = embeddings.first().unwrap().dimension();
+
+        Ok(this)
     }
 
-    pub async fn embed(
+    pub fn embed(
         &self,
         mut texts: Vec<String>,
     ) -> std::result::Result<Vec<Embeddings<f32>>, EmbedError> {
@@ -170,12 +178,11 @@ impl Embedder {
         Ok(embeddings.into_iter().map(Embeddings::from_single_embedding).collect())
     }
 
-    pub async fn embed_chunks(
+    pub fn embed_chunks(
         &self,
         text_chunks: Vec<Vec<String>>,
     ) -> std::result::Result<Vec<Vec<Embeddings<f32>>>, EmbedError> {
-        futures::future::try_join_all(text_chunks.into_iter().map(|prompts| self.embed(prompts)))
+        text_chunks.into_iter().map(|prompts| self.embed(prompts)).collect()
-            .await
     }
 
     pub fn chunk_count_hint(&self) -> usize {
@@ -185,6 +192,10 @@ impl Embedder {
     pub fn prompt_count_in_chunk_hint(&self) -> usize {
         std::thread::available_parallelism().map(|x| x.get()).unwrap_or(8)
     }
+
+    pub fn dimensions(&self) -> usize {
+        self.dimensions
+    }
 }
 
 fn normalize_l2(v: &Tensor) -> Result<Tensor, candle_core::Error> {

milli/src/vector/mod.rs

@@ -3,6 +3,7 @@ use crate::prompt::PromptData;
 
 pub mod error;
 pub mod hf;
+pub mod manual;
 pub mod openai;
 pub mod settings;
 
@@ -67,6 +68,7 @@ impl<F> Embeddings<F> {
 pub enum Embedder {
     HuggingFace(hf::Embedder),
     OpenAi(openai::Embedder),
+    UserProvided(manual::Embedder),
 }
 
 #[derive(Debug, Clone, Default, serde::Deserialize, serde::Serialize)]
@@ -80,6 +82,7 @@ pub struct EmbeddingConfig {
 pub enum EmbedderOptions {
     HuggingFace(hf::EmbedderOptions),
     OpenAi(openai::EmbedderOptions),
+    UserProvided(manual::EmbedderOptions),
 }
 
 impl Default for EmbedderOptions {
@@ -93,7 +96,7 @@ impl EmbedderOptions {
         Self::HuggingFace(hf::EmbedderOptions::new())
     }
 
-    pub fn openai(api_key: String) -> Self {
+    pub fn openai(api_key: Option<String>) -> Self {
         Self::OpenAi(openai::EmbedderOptions::with_default_model(api_key))
     }
 }
@@ -103,6 +106,9 @@ impl Embedder {
         Ok(match options {
             EmbedderOptions::HuggingFace(options) => Self::HuggingFace(hf::Embedder::new(options)?),
             EmbedderOptions::OpenAi(options) => Self::OpenAi(openai::Embedder::new(options)?),
+            EmbedderOptions::UserProvided(options) => {
+                Self::UserProvided(manual::Embedder::new(options))
+            }
         })
     }
 
@@ -111,8 +117,9 @@ impl Embedder {
         texts: Vec<String>,
     ) -> std::result::Result<Vec<Embeddings<f32>>, EmbedError> {
         match self {
-            Embedder::HuggingFace(embedder) => embedder.embed(texts).await,
+            Embedder::HuggingFace(embedder) => embedder.embed(texts),
             Embedder::OpenAi(embedder) => embedder.embed(texts).await,
+            Embedder::UserProvided(embedder) => embedder.embed(texts),
         }
     }
 
@@ -121,8 +128,9 @@ impl Embedder {
         text_chunks: Vec<Vec<String>>,
     ) -> std::result::Result<Vec<Vec<Embeddings<f32>>>, EmbedError> {
         match self {
-            Embedder::HuggingFace(embedder) => embedder.embed_chunks(text_chunks).await,
+            Embedder::HuggingFace(embedder) => embedder.embed_chunks(text_chunks),
             Embedder::OpenAi(embedder) => embedder.embed_chunks(text_chunks).await,
+            Embedder::UserProvided(embedder) => embedder.embed_chunks(text_chunks),
         }
     }
 
@@ -130,6 +138,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.chunk_count_hint(),
             Embedder::OpenAi(embedder) => embedder.chunk_count_hint(),
+            Embedder::UserProvided(_) => 1,
         }
     }
 
