Updated pr.

Author: lu-ohai

ads/llm/__init__.py

@@ -12,6 +12,9 @@
         ChatOCIModelDeploymentTGI,
         ChatOCIModelDeploymentVLLM,
     )
+    from ads.llm.langchain.plugins.embeddings.oci_data_science_model_deployment_endpoint import (
+        OCIDataScienceEmbedding,
+    )
     from ads.llm.langchain.plugins.llms.oci_data_science_model_deployment_endpoint import (
         OCIModelDeploymentTGI,
         OCIModelDeploymentVLLM,

ads/llm/langchain/plugins/embeddings/oci_data_science_model_deployment_endpoint.py

@@ -8,8 +8,7 @@
 import requests
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import create_base_retry_decorator
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, Field
 
 DEFAULT_HEADER = {
     "Content-Type": "application/json",
@@ -29,16 +28,16 @@ def _create_retry_decorator(llm) -> Callable[[Any], Any]:
     return decorator
 
 
-class OCIModelDeploymentEndpointEmbeddings(BaseModel, Embeddings):
+class OCIDataScienceEmbedding(BaseModel, Embeddings):
     """Embedding model deployed on OCI Data Science Model Deployment.
 
     Example:
 
         .. code-block:: python
 
-            from langchain_community.embeddings import OCIModelDeploymentEndpointEmbeddings
+            from ads.llm import OCIDataScienceEmbedding
 
-            embeddings = OCIModelDeploymentEndpointEmbeddings(
+            embeddings = OCIDataScienceEmbedding(
                 endpoint="https://modeldeployment.us-ashburn-1.oci.customer-oci.com/<md_ocid>/predict",
             )
     """  # noqa: E501
@@ -64,28 +63,6 @@ class OCIModelDeploymentEndpointEmbeddings(BaseModel, Embeddings):
     max_retries: int = 1
     """The maximum number of retries to make when generating."""
 
-    @root_validator()
-    def validate_environment(  # pylint: disable=no-self-argument
-        cls, values: Dict
-    ) -> Dict:
-        """Validate that python package exists in environment."""
-        try:
-            import ads
-
-        except ImportError as ex:
-            raise ImportError(
-                "Could not import ads python package. "
-                "Please install it with `pip install oracle_ads`."
-            ) from ex
-        if not values.get("auth"):
-            values["auth"] = ads.common.auth.default_signer()
-        values["endpoint"] = get_from_dict_or_env(
-            values,
-            "endpoint",
-            "OCI_LLM_ENDPOINT",
-        )
-        return values
-
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""

docs/source/user_guide/large_language_model/langchain_models.rst

@@ -135,11 +135,11 @@ You can also use embedding model that's hosted on a `OCI Data Science Model Depl
 
 .. code-block:: python3
 
-    from langchain_community.embeddings import OCIModelDeploymentEndpointEmbeddings
+    from ads.llm import OCIDataScienceEmbedding
 
     # Create an instance of OCI Model Deployment Endpoint
     # Replace the endpoint uri with your own
-    embeddings = OCIModelDeploymentEndpointEmbeddings(
+    embeddings = OCIDataScienceEmbedding(
         endpoint="https://modeldeployment.us-ashburn-1.oci.customer-oci.com/<MD_OCID>/predict",
     )
 

tests/unitary/with_extras/langchain/embeddings/test_oci_model_deployment_endpoint.py

@@ -7,12 +7,10 @@
 """Test OCI Data Science Model Deployment Endpoint."""
 
 from unittest.mock import MagicMock, patch
-from ads.llm.langchain.plugins.embeddings.oci_data_science_model_deployment_endpoint import (
-    OCIModelDeploymentEndpointEmbeddings,
-)
+from ads.llm import OCIDataScienceEmbedding
 
 
-@patch("ads.llm.OCIModelDeploymentEndpointEmbeddings._embed_with_retry")
+@patch("ads.llm.OCIDataScienceEmbedding._embed_with_retry")
 def test_embed_documents(mock_embed_with_retry) -> None:
     """Test valid call to oci model deployment endpoint."""
     expected_output = [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]
@@ -26,15 +24,15 @@ def test_embed_documents(mock_embed_with_retry) -> None:
     endpoint = "https://MD_OCID/predict"
     documents = ["Hello", "World"]
 
-    embeddings = OCIModelDeploymentEndpointEmbeddings(
+    embeddings = OCIDataScienceEmbedding(
         endpoint=endpoint,
     )
 
     output = embeddings.embed_documents(documents)
     assert output == expected_output
 
 
-@patch("ads.llm.OCIModelDeploymentEndpointEmbeddings._embed_with_retry")
+@patch("ads.llm.OCIDataScienceEmbedding._embed_with_retry")
 def test_embed_query(mock_embed_with_retry) -> None:
     """Test valid call to oci model deployment endpoint."""
     expected_output = [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]
@@ -48,7 +46,7 @@ def test_embed_query(mock_embed_with_retry) -> None:
     endpoint = "https://MD_OCID/predict"
     query = "Hello world"
 
-    embeddings = OCIModelDeploymentEndpointEmbeddings(
+    embeddings = OCIDataScienceEmbedding(
         endpoint=endpoint,
     )