Only insert facets in bulks no more incrementally

4318: Hide embedders r=ManyTheFish a=dureuill

Hides `embedders` when it is an empty dictionary.

Manual tests:

- getting settings with empty embedders: not displayed
- getting settings with non-empty embedders: displayed like before
- dump with empty embedders: can be imported
- dump with non-empty embedders: can be imported

Co-authored-by: Louis Dureuil <louis@meilisearch.com>

Cargo.lock

@@ -383,7 +383,7 @@ dependencies = [
 [[package]]
 name = "arroy"
 version = "0.1.0"
-source = "git+https://github.com/meilisearch/arroy.git#4f193fd534acd357b65bfe9eec4b3fed8ece2007"
+source = "git+https://github.com/meilisearch/arroy.git#d372648212e561a4845077cdb9239423d78655a2"
 dependencies = [
  "bytemuck",
  "byteorder",
@@ -1592,9 +1592,6 @@ name = "esaxx-rs"
 version = "0.1.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d817e038c30374a4bcb22f94d0a8a0e216958d4c3dcde369b1439fec4bdda6e6"
-dependencies = [
- "cc",
-]
 
 [[package]]
 name = "fancy-regex"
@@ -5313,11 +5310,9 @@ version = "0.14.1"
 source = "git+https://github.com/huggingface/tokenizers.git?tag=v0.14.1#6357206cdcce4d78ffb1e0372feb456caea09375"
 dependencies = [
  "aho-corasick",
- "clap",
  "derive_builder",
  "esaxx-rs",
  "getrandom",
- "indicatif",
  "itertools 0.11.0",
  "lazy_static",
  "log",

index-scheduler/src/batch.rs

@@ -936,8 +936,8 @@ impl IndexScheduler {
                 };
 
                 // the index operation can take a long time, so save this handle to make it available to the search for the duration of the tick
-                *self.currently_updating_index.write().unwrap() =
-                    Some((index_uid.clone(), index.clone()));
+                self.index_mapper
+                    .set_currently_updating_index(Some((index_uid.clone(), index.clone())));
 
                 let mut index_wtxn = index.write_txn()?;
                 let tasks = self.apply_index_operation(&mut index_wtxn, &index, op)?;
@@ -1351,9 +1351,6 @@ impl IndexScheduler {
 
                 for (task, (_, settings)) in tasks.iter_mut().zip(settings) {
                     let checked_settings = settings.clone().check();
-                    if matches!(checked_settings.embedders, milli::update::Setting::Set(_)) {
-                        self.features().check_vector("Passing `embedders` in settings")?
-                    }
                     task.details = Some(Details::SettingsUpdate { settings: Box::new(settings) });
                     apply_settings_to_builder(&checked_settings, &mut builder);
 

index-scheduler/src/index_mapper/mod.rs

@@ -69,6 +69,10 @@ pub struct IndexMapper {
     /// Whether we open a meilisearch index with the MDB_WRITEMAP option or not.
     enable_mdb_writemap: bool,
     pub indexer_config: Arc<IndexerConfig>,
+
+    /// A few types of long running batches of tasks that act on a single index set this field
+    /// so that a handle to the index is available from other threads (search) in an optimized manner.
+    currently_updating_index: Arc<RwLock<Option<(String, Index)>>>,
 }
 
 /// Whether the index is available for use or is forbidden to be inserted back in the index map
@@ -151,6 +155,7 @@ impl IndexMapper {
             index_growth_amount,
             enable_mdb_writemap,
             indexer_config: Arc::new(indexer_config),
+            currently_updating_index: Default::default(),
         })
     }
 
@@ -303,6 +308,14 @@ impl IndexMapper {
 
     /// Return an index, may open it if it wasn't already opened.
     pub fn index(&self, rtxn: &RoTxn, name: &str) -> Result<Index> {
+        if let Some((current_name, current_index)) =
+            self.currently_updating_index.read().unwrap().as_ref()
+        {
+            if current_name == name {
+                return Ok(current_index.clone());
+            }
+        }
+
         let uuid = self
             .index_mapping
             .get(rtxn, name)?
@@ -474,4 +487,8 @@ impl IndexMapper {
     pub fn indexer_config(&self) -> &IndexerConfig {
         &self.indexer_config
     }
+
+    pub fn set_currently_updating_index(&self, index: Option<(String, Index)>) {
+        *self.currently_updating_index.write().unwrap() = index;
+    }
 }

index-scheduler/src/insta_snapshot.rs

@@ -42,7 +42,6 @@ pub fn snapshot_index_scheduler(scheduler: &IndexScheduler) -> String {
         test_breakpoint_sdr: _,
         planned_failures: _,
         run_loop_iteration: _,
-        currently_updating_index: _,
         embedders: _,
     } = scheduler;
 

index-scheduler/src/lib.rs

@@ -351,10 +351,6 @@ pub struct IndexScheduler {
     /// The path to the version file of Meilisearch.
     pub(crate) version_file_path: PathBuf,
 
-    /// A few types of long running batches of tasks that act on a single index set this field
-    /// so that a handle to the index is available from other threads (search) in an optimized manner.
-    currently_updating_index: Arc<RwLock<Option<(String, Index)>>>,
-
     embedders: Arc<RwLock<HashMap<EmbedderOptions, Arc<Embedder>>>>,
 
     // ================= test
@@ -403,7 +399,6 @@ impl IndexScheduler {
             version_file_path: self.version_file_path.clone(),
             webhook_url: self.webhook_url.clone(),
             webhook_authorization_header: self.webhook_authorization_header.clone(),
-            currently_updating_index: self.currently_updating_index.clone(),
             embedders: self.embedders.clone(),
             #[cfg(test)]
             test_breakpoint_sdr: self.test_breakpoint_sdr.clone(),
@@ -504,7 +499,6 @@ impl IndexScheduler {
             version_file_path: options.version_file_path,
             webhook_url: options.webhook_url,
             webhook_authorization_header: options.webhook_authorization_header,
-            currently_updating_index: Arc::new(RwLock::new(None)),
             embedders: Default::default(),
 
             #[cfg(test)]
@@ -688,13 +682,6 @@ impl IndexScheduler {
     /// If you need to fetch information from or perform an action on all indexes,
     /// see the `try_for_each_index` function.
     pub fn index(&self, name: &str) -> Result<Index> {
-        if let Some((current_name, current_index)) =
-            self.currently_updating_index.read().unwrap().as_ref()
-        {
-            if current_name == name {
-                return Ok(current_index.clone());
-            }
-        }
         let rtxn = self.env.read_txn()?;
         self.index_mapper.index(&rtxn, name)
     }
@@ -1175,7 +1162,7 @@ impl IndexScheduler {
         };
 
         // Reset the currently updating index to relinquish the index handle
-        *self.currently_updating_index.write().unwrap() = None;
+        self.index_mapper.set_currently_updating_index(None);
 
         #[cfg(test)]
         self.maybe_fail(tests::FailureLocation::AcquiringWtxn)?;

meilisearch-types/src/error.rs

@@ -344,7 +344,10 @@ impl ErrorCode for milli::Error {
                         Code::InvalidDocumentId
                     }
                     UserError::MissingDocumentField(_) => Code::InvalidDocumentFields,
-                    UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
+                    UserError::InvalidFieldForSource { .. }
+                    | UserError::MissingFieldForSource { .. }
+                    | UserError::InvalidOpenAiModel { .. }
+                    | UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
                     UserError::TooManyEmbedders(_) => Code::InvalidSettingsEmbedders,
                     UserError::InvalidPromptForEmbeddings(..) => Code::InvalidSettingsEmbedders,
                     UserError::NoPrimaryKeyCandidateFound => Code::IndexPrimaryKeyNoCandidateFound,

meilisearch-types/src/settings.rs

@@ -318,6 +318,21 @@ impl Settings<Unchecked> {
             _kind: PhantomData,
         }
     }
+
+    pub fn validate(self) -> Result<Self, milli::Error> {
+        self.validate_embedding_settings()
+    }
+
+    fn validate_embedding_settings(mut self) -> Result<Self, milli::Error> {
+        let Setting::Set(mut configs) = self.embedders else { return Ok(self) };
+        for (name, config) in configs.iter_mut() {
+            let config_to_check = std::mem::take(config);
+            let checked_config = milli::update::validate_embedding_settings(config_to_check, name)?;
+            *config = checked_config
+        }
+        self.embedders = Setting::Set(configs);
+        Ok(self)
+    }
 }
 