@@ -137,6 +146,15 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.prompt_count_in_chunk_hint(),
             Embedder::OpenAi(embedder) => embedder.prompt_count_in_chunk_hint(),
+            Embedder::UserProvided(_) => 1,
+        }
+    }
+
+    pub fn dimensions(&self) -> usize {
+        match self {
+            Embedder::HuggingFace(embedder) => embedder.dimensions(),
+            Embedder::OpenAi(embedder) => embedder.dimensions(),
+            Embedder::UserProvided(embedder) => embedder.dimensions(),
         }
     }
 }

milli/src/vector/openai.rs

@@ -15,7 +15,7 @@ pub struct Embedder {
 
 #[derive(Debug, Clone, Hash, PartialEq, Eq, serde::Deserialize, serde::Serialize)]
 pub struct EmbedderOptions {
-    pub api_key: String,
+    pub api_key: Option<String>,
     pub embedding_model: EmbeddingModel,
 }
 
@@ -68,11 +68,11 @@ impl EmbeddingModel {
 pub const OPENAI_EMBEDDINGS_URL: &str = "https://api.openai.com/v1/embeddings";
 
 impl EmbedderOptions {
-    pub fn with_default_model(api_key: String) -> Self {
+    pub fn with_default_model(api_key: Option<String>) -> Self {
         Self { api_key, embedding_model: Default::default() }
     }
 
-    pub fn with_embedding_model(api_key: String, embedding_model: EmbeddingModel) -> Self {
+    pub fn with_embedding_model(api_key: Option<String>, embedding_model: EmbeddingModel) -> Self {
         Self { api_key, embedding_model }
     }
 }
@@ -80,9 +80,14 @@ impl EmbedderOptions {
 impl Embedder {
     pub fn new(options: EmbedderOptions) -> Result<Self, NewEmbedderError> {
         let mut headers = reqwest::header::HeaderMap::new();
+        let mut inferred_api_key = Default::default();
+        let api_key = options.api_key.as_ref().unwrap_or_else(|| {
+            inferred_api_key = infer_api_key();
+            &inferred_api_key
+        });
         headers.insert(
             reqwest::header::AUTHORIZATION,
-            reqwest::header::HeaderValue::from_str(&format!("Bearer {}", &options.api_key))
+            reqwest::header::HeaderValue::from_str(&format!("Bearer {}", api_key))
                 .map_err(NewEmbedderError::openai_invalid_api_key_format)?,
         );
         headers.insert(
@@ -315,6 +320,10 @@ impl Embedder {
     pub fn prompt_count_in_chunk_hint(&self) -> usize {
         10
     }
+
+    pub fn dimensions(&self) -> usize {
+        self.options.embedding_model.dimensions()
+    }
 }
 
 // retrying in case of failure
@@ -414,3 +423,9 @@ struct OpenAiEmbedding {
     // object: String,
     // index: usize,
 }
+
+fn infer_api_key() -> String {
+    std::env::var("MEILI_OPENAI_API_KEY")
+        .or_else(|_| std::env::var("OPENAI_API_KEY"))
+        .unwrap_or_default()
+}

milli/src/vector/settings.rs

@@ -15,14 +15,14 @@ pub struct EmbeddingSettings {
     pub embedder_options: Setting<EmbedderSettings>,
     #[serde(default, skip_serializing_if = "Setting::is_not_set")]
     #[deserr(default)]
-    pub prompt: Setting<PromptSettings>,
+    pub document_template: Setting<PromptSettings>,
 }
 
 impl EmbeddingSettings {
     pub fn apply(&mut self, new: Self) {
-        let EmbeddingSettings { embedder_options, prompt } = new;
+        let EmbeddingSettings { embedder_options, document_template: prompt } = new;
         self.embedder_options.apply(embedder_options);
-        self.prompt.apply(prompt);
+        self.document_template.apply(prompt);
     }
 }
 
@@ -30,7 +30,7 @@ impl From<EmbeddingConfig> for EmbeddingSettings {
     fn from(value: EmbeddingConfig) -> Self {
         Self {
             embedder_options: Setting::Set(value.embedder_options.into()),
-            prompt: Setting::Set(value.prompt.into()),
+            document_template: Setting::Set(value.prompt.into()),
         }
     }
 }
@@ -38,7 +38,7 @@ impl From<EmbeddingConfig> for EmbeddingSettings {
 impl From<EmbeddingSettings> for EmbeddingConfig {
     fn from(value: EmbeddingSettings) -> Self {
         let mut this = Self::default();
-        let EmbeddingSettings { embedder_options, prompt } = value;
+        let EmbeddingSettings { embedder_options, document_template: prompt } = value;
         if let Some(embedder_options) = embedder_options.set() {
             this.embedder_options = embedder_options.into();
         }
@@ -105,6 +105,7 @@ impl From<PromptSettings> for PromptData {
 pub enum EmbedderSettings {
     HuggingFace(Setting<HfEmbedderSettings>),
     OpenAi(Setting<OpenAiEmbedderSettings>),
+    UserProvided(UserProvidedSettings),
 }
 
