feat(config): add multi2vec-twelvelabs vectorizer support (#2113)

test/collection/test_config.py

@@ -2261,6 +2261,28 @@ def test_config_with_named_vectors(
             }
         },
     ),
+    (
+        [
+            Configure.Vectors.multi2vec_twelvelabs(
+                name="test",
+                image_fields=["image"],
+                text_fields=["prop"],
+                model="marengo3.0",
+            )
+        ],
+        {
+            "test": {
+                "vectorizer": {
+                    "multi2vec-twelvelabs": {
+                        "imageFields": ["image"],
+                        "textFields": ["prop"],
+                        "model": "marengo3.0",
+                    }
+                },
+                "vectorIndexType": "hnsw",
+            }
+        },
+    ),
     (
         [Configure.Vectors.multi2vec_jinaai(name="test", dimensions=256, text_fields=["prop"])],
         {

weaviate/collections/classes/config_vectorizers.py

@@ -110,6 +110,7 @@ class Vectorizers(str, Enum):
         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.
         MULTI2VEC_NVIDIA: Weaviate module backed by NVIDIA multimodal embedding models.
+        MULTI2VEC_TWELVELABS: Weaviate module backed by TwelveLabs multimodal embedding models.
         REF2VEC_CENTROID: Weaviate module backed by a centroid-based model that calculates an object's vectors from its referenced vectors.
     """
 
@@ -144,6 +145,7 @@ class Vectorizers(str, Enum):
     MULTI2VEC_PALM = "multi2vec-palm"  # change to google once 1.27 is the lowest supported version
     MULTI2VEC_VOYAGEAI = "multi2vec-voyageai"
     MULTI2VEC_NVIDIA = "multi2vec-nvidia"
+    MULTI2VEC_TWELVELABS = "multi2vec-twelvelabs"
     REF2VEC_CENTROID = "ref2vec-centroid"
 
 
@@ -619,6 +621,20 @@ def _to_dict(self) -> Dict[str, Any]:
         return ret_dict
 
 
+class _Multi2VecTwelvelabsConfig(_Multi2VecBase):
+    vectorizer: Union[Vectorizers, _EnumLikeStr] = Field(
+        default=Vectorizers.MULTI2VEC_TWELVELABS, frozen=True, exclude=True
+    )
+    baseURL: Optional[AnyHttpUrl]
+    model: 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

weaviate/collections/classes/config_vectors.py

@@ -51,6 +51,7 @@
     _Multi2VecGoogleConfig,
     _Multi2VecJinaConfig,
     _Multi2VecNvidiaConfig,
+    _Multi2VecTwelvelabsConfig,
     _Multi2VecVoyageaiConfig,
     _Ref2VecCentroidConfig,
     _Text2ColbertJinaAIConfig,
@@ -1311,6 +1312,42 @@ def multi2vec_nvidia(
             vector_index_config=_IndexWrappers.single(vector_index_config, quantizer),
         )
 
+    @staticmethod
+    def multi2vec_twelvelabs(
+        *,
+        name: Optional[str] = None,
+        quantizer: Optional[_QuantizerConfigCreate] = None,
+        base_url: Optional[AnyHttpUrl] = None,
+        image_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+        model: Optional[str] = None,
+        text_fields: Optional[Union[List[str], List[Multi2VecField]]] = None,
+        vector_index_config: Optional[_VectorIndexConfigCreate] = None,
+    ) -> _VectorConfigCreate:
+        """Create a vector using the `multi2vec-twelvelabs` module.
+
+        See the [documentation](https://weaviate.io/developers/weaviate/model-providers/twelvelabs/embeddings-multimodal)
+        for detailed usage.
+
+        Args:
+            name: The name of the vector.
+            quantizer: The quantizer to use for the vector index. If not provided, no quantization will be applied.
+            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.
+            model: The model to use. Defaults to `None`, which uses the server-defined default.
+            text_fields: The text fields to use in vectorization.
+            vector_index_config: The configuration for Weaviate's vector index. Use `wvc.config.Configure.VectorIndex` to create a vector index configuration. None by default
+        """
+        return _VectorConfigCreate(
+            name=name,
+            vectorizer=_Multi2VecTwelvelabsConfig(
+                baseURL=base_url,
+                model=model,
+                imageFields=_map_multi2vec_fields(image_fields),
+                textFields=_map_multi2vec_fields(text_fields),
+            ),
+            vector_index_config=_IndexWrappers.single(vector_index_config, quantizer),
+        )
+
     @staticmethod
     def ref2vec_centroid(
         *,