 #[derive(Debug, Clone, Serialize, Deserialize)]
@@ -585,11 +600,12 @@ pub fn settings(
         ),
     };
 
-    let embedders = index
+    let embedders: BTreeMap<_, _> = index
         .embedding_configs(rtxn)?
         .into_iter()
         .map(|(name, config)| (name, Setting::Set(config.into())))
         .collect();
+    let embedders = if embedders.is_empty() { Setting::NotSet } else { Setting::Set(embedders) };
 
     Ok(Settings {
         displayed_attributes: match displayed_attributes {
@@ -611,15 +627,12 @@ pub fn settings(
             Some(field) => Setting::Set(field),
             None => Setting::Reset,
         },
-        proximity_precision: match proximity_precision {
-            Some(precision) => Setting::Set(precision),
-            None => Setting::Reset,
-        },
+        proximity_precision: Setting::Set(proximity_precision.unwrap_or_default()),
         synonyms: Setting::Set(synonyms),
         typo_tolerance: Setting::Set(typo_tolerance),
         faceting: Setting::Set(faceting),
         pagination: Setting::Set(pagination),
-        embedders: Setting::Set(embedders),
+        embedders,
         _kind: PhantomData,
     })
 }
@@ -720,10 +733,11 @@ impl From<RankingRuleView> for Criterion {
     }
 }
 
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Deserr, Serialize, Deserialize)]
+#[derive(Default, Debug, Clone, Copy, PartialEq, Eq, Deserr, Serialize, Deserialize)]
 #[serde(deny_unknown_fields, rename_all = "camelCase")]
 #[deserr(error = DeserrJsonError<InvalidSettingsProximityPrecision>, rename_all = camelCase, deny_unknown_fields)]
 pub enum ProximityPrecisionView {
+    #[default]
     ByWord,
     ByAttribute,
 }

meilisearch/Cargo.toml

@@ -154,5 +154,5 @@ greek = ["meilisearch-types/greek"]
 khmer = ["meilisearch-types/khmer"]
 
 [package.metadata.mini-dashboard]
-assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.11/build.zip"
-sha1 = "83cd44ed1e5f97ecb581dc9f958a63f4ccc982d9"
+assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.12/build.zip"
+sha1 = "acfe9a018c93eb0604ea87ee87bff7df5474e18e"

meilisearch/src/routes/indexes/settings.rs

@@ -90,6 +90,11 @@ macro_rules! make_setting_route {
                     ..Default::default()
                 };
 
+                let new_settings = $crate::routes::indexes::settings::validate_settings(
+                    new_settings,
+                    &index_scheduler,
+                )?;
+
                 let allow_index_creation =
                     index_scheduler.filters().allow_index_creation(&index_uid);
 
@@ -453,7 +458,7 @@ make_setting_route!(
             json!({
                 "proximity_precision": {
                     "set": precision.is_some(),
-                    "value": precision,
+                    "value": precision.unwrap_or_default(),
                 }
             }),
             Some(req),
@@ -582,13 +587,13 @@ fn embedder_analytics(
         for source in s
             .values()
             .filter_map(|config| config.clone().set())
-            .filter_map(|config| config.embedder_options.set())
+            .filter_map(|config| config.source.set())
         {
-            use meilisearch_types::milli::vector::settings::EmbedderSettings;
+            use meilisearch_types::milli::vector::settings::EmbedderSource;
             match source {
-                EmbedderSettings::OpenAi(_) => sources.insert("openAi"),
-                EmbedderSettings::HuggingFace(_) => sources.insert("huggingFace"),
-                EmbedderSettings::UserProvided(_) => sources.insert("userProvided"),
+                EmbedderSource::OpenAi => sources.insert("openAi"),
+                EmbedderSource::HuggingFace => sources.insert("huggingFace"),
+                EmbedderSource::UserProvided => sources.insert("userProvided"),
             };
         }
     };
@@ -651,6 +656,7 @@ pub async fn update_all(
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
 
     let new_settings = body.into_inner();
+    let new_settings = validate_settings(new_settings, &index_scheduler)?;
 
     analytics.publish(
         "Settings Updated".to_string(),
@@ -684,7 +690,8 @@ pub async fn update_all(
                 "set": new_settings.distinct_attribute.as_ref().set().is_some()
             },
             "proximity_precision": {
-                "set": new_settings.proximity_precision.as_ref().set().is_some()
+                "set": new_settings.proximity_precision.as_ref().set().is_some(),
+                "value": new_settings.proximity_precision.as_ref().set().copied().unwrap_or_default()
             },
             "typo_tolerance": {
                 "enabled": new_settings.typo_tolerance
@@ -800,3 +807,13 @@ pub async fn delete_all(
     debug!("returns: {:?}", task);
     Ok(HttpResponse::Accepted().json(task))
 }
+
+fn validate_settings(
+    settings: Settings<Unchecked>,
+    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()?)
+}

meilisearch/src/search.rs

@@ -735,6 +735,9 @@ pub fn perform_facet_search(
     if let Some(facet_query) = &facet_query {
         facet_search.query(facet_query);
     }
+    if let Some(max_facets) = index.max_values_per_facet(&rtxn)? {
+        facet_search.max_values(max_facets as usize);
+    }
 
     Ok(FacetSearchResult {
         facet_hits: facet_search.execute()?,
@@ -897,6 +900,14 @@ fn format_fields<'a>(
     let mut matches_position = compute_matches.then(BTreeMap::new);
     let mut document = document.clone();
 
+    // reduce the formatted option list to the attributes that should be formatted,
+    // instead of all the attributes to display.
+    let formatting_fields_options: Vec<_> = formatted_options
+        .iter()
+        .filter(|(_, option)| option.should_format())
+        .map(|(fid, option)| (field_ids_map.name(*fid).unwrap(), option))
+        .collect();
+
     // select the attributes to retrieve
     let displayable_names =
         displayable_ids.iter().map(|&fid| field_ids_map.name(fid).expect("Missing field name"));
@@ -905,13 +916,15 @@ fn format_fields<'a>(
         // to the value and merge them together. eg. If a user said he wanted to highlight `doggo`
         // and crop `doggo.name`. `doggo.name` needs to be highlighted + cropped while `doggo.age` is only
         // highlighted.
-        let format = formatted_options
+        // Warn: The time to compute the format list scales with the number of fields to format;
+        // cumulated with map_leaf_values that iterates over all the nested fields, it gives a quadratic complexity:
+        // d*f where d is the total number of fields to display and f is the total number of fields to format.
+        let format = formatting_fields_options
             .iter()
-            .filter(|(field, _option)| {
-                let name = field_ids_map.name(**field).unwrap();
+            .filter(|(name, _option)| {
                 milli::is_faceted_by(name, key) || milli::is_faceted_by(key, name)
             })
-            .map(|(_, option)| *option)
+            .map(|(_, option)| **option)
             .reduce(|acc, option| acc.merge(option));
         let mut infos = Vec::new();
 
