fix: Clean up unused EmbeddingModelConfig.

PiperOrigin-RevId: 731061492

Author: vertex-sdk-bot

vertexai/rag/__init__.py

@@ -39,7 +39,6 @@
 )
 from vertexai.rag.utils.resources import (
     ChunkingConfig,
-    EmbeddingModelConfig,
     Filter,
     JiraQuery,
     JiraSource,
@@ -63,7 +62,6 @@
 
 __all__ = (
     "ChunkingConfig",
-    "EmbeddingModelConfig",
     "Filter",
     "JiraQuery",
     "JiraSource",

vertexai/rag/utils/resources.py

@@ -78,38 +78,6 @@ class RagEmbeddingModelConfig:
     vertex_prediction_endpoint: Optional[VertexPredictionEndpoint] = None
 
 
-@dataclasses.dataclass
-class EmbeddingModelConfig:
-    """EmbeddingModelConfig.
-
-    The representation of the embedding model config. Users input a 1P embedding
-    model as a Publisher model resource, or a 1P fine tuned embedding model
-    as an Endpoint resource.
-
-    Attributes:
-        publisher_model: 1P publisher model resource name. Format:
-            ``publishers/google/models/{model}`` or
-            ``projects/{project}/locations/{location}/publishers/google/models/{model}``
-        endpoint: 1P fine tuned embedding model resource name. Format:
-            ``endpoints/{endpoint}`` or
-            ``projects/{project}/locations/{location}/endpoints/{endpoint}``.
-        model:
-            Output only. The resource name of the model that is deployed
-            on the endpoint. Present only when the endpoint is not a
-            publisher model. Pattern:
-            ``projects/{project}/locations/{location}/models/{model}``
-        model_version_id:
-            Output only. Version ID of the model that is
-            deployed on the endpoint. Present only when the
-            endpoint is not a publisher model.
-    """
-
-    publisher_model: Optional[str] = None
-    endpoint: Optional[str] = None
-    model: Optional[str] = None
-    model_version_id: Optional[str] = None
-
-
 @dataclasses.dataclass
 class Weaviate:
     """Weaviate.