Add Ollama as an embeddings provider

meilisearch/src/routes/indexes/settings.rs

@@ -604,6 +604,7 @@ fn embedder_analytics(
                 EmbedderSource::OpenAi => sources.insert("openAi"),
                 EmbedderSource::HuggingFace => sources.insert("huggingFace"),
                 EmbedderSource::UserProvided => sources.insert("userProvided"),
+                EmbedderSource::Ollama => sources.insert("ollama"),
             };
         }
     };

milli/src/update/settings.rs

@@ -1178,6 +1178,13 @@ pub fn validate_embedding_settings(
                 }
             }
         }
+        EmbedderSource::Ollama => {
+            // Dimensions get inferred, only model name is required
+            check_unset(&dimensions, "dimensions", inferred_source, name)?;
+            check_set(&model, "model", inferred_source, name)?;
+            check_unset(&api_key, "apiKey", inferred_source, name)?;
+            check_unset(&revision, "revision", inferred_source, name)?;
+        }
         EmbedderSource::HuggingFace => {
             check_unset(&api_key, "apiKey", inferred_source, name)?;
             check_unset(&dimensions, "dimensions", inferred_source, name)?;

milli/src/vector/error.rs

@@ -2,6 +2,7 @@ use std::path::PathBuf;
 
 use hf_hub::api::sync::ApiError;
 
+use super::ollama::OllamaError;
 use crate::error::FaultSource;
 use crate::vector::openai::OpenAiError;
 
@@ -71,6 +72,17 @@ pub enum EmbedErrorKind {
     OpenAiRuntimeInit(std::io::Error),
     #[error("initializing web client for sending embedding requests failed: {0}")]
     InitWebClient(reqwest::Error),
+    // Dedicated Ollama error kinds, might have to merge them into one cohesive error type for all backends.
+    #[error("unexpected response from Ollama: {0}")]
+    OllamaUnexpected(reqwest::Error),
+    #[error("sent too many requests to Ollama: {0}")]
+    OllamaTooManyRequests(OllamaError),
+    #[error("received internal error from Ollama: {0}")]
+    OllamaInternalServerError(OllamaError),
+    #[error("model not found. Meilisearch will not automatically download models from the Ollama library, please pull the model manually: {0}")]
+    OllamaModelNotFoundError(OllamaError),
+    #[error("received unhandled HTTP status code {0} from Ollama")]
+    OllamaUnhandledStatusCode(u16),
 }
 
 impl EmbedError {
@@ -129,6 +141,26 @@ impl EmbedError {
     pub fn openai_initialize_web_client(inner: reqwest::Error) -> Self {
         Self { kind: EmbedErrorKind::InitWebClient(inner), fault: FaultSource::Runtime }
     }
+
+    pub(crate) fn ollama_unexpected(inner: reqwest::Error) -> EmbedError {
+        Self { kind: EmbedErrorKind::OllamaUnexpected(inner), fault: FaultSource::Bug }
+    }
+
+    pub(crate) fn ollama_model_not_found(inner: OllamaError) -> EmbedError {
+        Self { kind: EmbedErrorKind::OllamaModelNotFoundError(inner), fault: FaultSource::User }
+    }
+
+    pub(crate) fn ollama_too_many_requests(inner: OllamaError) -> EmbedError {
+        Self { kind: EmbedErrorKind::OllamaTooManyRequests(inner), fault: FaultSource::Runtime }
+    }
+
+    pub(crate) fn ollama_internal_server_error(inner: OllamaError) -> EmbedError {
+        Self { kind: EmbedErrorKind::OllamaInternalServerError(inner), fault: FaultSource::Runtime }
+    }
+
+    pub(crate) fn ollama_unhandled_status_code(code: u16) -> EmbedError {
+        Self { kind: EmbedErrorKind::OllamaUnhandledStatusCode(code), fault: FaultSource::Bug }
+    }
 }
 
 #[derive(Debug, thiserror::Error)]
@@ -195,6 +227,13 @@ impl NewEmbedderError {
         }
     }
 