@@ -1008,7 +1021,7 @@ fn format_value<'a>(
                     let value = matcher.format(format_options);
                     Value::String(value.into_owned())
                 }
-                None => Value::Number(number),
+                None => Value::String(s),
             }
         }
         value => value,

meilisearch/tests/dumps/mod.rs

@@ -59,7 +59,7 @@ async fn import_dump_v1_movie_raw() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -77,8 +77,7 @@ async fn import_dump_v1_movie_raw() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -221,7 +220,7 @@ async fn import_dump_v1_movie_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -239,8 +238,7 @@ async fn import_dump_v1_movie_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -369,7 +367,7 @@ async fn import_dump_v1_rubygems_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -387,8 +385,7 @@ async fn import_dump_v1_rubygems_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -503,7 +500,7 @@ async fn import_dump_v2_movie_raw() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -521,8 +518,7 @@ async fn import_dump_v2_movie_raw() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -649,7 +645,7 @@ async fn import_dump_v2_movie_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -667,8 +663,7 @@ async fn import_dump_v2_movie_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -794,7 +789,7 @@ async fn import_dump_v2_rubygems_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -812,8 +807,7 @@ async fn import_dump_v2_rubygems_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -928,7 +922,7 @@ async fn import_dump_v3_movie_raw() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -946,8 +940,7 @@ async fn import_dump_v3_movie_raw() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1074,7 +1067,7 @@ async fn import_dump_v3_movie_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -1092,8 +1085,7 @@ async fn import_dump_v3_movie_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1219,7 +1211,7 @@ async fn import_dump_v3_rubygems_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -1237,8 +1229,7 @@ async fn import_dump_v3_rubygems_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1353,7 +1344,7 @@ async fn import_dump_v4_movie_raw() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -1371,8 +1362,7 @@ async fn import_dump_v4_movie_raw() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1499,7 +1489,7 @@ async fn import_dump_v4_movie_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -1517,8 +1507,7 @@ async fn import_dump_v4_movie_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1644,7 +1633,7 @@ async fn import_dump_v4_rubygems_with_settings() {
       "dictionary": [],
       "synonyms": {},
       "distinctAttribute": null,
-      "proximityPrecision": null,
+      "proximityPrecision": "byWord",
       "typoTolerance": {
         "enabled": true,
         "minWordSizeForTypos": {
@@ -1662,8 +1651,7 @@ async fn import_dump_v4_rubygems_with_settings() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###
     );
@@ -1907,8 +1895,7 @@ async fn import_dump_v6_containing_experimental_features() {
       },
       "pagination": {
         "maxTotalHits": 1000
-      },
-      "embedders": {}
+      }
     }
     "###);
 

meilisearch/tests/search/facet_search.rs

@@ -105,6 +105,24 @@ async fn more_advanced_facet_search() {
     snapshot!(response["facetHits"].as_array().unwrap().len(), @"1");
 }
 
+#[actix_rt::test]
+async fn simple_facet_search_with_max_values() {
+    let server = Server::new().await;
+    let index = server.index("test");
+
+    let documents = DOCUMENTS.clone();
+    index.update_settings_faceting(json!({ "maxValuesPerFacet": 1 })).await;
+    index.update_settings_filterable_attributes(json!(["genres"])).await;
+    index.add_documents(documents, None).await;
+    index.wait_task(2).await;
+
+    let (response, code) =
+        index.facet_search(json!({"facetName": "genres", "facetQuery": "a"})).await;
+
+    assert_eq!(code, 200, "{}", response);
+    assert_eq!(dbg!(response)["facetHits"].as_array().unwrap().len(), 1);
+}
+
 #[actix_rt::test]
 async fn non_filterable_facet_search_error() {
     let server = Server::new().await;

meilisearch/tests/search/hybrid.rs

@@ -21,9 +21,9 @@ async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Inde
     "###);
 
     let (response, code) = index
-        .update_settings(
-            json!({ "embedders": {"default": {"source": {"userProvided": {"dimensions": 2}}}} }),
-        )
+        .update_settings(json!({ "embedders": {"default": {
+                "source": "userProvided",
+                "dimensions": 2}}} ))
         .await;
     assert_eq!(202, code, "{:?}", response);
     index.wait_task(response.uid()).await;
@@ -56,6 +56,15 @@ static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
     }])
 });
 
+static SINGLE_DOCUMENT: Lazy<Value> = Lazy::new(|| {
+    json!([{
+            "title": "Shazam!",
+            "desc": "a Captain Marvel ersatz",
+            "id": "1",
+            "_vectors": {"default": [1.0, 3.0]},
+    }])
+});
+
 #[actix_rt::test]
 async fn simple_search() {
     let server = Server::new().await;
@@ -149,3 +158,18 @@ async fn invalid_semantic_ratio() {
     }
     "###);
 }
+
+#[actix_rt::test]
+async fn single_document() {
+    let server = Server::new().await;
+    let index = index_with_documents(&server, &SINGLE_DOCUMENT).await;
+
+    let (response, code) = index
+    .search_post(
+        json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
+    )
+    .await;
+
+    snapshot!(code, @"200 OK");
+    snapshot!(response["hits"][0], @r###"{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0,"_semanticScore":1.0}"###);
+}

meilisearch/tests/search/mod.rs

@@ -890,13 +890,21 @@ async fn experimental_feature_vector_store() {
     let (response, code) = index
         .update_settings(json!({"embedders": {
             "manual": {
-                "source": {
-                    "userProvided": {"dimensions": 3}
-                }
+                "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;
 

meilisearch/tests/settings/get_settings.rs

@@ -54,7 +54,7 @@ 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(), 16);
+    assert_eq!(settings.keys().len(), 15);
     assert_eq!(settings["displayedAttributes"], json!(["*"]));
     assert_eq!(settings["searchableAttributes"], json!(["*"]));
     assert_eq!(settings["filterableAttributes"], json!([]));
@@ -83,7 +83,7 @@ async fn get_settings() {
             "maxTotalHits": 1000,
         })
     );
-    assert_eq!(settings["embedders"], json!({}));
+    assert_eq!(settings["proximityPrecision"], json!("byWord"));
 }
 
 #[actix_rt::test]

milli/Cargo.toml

@@ -77,7 +77,7 @@ csv = "1.2.1"
 candle-core = { git = "https://github.com/huggingface/candle.git", version = "0.3.1" }
 candle-transformers = { git = "https://github.com/huggingface/candle.git", version = "0.3.1" }
 candle-nn = { git = "https://github.com/huggingface/candle.git", version = "0.3.1" }
-tokenizers = { git = "https://github.com/huggingface/tokenizers.git", tag = "v0.14.1", version = "0.14.1" }
+tokenizers = { git = "https://github.com/huggingface/tokenizers.git", tag = "v0.14.1", version = "0.14.1", default_features = false, features = ["onig"] }
 hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls", default_features = false, features = [
     "online",
 ] }

milli/src/error.rs

@@ -192,7 +192,7 @@ 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("`.embedders.{0}.documentTemplate`: Invalid template: {1}.")]
     InvalidPromptForEmbeddings(String, crate::prompt::error::NewPromptError),
     #[error("Too many embedders in the configuration. Found {0}, but limited to 256.")]
     TooManyEmbedders(usize),
@@ -200,6 +200,33 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
     InvalidEmbedder(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: {}",
+        allowed_sources_for_field
+         .iter()
+         .map(|accepted| format!("`{}`", accepted))
+         .collect::<Vec<String>>()
+         .join(", "),
+        allowed_fields_for_source
+         .iter()
+         .map(|accepted| format!("`{}`", accepted))
+         .collect::<Vec<String>>()
+         .join(", ")
+    )]
+    InvalidFieldForSource {
+        embedder_name: String,
+        source_: crate::vector::settings::EmbedderSource,
+        field: &'static str,
+        allowed_fields_for_source: &'static [&'static str],
+        allowed_sources_for_field: &'static [crate::vector::settings::EmbedderSource],
+    },
+    #[error("`.embedders.{embedder_name}.model`: Invalid model `{model}` for OpenAI. Supported models: {:?}", crate::vector::openai::EmbeddingModel::supported_models())]
+    InvalidOpenAiModel { embedder_name: String, model: String },
+    #[error("`.embedders.{embedder_name}`: Missing field `{field}` (note: this field is mandatory for source {source_})")]
+    MissingFieldForSource {
+        field: &'static str,
+        source_: crate::vector::settings::EmbedderSource,
+        embedder_name: String,
+    },
 }
 
 impl From<crate::vector::Error> for Error {

milli/src/search/mod.rs

@@ -27,8 +27,8 @@ static LEVDIST0: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(0, true));
 static LEVDIST1: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(1, true));
 static LEVDIST2: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(2, true));
 
-/// The maximum number of facets returned by the facet search route.
-const MAX_NUMBER_OF_FACETS: usize = 100;
+/// The maximum number of values per facet returned by the facet search route.
+const DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET: usize = 100;
 
 pub mod facet;
 mod fst_utils;
@@ -306,6 +306,7 @@ pub struct SearchForFacetValues<'a> {
     query: Option<String>,
     facet: String,
     search_query: Search<'a>,
+    max_values: usize,
     is_hybrid: bool,
 }
 
