fix: azure openai key and test error (camel-ai#2150)

Author: Wendong-Fan

.github/workflows/pytest_package.yml

@@ -35,10 +35,10 @@ jobs:
         ZHIPUAI_API_BASE_URL: "${{ secrets.ZHIPUAI_API_BASE_URL }}"
         ZHIPUAI_API_KEY: "${{ secrets.ZHIPUAI_API_KEY }}"
         HF_TOKEN: "${{ secrets.HF_TOKEN }}"
-        AZURE_OPENAI_API_KEY: "to-be-filled"
-        AZURE_API_VERSION: "to-be-filled"
-        AZURE_DEPLOYMENT_NAME: "to-be-filled"
-        AZURE_OPENAI_BASE_URL: "https://camel.openai.azure.com/"
+        AZURE_OPENAI_API_KEY: "${{ secrets.AZURE_OPENAI_API_KEY }}"
+        AZURE_API_VERSION: "${{ secrets.AZURE_API_VERSION }}"
+        AZURE_DEPLOYMENT_NAME: "${{ secrets.AZURE_DEPLOYMENT_NAME }}"
+        AZURE_OPENAI_BASE_URL: "${{ secrets.AZURE_OPENAI_BASE_URL }}"
         MISTRAL_API_KEY: "${{ secrets.MISTRAL_API_KEY }}"
         REKA_API_KEY: "${{ secrets.REKA_API_KEY }}"
         NEO4J_URI: "${{ secrets.NEO4J_URI }}"
@@ -95,10 +95,10 @@ jobs:
         ZHIPUAI_API_BASE_URL: "${{ secrets.ZHIPUAI_API_BASE_URL }}"
         ZHIPUAI_API_KEY: "${{ secrets.ZHIPUAI_API_KEY }}"
         HF_TOKEN: "${{ secrets.HF_TOKEN }}"
-        AZURE_OPENAI_API_KEY: "to-be-filled"
-        AZURE_API_VERSION: "to-be-filled"
-        AZURE_DEPLOYMENT_NAME: "to-be-filled"
-        AZURE_OPENAI_BASE_URL: "https://camel.openai.azure.com/"
+        AZURE_OPENAI_API_KEY: "${{ secrets.AZURE_OPENAI_API_KEY }}"
+        AZURE_API_VERSION: "${{ secrets.AZURE_API_VERSION }}"
+        AZURE_DEPLOYMENT_NAME: "${{ secrets.AZURE_DEPLOYMENT_NAME }}"
+        AZURE_OPENAI_BASE_URL: "${{ secrets.AZURE_OPENAI_BASE_URL }}"
         MISTRAL_API_KEY: "${{ secrets.MISTRAL_API_KEY }}"
         REKA_API_KEY: "${{ secrets.REKA_API_KEY }}"
         NEO4J_URI: "${{ secrets.NEO4J_URI }}"

test/embeddings/test_azure_embedding.py

@@ -13,16 +13,73 @@
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 
 
+from typing import List
+from unittest.mock import MagicMock, patch
+
+import pytest
+
 from camel.embeddings import AzureEmbedding
+from camel.types import EmbeddingModelType
+
+
+class MockEmbeddingData:
+    def __init__(self, embedding: List[float]):
+        self.embedding = embedding
+
+
+class MockResponse:
+    def __init__(self, data: List[MockEmbeddingData]):
+        self.data = data
+
 
+@pytest.fixture
+def mock_env_vars(monkeypatch):
+    r"""Set up environment variables to prevent API calls during testing."""
+    monkeypatch.setenv("AZURE_OPENAI_API_KEY", "test_api_key")
+    monkeypatch.setenv(
+        "AZURE_OPENAI_BASE_URL", "https://test.openai.azure.com"
+    )
+    monkeypatch.setenv("AZURE_API_VERSION", "2023-05-15")
 
-def test_azure_embedding():
+
+@patch('camel.embeddings.azure_embedding.AzureOpenAI')
+def test_azure_embedding(mock_azure_openai, mock_env_vars):
+    # Create mock client and mock embeddings object
+    mock_client = MagicMock()
+    mock_embeddings = MagicMock()
+    mock_client.embeddings = mock_embeddings
+    mock_azure_openai.return_value = mock_client
+
+    # Default model test with mocked response (1536 dimensions)
+    default_dim = EmbeddingModelType.TEXT_EMBEDDING_3_SMALL.output_dim
+    mock_embedding = [0.1] * default_dim
+    mock_response = MockResponse([MockEmbeddingData(mock_embedding)])
+    mock_embeddings.create.return_value = mock_response
+
+    # Test with default dimensions
     embedding_model = AzureEmbedding()
     text = "test 1."
     vector = embedding_model.embed(text)
+
+    # Verify mock was called correctly
+    mock_embeddings.create.assert_called_once()
     assert len(vector) == embedding_model.get_output_dim()
 
-    embedding_model = AzureEmbedding(dimensions=256)
+    # Reset mock for second test
+    mock_embeddings.create.reset_mock()
+
+    # Test with custom dimensions
+    custom_dim = 256
+    mock_embedding_custom = [0.1] * custom_dim
+    mock_response_custom = MockResponse(
+        [MockEmbeddingData(mock_embedding_custom)]
+    )
+    mock_embeddings.create.return_value = mock_response_custom
+
+    embedding_model = AzureEmbedding(dimensions=custom_dim)
     text = "test 2"
     vector = embedding_model.embed(text)
-    assert len(vector) == embedding_model.get_output_dim() == 256
+
+    # Verify dimensions were passed correctly
+    mock_embeddings.create.assert_called_once()
+    assert len(vector) == embedding_model.get_output_dim() == custom_dim