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 +1,77 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+
+from dataclasses import field
+from typing import Annotated, Any
+from uuid import uuid4
+
+from pydantic import BaseModel
+from pytest import fixture
+
+from semantic_kernel.data.vector import VectorStoreField, vectorstoremodel
+
+
+@fixture
+def data_record() -> dict[str, Any]:
+    return {
+        "id": "e6103c03-487f-4d7d-9c23-4723651c17f4",
+        "description": "This is a test record",
+        "product_type": "test",
+        "vector": [0.1, 0.2, 0.3, 0.4, 0.5],
+    }
+
+
+@fixture
+def record_type() -> type:
+    @vectorstoremodel
+    class TestDataModelType(BaseModel):
+        vector: Annotated[
+            list[float] | None,
+            VectorStoreField(
+                "vector",
+                index_kind="flat",
+                dimensions=5,
+                distance_function="cosine_similarity",
+                type="float",
+            ),
+        ] = None
+        id: Annotated[str, VectorStoreField("key")] = field(default_factory=lambda: str(uuid4()))
+        product_type: Annotated[str, VectorStoreField("data")] = "N/A"
+        description: Annotated[
+            str, VectorStoreField("data", has_embedding=True, embedding_property_name="vector", type="str")
+        ] = "N/A"
+
+    return TestDataModelType
+
+
+@fixture
+def data_record_with_key_as_key_field() -> dict[str, Any]:
+    return {
+        "key": "e6103c03-487f-4d7d-9c23-4723651c17f4",
+        "description": "This is a test record",
+        "product_type": "test",
+        "vector": [0.1, 0.2, 0.3, 0.4, 0.5],
+    }
+
+
+@fixture
+def record_type_with_key_as_key_field() -> type:
+    @vectorstoremodel
+    class TestDataModelType(BaseModel):
+        vector: Annotated[
+            list[float] | None,
+            VectorStoreField(
+                "vector",
+                index_kind="flat",
+                dimensions=5,
+                distance_function="cosine_similarity",
+                type="float",
+            ),
+        ] = None
+        key: Annotated[str, VectorStoreField("key")] = field(default_factory=lambda: str(uuid4()))
+        product_type: Annotated[str, VectorStoreField("data")] = "N/A"
+        description: Annotated[
+            str, VectorStoreField("data", has_embedding=True, embedding_property_name="vector", type="str")
+        ] = "N/A"
+
+    return TestDataModelType