@@ -315,7 +316,13 @@ impl<'a> SearchForFacetValues<'a> {
         search_query: Search<'a>,
         is_hybrid: bool,
     ) -> SearchForFacetValues<'a> {
-        SearchForFacetValues { query: None, facet, search_query, is_hybrid }
+        SearchForFacetValues {
+            query: None,
+            facet,
+            search_query,
+            max_values: DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET,
+            is_hybrid,
+        }
     }
 
     pub fn query(&mut self, query: impl Into<String>) -> &mut Self {
@@ -323,6 +330,11 @@ impl<'a> SearchForFacetValues<'a> {
         self
     }
 
+    pub fn max_values(&mut self, max: usize) -> &mut Self {
+        self.max_values = max;
+        self
+    }
+
     fn one_original_value_of(
         &self,
         field_id: FieldId,
@@ -462,7 +474,7 @@ impl<'a> SearchForFacetValues<'a> {
                             .unwrap_or_else(|| left_bound.to_string());
                         results.push(FacetValueHit { value, count });
                     }
-                    if results.len() >= MAX_NUMBER_OF_FACETS {
+                    if results.len() >= self.max_values {
                         break;
                     }
                 }
@@ -507,7 +519,7 @@ impl<'a> SearchForFacetValues<'a> {
                     .unwrap_or_else(|| query.to_string());
                 results.push(FacetValueHit { value, count });
             }
-            if results.len() >= MAX_NUMBER_OF_FACETS {
+            if results.len() >= self.max_values {
                 return Ok(ControlFlow::Break(()));
             }
         }

milli/src/search/new/bucket_sort.rs

@@ -15,6 +15,7 @@ pub struct BucketSortOutput {
 
 // TODO: would probably be good to regroup some of these inside of a struct?
 #[allow(clippy::too_many_arguments)]
+#[logging_timer::time]
 pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
     ctx: &mut SearchContext<'ctx>,
     mut ranking_rules: Vec<BoxRankingRule<'ctx, Q>>,

milli/src/search/new/matches/mod.rs

@@ -72,7 +72,7 @@ impl<'m> MatcherBuilder<'m> {
     }
 }
 
-#[derive(Copy, Clone, Default)]
+#[derive(Copy, Clone, Default, Debug)]
 pub struct FormatOptions {
     pub highlight: bool,
     pub crop: Option<usize>,
@@ -82,6 +82,10 @@ impl FormatOptions {
     pub fn merge(self, other: Self) -> Self {
         Self { highlight: self.highlight || other.highlight, crop: self.crop.or(other.crop) }
     }
+
+    pub fn should_format(&self) -> bool {
+        self.highlight || self.crop.is_some()
+    }
 }
 
 #[derive(Clone, Debug)]

milli/src/search/new/mod.rs

@@ -191,6 +191,7 @@ fn resolve_maximally_reduced_query_graph(
     Ok(docids)
 }
 
+#[logging_timer::time]
 fn resolve_universe(
     ctx: &mut SearchContext,
     initial_universe: &RoaringBitmap,
@@ -556,6 +557,7 @@ pub fn execute_vector_search(
 }
 
 #[allow(clippy::too_many_arguments)]
+#[logging_timer::time]
 pub fn execute_search(
     ctx: &mut SearchContext,
     query: Option<&str>,

milli/src/search/new/query_term/parse_query.rs

@@ -5,6 +5,7 @@ use super::*;
 use crate::{Result, SearchContext, MAX_WORD_LENGTH};
 
 /// Convert the tokenised search query into a list of located query terms.
+#[logging_timer::time]
 pub fn located_query_terms_from_tokens(
     ctx: &mut SearchContext,
     query: NormalizedTokenIter,

milli/src/update/facet/incremental.rs

@@ -61,6 +61,7 @@ impl FacetsUpdateIncremental {
         }
     }
 
+    #[logging_timer::time("FacetsUpdateIncremental::{}")]
     pub fn execute(self, wtxn: &mut RwTxn) -> crate::Result<()> {
         let mut cursor = self.delta_data.into_cursor()?;
         while let Some((key, value)) = cursor.move_on_next()? {

milli/src/update/facet/mod.rs

@@ -76,26 +76,18 @@ pub const FACET_MAX_GROUP_SIZE: u8 = 8;
 pub const FACET_GROUP_SIZE: u8 = 4;
 pub const FACET_MIN_LEVEL_SIZE: u8 = 5;
 
-use std::collections::BTreeSet;
 use std::fs::File;
 use std::io::BufReader;
-use std::iter::FromIterator;
 
-use charabia::normalizer::{Normalize, NormalizerOption};
-use grenad::{CompressionType, SortAlgorithm};
-use heed::types::{Bytes, DecodeIgnore, SerdeJson};
-use heed::BytesEncode;
 use log::debug;
 use time::OffsetDateTime;
 
 use self::incremental::FacetsUpdateIncremental;
 use super::FacetsUpdateBulk;
 use crate::facet::FacetType;
-use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec};
+use crate::heed_codec::facet::{FacetGroupKeyCodec, FacetGroupValueCodec};
 use crate::heed_codec::BytesRefCodec;
-use crate::update::index_documents::create_sorter;
-use crate::update::merge_btreeset_string;
-use crate::{BEU16StrCodec, Index, Result, MAX_FACET_VALUE_LENGTH};
+use crate::{Index, Result};
 
 pub mod bulk;
 pub mod incremental;
@@ -146,115 +138,114 @@ impl<'i> FacetsUpdate<'i> {
         self.index.set_updated_at(wtxn, &OffsetDateTime::now_utc())?;
 
         // See self::comparison_bench::benchmark_facet_indexing
-        if self.delta_data.len() >= (self.database.len(wtxn)? / 50) {
-            let field_ids =
-                self.index.faceted_fields_ids(wtxn)?.iter().copied().collect::<Vec<_>>();
-            let bulk_update = FacetsUpdateBulk::new(
-                self.index,
-                field_ids,
-                self.facet_type,
-                self.delta_data,
-                self.group_size,
-                self.min_level_size,
-            );
-            bulk_update.execute(wtxn)?;
-        } else {
-            let incremental_update = FacetsUpdateIncremental::new(
-                self.index,
-                self.facet_type,
-                self.delta_data,
-                self.group_size,
-                self.min_level_size,
-                self.max_group_size,
-            );
-            incremental_update.execute(wtxn)?;
-        }
-
-        // We clear the list of normalized-for-search facets
-        // and the previous FSTs to compute everything from scratch
-        self.index.facet_id_normalized_string_strings.clear(wtxn)?;
-        self.index.facet_id_string_fst.clear(wtxn)?;
-
-        // As we can't use the same write transaction to read and write in two different databases
-        // we must create a temporary sorter that we will write into LMDB afterward.
-        // As multiple unnormalized facet values can become the same normalized facet value
-        // we must merge them together.
-        let mut sorter = create_sorter(
-            SortAlgorithm::Unstable,
-            merge_btreeset_string,
-            CompressionType::None,
-            None,
-            None,
-            None,
+        // if self.delta_data.len() >= (self.database.len(wtxn)? / 50) {
+        let field_ids = self.index.faceted_fields_ids(wtxn)?.iter().copied().collect::<Vec<_>>();
+        let bulk_update = FacetsUpdateBulk::new(
+            self.index,
+            field_ids,
+            self.facet_type,
+            self.delta_data,
+            self.group_size,
+            self.min_level_size,
         );
+        bulk_update.execute(wtxn)?;
+        // } else {
+        //     let incremental_update = FacetsUpdateIncremental::new(
+        //         self.index,
+        //         self.facet_type,
+        //         self.delta_data,
+        //         self.group_size,
+        //         self.min_level_size,
+        //         self.max_group_size,
+        //     );
+        //     incremental_update.execute(wtxn)?;
+        // }
 
