Merge #4275

4275: Flatten settings r=dureuill a=dureuill

# Pull Request

## Related issue
Initial internal feedback seems to indicate that the current shape of the `embedders` setting is undesirable: it has too much depth.

This PR changes this by flattening the structure of the embedders to the following:

```json5
// NEW structure
"embedders": {
  // still starts with the embedder name
  "default": {
    "source": "huggingFace", // now a string
    // properties of the source are all at the same level as the source
    "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
    "revision": "a9c555277f9bcf24f28fa5e092e665fc6f7c49cd",
    "documentTemplate": "A product titled '{{doc.title}}'" // now a string
  }
}
```

By comparison, the old structure was:

```json5
// PREVIOUS version, no longer working with this PR
"embedders": {
  // still starts with the embedder name
  "default": {
    "source": {
      "huggingFace": {
        "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
        "revision": "a9c555277f9bcf24f28fa5e092e665fc6f7c49cd"
      },
    "documentTemplate": { 
      "template": "A product titled '{{doc.title}}'" // now a string
    }
  }
}
```

The fields that are accepted in the new version of the `embedders` setting are depending on the value of the `source` field:

```json5
// huggingFace
"embedders": {
   "default": {
    "source": "huggingFace",
    "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
    "revision": "a9c555277f9bcf24f28fa5e092e665fc6f7c49cd",
    "documentTemplate": "A product titled '{{doc.title}}'"
  }
}

// openAi
"embedders": {
   "default": {
    "source": "openAi",
    "model": "text-embedding-ada-002",
    "apiKey": "open_ai_api_key",
    "documentTemplate": "A product titled '{{doc.title}}'"
  }
}

// userProvided
"embedders": {
   "default": {
    "source": "userProvided",
    "dimensions": 42, // mandatory
  }
}
```

## What does this PR do?
- Flatten the settings structure
- Validate the prompt earlier to return a synchronous error on setting change rather than in the failing task
- Make it an error to pass a field for the wrong source (see above for allowed fields for each source)
- Not changed: It is still an error not to pass `dimensions` to the `userProvided` embedder
- If `source` was specified in the settings, validate the setting early to return a synchronous error in case of a missing mandatory field for the userProvided source (dimensions) or a forbidden field for the specified source.
- If `source` was not specified in the settings, still validate the setting, but only at indexing time, by using the source stored in the DB.
- Resets all values if the source changes, even if the user did not reset them explicitly.

## PR checklist
Please check if your PR fulfills the following requirements:
- [ ] Change the public facing guide for using the API
- [ ] Change examples of use in the changelog


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

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)]

meilisearch/src/routes/indexes/settings.rs

@@ -90,6 +90,8 @@ macro_rules! make_setting_route {
                     ..Default::default()
                 };
 
+                let new_settings = new_settings.validate()?;
+
                 let allow_index_creation =
                     index_scheduler.filters().allow_index_creation(&index_uid);
 
@@ -582,13 +584,13 @@ 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"),
+                EmbedderSource::OpenAi => sources.insert("openAi"),
-                EmbedderSettings::HuggingFace(_) => sources.insert("huggingFace"),
+                EmbedderSource::HuggingFace => sources.insert("huggingFace"),
-                EmbedderSettings::UserProvided(_) => sources.insert("userProvided"),
+                EmbedderSource::UserProvided => sources.insert("userProvided"),
             };
         }
     };
@@ -651,6 +653,7 @@ pub async fn update_all(
     let index_uid = IndexUid::try_from(index_uid.into_inner())?;
 
     let new_settings = body.into_inner();
+    let new_settings = new_settings.validate()?;
 
     analytics.publish(
         "Settings Updated".to_string(),

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(
+        .update_settings(json!({ "embedders": {"default": {
-            json!({ "embedders": {"default": {"source": {"userProvided": {"dimensions": 2}}}} }),
+                "source": "userProvided",
-        )
+                "dimensions": 2}}} ))
         .await;
     assert_eq!(202, code, "{:?}", response);
     index.wait_task(response.uid()).await;

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": {
+                "source": "userProvided",
-                    "userProvided": {"dimensions": 3}
+                "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;
 

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/update/index_documents/mod.rs

@@ -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(
+                        source: Setting::Set(crate::vector::settings::EmbedderSource::UserProvided),
-                            crate::vector::settings::UserProvidedSettings { dimensions: 3 },
+                        model: Setting::NotSet,
-                        )),
+                        revision: Setting::NotSet,
+                        api_key: Setting::NotSet,
+                        dimensions: Setting::Set(3),
                         document_template: Setting::NotSet,
                     }),
                 );

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);
+                            changed |= old.apply(new);
-                            let new = validate_prompt(&name, old)?;
+                            let new = validate_embedding_settings(old, &name)?;
-                            changed = true;
                             new_configs.insert(name, new);
                         }
+                        // unchanged config
                         EitherOrBoth::Left((name, setting)) => {
                             new_configs.insert(name, setting);
                         }
-                        EitherOrBoth::Right((name, setting)) => {
+                        // new config
-                            let setting = validate_prompt(&name, setting)?;
+                        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,
+            source,
-            document_template: Setting::Set(PromptSettings { template: Setting::Set(template) }),
+            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,
+                source,
-                document_template: Setting::Set(PromptSettings {
+                model,
-                    template: Setting::Set(template),
+                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;
+        let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
-        self.embedder_options.apply(embedder_options);
+            new;
-        self.document_template.apply(prompt);
+        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 {
+        let EmbeddingConfig { embedder_options, prompt } = value;
-            embedder_options: Setting::Set(value.embedder_options.into()),
+        match embedder_options {
-            document_template: Setting::Set(value.prompt.into()),
+            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,
+            },
         }
     }
 }
@@ -37,262 +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;
+        let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
-        if let Some(embedder_options) = embedder_options.set() {
+            value;
-            this.embedder_options = embedder_options.into();
+        if let Some(source) = source.set() {
-        }
+            match source {
-        if let Some(prompt) = prompt.set() {
+                EmbedderSource::OpenAi => {
-            this.prompt = prompt.into();
+                    let mut options = super::openai::EmbedderOptions::with_default_model(None);
-        }
-        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 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,
-                    ))),
-                }
-            }
-            _ => 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())
-            }
-        }
-    }
-}
-
-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(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);
+                }
+                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
-            this.revision = None;
+                        options.revision = None;
                     }
                     if let Some(revision) = revision.set() {
-            this.revision = Some(revision);
+                        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(),
+                        });
+                }
+            }
+        }
+
+        if let Setting::Set(template) = document_template {
+            this.prompt = PromptData { template }
+        }
+
         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 }
-    }
-}