Merge #4375

4375: Feat: add new OpenAI models and ability to override dimensions r=dureuill a=Gosti

# Pull Request

Fixes #4394 

## Related discussion
https://github.com/orgs/meilisearch/discussions/677#discussioncomment-8306384

## What does this PR do?
- Add text-embedding-3-small
- Add text-embedding-3-large
- Add optional dimensions parameter for both new models


## Note
As the dimensions option is not available for text-embedding-ada-002 I've added a manual check to prevent, but I feel it could be implemented in a more idiomatic rust 

## PR checklist
Please check if your PR fulfills the following requirements:
- [x] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [x] Have you read the contributing guidelines?
- [x] Have you made sure that the title is accurate and descriptive of the changes?

Thank you so much for contributing to Meilisearch!


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

meilisearch-types/src/error.rs

@@ -347,6 +347,9 @@ impl ErrorCode for milli::Error {
                     UserError::InvalidFieldForSource { .. }
                     | UserError::MissingFieldForSource { .. }
                     | UserError::InvalidOpenAiModel { .. }
+                    | UserError::InvalidOpenAiModelDimensions { .. }
+                    | UserError::InvalidOpenAiModelDimensionsMax { .. }
+                    | UserError::InvalidSettingsDimensions { .. }
                     | UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
                     UserError::TooManyEmbedders(_) => Code::InvalidSettingsEmbedders,
                     UserError::InvalidPromptForEmbeddings(..) => Code::InvalidSettingsEmbedders,

milli/src/error.rs

@@ -227,6 +227,22 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
         source_: crate::vector::settings::EmbedderSource,
         embedder_name: String,
     },
+    #[error("`.embedders.{embedder_name}.dimensions`: Model `{model}` does not support overriding its native dimensions of {expected_dimensions}. Found {dimensions}")]
+    InvalidOpenAiModelDimensions {
+        embedder_name: String,
+        model: &'static str,
+        dimensions: usize,
+        expected_dimensions: usize,
+    },
+    #[error("`.embedders.{embedder_name}.dimensions`: Model `{model}` does not support overriding its dimensions to a value higher than {max_dimensions}. Found {dimensions}")]
+    InvalidOpenAiModelDimensionsMax {
+        embedder_name: String,
+        model: &'static str,
+        dimensions: usize,
+        max_dimensions: usize,
+    },
+    #[error("`.embedders.{embedder_name}.dimensions`: `dimensions` cannot be zero")]
+    InvalidSettingsDimensions { embedder_name: String },
 }
 
 impl From<crate::vector::Error> for Error {

milli/src/update/settings.rs

@@ -974,6 +974,9 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
                             crate::vector::settings::EmbeddingSettings::apply_default_source(
                                 &mut setting,
                             );
+                            crate::vector::settings::EmbeddingSettings::apply_default_openai_model(
+                                &mut setting,
+                            );
                             let setting = validate_embedding_settings(setting, &name)?;
                             changed = true;
                             new_configs.insert(name, setting);
@@ -1119,6 +1122,14 @@ pub fn validate_embedding_settings(
     let Setting::Set(settings) = settings else { return Ok(settings) };
     let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
         settings;
+
+    if let Some(0) = dimensions.set() {
+        return Err(crate::error::UserError::InvalidSettingsDimensions {
+            embedder_name: name.to_owned(),
+        }
+        .into());
+    }
+
     let Some(inferred_source) = source.set() else {
         return Ok(Setting::Set(EmbeddingSettings {
             source,
@@ -1132,14 +1143,34 @@ pub fn validate_embedding_settings(
     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 {
+                let model = crate::vector::openai::EmbeddingModel::from_name(model.as_str())
+                    .ok_or(crate::error::UserError::InvalidOpenAiModel {
                         embedder_name: name.to_owned(),
                         model: model.clone(),
-                    },
-                )?;
+                    })?;
+                if let Setting::Set(dimensions) = dimensions {
+                    if !model.supports_overriding_dimensions()
+                        && dimensions != model.default_dimensions()
+                    {
+                        return Err(crate::error::UserError::InvalidOpenAiModelDimensions {
+                            embedder_name: name.to_owned(),
+                            model: model.name(),
+                            dimensions,
+                            expected_dimensions: model.default_dimensions(),
+                        }
+                        .into());
+                    }
+                    if dimensions > model.default_dimensions() {
+                        return Err(crate::error::UserError::InvalidOpenAiModelDimensionsMax {
+                            embedder_name: name.to_owned(),
+                            model: model.name(),
+                            dimensions,
+                            max_dimensions: model.default_dimensions(),
+                        }
+                        .into());
+                    }
+                }
             }
         }
         EmbedderSource::HuggingFace => {

milli/src/vector/openai.rs

@@ -17,6 +17,7 @@ pub struct Embedder {
 pub struct EmbedderOptions {
     pub api_key: Option<String>,
     pub embedding_model: EmbeddingModel,
+    pub dimensions: Option<usize>,
 }
 