-        // We iterate on the list of original, semi-normalized, facet values
-        // and normalize them for search, inserting them in LMDB in any given order.
-        let options = NormalizerOption { lossy: true, ..Default::default() };
-        let database = self.index.facet_id_string_docids.remap_data_type::<DecodeIgnore>();
-        for result in database.iter(wtxn)? {
-            let (facet_group_key, ()) = result?;
-            if let FacetGroupKey { field_id, level: 0, left_bound } = facet_group_key {
-                let mut normalized_facet = left_bound.normalize(&options);
-                let normalized_truncated_facet: String;
-                if normalized_facet.len() > MAX_FACET_VALUE_LENGTH {
-                    normalized_truncated_facet = normalized_facet
-                        .char_indices()
-                        .take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
-                        .map(|(_, c)| c)
-                        .collect();
-                    normalized_facet = normalized_truncated_facet.into();
-                }
-                let set = BTreeSet::from_iter(std::iter::once(left_bound));
-                let key = (field_id, normalized_facet.as_ref());
-                let key = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
-                let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
-                sorter.insert(key, val)?;
-            }
-        }
+        // // We clear the list of normalized-for-search facets
+        // // and the previous FSTs to compute everything from scratch
+        // self.index.facet_id_normalized_string_strings.clear(wtxn)?;
+        // self.index.facet_id_string_fst.clear(wtxn)?;
 
-        // In this loop we don't need to take care of merging bitmaps
-        // as the grenad sorter already merged them for us.
-        let mut merger_iter = sorter.into_stream_merger_iter()?;
-        while let Some((key_bytes, btreeset_bytes)) = merger_iter.next()? {
-            self.index.facet_id_normalized_string_strings.remap_types::<Bytes, Bytes>().put(
-                wtxn,
-                key_bytes,
-                btreeset_bytes,
-            )?;
-        }
+        // // As we can't use the same write transaction to read and write in two different databases
+        // // we must create a temporary sorter that we will write into LMDB afterward.
+        // // As multiple unnormalized facet values can become the same normalized facet value
+        // // we must merge them together.
+        // let mut sorter = create_sorter(
+        //     SortAlgorithm::Unstable,
+        //     merge_btreeset_string,
+        //     CompressionType::None,
+        //     None,
+        //     None,
+        //     None,
+        // );
 
-        // We compute one FST by string facet
-        let mut text_fsts = vec![];
-        let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
-        let database =
-            self.index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
-        for result in database.iter(wtxn)? {
-            let ((field_id, normalized_facet), _) = result?;
-            current_fst = match current_fst.take() {
-                Some((fid, fst_builder)) if fid != field_id => {
-                    let fst = fst_builder.into_set();
-                    text_fsts.push((fid, fst));
-                    Some((field_id, fst::SetBuilder::memory()))
-                }
-                Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
-                None => Some((field_id, fst::SetBuilder::memory())),
-            };
+        // // We iterate on the list of original, semi-normalized, facet values
+        // // and normalize them for search, inserting them in LMDB in any given order.
+        // let options = NormalizerOption { lossy: true, ..Default::default() };
+        // let database = self.index.facet_id_string_docids.remap_data_type::<DecodeIgnore>();
+        // for result in database.iter(wtxn)? {
+        //     let (facet_group_key, ()) = result?;
+        //     if let FacetGroupKey { field_id, level: 0, left_bound } = facet_group_key {
+        //         let mut normalized_facet = left_bound.normalize(&options);
+        //         let normalized_truncated_facet: String;
+        //         if normalized_facet.len() > MAX_FACET_VALUE_LENGTH {
+        //             normalized_truncated_facet = normalized_facet
+        //                 .char_indices()
+        //                 .take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
+        //                 .map(|(_, c)| c)
+        //                 .collect();
+        //             normalized_facet = normalized_truncated_facet.into();
+        //         }
+        //         let set = BTreeSet::from_iter(std::iter::once(left_bound));
+        //         let key = (field_id, normalized_facet.as_ref());
+        //         let key = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
+        //         let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
+        //         sorter.insert(key, val)?;
+        //     }
+        // }
 
-            if let Some((_, fst_builder)) = current_fst.as_mut() {
-                fst_builder.insert(normalized_facet)?;
-            }
-        }
+        // // In this loop we don't need to take care of merging bitmaps
+        // // as the grenad sorter already merged them for us.
+        // let mut merger_iter = sorter.into_stream_merger_iter()?;
+        // while let Some((key_bytes, btreeset_bytes)) = merger_iter.next()? {
+        //     self.index.facet_id_normalized_string_strings.remap_types::<Bytes, Bytes>().put(
+        //         wtxn,
+        //         key_bytes,
+        //         btreeset_bytes,
+        //     )?;
+        // }
 
-        if let Some((field_id, fst_builder)) = current_fst {
-            let fst = fst_builder.into_set();
-            text_fsts.push((field_id, fst));
-        }
+        // // We compute one FST by string facet
+        // let mut text_fsts = vec![];
+        // let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
+        // let database =
+        //     self.index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
+        // for result in database.iter(wtxn)? {
+        //     let ((field_id, normalized_facet), _) = result?;
+        //     current_fst = match current_fst.take() {
+        //         Some((fid, fst_builder)) if fid != field_id => {
+        //             let fst = fst_builder.into_set();
+        //             text_fsts.push((fid, fst));
+        //             Some((field_id, fst::SetBuilder::memory()))
+        //         }
+        //         Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
+        //         None => Some((field_id, fst::SetBuilder::memory())),
+        //     };
 
-        // We write those FSTs in LMDB now
-        for (field_id, fst) in text_fsts {
-            self.index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
-        }
+        //     if let Some((_, fst_builder)) = current_fst.as_mut() {
+        //         fst_builder.insert(normalized_facet)?;
+        //     }
+        // }
+
+        // if let Some((field_id, fst_builder)) = current_fst {
+        //     let fst = fst_builder.into_set();
+        //     text_fsts.push((field_id, fst));
+        // }
+
+        // // We write those FSTs in LMDB now
+        // for (field_id, fst) in text_fsts {
+        //     self.index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
+        // }
 
         Ok(())
     }

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

@@ -16,7 +16,7 @@ pub use merge_functions::{
     keep_first, keep_latest_obkv, merge_btreeset_string, merge_cbo_roaring_bitmaps,
     merge_deladd_cbo_roaring_bitmaps, merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
     merge_roaring_bitmaps, obkvs_keep_last_addition_merge_deletions,
-    obkvs_merge_additions_and_deletions, serialize_roaring_bitmap, MergeFn,
+    obkvs_merge_additions_and_deletions, MergeFn,
 };
 
 use crate::MAX_WORD_LENGTH;

milli/src/update/index_documents/mod.rs

@@ -21,7 +21,7 @@ use slice_group_by::GroupBy;
 use typed_chunk::{write_typed_chunk_into_index, TypedChunk};
 
 use self::enrich::enrich_documents_batch;
-pub use self::enrich::{extract_finite_float_from_value, validate_geo_from_json, DocumentId};
+pub use self::enrich::{extract_finite_float_from_value, DocumentId};
 pub use self::helpers::{
     as_cloneable_grenad, create_sorter, create_writer, fst_stream_into_hashset,
     fst_stream_into_vec, merge_btreeset_string, merge_cbo_roaring_bitmaps,
@@ -2553,7 +2553,7 @@ mod tests {
     /// Vectors must be of the same length.
     #[test]
     fn test_multiple_vectors() {
-        use crate::vector::settings::{EmbedderSettings, EmbeddingSettings};
+        use crate::vector::settings::EmbeddingSettings;
         let index = TempIndex::new();
 
         index
@@ -2562,9 +2562,11 @@ mod tests {
                 embedders.insert(
                     "manual".to_string(),
                     Setting::Set(EmbeddingSettings {
-                        embedder_options: Setting::Set(EmbedderSettings::UserProvided(
-                            crate::vector::settings::UserProvidedSettings { dimensions: 3 },
-                        )),
+                        source: Setting::Set(crate::vector::settings::EmbedderSource::UserProvided),
+                        model: Setting::NotSet,
+                        revision: Setting::NotSet,
+                        api_key: Setting::NotSet,
+                        dimensions: Setting::Set(3),
                         document_template: Setting::NotSet,
                     }),
                 );
@@ -2579,10 +2581,10 @@ mod tests {
             .unwrap();
         index.add_documents(documents!([{"id": 1, "_vectors": { "manual": [6, 7, 8] }}])).unwrap();
         index
-            .add_documents(
-                documents!([{"id": 2, "_vectors": { "manual": [[9, 10, 11], [12, 13, 14], [15, 16, 17]] }}]),
-            )
-            .unwrap();
+               .add_documents(
+                   documents!([{"id": 2, "_vectors": { "manual": [[9, 10, 11], [12, 13, 14], [15, 16, 17]] }}]),
+               )
+               .unwrap();
 
         let rtxn = index.read_txn().unwrap();
         let res = index.search(&rtxn).vector([0.0, 1.0, 2.0].to_vec()).execute().unwrap();

milli/src/update/index_documents/typed_chunk.rs

@@ -123,6 +123,8 @@ pub(crate) fn write_typed_chunk_into_index(
 ) -> Result<(RoaringBitmap, bool)> {
     puffin::profile_function!(typed_chunk.to_debug_string());
 
