VoyageAI's new multimodal embedding model

test/collection/test_config.py

@@ -98,6 +98,24 @@ def test_basic_config():
             }
         },
     ),
+    (
+        Configure.Vectorizer.multi2vec_voyageai(
+            model="voyage-multimodal-3",
+            truncation=False,
+            output_encoding="base64",
+            vectorize_collection_name=False,
+            base_url="https://api.voyageai.com",
+        ),
+        {
+            "multi2vec-voyageai": {
+                "model": "voyage-multimodal-3",
+                "truncation": False,
+                "output_encoding": "base64",
+                "vectorizeClassName": False,
+                "baseURL": "https://api.voyageai.com/",
+            }
+        },
+    ),
     (
         Configure.Vectorizer.text2vec_gpt4all(),
         {
@@ -1293,6 +1311,20 @@ def test_vector_config_flat_pq() -> None:
             }
         },
     ),
+    (
+        [Configure.NamedVectors.multi2vec_voyageai(name="test", text_fields=["prop"])],
+        {
+            "test": {
+                "vectorizer": {
+                    "multi2vec-voyageai": {
+                        "vectorizeClassName": True,
+                        "textFields": ["prop"],
+                    }
+                },
+                "vectorIndexType": "hnsw",
+            }
+        },
+    ),
     (
         [
             Configure.NamedVectors.multi2vec_jinaai(

weaviate/collections/classes/config_named_vectors.py

@@ -21,6 +21,7 @@
     _Img2VecNeuralConfig,
     _Multi2VecBindConfig,
     _Multi2VecClipConfig,
+    _Multi2VecVoyageaiConfig,
     _Multi2VecGoogleConfig,
     _Ref2VecCentroidConfig,
     _Text2VecAWSConfig,
@@ -48,6 +49,7 @@
     OpenAIType,
     Vectorizers,
     VoyageModel,
+    VoyageMultimodalModel,
     _map_multi2vec_fields,
     _VectorizerCustomConfig,
     _Text2VecDatabricksConfig,
@@ -755,6 +757,59 @@ def multi2vec_bind(
             vector_index_config=vector_index_config,
         )
 
+    @staticmethod
+    def multi2vec_voyageai(
+        name: str,
+        *,
+        vector_index_config: Optional[_VectorIndexConfigCreate] = None,
+        vectorize_collection_name: bool = True,
+        base_url: Optional[AnyHttpUrl] = None,
+        model: Optional[Union[VoyageMultimodalModel, str]] = None,
+        truncation: Optional[bool] = None,
+        output_encoding: Optional[str] = None,
+        image_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+        text_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+    ) -> _NamedVectorConfigCreate:
+        """Create a named vector using the `multi2vec_voyageai` model.
+
+        See the [documentation](https://weaviate.io/developers/weaviate/model-providers/voyageai/embeddings-multimodal)
+        for detailed usage.
+
+        Arguments:
+            `name`
+                The name of the named vector.
+            `vector_index_config`
+                The configuration for Weaviate's vector index. Use wvc.config.Configure.VectorIndex to create a vector index configuration. None by default
+            `vectorize_collection_name`
+                Whether to vectorize the collection name. Defaults to `True`.
+            `model`
+                The model to use. Defaults to `None`, which uses the server-defined default.
+            `truncation`
+                The truncation strategy to use. Defaults to `None`, which uses the server-defined default.
+            `base_url`
+                The base URL to use where API requests should go. Defaults to `None`, which uses the server-defined default.
+            `image_fields`
+                The image fields to use in vectorization.
+            `text_fields`
+                The text fields to use in vectorization.
+
+        Raises:
+            `pydantic.ValidationError` if `model` is not a valid value from the `VoyageaiMultimodalModel` type.
+        """
+        return _NamedVectorConfigCreate(
+            name=name,
+            vectorizer=_Multi2VecVoyageaiConfig(
+                baseURL=base_url,
+                model=model,
+                truncation=truncation,
+                output_encoding=output_encoding,
+                vectorizeClassName=vectorize_collection_name,
+                imageFields=_map_multi2vec_fields(image_fields),
+                textFields=_map_multi2vec_fields(text_fields),
+            ),
+            vector_index_config=vector_index_config,
+        )
+
     @staticmethod
     def ref2vec_centroid(
         name: str,