 #[derive(
@@ -41,34 +42,50 @@ pub enum EmbeddingModel {
     #[serde(rename = "text-embedding-ada-002")]
     #[deserr(rename = "text-embedding-ada-002")]
     TextEmbeddingAda002,
+
+    #[serde(rename = "text-embedding-3-small")]
+    #[deserr(rename = "text-embedding-3-small")]
+    TextEmbedding3Small,
+
+    #[serde(rename = "text-embedding-3-large")]
+    #[deserr(rename = "text-embedding-3-large")]
+    TextEmbedding3Large,
 }
 
 impl EmbeddingModel {
     pub fn supported_models() -> &'static [&'static str] {
-        &["text-embedding-ada-002"]
+        &["text-embedding-ada-002", "text-embedding-3-small", "text-embedding-3-large"]
     }
 
     pub fn max_token(&self) -> usize {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => 8191,
+            EmbeddingModel::TextEmbedding3Large => 8191,
+            EmbeddingModel::TextEmbedding3Small => 8191,
         }
     }
 
-    pub fn dimensions(&self) -> usize {
+    pub fn default_dimensions(&self) -> usize {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => 1536,
+            EmbeddingModel::TextEmbedding3Large => 3072,
+            EmbeddingModel::TextEmbedding3Small => 1536,
         }
     }
 
     pub fn name(&self) -> &'static str {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => "text-embedding-ada-002",
+            EmbeddingModel::TextEmbedding3Large => "text-embedding-3-large",
+            EmbeddingModel::TextEmbedding3Small => "text-embedding-3-small",
         }
     }
 
     pub fn from_name(name: &str) -> Option<Self> {
         match name {
             "text-embedding-ada-002" => Some(EmbeddingModel::TextEmbeddingAda002),
+            "text-embedding-3-large" => Some(EmbeddingModel::TextEmbedding3Large),
+            "text-embedding-3-small" => Some(EmbeddingModel::TextEmbedding3Small),
             _ => None,
         }
     }
@@ -78,6 +95,20 @@ impl EmbeddingModel {
             EmbeddingModel::TextEmbeddingAda002 => {
                 Some(DistributionShift { current_mean: 0.90, current_sigma: 0.08 })
             }
+            EmbeddingModel::TextEmbedding3Large => {
+                Some(DistributionShift { current_mean: 0.70, current_sigma: 0.1 })
+            }
+            EmbeddingModel::TextEmbedding3Small => {
+                Some(DistributionShift { current_mean: 0.75, current_sigma: 0.1 })
+            }
+        }
+    }
+
+    pub fn supports_overriding_dimensions(&self) -> bool {
+        match self {
+            EmbeddingModel::TextEmbeddingAda002 => false,
+            EmbeddingModel::TextEmbedding3Large => true,
+            EmbeddingModel::TextEmbedding3Small => true,
         }
     }
 }
@@ -86,11 +117,11 @@ pub const OPENAI_EMBEDDINGS_URL: &str = "https://api.openai.com/v1/embeddings";
 
 impl EmbedderOptions {
     pub fn with_default_model(api_key: Option<String>) -> Self {
-        Self { api_key, embedding_model: Default::default() }
+        Self { api_key, embedding_model: Default::default(), dimensions: None }
     }
 
     pub fn with_embedding_model(api_key: Option<String>, embedding_model: EmbeddingModel) -> Self {
-        Self { api_key, embedding_model }
+        Self { api_key, embedding_model, dimensions: None }
     }
 }
 
@@ -237,7 +268,11 @@ impl Embedder {
         for text in texts {
             log::trace!("Received prompt: {}", text.as_ref())
         }
-        let request = OpenAiRequest { model: self.options.embedding_model.name(), input: texts };
+        let request = OpenAiRequest {
+            model: self.options.embedding_model.name(),
+            input: texts,
+            dimensions: self.overriden_dimensions(),
+        };
         let response = client
             .post(OPENAI_EMBEDDINGS_URL)
             .json(&request)
@@ -280,8 +315,7 @@ impl Embedder {
             }
 
             let mut tokens = encoded.as_slice();
-            let mut embeddings_for_prompt =
-                Embeddings::new(self.options.embedding_model.dimensions());
+            let mut embeddings_for_prompt = Embeddings::new(self.dimensions());
             while tokens.len() > max_token_count {
                 let window = &tokens[..max_token_count];
                 embeddings_for_prompt.push(self.embed_tokens(window, client).await?).unwrap();
@@ -322,8 +356,11 @@ impl Embedder {
         tokens: &[usize],
         client: &reqwest::Client,
     ) -> Result<Embedding, Retry> {
-        let request =
-            OpenAiTokensRequest { model: self.options.embedding_model.name(), input: tokens };
+        let request = OpenAiTokensRequest {
+            model: self.options.embedding_model.name(),
+            input: tokens,
+            dimensions: self.overriden_dimensions(),
+        };
         let response = client
             .post(OPENAI_EMBEDDINGS_URL)
             .json(&request)
@@ -366,12 +403,24 @@ impl Embedder {
     }
 