+    log::debug!("Received a chunk to process: {}", typed_chunk.to_debug_string());
+
     let mut is_merged_database = false;
     match typed_chunk {
         TypedChunk::Documents(obkv_documents_iter) => {

milli/src/update/mod.rs

@@ -8,7 +8,7 @@ pub use self::index_documents::{
     MergeFn,
 };
 pub use self::indexer_config::IndexerConfig;
-pub use self::settings::{Setting, Settings};
+pub use self::settings::{validate_embedding_settings, Setting, Settings};
 pub use self::update_step::UpdateIndexingStep;
 pub use self::word_prefix_docids::WordPrefixDocids;
 pub use self::words_prefix_integer_docids::WordPrefixIntegerDocids;

milli/src/update/settings.rs

@@ -17,7 +17,7 @@ use crate::index::{DEFAULT_MIN_WORD_LEN_ONE_TYPO, DEFAULT_MIN_WORD_LEN_TWO_TYPOS
 use crate::proximity::ProximityPrecision;
 use crate::update::index_documents::IndexDocumentsMethod;
 use crate::update::{IndexDocuments, UpdateIndexingStep};
-use crate::vector::settings::{EmbeddingSettings, PromptSettings};
+use crate::vector::settings::{check_set, check_unset, EmbedderSource, EmbeddingSettings};
 use crate::vector::{Embedder, EmbeddingConfig, EmbeddingConfigs};
 use crate::{FieldsIdsMap, Index, OrderBy, Result};
 
@@ -78,11 +78,19 @@ impl<T> Setting<T> {
         }
     }
 
-    pub fn apply(&mut self, new: Self) {
+    /// Returns `true` if applying the new setting changed this setting
+    pub fn apply(&mut self, new: Self) -> bool
+    where
+        T: PartialEq + Eq,
+    {
         if let Setting::NotSet = new {
-            return;
+            return false;
+        }
+        if self == &new {
+            return false;
         }
         *self = new;
+        true
     }
 }
 
@@ -950,17 +958,23 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
                     .merge_join_by(configs.into_iter(), |(left, _), (right, _)| left.cmp(right))
                 {
                     match joined {
+                        // updated config
                         EitherOrBoth::Both((name, mut old), (_, new)) => {
-                            old.apply(new);
-                            let new = validate_prompt(&name, old)?;
-                            changed = true;
+                            changed |= old.apply(new);
+                            let new = validate_embedding_settings(old, &name)?;
                             new_configs.insert(name, new);
                         }
+                        // unchanged config
                         EitherOrBoth::Left((name, setting)) => {
                             new_configs.insert(name, setting);
                         }
-                        EitherOrBoth::Right((name, setting)) => {
-                            let setting = validate_prompt(&name, setting)?;
+                        // new config
+                        EitherOrBoth::Right((name, mut setting)) => {
+                            // apply the default source in case the source was not set so that it gets validated
+                            crate::vector::settings::EmbeddingSettings::apply_default_source(
+                                &mut setting,
+                            );
+                            let setting = validate_embedding_settings(setting, &name)?;
                             changed = true;
                             new_configs.insert(name, setting);
                         }
@@ -1072,8 +1086,12 @@ fn validate_prompt(
 ) -> Result<Setting<EmbeddingSettings>> {
     match new {
         Setting::Set(EmbeddingSettings {
-            embedder_options,
-            document_template: Setting::Set(PromptSettings { template: Setting::Set(template) }),
+            source,
+            model,
+            revision,
+            api_key,
+            dimensions,
+            document_template: Setting::Set(template),
         }) => {
             // validate
             let template = crate::prompt::Prompt::new(template)
@@ -1081,16 +1099,71 @@ fn validate_prompt(
                 .map_err(|inner| UserError::InvalidPromptForEmbeddings(name.to_owned(), inner))?;
 
             Ok(Setting::Set(EmbeddingSettings {
-                embedder_options,
-                document_template: Setting::Set(PromptSettings {
-                    template: Setting::Set(template),
-                }),
+                source,
+                model,
+                revision,
+                api_key,
+                dimensions,
+                document_template: Setting::Set(template),
             }))
         }
         new => Ok(new),
     }
 }
 
+pub fn validate_embedding_settings(
+    settings: Setting<EmbeddingSettings>,
+    name: &str,
+) -> Result<Setting<EmbeddingSettings>> {
+    let settings = validate_prompt(name, settings)?;
+    let Setting::Set(settings) = settings else { return Ok(settings) };
+    let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
+        settings;
+    let Some(inferred_source) = source.set() else {
+        return Ok(Setting::Set(EmbeddingSettings {
+            source,
+            model,
+            revision,
+            api_key,
+            dimensions,
+            document_template,
+        }));
+    };
+    match inferred_source {
+        EmbedderSource::OpenAi => {
+            check_unset(&revision, "revision", inferred_source, name)?;
+            check_unset(&dimensions, "dimensions", inferred_source, name)?;
+            if let Setting::Set(model) = &model {
+                crate::vector::openai::EmbeddingModel::from_name(model.as_str()).ok_or(
+                    crate::error::UserError::InvalidOpenAiModel {
+                        embedder_name: name.to_owned(),
+                        model: model.clone(),
+                    },
+                )?;
+            }
+        }
+        EmbedderSource::HuggingFace => {
+            check_unset(&api_key, "apiKey", inferred_source, name)?;
+            check_unset(&dimensions, "dimensions", inferred_source, name)?;
+        }
+        EmbedderSource::UserProvided => {
+            check_unset(&model, "model", inferred_source, name)?;
+            check_unset(&revision, "revision", inferred_source, name)?;
+            check_unset(&api_key, "apiKey", inferred_source, name)?;
+            check_unset(&document_template, "documentTemplate", inferred_source, name)?;
+            check_set(&dimensions, "dimensions", inferred_source, name)?;
+        }
+    }
+    Ok(Setting::Set(EmbeddingSettings {
+        source,
+        model,
+        revision,
+        api_key,
+        dimensions,
+        document_template,
+    }))
+}
+
 #[cfg(test)]
 mod tests {
     use big_s::S;

milli/src/vector/openai.rs

@@ -34,6 +34,9 @@ pub struct EmbedderOptions {
 #[serde(deny_unknown_fields, rename_all = "camelCase")]
 #[deserr(rename_all = camelCase, deny_unknown_fields)]
 pub enum EmbeddingModel {
+    // # WARNING
+    //
+    // If ever adding a model, make sure to add it to the list of supported models below.
     #[default]
     #[serde(rename = "text-embedding-ada-002")]
     #[deserr(rename = "text-embedding-ada-002")]
@@ -41,6 +44,10 @@ pub enum EmbeddingModel {
 }
 
 impl EmbeddingModel {
+    pub fn supported_models() -> &'static [&'static str] {
+        &["text-embedding-ada-002"]
+    }
+
     pub fn max_token(&self) -> usize {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => 8191,
@@ -59,7 +66,7 @@ impl EmbeddingModel {
         }
     }
 
-    pub fn from_name(name: &'static str) -> Option<Self> {
+    pub fn from_name(name: &str) -> Option<Self> {
         match name {
             "text-embedding-ada-002" => Some(EmbeddingModel::TextEmbeddingAda002),
             _ => None,

milli/src/vector/settings.rs

@@ -4,32 +4,189 @@ use serde::{Deserialize, Serialize};
 use crate::prompt::PromptData;
 use crate::update::Setting;
 use crate::vector::EmbeddingConfig;
+use crate::UserError;
 
