Fix bug where AzureOpenAIEmbeddings inherits from OpenAIEmbeddings (#203

)

* Fix bug where AzureOpenAIEmbeddings inherits from OpenAIEmbeddings

* Cast embedding to list[float]

* Refactored embed_query method to be in base class

CHANGELOG.md

@@ -13,6 +13,8 @@
 - Removed support for neo4j.AsyncDriver in the KG creation pipeline, affecting Neo4jWriter and related components.
 - Updated examples and unit tests to reflect the removal of async driver support.
 
+### Fixed
+- Resolved issue with `AzureOpenAIEmbeddings` incorrectly inheriting from `OpenAIEmbeddings`, now inherits from `BaseOpenAIEmbeddings`.
 
 ## 1.1.0
 

examples/customize/embeddings/azure_openai_embeddings.py

@@ -4,11 +4,11 @@
 
 from neo4j_graphrag.embeddings import AzureOpenAIEmbeddings
 
-embeder = AzureOpenAIEmbeddings(
+embedder = AzureOpenAIEmbeddings(
     model="text-embedding-ada-002",
     azure_endpoint="https://my-endpoint.openai.azure.com/",
     api_key="<my key>",
     api_version="<update version>",
 )
-res = embeder.embed_query("my question")
+res = embedder.embed_query("my question")
 print(res[:10])

src/neo4j_graphrag/embeddings/openai.py

@@ -15,20 +15,22 @@
 
 from __future__ import annotations
 
-from typing import Any
+import abc
+from typing import TYPE_CHECKING, Any
+
 from neo4j_graphrag.embeddings.base import Embedder
 
+if TYPE_CHECKING:
+    import openai
 
-class OpenAIEmbeddings(Embedder):
-    """
-    OpenAI embeddings class.
-    This class uses the OpenAI python client to generate embeddings for text data.
 
-    Args:
-        model (str): The name of the OpenAI embedding model to use. Defaults to "text-embedding-ada-002".
-        kwargs: All other parameters will be passed to the openai.OpenAI init.
+class BaseOpenAIEmbeddings(Embedder, abc.ABC):
+    """
+    Abstract base class for OpenAI embeddings.
     """
 
+    client: openai.OpenAI
+
     def __init__(self, model: str = "text-embedding-ada-002", **kwargs: Any) -> None:
         try:
             import openai
@@ -39,23 +41,52 @@ def __init__(self, model: str = "text-embedding-ada-002", **kwargs: Any) -> None
             )
         self.openai = openai
         self.model = model
-        self.openai_client = self.openai.OpenAI(**kwargs)
+        self.client = self._initialize_client(**kwargs)
+
+    @abc.abstractmethod
+    def _initialize_client(self, **kwargs: Any) -> Any:
+        """
+        Initialize the OpenAI client.
+        Must be implemented by subclasses.
+        """
+        pass
 
     def embed_query(self, text: str, **kwargs: Any) -> list[float]:
         """
-        Generate embeddings for a given query using a OpenAI text embedding model.
+        Generate embeddings for a given query using an OpenAI text embedding model.
 
         Args:
             text (str): The text to generate an embedding for.
             **kwargs (Any): Additional arguments to pass to the OpenAI embedding generation function.
         """
-        response = self.openai_client.embeddings.create(
-            input=text, model=self.model, **kwargs
-        )
-        return response.data[0].embedding
+        response = self.client.embeddings.create(input=text, model=self.model, **kwargs)
+        embedding: list[float] = response.data[0].embedding
+        return embedding
 
 
-class AzureOpenAIEmbeddings(OpenAIEmbeddings):
-    def __init__(self, model: str = "text-embedding-ada-002", **kwargs: Any) -> None:
-        super().__init__(model, **kwargs)
-        self.openai_client = self.openai.AzureOpenAI(**kwargs)
+class OpenAIEmbeddings(BaseOpenAIEmbeddings):
+    """
+    OpenAI embeddings class.
+    This class uses the OpenAI python client to generate embeddings for text data.
+
+    Args:
+        model (str): The name of the OpenAI embedding model to use. Defaults to "text-embedding-ada-002".
+        kwargs: All other parameters will be passed to the openai.OpenAI init.
+    """
+
+    def _initialize_client(self, **kwargs: Any) -> Any:
+        return self.openai.OpenAI(**kwargs)
+
+
+class AzureOpenAIEmbeddings(BaseOpenAIEmbeddings):
+    """
+    Azure OpenAI embeddings class.
+    This class uses the Azure OpenAI python client to generate embeddings for text data.
+
+    Args:
+        model (str): The name of the Azure OpenAI embedding model to use. Defaults to "text-embedding-ada-002".
+        kwargs: All other parameters will be passed to the openai.AzureOpenAI init.
+    """
+
+    def _initialize_client(self, **kwargs: Any) -> Any:
+        return self.openai.AzureOpenAI(**kwargs)

