mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-22 12:54:26 +01:00
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>
This commit is contained in:
commit
d4cb0a885b
@ -344,7 +344,10 @@ impl ErrorCode for milli::Error {
|
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Code::InvalidDocumentId
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}
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UserError::MissingDocumentField(_) => Code::InvalidDocumentFields,
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UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
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UserError::InvalidFieldForSource { .. }
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| UserError::MissingFieldForSource { .. }
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| UserError::InvalidOpenAiModel { .. }
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| UserError::InvalidPrompt(_) => Code::InvalidSettingsEmbedders,
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UserError::TooManyEmbedders(_) => Code::InvalidSettingsEmbedders,
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UserError::InvalidPromptForEmbeddings(..) => Code::InvalidSettingsEmbedders,
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UserError::NoPrimaryKeyCandidateFound => Code::IndexPrimaryKeyNoCandidateFound,
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|
@ -318,6 +318,21 @@ impl Settings<Unchecked> {
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_kind: PhantomData,
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}
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}
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pub fn validate(self) -> Result<Self, milli::Error> {
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self.validate_embedding_settings()
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}
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fn validate_embedding_settings(mut self) -> Result<Self, milli::Error> {
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let Setting::Set(mut configs) = self.embedders else { return Ok(self) };
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for (name, config) in configs.iter_mut() {
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let config_to_check = std::mem::take(config);
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let checked_config = milli::update::validate_embedding_settings(config_to_check, name)?;
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*config = checked_config
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}
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self.embedders = Setting::Set(configs);
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Ok(self)
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}
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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|
@ -90,6 +90,8 @@ macro_rules! make_setting_route {
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..Default::default()
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};
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let new_settings = new_settings.validate()?;
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let allow_index_creation =
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index_scheduler.filters().allow_index_creation(&index_uid);
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@ -582,13 +584,13 @@ fn embedder_analytics(
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for source in s
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.values()
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.filter_map(|config| config.clone().set())
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.filter_map(|config| config.embedder_options.set())
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.filter_map(|config| config.source.set())
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{
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use meilisearch_types::milli::vector::settings::EmbedderSettings;
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use meilisearch_types::milli::vector::settings::EmbedderSource;
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match source {
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EmbedderSettings::OpenAi(_) => sources.insert("openAi"),
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EmbedderSettings::HuggingFace(_) => sources.insert("huggingFace"),
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EmbedderSettings::UserProvided(_) => sources.insert("userProvided"),
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EmbedderSource::OpenAi => sources.insert("openAi"),
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EmbedderSource::HuggingFace => sources.insert("huggingFace"),
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EmbedderSource::UserProvided => sources.insert("userProvided"),
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};
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}
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};
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@ -651,6 +653,7 @@ pub async fn update_all(
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let index_uid = IndexUid::try_from(index_uid.into_inner())?;
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let new_settings = body.into_inner();
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let new_settings = new_settings.validate()?;
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analytics.publish(
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"Settings Updated".to_string(),
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|
@ -21,9 +21,9 @@ async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Inde
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"###);
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let (response, code) = index
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.update_settings(
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json!({ "embedders": {"default": {"source": {"userProvided": {"dimensions": 2}}}} }),
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)
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.update_settings(json!({ "embedders": {"default": {
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"source": "userProvided",
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"dimensions": 2}}} ))
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.await;
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assert_eq!(202, code, "{:?}", response);
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index.wait_task(response.uid()).await;
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|
@ -890,13 +890,21 @@ async fn experimental_feature_vector_store() {
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let (response, code) = index
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.update_settings(json!({"embedders": {
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"manual": {
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"source": {
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"userProvided": {"dimensions": 3}
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}
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"source": "userProvided",
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"dimensions": 3,
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}
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}}))
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.await;
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meili_snap::snapshot!(response, @r###"
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{
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"taskUid": 1,
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"indexUid": "test",
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"status": "enqueued",
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"type": "settingsUpdate",
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"enqueuedAt": "[date]"
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}
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"###);
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meili_snap::snapshot!(code, @"202 Accepted");
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let response = index.wait_task(response.uid()).await;
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|
@ -192,7 +192,7 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
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MissingDocumentField(#[from] crate::prompt::error::RenderPromptError),
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#[error(transparent)]
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InvalidPrompt(#[from] crate::prompt::error::NewPromptError),
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#[error("Invalid prompt in for embeddings with name '{0}': {1}.")]
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#[error("`.embedders.{0}.documentTemplate`: Invalid template: {1}.")]
