Use mock OpenAI embedding method in test cases instead of calling API

pyproject.toml

@@ -28,6 +28,7 @@ pydantic = "^2.6.3"
 eval-type-backport = "^0.1.3"
 smart-open = "^7.0.1"
 openai = "^1.16.2"
+pytest-mock = "^3.14.0"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.11.0"

tests/embedders/test_openai.py

@@ -1,13 +1,45 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
 import numpy as np
+import pytest
+from pytest_mock import MockerFixture
 
-from jmteb.embedders.openai_embedder import OpenAIEmbedder
+from jmteb.embedders import OpenAIEmbedder, TextEmbedder
 
 OUTPUT_DIM = 1536
 
 
-class TestSentenceBertEmbedder:
-    def setup_class(cls):
-        cls.model = OpenAIEmbedder(model="text-embedding-3-small")
+@pytest.fixture(scope="function")
+def mock_openai_embedder(mocker: MockerFixture):
+    mocker.patch("jmteb.embedders.openai_embedder.OpenAI")
+    return OpenAIEmbedder(model="text-embedding-3-small")
+
+
+@dataclass
+class MockData:
+    data: list
+
+
+@dataclass
+class MockEmbedding:
+    embedding: list
+
+
+class MockEmbedder:
+    def create(input: str | list[str], model: str, dimensions: int):
+        if isinstance(input, str):
+            input = [input]
+        return MockData([MockEmbedding(embedding=[0.1] * dimensions)] * len(input))
+
+
+@pytest.mark.usefixtures("mock_openai_embedder")
+class TestOpenAIEmbedder:
+    @pytest.fixture(autouse=True)
+    def setup_class(cls, mocker: MockerFixture, mock_openai_embedder: TextEmbedder):
+        cls.model = mock_openai_embedder
+        cls.mock_create = mocker.patch.object(cls.model.client, "embeddings", new=MockEmbedder)
 
     def test_encode(self):
         embeddings = self.model.encode("任意のテキスト")