src/neo4j_graphrag/llm/openai_llm.py

@@ -15,7 +15,7 @@
 from __future__ import annotations
 
 import abc
-from typing import Any, Optional, TYPE_CHECKING, Iterable
+from typing import TYPE_CHECKING, Any, Iterable, Optional
 
 from ..exceptions import LLMGenerationError
 from .base import LLMInterface

tests/unit/embeddings/test_openai_embedder.py

@@ -14,12 +14,12 @@
 #  limitations under the License.
 from unittest.mock import MagicMock, Mock, patch
 
+import openai
 import pytest
 from neo4j_graphrag.embeddings.openai import (
     AzureOpenAIEmbeddings,
     OpenAIEmbeddings,
 )
-import openai
 
 
 def get_mock_openai() -> MagicMock:
@@ -71,3 +71,24 @@ def test_azure_openai_embedder_happy_path(mock_import: Mock) -> None:
     res = embedder.embed_query("my text")
     assert isinstance(res, list)
     assert res == [1.0, 2.0]
+
+
+def test_azure_openai_embedder_does_not_call_openai_client() -> None:
+    from unittest.mock import patch
+
+    mock_openai = get_mock_openai()
+
+    with patch.dict("sys.modules", {"openai": mock_openai}):
+        AzureOpenAIEmbeddings(
+            model="text-embedding-ada-002",
+            azure_endpoint="https://test.openai.azure.com/",
+            api_key="my_key",
+            api_version="2023-05-15",
+        )
+
+        mock_openai.OpenAI.assert_not_called()
+        mock_openai.AzureOpenAI.assert_called_once_with(
+            azure_endpoint="https://test.openai.azure.com/",
+            api_key="my_key",
+            api_version="2023-05-15",
+        )

tests/unit/embeddings/test_sentence_transformers.py

@@ -1,12 +1,12 @@
-from unittest.mock import MagicMock, patch, Mock
+from unittest.mock import MagicMock, Mock, patch
 
 import numpy as np
 import pytest
+import torch
 from neo4j_graphrag.embeddings.base import Embedder
 from neo4j_graphrag.embeddings.sentence_transformers import (
     SentenceTransformerEmbeddings,
 )
-import torch
 
 
 def get_mock_sentence_transformers() -> MagicMock:

tests/unit/llm/test_anthropic_llm.py

@@ -13,13 +13,13 @@
 #  limitations under the License.
 from __future__ import annotations
 
-from unittest.mock import AsyncMock, MagicMock, patch, Mock
+import sys
+from typing import Generator
+from unittest.mock import AsyncMock, MagicMock, Mock, patch
 
+import anthropic
 import pytest
 from neo4j_graphrag.llm.anthropic_llm import AnthropicLLM
-import sys
-import anthropic
-from typing import Generator
 
 
 @pytest.fixture

tests/unit/llm/test_cohere_llm.py

@@ -12,15 +12,15 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
+import sys
+from typing import Generator
 from unittest.mock import AsyncMock, MagicMock, Mock, patch
 
 import cohere.core
 import pytest
 from neo4j_graphrag.exceptions import LLMGenerationError
 from neo4j_graphrag.llm import LLMResponse
 from neo4j_graphrag.llm.cohere_llm import CohereLLM
-import sys
-from typing import Generator
 
 
 @pytest.fixture

tests/unit/llm/test_openai_llm.py

@@ -12,12 +12,12 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
-from unittest.mock import MagicMock, patch, Mock
+from unittest.mock import MagicMock, Mock, patch
 
+import openai
 import pytest
 from neo4j_graphrag.llm import LLMResponse
 from neo4j_graphrag.llm.openai_llm import AzureOpenAILLM, OpenAILLM
-import openai
 
 
 def get_mock_openai() -> MagicMock: