Merge #4740

4740: Make `embeddings` optional and improve error message for `regenerate` r=dureuill a=irevoire

# Pull Request

## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4741

## What does this PR do?
- Make the `embeddings` parameter optional when manually specifying embeddings for an embedder
- Adds a lot of tests around malformed `_vectors.embedder` objects
- Use `deserr` to deserialize the `_vectors.embedder` field, improving error messages


Co-authored-by: Tamo <tamo@meilisearch.com>

meilisearch-types/src/error.rs

@@ -398,7 +398,8 @@ impl ErrorCode for milli::Error {
                     UserError::CriterionError(_) => Code::InvalidSettingsRankingRules,
                     UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
                     UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
-                    UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
+                    UserError::InvalidVectorsMapType { .. }
+                    | UserError::InvalidVectorsEmbedderConf { .. } => Code::InvalidVectorsType,
                     UserError::TooManyVectors(_, _) => Code::TooManyVectors,
                     UserError::SortError(_) => Code::InvalidSearchSort,
                     UserError::InvalidMinTypoWordLenSetting(_, _) => {

meilisearch/tests/vector/mod.rs

@@ -190,6 +190,285 @@ async fn generate_default_user_provided_documents(server: &Server) -> Index {
     index
 }
 
+#[actix_rt::test]
+async fn user_provided_embeddings_error() {
+    let server = Server::new().await;
+    let index = generate_default_user_provided_documents(&server).await;
+
+    // First case, we forget to specify the `regenerate`
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [0, 0, 0] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 2,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    // Second case, we don't specify anything
+    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": {}}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 3,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Missing field `regenerate` inside `.manual`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    // Third case, we specify something wrong in place of regenerate
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": "yes please" }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 4,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.regenerate`: expected a boolean, but found a string: `\"yes please\"`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": true }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 5,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings`: expected null or an array, but found a boolean: `true`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [true] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 6,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0]`: expected a number or an array, but found a boolean: `true`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [[true]] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 7,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][0]`: expected a number, but found a boolean: `true`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "embeddings": [23, 0.1, -12], "regenerate": true }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task["status"], @r###""succeeded""###);
+
+    let documents =
+        json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task["status"], @r###""succeeded""###);
+
+    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [0.1, [0.2, 0.3]] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 10,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected a number, but found an array: `[0.2,0.3]`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [[0.1, 0.2], 0.3] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 11,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[1]`: expected an array, but found a number: `0.3`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+
+    let documents = json!({"id": 0, "name": "kefir", "_vectors": { "manual": { "regenerate": false, "embeddings": [[0.1, true], 0.3] }}});
+    let (value, code) = index.add_documents(documents, None).await;
+    snapshot!(code, @"202 Accepted");
+    let task = index.wait_task(value.uid()).await;
+    snapshot!(task, @r###"
+    {
+      "uid": 12,
+      "indexUid": "doggo",
+      "status": "failed",
+      "type": "documentAdditionOrUpdate",
+      "canceledBy": null,
+      "details": {
+        "receivedDocuments": 1,
+        "indexedDocuments": 0
+      },
+      "error": {
+        "message": "Bad embedder configuration in the document with id: `\"0\"`. Invalid value type at `.manual.embeddings[0][1]`: expected a number, but found a boolean: `true`",
+        "code": "invalid_vectors_type",
+        "type": "invalid_request",
+        "link": "https://docs.meilisearch.com/errors#invalid_vectors_type"
+      },
+      "duration": "[duration]",
+      "enqueuedAt": "[date]",
+      "startedAt": "[date]",
+      "finishedAt": "[date]"
+    }
+    "###);
+}
+
 #[actix_rt::test]
 async fn clear_documents() {
     let server = Server::new().await;

milli/src/error.rs

@@ -119,6 +119,8 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
     InvalidVectorDimensions { expected: usize, found: usize },
     #[error("The `_vectors` field in the document with id: `{document_id}` is not an object. Was expecting an object with a key for each embedder with manually provided vectors, but instead got `{value}`")]
     InvalidVectorsMapType { document_id: String, value: Value },
+    #[error("Bad embedder configuration in the document with id: `{document_id}`. {error}")]
+    InvalidVectorsEmbedderConf { document_id: String, error: deserr::errors::JsonError },
     #[error("{0}")]
     InvalidFilter(String),
     #[error("Invalid type for filter subexpression: expected: {}, found: {1}.", .0.join(", "))]

milli/src/vector/parsed_vectors.rs

@@ -1,5 +1,6 @@
 use std::collections::{BTreeMap, BTreeSet};
 
+use deserr::{take_cf_content, DeserializeError, Deserr, Sequence};
 use obkv::KvReader;
 use serde_json::{from_slice, Value};
 