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InvalidPromptForEmbeddings(String, crate::prompt::error::NewPromptError),
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#[error("Too many embedders in the configuration. Found {0}, but limited to 256.")]
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TooManyEmbedders(usize),
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@ -200,6 +200,33 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
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InvalidEmbedder(String),
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#[error("Too many vectors for document with id {0}: found {1}, but limited to 256.")]
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TooManyVectors(String, usize),
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#[error("`.embedders.{embedder_name}`: Field `{field}` unavailable for source `{source_}` (only available for sources: {}). Available fields: {}",
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allowed_sources_for_field
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.iter()
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.map(|accepted| format!("`{}`", accepted))
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.collect::<Vec<String>>()
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.join(", "),
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allowed_fields_for_source
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.iter()
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.map(|accepted| format!("`{}`", accepted))
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.collect::<Vec<String>>()
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.join(", ")
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)]
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InvalidFieldForSource {
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embedder_name: String,
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source_: crate::vector::settings::EmbedderSource,
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field: &'static str,
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allowed_fields_for_source: &'static [&'static str],
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allowed_sources_for_field: &'static [crate::vector::settings::EmbedderSource],
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},
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#[error("`.embedders.{embedder_name}.model`: Invalid model `{model}` for OpenAI. Supported models: {:?}", crate::vector::openai::EmbeddingModel::supported_models())]
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InvalidOpenAiModel { embedder_name: String, model: String },
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#[error("`.embedders.{embedder_name}`: Missing field `{field}` (note: this field is mandatory for source {source_})")]
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MissingFieldForSource {
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field: &'static str,
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source_: crate::vector::settings::EmbedderSource,
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embedder_name: String,
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},
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}
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impl From<crate::vector::Error> for Error {
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|
@ -2553,7 +2553,7 @@ mod tests {
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/// Vectors must be of the same length.
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#[test]
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fn test_multiple_vectors() {
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use crate::vector::settings::{EmbedderSettings, EmbeddingSettings};
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use crate::vector::settings::EmbeddingSettings;
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let index = TempIndex::new();
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index
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@ -2562,9 +2562,11 @@ mod tests {
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embedders.insert(
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"manual".to_string(),
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Setting::Set(EmbeddingSettings {
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embedder_options: Setting::Set(EmbedderSettings::UserProvided(
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crate::vector::settings::UserProvidedSettings { dimensions: 3 },
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)),
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source: Setting::Set(crate::vector::settings::EmbedderSource::UserProvided),
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model: Setting::NotSet,
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revision: Setting::NotSet,
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api_key: Setting::NotSet,
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dimensions: Setting::Set(3),
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document_template: Setting::NotSet,
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}),
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);
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@ -2579,10 +2581,10 @@ mod tests {
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.unwrap();
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index.add_documents(documents!([{"id": 1, "_vectors": { "manual": [6, 7, 8] }}])).unwrap();
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index
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.add_documents(
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documents!([{"id": 2, "_vectors": { "manual": [[9, 10, 11], [12, 13, 14], [15, 16, 17]] }}]),
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)
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.unwrap();
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.add_documents(
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documents!([{"id": 2, "_vectors": { "manual": [[9, 10, 11], [12, 13, 14], [15, 16, 17]] }}]),
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)
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.unwrap();
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let rtxn = index.read_txn().unwrap();
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let res = index.search(&rtxn).vector([0.0, 1.0, 2.0].to_vec()).execute().unwrap();
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|
@ -8,7 +8,7 @@ pub use self::index_documents::{
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MergeFn,
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};
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pub use self::indexer_config::IndexerConfig;
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pub use self::settings::{Setting, Settings};
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pub use self::settings::{validate_embedding_settings, Setting, Settings};
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pub use self::update_step::UpdateIndexingStep;
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pub use self::word_prefix_docids::WordPrefixDocids;
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pub use self::words_prefix_integer_docids::WordPrefixIntegerDocids;
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|
@ -17,7 +17,7 @@ use crate::index::{DEFAULT_MIN_WORD_LEN_ONE_TYPO, DEFAULT_MIN_WORD_LEN_TWO_TYPOS
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use crate::proximity::ProximityPrecision;
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use crate::update::index_documents::IndexDocumentsMethod;
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use crate::update::{IndexDocuments, UpdateIndexingStep};
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use crate::vector::settings::{EmbeddingSettings, PromptSettings};
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use crate::vector::settings::{check_set, check_unset, EmbedderSource, EmbeddingSettings};
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use crate::vector::{Embedder, EmbeddingConfig, EmbeddingConfigs};
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use crate::{FieldsIdsMap, Index, OrderBy, Result};
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@ -78,11 +78,19 @@ impl<T> Setting<T> {
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}
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}
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pub fn apply(&mut self, new: Self) {
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/// Returns `true` if applying the new setting changed this setting
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pub fn apply(&mut self, new: Self) -> bool
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where
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T: PartialEq + Eq,
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{
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if let Setting::NotSet = new {
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return;
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return false;
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}
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if self == &new {