+    pub fn ollama_could_not_determine_dimension(inner: EmbedError) -> NewEmbedderError {
+        Self {
+            kind: NewEmbedderErrorKind::CouldNotDetermineDimension(inner),
+            fault: FaultSource::User,
+        }
+    }
+
     pub fn openai_invalid_api_key_format(inner: reqwest::header::InvalidHeaderValue) -> Self {
         Self { kind: NewEmbedderErrorKind::InvalidApiKeyFormat(inner), fault: FaultSource::User }
     }

milli/src/vector/mod.rs

@@ -10,6 +10,8 @@ pub mod manual;
 pub mod openai;
 pub mod settings;
 
+pub mod ollama;
+
 pub use self::error::Error;
 
 pub type Embedding = Vec<f32>;
@@ -76,6 +78,7 @@ pub enum Embedder {
     HuggingFace(hf::Embedder),
     OpenAi(openai::Embedder),
     UserProvided(manual::Embedder),
+    Ollama(ollama::Embedder),
 }
 
 #[derive(Debug, Clone, Default, serde::Deserialize, serde::Serialize)]
@@ -127,6 +130,7 @@ impl IntoIterator for EmbeddingConfigs {
 pub enum EmbedderOptions {
     HuggingFace(hf::EmbedderOptions),
     OpenAi(openai::EmbedderOptions),
+    Ollama(ollama::EmbedderOptions),
     UserProvided(manual::EmbedderOptions),
 }
 
@@ -144,13 +148,18 @@ impl EmbedderOptions {
     pub fn openai(api_key: Option<String>) -> Self {
         Self::OpenAi(openai::EmbedderOptions::with_default_model(api_key))
     }
+
+    pub fn ollama() -> Self {
+        Self::Ollama(ollama::EmbedderOptions::with_default_model())
+    }
 }
 
 impl Embedder {
     pub fn new(options: EmbedderOptions) -> std::result::Result<Self, NewEmbedderError> {
         Ok(match options {
             EmbedderOptions::HuggingFace(options) => Self::HuggingFace(hf::Embedder::new(options)?),
             EmbedderOptions::OpenAi(options) => Self::OpenAi(openai::Embedder::new(options)?),
+            EmbedderOptions::Ollama(options) => Self::Ollama(ollama::Embedder::new(options)?),
             EmbedderOptions::UserProvided(options) => {
                 Self::UserProvided(manual::Embedder::new(options))
             }
@@ -167,6 +176,10 @@ impl Embedder {
                 let client = embedder.new_client()?;
                 embedder.embed(texts, &client).await
             }
+            Embedder::Ollama(embedder) => {
+                let client = embedder.new_client()?;
+                embedder.embed(texts, &client).await
+            }
             Embedder::UserProvided(embedder) => embedder.embed(texts),
         }
     }
@@ -181,6 +194,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.embed_chunks(text_chunks),
             Embedder::OpenAi(embedder) => embedder.embed_chunks(text_chunks),
+            Embedder::Ollama(embedder) => embedder.embed_chunks(text_chunks),
             Embedder::UserProvided(embedder) => embedder.embed_chunks(text_chunks),
         }
     }
@@ -189,6 +203,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.chunk_count_hint(),
             Embedder::OpenAi(embedder) => embedder.chunk_count_hint(),
+            Embedder::Ollama(embedder) => embedder.chunk_count_hint(),
             Embedder::UserProvided(_) => 1,
         }
     }
@@ -197,6 +212,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.prompt_count_in_chunk_hint(),
             Embedder::OpenAi(embedder) => embedder.prompt_count_in_chunk_hint(),
+            Embedder::Ollama(embedder) => embedder.prompt_count_in_chunk_hint(),
             Embedder::UserProvided(_) => 1,
         }
     }
@@ -205,6 +221,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.dimensions(),
             Embedder::OpenAi(embedder) => embedder.dimensions(),
+            Embedder::Ollama(embedder) => embedder.dimensions(),
             Embedder::UserProvided(embedder) => embedder.dimensions(),
         }
     }
@@ -213,6 +230,7 @@ impl Embedder {
         match self {
             Embedder::HuggingFace(embedder) => embedder.distribution(),
             Embedder::OpenAi(embedder) => embedder.distribution(),
+            Embedder::Ollama(embedder) => embedder.distribution(),
             Embedder::UserProvided(_embedder) => None,
         }
     }