 #[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
 #[serde(deny_unknown_fields, rename_all = "camelCase")]
 #[deserr(rename_all = camelCase, deny_unknown_fields)]
 pub struct EmbeddingSettings {
-    #[serde(default, skip_serializing_if = "Setting::is_not_set", rename = "source")]
-    #[deserr(default, rename = "source")]
-    pub embedder_options: Setting<EmbedderSettings>,
     #[serde(default, skip_serializing_if = "Setting::is_not_set")]
     #[deserr(default)]
-    pub document_template: Setting<PromptSettings>,
+    pub source: Setting<EmbedderSource>,
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
+    #[deserr(default)]
+    pub model: Setting<String>,
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
+    #[deserr(default)]
+    pub revision: Setting<String>,
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
+    #[deserr(default)]
+    pub api_key: Setting<String>,
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
+    #[deserr(default)]
+    pub dimensions: Setting<usize>,
+    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
+    #[deserr(default)]
+    pub document_template: Setting<String>,
+}
+
+pub fn check_unset<T>(
+    key: &Setting<T>,
+    field: &'static str,
+    source: EmbedderSource,
+    embedder_name: &str,
+) -> Result<(), UserError> {
+    if matches!(key, Setting::NotSet) {
+        Ok(())
+    } else {
+        Err(UserError::InvalidFieldForSource {
+            embedder_name: embedder_name.to_owned(),
+            source_: source,
+            field,
+            allowed_fields_for_source: EmbeddingSettings::allowed_fields_for_source(source),
+            allowed_sources_for_field: EmbeddingSettings::allowed_sources_for_field(field),
+        })
+    }
+}
+
+pub fn check_set<T>(
+    key: &Setting<T>,
+    field: &'static str,
+    source: EmbedderSource,
+    embedder_name: &str,
+) -> Result<(), UserError> {
+    if matches!(key, Setting::Set(_)) {
+        Ok(())
+    } else {
+        Err(UserError::MissingFieldForSource {
+            field,
+            source_: source,
+            embedder_name: embedder_name.to_owned(),
+        })
+    }
+}
+
+impl EmbeddingSettings {
+    pub const SOURCE: &'static str = "source";
+    pub const MODEL: &'static str = "model";
+    pub const REVISION: &'static str = "revision";
+    pub const API_KEY: &'static str = "apiKey";
+    pub const DIMENSIONS: &'static str = "dimensions";
+    pub const DOCUMENT_TEMPLATE: &'static str = "documentTemplate";
+
+    pub fn allowed_sources_for_field(field: &'static str) -> &'static [EmbedderSource] {
+        match field {
+            Self::SOURCE => {
+                &[EmbedderSource::HuggingFace, EmbedderSource::OpenAi, EmbedderSource::UserProvided]
+            }
+            Self::MODEL => &[EmbedderSource::HuggingFace, EmbedderSource::OpenAi],
+            Self::REVISION => &[EmbedderSource::HuggingFace],
+            Self::API_KEY => &[EmbedderSource::OpenAi],
+            Self::DIMENSIONS => &[EmbedderSource::UserProvided],
+            Self::DOCUMENT_TEMPLATE => &[EmbedderSource::HuggingFace, EmbedderSource::OpenAi],
+            _other => unreachable!("unknown field"),
+        }
+    }
+
+    pub fn allowed_fields_for_source(source: EmbedderSource) -> &'static [&'static str] {
+        match source {
+            EmbedderSource::OpenAi => {
+                &[Self::SOURCE, Self::MODEL, Self::API_KEY, Self::DOCUMENT_TEMPLATE]
+            }
+            EmbedderSource::HuggingFace => {
+                &[Self::SOURCE, Self::MODEL, Self::REVISION, Self::DOCUMENT_TEMPLATE]
+            }
+            EmbedderSource::UserProvided => &[Self::SOURCE, Self::DIMENSIONS],
+        }
+    }
+
+    pub(crate) fn apply_default_source(setting: &mut Setting<EmbeddingSettings>) {
+        if let Setting::Set(EmbeddingSettings {
+            source: source @ (Setting::NotSet | Setting::Reset),
+            ..
+        }) = setting
+        {
+            *source = Setting::Set(EmbedderSource::default())
+        }
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
+#[serde(deny_unknown_fields, rename_all = "camelCase")]
+#[deserr(rename_all = camelCase, deny_unknown_fields)]
+pub enum EmbedderSource {
+    #[default]
+    OpenAi,
+    HuggingFace,
+    UserProvided,
+}
+
+impl std::fmt::Display for EmbedderSource {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        let s = match self {
+            EmbedderSource::OpenAi => "openAi",
+            EmbedderSource::HuggingFace => "huggingFace",
+            EmbedderSource::UserProvided => "userProvided",
+        };
+        f.write_str(s)
+    }
 }
 
 impl EmbeddingSettings {
     pub fn apply(&mut self, new: Self) {
-        let EmbeddingSettings { embedder_options, document_template: prompt } = new;
-        self.embedder_options.apply(embedder_options);
-        self.document_template.apply(prompt);
+        let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
+            new;
+        let old_source = self.source;
+        self.source.apply(source);
+        // Reinitialize the whole setting object on a source change
+        if old_source != self.source {
+            *self = EmbeddingSettings {
+                source,
+                model,
+                revision,
+                api_key,
+                dimensions,
+                document_template,
+            };
+            return;
+        }
+
+        self.model.apply(model);
+        self.revision.apply(revision);
+        self.api_key.apply(api_key);
+        self.dimensions.apply(dimensions);
+        self.document_template.apply(document_template);
     }
 }
 