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return false;
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}
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*self = new;
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true
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}
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}
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@ -950,17 +958,23 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
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.merge_join_by(configs.into_iter(), |(left, _), (right, _)| left.cmp(right))
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{
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match joined {
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// updated config
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EitherOrBoth::Both((name, mut old), (_, new)) => {
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old.apply(new);
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let new = validate_prompt(&name, old)?;
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changed = true;
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changed |= old.apply(new);
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let new = validate_embedding_settings(old, &name)?;
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new_configs.insert(name, new);
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}
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// unchanged config
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EitherOrBoth::Left((name, setting)) => {
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new_configs.insert(name, setting);
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}
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EitherOrBoth::Right((name, setting)) => {
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let setting = validate_prompt(&name, setting)?;
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// new config
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EitherOrBoth::Right((name, mut setting)) => {
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// apply the default source in case the source was not set so that it gets validated
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crate::vector::settings::EmbeddingSettings::apply_default_source(
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&mut setting,
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);
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let setting = validate_embedding_settings(setting, &name)?;
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changed = true;
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new_configs.insert(name, setting);
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}
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@ -1072,8 +1086,12 @@ fn validate_prompt(
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) -> Result<Setting<EmbeddingSettings>> {
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match new {
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Setting::Set(EmbeddingSettings {
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embedder_options,
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document_template: Setting::Set(PromptSettings { template: Setting::Set(template) }),
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source,
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model,
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revision,
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api_key,
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dimensions,
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document_template: Setting::Set(template),
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}) => {
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// validate
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let template = crate::prompt::Prompt::new(template)
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@ -1081,16 +1099,71 @@ fn validate_prompt(
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.map_err(|inner| UserError::InvalidPromptForEmbeddings(name.to_owned(), inner))?;
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Ok(Setting::Set(EmbeddingSettings {
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embedder_options,
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document_template: Setting::Set(PromptSettings {
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template: Setting::Set(template),
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}),
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source,
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model,
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revision,
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api_key,
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dimensions,
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document_template: Setting::Set(template),
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}))
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}
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new => Ok(new),
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}
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}
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pub fn validate_embedding_settings(
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settings: Setting<EmbeddingSettings>,
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name: &str,
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) -> Result<Setting<EmbeddingSettings>> {
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let settings = validate_prompt(name, settings)?;
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let Setting::Set(settings) = settings else { return Ok(settings) };
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let EmbeddingSettings { source, model, revision, api_key, dimensions, document_template } =
|
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settings;
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let Some(inferred_source) = source.set() else {
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return Ok(Setting::Set(EmbeddingSettings {
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source,
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model,
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revision,
|
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api_key,
|
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dimensions,
|
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document_template,
|
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}));
|
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};
|
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match inferred_source {
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EmbedderSource::OpenAi => {
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check_unset(&revision, "revision", inferred_source, name)?;
|
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check_unset(&dimensions, "dimensions", inferred_source, name)?;
|
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if let Setting::Set(model) = &model {
|
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crate::vector::openai::EmbeddingModel::from_name(model.as_str()).ok_or(
|
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crate::error::UserError::InvalidOpenAiModel {
|
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embedder_name: name.to_owned(),
|
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model: model.clone(),
|
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},
|
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)?;
|
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}
|
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}
|
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EmbedderSource::HuggingFace => {
|
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check_unset(&api_key, "apiKey", inferred_source, name)?;
|
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check_unset(&dimensions, "dimensions", inferred_source, name)?;
|
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}
|
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EmbedderSource::UserProvided => {
|
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check_unset(&model, "model", inferred_source, name)?;
|
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check_unset(&revision, "revision", inferred_source, name)?;
|
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check_unset(&api_key, "apiKey", inferred_source, name)?;
|
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check_unset(&document_template, "documentTemplate", inferred_source, name)?;
|
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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;
|
||||
|
@ -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,
|
||||
|
@ -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,
|
||||
},
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -37,262 +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;
|
||||
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;
|
||||
// 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;
|
||||
}
|
||||
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 }
|
||||
}
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user