     pub fn dimensions(&self) -> usize {
-        self.options.embedding_model.dimensions()
+        if self.options.embedding_model.supports_overriding_dimensions() {
+            self.options.dimensions.unwrap_or(self.options.embedding_model.default_dimensions())
+        } else {
+            self.options.embedding_model.default_dimensions()
+        }
     }
 
     pub fn distribution(&self) -> Option<DistributionShift> {
         self.options.embedding_model.distribution()
     }
+
+    fn overriden_dimensions(&self) -> Option<usize> {
+        if self.options.embedding_model.supports_overriding_dimensions() {
+            self.options.dimensions
+        } else {
+            None
+        }
+    }
 }
 
 // retrying in case of failure
@@ -431,12 +480,16 @@ impl Retry {
 struct OpenAiRequest<'a, S: AsRef<str> + serde::Serialize> {
     model: &'a str,
     input: &'a [S],
+    #[serde(skip_serializing_if = "Option::is_none")]
+    dimensions: Option<usize>,
 }
 
 #[derive(Debug, Serialize)]
 struct OpenAiTokensRequest<'a> {
     model: &'a str,
     input: &'a [usize],
+    #[serde(skip_serializing_if = "Option::is_none")]
+    dimensions: Option<usize>,
 }
 
 #[derive(Debug, Deserialize)]

milli/src/vector/settings.rs

@@ -1,6 +1,7 @@
 use deserr::Deserr;
 use serde::{Deserialize, Serialize};
 
+use super::openai;
 use crate::prompt::PromptData;
 use crate::update::Setting;
 use crate::vector::EmbeddingConfig;
@@ -82,7 +83,7 @@ impl EmbeddingSettings {
             Self::MODEL => &[EmbedderSource::HuggingFace, EmbedderSource::OpenAi],
             Self::REVISION => &[EmbedderSource::HuggingFace],
             Self::API_KEY => &[EmbedderSource::OpenAi],
-            Self::DIMENSIONS => &[EmbedderSource::UserProvided],
+            Self::DIMENSIONS => &[EmbedderSource::OpenAi, EmbedderSource::UserProvided],
             Self::DOCUMENT_TEMPLATE => &[EmbedderSource::HuggingFace, EmbedderSource::OpenAi],
             _other => unreachable!("unknown field"),
         }
@@ -90,9 +91,13 @@ impl EmbeddingSettings {
 
     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::OpenAi => &[
+                Self::SOURCE,
+                Self::MODEL,
+                Self::API_KEY,
+                Self::DOCUMENT_TEMPLATE,
+                Self::DIMENSIONS,
+            ],
             EmbedderSource::HuggingFace => {
                 &[Self::SOURCE, Self::MODEL, Self::REVISION, Self::DOCUMENT_TEMPLATE]
             }
@@ -109,6 +114,17 @@ impl EmbeddingSettings {
             *source = Setting::Set(EmbedderSource::default())
         }
     }
+
+    pub(crate) fn apply_default_openai_model(setting: &mut Setting<EmbeddingSettings>) {
+        if let Setting::Set(EmbeddingSettings {
+            source: Setting::Set(EmbedderSource::OpenAi),
+            model: model @ (Setting::NotSet | Setting::Reset),
+            ..
+        }) = setting
+        {
+            *model = Setting::Set(openai::EmbeddingModel::default().name().to_owned())
+        }
+    }
 }
 
 #[derive(Debug, Clone, Copy, Default, Serialize, Deserialize, PartialEq, Eq, Deserr)]
@@ -176,7 +192,7 @@ impl From<EmbeddingConfig> for EmbeddingSettings {
                 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,
+                dimensions: options.dimensions.map(Setting::Set).unwrap_or_default(),
                 document_template: Setting::Set(prompt.template),
             },
             super::EmbedderOptions::UserProvided(options) => Self {
@@ -208,6 +224,9 @@ impl From<EmbeddingSettings> for EmbeddingConfig {
                     if let Some(api_key) = api_key.set() {
                         options.api_key = Some(api_key);
                     }
+                    if let Some(dimensions) = dimensions.set() {
+                        options.dimensions = Some(dimensions);
+                    }
                     this.embedder_options = super::EmbedderOptions::OpenAi(options);
                 }
                 EmbedderSource::HuggingFace => {