@@ -10,13 +11,44 @@ use crate::{DocumentId, FieldId, InternalError, UserError};
 
 pub const RESERVED_VECTORS_FIELD_NAME: &str = "_vectors";
 
-#[derive(serde::Serialize, serde::Deserialize, Debug)]
+#[derive(serde::Serialize, Debug)]
 #[serde(untagged)]
 pub enum Vectors {
     ImplicitlyUserProvided(VectorOrArrayOfVectors),
     Explicit(ExplicitVectors),
 }
 
+impl<E: DeserializeError> Deserr<E> for Vectors {
+    fn deserialize_from_value<V: deserr::IntoValue>(
+        value: deserr::Value<V>,
+        location: deserr::ValuePointerRef,
+    ) -> Result<Self, E> {
+        match value {
+            deserr::Value::Sequence(_) | deserr::Value::Null => {
+                Ok(Vectors::ImplicitlyUserProvided(VectorOrArrayOfVectors::deserialize_from_value(
+                    value, location,
+                )?))
+            }
+            deserr::Value::Map(_) => {
+                Ok(Vectors::Explicit(ExplicitVectors::deserialize_from_value(value, location)?))
+            }
+
+            value => Err(take_cf_content(E::error(
+                None,
+                deserr::ErrorKind::IncorrectValueKind {
+                    actual: value,
+                    accepted: &[
+                        deserr::ValueKind::Sequence,
+                        deserr::ValueKind::Map,
+                        deserr::ValueKind::Null,
+                    ],
+                },
+                location,
+            ))),
+        }
+    }
+}
+
 impl Vectors {
     pub fn must_regenerate(&self) -> bool {
         match self {
@@ -37,9 +69,11 @@ impl Vectors {
     }
 }
 
-#[derive(serde::Serialize, serde::Deserialize, Debug)]
+#[derive(serde::Serialize, Deserr, Debug)]
 #[serde(rename_all = "camelCase")]
 pub struct ExplicitVectors {
+    #[serde(default)]
+    #[deserr(default)]
     pub embeddings: Option<VectorOrArrayOfVectors>,
     pub regenerate: bool,
 }
@@ -149,13 +183,20 @@ impl ParsedVectorsDiff {
 
 pub struct ParsedVectors(pub BTreeMap<String, Vectors>);
 
+impl<E: DeserializeError> Deserr<E> for ParsedVectors {
+    fn deserialize_from_value<V: deserr::IntoValue>(
+        value: deserr::Value<V>,
+        location: deserr::ValuePointerRef,
+    ) -> Result<Self, E> {
+        let value = <BTreeMap<String, Vectors>>::deserialize_from_value(value, location)?;
+        Ok(ParsedVectors(value))
+    }
+}
+
 impl ParsedVectors {
     pub fn from_bytes(value: &[u8]) -> Result<Self, Error> {
-        let Ok(value) = from_slice(value) else {
-            let value = from_slice(value).map_err(Error::InternalSerdeJson)?;
-            return Err(Error::InvalidMap(value));
-        };
-        Ok(ParsedVectors(value))
+        let value: serde_json::Value = from_slice(value).map_err(Error::InternalSerdeJson)?;
+        deserr::deserialize(value).map_err(|error| Error::InvalidEmbedderConf { error })
     }
 
     pub fn retain_not_embedded_vectors(&mut self, embedders: &BTreeSet<String>) {
@@ -165,6 +206,7 @@ impl ParsedVectors {
 
 pub enum Error {
     InvalidMap(Value),
+    InvalidEmbedderConf { error: deserr::errors::JsonError },
     InternalSerdeJson(serde_json::Error),
 }
 
@@ -174,6 +216,12 @@ impl Error {
             Error::InvalidMap(value) => {
                 crate::Error::UserError(UserError::InvalidVectorsMapType { document_id, value })
             }
+            Error::InvalidEmbedderConf { error } => {
+                crate::Error::UserError(UserError::InvalidVectorsEmbedderConf {
+                    document_id,
+                    error,
+                })
+            }
             Error::InternalSerdeJson(error) => {
                 crate::Error::InternalError(InternalError::SerdeJson(error))
             }
@@ -194,13 +242,84 @@ fn to_vector_map(
 }
 
 /// Represents either a vector or an array of multiple vectors.
-#[derive(serde::Serialize, serde::Deserialize, Debug)]
+#[derive(serde::Serialize, Debug)]
 #[serde(transparent)]
 pub struct VectorOrArrayOfVectors {
     #[serde(with = "either::serde_untagged_optional")]
     inner: Option<either::Either<Vec<Embedding>, Embedding>>,
 }
 