 impl<E> Deserr<E> for EmbedderSettings
@@ -145,11 +146,17 @@ where
                             location.push_key(&k),
                         )?,
                     ))),
+                    "userProvided" => Ok(EmbedderSettings::UserProvided(
+                        UserProvidedSettings::deserialize_from_value(
+                            v.into_value(),
+                            location.push_key(&k),
+                        )?,
+                    )),
                     other => Err(deserr::take_cf_content(E::error::<V>(
                         None,
                         deserr::ErrorKind::UnknownKey {
                             key: other,
-                            accepted: &["huggingFace", "openAi"],
+                            accepted: &["huggingFace", "openAi", "userProvided"],
                         },
                         location,
                     ))),
@@ -182,6 +189,9 @@ impl From<crate::vector::EmbedderOptions> for EmbedderSettings {
             crate::vector::EmbedderOptions::OpenAi(openai) => {
                 Self::OpenAi(Setting::Set(openai.into()))
             }
+            crate::vector::EmbedderOptions::UserProvided(user_provided) => {
+                Self::UserProvided(user_provided.into())
+            }
         }
     }
 }
@@ -192,9 +202,12 @@ impl From<EmbedderSettings> for crate::vector::EmbedderOptions {
             EmbedderSettings::HuggingFace(Setting::Set(hf)) => Self::HuggingFace(hf.into()),
             EmbedderSettings::HuggingFace(_setting) => Self::HuggingFace(Default::default()),
             EmbedderSettings::OpenAi(Setting::Set(ai)) => Self::OpenAi(ai.into()),
-            EmbedderSettings::OpenAi(_setting) => Self::OpenAi(
+            EmbedderSettings::OpenAi(_setting) => {
-                crate::vector::openai::EmbedderOptions::with_default_model(infer_api_key()),
+                Self::OpenAi(crate::vector::openai::EmbedderOptions::with_default_model(None))
-            ),
+            }
+            EmbedderSettings::UserProvided(user_provided) => {
+                Self::UserProvided(user_provided.into())
+            }
         }
     }
 }
@@ -286,7 +299,7 @@ impl OpenAiEmbedderSettings {
 impl From<crate::vector::openai::EmbedderOptions> for OpenAiEmbedderSettings {
     fn from(value: crate::vector::openai::EmbedderOptions) -> Self {
         Self {
-            api_key: Setting::Set(value.api_key),
+            api_key: value.api_key.map(Setting::Set).unwrap_or(Setting::Reset),
             embedding_model: Setting::Set(value.embedding_model),
         }
     }
@@ -295,14 +308,25 @@ impl From<crate::vector::openai::EmbedderOptions> for OpenAiEmbedderSettings {
 impl From<OpenAiEmbedderSettings> for crate::vector::openai::EmbedderOptions {
     fn from(value: OpenAiEmbedderSettings) -> Self {
         let OpenAiEmbedderSettings { api_key, embedding_model } = value;
-        Self {
+        Self { api_key: api_key.set(), embedding_model: embedding_model.set().unwrap_or_default() }
-            api_key: api_key.set().unwrap_or_else(infer_api_key),
-            embedding_model: embedding_model.set().unwrap_or_default(),
-        }
     }
 }
 
-fn infer_api_key() -> String {
+#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
-    /// FIXME: get key from instance options?
+#[serde(deny_unknown_fields, rename_all = "camelCase")]
-    std::env::var("MEILI_OPENAI_API_KEY").unwrap_or_default()
+#[deserr(rename_all = camelCase, deny_unknown_fields)]
+pub struct UserProvidedSettings {
+    pub dimensions: usize,
+}
+
+impl From<UserProvidedSettings> for crate::vector::manual::EmbedderOptions {
+    fn from(value: UserProvidedSettings) -> Self {
+        Self { dimensions: value.dimensions }
+    }
+}
+
+impl From<crate::vector::manual::EmbedderOptions> for UserProvidedSettings {
+    fn from(value: crate::vector::manual::EmbedderOptions) -> Self {
+        Self { dimensions: value.dimensions }
+    }
 }