weaviate/collections/classes/config_vectorizers.py

@@ -55,6 +55,7 @@
     "voyage-finance-2",
     "voyage-multilingual-2",
 ]
+VoyageMultimodalModel: TypeAlias = Literal["voyage-multimodal-3",]
 AWSModel: TypeAlias = Literal[
     "amazon.titan-embed-text-v1",
     "cohere.embed-english-v3",
@@ -106,6 +107,8 @@ class Vectorizers(str, Enum):
             Weaviate module backed by a palm model for images and text.
         `MULTI2VEC_BIND`
             Weaviate module backed by the ImageBind model for images, text, audio, depth, IMU, thermal, and video.
+        `MULTI2VEC_VOYAGEAI`
+            Weaviate module backed by a Voyage AI multimodal embedding models.
         `REF2VEC_CENTROID`
             Weaviate module backed by a centroid-based model that calculates an object's vectors from its referenced vectors.
     """
@@ -131,6 +134,7 @@ class Vectorizers(str, Enum):
     MULTI2VEC_JINAAI = "multi2vec-jinaai"
     MULTI2VEC_BIND = "multi2vec-bind"
     MULTI2VEC_PALM = "multi2vec-palm"  # change to google once 1.27 is the lowest supported version
+    MULTI2VEC_VOYAGEAI = "multi2vec-voyageai"
     REF2VEC_CENTROID = "ref2vec-centroid"
 
 
@@ -462,6 +466,22 @@ class _Multi2VecBindConfig(_Multi2VecBase):
     videoFields: Optional[List[Multi2VecField]]
 
 
+class _Multi2VecVoyageaiConfig(_Multi2VecBase):
+    vectorizer: Union[Vectorizers, _EnumLikeStr] = Field(
+        default=Vectorizers.MULTI2VEC_VOYAGEAI, frozen=True, exclude=True
+    )
+    baseURL: Optional[AnyHttpUrl]
+    model: Optional[str]
+    truncation: Optional[bool]
+    output_encoding: Optional[str]
+
+    def _to_dict(self) -> Dict[str, Any]:
+        ret_dict = super()._to_dict()
+        if self.baseURL is not None:
+            ret_dict["baseURL"] = self.baseURL.unicode_string()
+        return ret_dict
+
+
 class _Ref2VecCentroidConfig(_VectorizerConfigCreate):
     vectorizer: Union[Vectorizers, _EnumLikeStr] = Field(
         default=Vectorizers.REF2VEC_CENTROID, frozen=True, exclude=True
@@ -796,6 +816,51 @@ def multi2vec_cohere(
             textFields=_map_multi2vec_fields(text_fields),
         )
 
+    @staticmethod
+    def multi2vec_voyageai(
+        *,
+        model: Optional[Union[CohereMultimodalModel, str]] = None,
+        truncation: Optional[bool] = None,
+        output_encoding: Optional[str],
+        vectorize_collection_name: bool = True,
+        base_url: Optional[AnyHttpUrl] = None,
+        image_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+        text_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+    ) -> _VectorizerConfigCreate:
+        """Create a `_Multi2VecCohereConfig` object for use when vectorizing using the `multi2vec-cohere` model.
+
+        See the [documentation](https://weaviate.io/developers/weaviate/model-providers/cohere/embeddings-multimodal)
+        for detailed usage.
+
+        Arguments:
+            `model`
+                The model to use. Defaults to `None`, which uses the server-defined default.
+            `truncate`
+                The truncation strategy to use. Defaults to `None`, which uses the server-defined default.
+            `output_encoding`
+                Format in which the embeddings are encoded. Defaults to `None`, so the embeddings are represented as a list of floating-point numbers.
+            `vectorize_collection_name`
+                Whether to vectorize the collection name. Defaults to `True`.
+            `base_url`
+                The base URL to use where API requests should go. Defaults to `None`, which uses the server-defined default.
+            `image_fields`
+                The image fields to use in vectorization.
+            `text_fields`
+                The text fields to use in vectorization.
+
+        Raises:
+            `pydantic.ValidationError` if `model` is not a valid value from the `CohereMultimodalModel` type or if `truncate` is not a valid value from the `CohereTruncation` type.
+        """
+        return _Multi2VecVoyageaiConfig(
+            baseURL=base_url,
+            model=model,
+            truncation=truncation,
+            output_encoding=output_encoding,
+            vectorizeClassName=vectorize_collection_name,
+            imageFields=_map_multi2vec_fields(image_fields),
+            textFields=_map_multi2vec_fields(text_fields),
+        )
+
     @staticmethod
     def text2vec_databricks(
         *,