 impl From<EmbeddingConfig> for EmbeddingSettings {
     fn from(value: EmbeddingConfig) -> Self {
-        Self {
-            embedder_options: Setting::Set(value.embedder_options.into()),
-            document_template: Setting::Set(value.prompt.into()),
+        let EmbeddingConfig { embedder_options, prompt } = value;
+        match embedder_options {
+            super::EmbedderOptions::HuggingFace(options) => Self {
+                source: Setting::Set(EmbedderSource::HuggingFace),
+                model: Setting::Set(options.model),
+                revision: options.revision.map(Setting::Set).unwrap_or_default(),
+                api_key: Setting::NotSet,
+                dimensions: Setting::NotSet,
+                document_template: Setting::Set(prompt.template),
+            },
+            super::EmbedderOptions::OpenAi(options) => Self {
+                source: Setting::Set(EmbedderSource::OpenAi),
+                model: Setting::Set(options.embedding_model.name().to_owned()),
+                revision: Setting::NotSet,
+                api_key: options.api_key.map(Setting::Set).unwrap_or_default(),
+                dimensions: Setting::NotSet,
+                document_template: Setting::Set(prompt.template),
+            },
+            super::EmbedderOptions::UserProvided(options) => Self {
+                source: Setting::Set(EmbedderSource::UserProvided),
+                model: Setting::NotSet,
+                revision: Setting::NotSet,
+                api_key: Setting::NotSet,
+                dimensions: Setting::Set(options.dimensions),
+                document_template: Setting::NotSet,
+            },
         }
     }
 }
@@ -37,256 +194,51 @@ impl From<EmbeddingConfig> for EmbeddingSettings {
 impl From<EmbeddingSettings> for EmbeddingConfig {
     fn from(value: EmbeddingSettings) -> Self {
         let mut this = Self::default();
-        let EmbeddingSettings { embedder_options, document_template: prompt } = value;
-        if let Some(embedder_options) = embedder_options.set() {
-            this.embedder_options = embedder_options.into();
-        }
-        if let Some(prompt) = prompt.set() {
-            this.prompt = prompt.into();
-        }
-        this
-    }
-}
-
-#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
-#[serde(deny_unknown_fields, rename_all = "camelCase")]
-#[deserr(rename_all = camelCase, deny_unknown_fields)]
-pub struct PromptSettings {
-    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
-    #[deserr(default)]
-    pub template: Setting<String>,
-}
-
-impl PromptSettings {
-    pub fn apply(&mut self, new: Self) {
-        let PromptSettings { template } = new;
-        self.template.apply(template);
-    }
-}
-
-impl From<PromptData> for PromptSettings {
-    fn from(value: PromptData) -> Self {
-        Self { template: Setting::Set(value.template) }
-    }
-}
-
-impl From<PromptSettings> for PromptData {
-    fn from(value: PromptSettings) -> Self {
-        let mut this = PromptData::default();
-        let PromptSettings { template } = value;
-        if let Some(template) = template.set() {
-            this.template = template;
-        }
-        this
-    }
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
-#[serde(deny_unknown_fields, rename_all = "camelCase")]
-pub enum EmbedderSettings {
-    HuggingFace(Setting<HfEmbedderSettings>),
-    OpenAi(Setting<OpenAiEmbedderSettings>),
-    UserProvided(UserProvidedSettings),
-}
-
-impl<E> Deserr<E> for EmbedderSettings
-where
-    E: deserr::DeserializeError,
-{
-    fn deserialize_from_value<V: deserr::IntoValue>(
-        value: deserr::Value<V>,
-        location: deserr::ValuePointerRef,
-    ) -> Result<Self, E> {
-        match value {
-            deserr::Value::Map(map) => {
-                if deserr::Map::len(&map) != 1 {
-                    return Err(deserr::take_cf_content(E::error::<V>(
-                        None,
-                        deserr::ErrorKind::Unexpected {
-                            msg: format!(
-                                "Expected a single field, got {} fields",
-                                deserr::Map::len(&map)
-                            ),
-                        },
-                        location,
-                    )));
+        let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
+            value;
+        if let Some(source) = source.set() {
+            match source {
+                EmbedderSource::OpenAi => {
+                    let mut options = super::openai::EmbedderOptions::with_default_model(None);
+                    if let Some(model) = model.set() {
+                        if let Some(model) = super::openai::EmbeddingModel::from_name(&model) {
+                            options.embedding_model = model;
+                        }
+                    }
+                    if let Some(api_key) = api_key.set() {
+                        options.api_key = Some(api_key);
+                    }
+                    this.embedder_options = super::EmbedderOptions::OpenAi(options);
                 }
-                let mut it = deserr::Map::into_iter(map);
-                let (k, v) = it.next().unwrap();
-
-                match k.as_str() {
-                    "huggingFace" => Ok(EmbedderSettings::HuggingFace(Setting::Set(
-                        HfEmbedderSettings::deserialize_from_value(
-                            v.into_value(),
-                            location.push_key(&k),
-                        )?,
-                    ))),
-                    "openAi" => Ok(EmbedderSettings::OpenAi(Setting::Set(
-                        OpenAiEmbedderSettings::deserialize_from_value(
-                            v.into_value(),
-                            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", "userProvided"],
-                        },
-                        location,
-                    ))),
+                EmbedderSource::HuggingFace => {
+                    let mut options = super::hf::EmbedderOptions::default();
+                    if let Some(model) = model.set() {
+                        options.model = model;
+                        // Reset the revision if we are setting the model.
+                        // This allows the following:
+                        // "huggingFace": {} -> default model with default revision
+                        // "huggingFace": { "model": "name-of-the-default-model" } -> default model without a revision
+                        // "huggingFace": { "model": "some-other-model" } -> most importantly, other model without a revision
+                        options.revision = None;
+                    }
+                    if let Some(revision) = revision.set() {
+                        options.revision = Some(revision);
+                    }
+                    this.embedder_options = super::EmbedderOptions::HuggingFace(options);
+                }
+                EmbedderSource::UserProvided => {
+                    this.embedder_options =
+                        super::EmbedderOptions::UserProvided(super::manual::EmbedderOptions {
+                            dimensions: dimensions.set().unwrap(),
+                        });
                 }
             }
-            _ => Err(deserr::take_cf_content(E::error::<V>(
-                None,
-                deserr::ErrorKind::IncorrectValueKind {
-                    actual: value,
-                    accepted: &[deserr::ValueKind::Map],
-                },
-                location,
-            ))),
         }
-    }
-}
 
-impl Default for EmbedderSettings {
-    fn default() -> Self {
-        Self::OpenAi(Default::default())
-    }
-}
-
-impl From<crate::vector::EmbedderOptions> for EmbedderSettings {
-    fn from(value: crate::vector::EmbedderOptions) -> Self {
-        match value {
-            crate::vector::EmbedderOptions::HuggingFace(hf) => {
-                Self::HuggingFace(Setting::Set(hf.into()))
-            }
-            crate::vector::EmbedderOptions::OpenAi(openai) => {
-                Self::OpenAi(Setting::Set(openai.into()))
-            }
-            crate::vector::EmbedderOptions::UserProvided(user_provided) => {
-                Self::UserProvided(user_provided.into())
-            }
+        if let Setting::Set(template) = document_template {
+            this.prompt = PromptData { template }
         }
-    }
-}
 
-impl From<EmbedderSettings> for crate::vector::EmbedderOptions {
-    fn from(value: EmbedderSettings) -> Self {
-        match value {
-            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(crate::vector::openai::EmbedderOptions::with_default_model(None))
-            }
-            EmbedderSettings::UserProvided(user_provided) => {
-                Self::UserProvided(user_provided.into())
-            }
-        }
-    }
-}
-
-#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
-#[serde(deny_unknown_fields, rename_all = "camelCase")]
-#[deserr(rename_all = camelCase, deny_unknown_fields)]
-pub struct HfEmbedderSettings {
-    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
-    #[deserr(default)]
-    pub model: Setting<String>,
-    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
-    #[deserr(default)]
-    pub revision: Setting<String>,
-}
-
-impl HfEmbedderSettings {
-    pub fn apply(&mut self, new: Self) {
-        let HfEmbedderSettings { model, revision } = new;
-        self.model.apply(model);
-        self.revision.apply(revision);
-    }
-}
-
-impl From<crate::vector::hf::EmbedderOptions> for HfEmbedderSettings {
-    fn from(value: crate::vector::hf::EmbedderOptions) -> Self {
-        Self {
-            model: Setting::Set(value.model),
-            revision: value.revision.map(Setting::Set).unwrap_or(Setting::NotSet),
-        }
-    }
-}
-
-impl From<HfEmbedderSettings> for crate::vector::hf::EmbedderOptions {
-    fn from(value: HfEmbedderSettings) -> Self {
-        let HfEmbedderSettings { model, revision } = value;
-        let mut this = Self::default();
-        if let Some(model) = model.set() {
-            this.model = model;
-        }
-        if let Some(revision) = revision.set() {
-            this.revision = Some(revision);
-        }
         this
     }
 }
-
-#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
-#[serde(deny_unknown_fields, rename_all = "camelCase")]
-#[deserr(rename_all = camelCase, deny_unknown_fields)]
-pub struct OpenAiEmbedderSettings {
-    #[serde(default, skip_serializing_if = "Setting::is_not_set")]
-    #[deserr(default)]
-    pub api_key: Setting<String>,
-    #[serde(default, skip_serializing_if = "Setting::is_not_set", rename = "model")]
-    #[deserr(default, rename = "model")]
-    pub embedding_model: Setting<crate::vector::openai::EmbeddingModel>,
-}
-
-impl OpenAiEmbedderSettings {
-    pub fn apply(&mut self, new: Self) {
-        let Self { api_key, embedding_model: embedding_mode } = new;
-        self.api_key.apply(api_key);
-        self.embedding_model.apply(embedding_mode);
-    }
-}
-
-impl From<crate::vector::openai::EmbedderOptions> for OpenAiEmbedderSettings {
-    fn from(value: crate::vector::openai::EmbedderOptions) -> Self {
-        Self {
-            api_key: value.api_key.map(Setting::Set).unwrap_or(Setting::Reset),
-            embedding_model: Setting::Set(value.embedding_model),
-        }
-    }
-}
-
-impl From<OpenAiEmbedderSettings> for crate::vector::openai::EmbedderOptions {
-    fn from(value: OpenAiEmbedderSettings) -> Self {
-        let OpenAiEmbedderSettings { api_key, embedding_model } = value;
-        Self { api_key: api_key.set(), embedding_model: embedding_model.set().unwrap_or_default() }
-    }
-}
-
-#[derive(Debug, Clone, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
-#[serde(deny_unknown_fields, rename_all = "camelCase")]
-#[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 }
-    }
-}