+impl<E: DeserializeError> Deserr<E> for VectorOrArrayOfVectors {
+    fn deserialize_from_value<V: deserr::IntoValue>(
+        value: deserr::Value<V>,
+        location: deserr::ValuePointerRef,
+    ) -> Result<Self, E> {
+        match value {
+            deserr::Value::Null => Ok(VectorOrArrayOfVectors { inner: None }),
+            deserr::Value::Sequence(seq) => {
+                let mut iter = seq.into_iter();
+                match iter.next().map(|v| v.into_value()) {
+                    None => {
+                        // With the strange way serde serialize the `Either`, we must send the left part
+                        // otherwise it'll consider we returned [[]]
+                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Left(Vec::new())) })
+                    }
+                    Some(val @ deserr::Value::Sequence(_)) => {
+                        let first = Embedding::deserialize_from_value(val, location.push_index(0))?;
+                        let mut collect = vec![first];
+                        let mut tail = iter
+                            .enumerate()
+                            .map(|(i, v)| {
+                                Embedding::deserialize_from_value(
+                                    v.into_value(),
+                                    location.push_index(i + 1),
+                                )
+                            })
+                            .collect::<Result<Vec<_>, _>>()?;
+                        collect.append(&mut tail);
+
+                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Left(collect)) })
+                    }
+                    Some(
+                        val @ deserr::Value::Integer(_)
+                        | val @ deserr::Value::NegativeInteger(_)
+                        | val @ deserr::Value::Float(_),
+                    ) => {
+                        let first = <f32>::deserialize_from_value(val, location.push_index(0))?;
+                        let mut embedding = iter
+                            .enumerate()
+                            .map(|(i, v)| {
+                                <f32>::deserialize_from_value(
+                                    v.into_value(),
+                                    location.push_index(i + 1),
+                                )
+                            })
+                            .collect::<Result<Vec<_>, _>>()?;
+                        embedding.insert(0, first);
+                        Ok(VectorOrArrayOfVectors { inner: Some(either::Either::Right(embedding)) })
+                    }
+                    Some(value) => Err(take_cf_content(E::error(
+                        None,
+                        deserr::ErrorKind::IncorrectValueKind {
+                            actual: value,
+                            accepted: &[deserr::ValueKind::Sequence, deserr::ValueKind::Float],
+                        },
+                        location.push_index(0),
+                    ))),
+                }
+            }
+            value => Err(take_cf_content(E::error(
+                None,
+                deserr::ErrorKind::IncorrectValueKind {
+                    actual: value,
+                    accepted: &[deserr::ValueKind::Sequence, deserr::ValueKind::Null],
+                },
+                location,
+            ))),
+        }
+    }
+}
+
 impl VectorOrArrayOfVectors {
     pub fn into_array_of_vectors(self) -> Option<Vec<Embedding>> {
         match self.inner? {
@@ -234,15 +353,19 @@ impl From<Vec<Embedding>> for VectorOrArrayOfVectors {
 mod test {
     use super::VectorOrArrayOfVectors;
 
+    fn embedding_from_str(s: &str) -> Result<VectorOrArrayOfVectors, deserr::errors::JsonError> {
+        let value: serde_json::Value = serde_json::from_str(s).unwrap();
+        deserr::deserialize(value)
+    }
+
     #[test]
     fn array_of_vectors() {
-        let null: VectorOrArrayOfVectors = serde_json::from_str("null").unwrap();
-        let empty: VectorOrArrayOfVectors = serde_json::from_str("[]").unwrap();
-        let one: VectorOrArrayOfVectors = serde_json::from_str("[0.1]").unwrap();
-        let two: VectorOrArrayOfVectors = serde_json::from_str("[0.1, 0.2]").unwrap();
-        let one_vec: VectorOrArrayOfVectors = serde_json::from_str("[[0.1, 0.2]]").unwrap();
-        let two_vecs: VectorOrArrayOfVectors =
-            serde_json::from_str("[[0.1, 0.2], [0.3, 0.4]]").unwrap();
+        let null = embedding_from_str("null").unwrap();
+        let empty = embedding_from_str("[]").unwrap();
+        let one = embedding_from_str("[0.1]").unwrap();
+        let two = embedding_from_str("[0.1, 0.2]").unwrap();
+        let one_vec = embedding_from_str("[[0.1, 0.2]]").unwrap();
+        let two_vecs = embedding_from_str("[[0.1, 0.2], [0.3, 0.4]]").unwrap();
 
         insta::assert_json_snapshot!(null.into_array_of_vectors(), @"null");
         insta::assert_json_snapshot!(empty.into_array_of_vectors(), @"[]");