chore: import upstream snapshot with attribution

2026-07-13 13:21:23 +08:00
commit b957a53def
5423 changed files with 863745 additions and 0 deletions
@@ -0,0 +1,129 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from importlib import util
+
+import pytest
+from azure.ai.inference.aio import EmbeddingsClient
+from azure.identity import AzureCliCredential
+from openai import AsyncAzureOpenAI
+
+from semantic_kernel.connectors.ai.azure_ai_inference import (
+    AzureAIInferenceEmbeddingPromptExecutionSettings,
+    AzureAIInferenceTextEmbedding,
+)
+from semantic_kernel.connectors.ai.bedrock import BedrockEmbeddingPromptExecutionSettings, BedrockTextEmbedding
+from semantic_kernel.connectors.ai.embedding_generator_base import EmbeddingGeneratorBase
+from semantic_kernel.connectors.ai.google.google_ai import (
+    GoogleAIEmbeddingPromptExecutionSettings,
+    GoogleAITextEmbedding,
+)
+from semantic_kernel.connectors.ai.hugging_face import HuggingFaceTextEmbedding
+from semantic_kernel.connectors.ai.mistral_ai import MistralAITextEmbedding
+from semantic_kernel.connectors.ai.ollama import OllamaEmbeddingPromptExecutionSettings, OllamaTextEmbedding
+from semantic_kernel.connectors.ai.open_ai import (
+    AzureOpenAISettings,
+    AzureTextEmbedding,
+    OpenAIEmbeddingPromptExecutionSettings,
+    OpenAITextEmbedding,
+)
+from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
+from semantic_kernel.utils.authentication.entra_id_authentication import get_entra_auth_token
+from tests.utils import is_service_setup_for_testing
+
+hugging_face_setup = util.find_spec("torch") is not None
+
+# Make sure all services are setup for before running the tests
+# The following exceptions apply:
+# 1. OpenAI and Azure OpenAI services are always setup for testing.
+azure_openai_setup = True
+# 2. The current Hugging Face service don't require any environment variables.
+# 3. Bedrock services don't use API keys and model providers are tested individually,
+#    so no environment variables are required.
+mistral_ai_setup: bool = is_service_setup_for_testing(
+    ["MISTRALAI_API_KEY", "MISTRALAI_EMBEDDING_MODEL_ID"], raise_if_not_set=False
+)  # We don't have a MistralAI deployment
+google_ai_setup: bool = is_service_setup_for_testing(["GOOGLE_AI_API_KEY", "GOOGLE_AI_EMBEDDING_MODEL_ID"])
+vertex_ai_setup: bool = is_service_setup_for_testing([
+    "GOOGLE_AI_CLOUD_PROJECT_ID",
+    "GOOGLE_AI_EMBEDDING_MODEL_ID",
+    "GOOGLE_AI_CLOUD_REGION",
+])
+ollama_setup: bool = is_service_setup_for_testing(["OLLAMA_EMBEDDING_MODEL_ID"])
+# When testing Bedrock, after logging into AWS CLI this has been set, so we can use it to check if the service is setup
+bedrock_setup: bool = is_service_setup_for_testing(["AWS_DEFAULT_REGION"], raise_if_not_set=False)
+
+
+class EmbeddingServiceTestBase:
+    @pytest.fixture(scope="class")
+    def services(self) -> dict[str, tuple[EmbeddingGeneratorBase | None, type[PromptExecutionSettings]]]:
+        azure_openai_setup = True
+        credential = AzureCliCredential()
+        azure_openai_settings = AzureOpenAISettings()
+        endpoint = str(azure_openai_settings.endpoint)
+        deployment_name = azure_openai_settings.embedding_deployment_name
+        ad_token = get_entra_auth_token(credential, azure_openai_settings.token_endpoint)
+        if not ad_token:
+            azure_openai_setup = False
+        api_version = azure_openai_settings.api_version
+        azure_custom_client = None
+        azure_ai_inference_client = None
+        if azure_openai_setup:
+            azure_custom_client = AzureTextEmbedding(
+                async_client=AsyncAzureOpenAI(
+                    azure_endpoint=endpoint,
+                    azure_deployment=deployment_name,
+                    azure_ad_token=ad_token,
+                    api_version=api_version,
+                    default_headers={"Test-User-X-ID": "test"},
+                ),
+                credential=credential,
+            )
+            azure_ai_inference_client = AzureAIInferenceTextEmbedding(
+                ai_model_id=deployment_name,
+                client=EmbeddingsClient(
+                    endpoint=f"{endpoint.strip('/')}/openai/deployments/{deployment_name}",
+                    credential=credential,
+                    credential_scopes=["https://cognitiveservices.azure.com/.default"],
+                ),
+            )
+
+        return {
+            "openai": (OpenAITextEmbedding(), OpenAIEmbeddingPromptExecutionSettings),
+            "azure": (
+                AzureTextEmbedding(credential=credential) if azure_openai_setup else None,
+                OpenAIEmbeddingPromptExecutionSettings,
+            ),
+            "azure_custom_client": (azure_custom_client, OpenAIEmbeddingPromptExecutionSettings),
+            "azure_ai_inference": (azure_ai_inference_client, AzureAIInferenceEmbeddingPromptExecutionSettings),
+            "mistral_ai": (
+                MistralAITextEmbedding() if mistral_ai_setup else None,
+                PromptExecutionSettings,
+            ),
+            "hugging_face": (
+                HuggingFaceTextEmbedding(ai_model_id="sentence-transformers/all-MiniLM-L6-v2")
+                if hugging_face_setup
+                else None,
+                PromptExecutionSettings,
+            ),
+            "ollama": (OllamaTextEmbedding() if ollama_setup else None, OllamaEmbeddingPromptExecutionSettings),
+            "google_ai": (
+                GoogleAITextEmbedding() if google_ai_setup else None,
+                GoogleAIEmbeddingPromptExecutionSettings,
+            ),
+            "vertex_ai": (
+                GoogleAITextEmbedding(use_vertexai=True) if vertex_ai_setup else None,
+                GoogleAIEmbeddingPromptExecutionSettings,
+            ),
+            "bedrock_amazon_titan-v1": (
+                BedrockTextEmbedding(model_id="amazon.titan-embed-text-v1") if bedrock_setup else None,
+                BedrockEmbeddingPromptExecutionSettings,
+            ),
+            "bedrock_amazon_titan-v2": (
+                BedrockTextEmbedding(model_id="amazon.titan-embed-text-v2:0") if bedrock_setup else None,
+                BedrockEmbeddingPromptExecutionSettings,
+            ),
+            "bedrock_cohere": (
+                BedrockTextEmbedding(model_id="cohere.embed-english-v3") if bedrock_setup else None,
+                BedrockEmbeddingPromptExecutionSettings,
+            ),
+        }