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Merge pull request #1145 from weaviate/better_type_checking
Add validation for types that are not installed
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,177 @@ | ||
| import uuid | ||
| from typing import Any | ||
|
|
||
| import numpy as np | ||
| import pandas as pd | ||
| import polars as pl | ||
| import pytest | ||
|
|
||
| from integration.conftest import CollectionFactory | ||
| from weaviate.collections.classes.config import ( | ||
| Configure, | ||
| DataType, | ||
| Property, | ||
| ) | ||
| from weaviate.collections.classes.grpc import ( | ||
| GroupBy, | ||
| MetadataQuery, | ||
| ) | ||
|
|
||
| UUID1 = uuid.UUID("806827e0-2b31-43ca-9269-24fa95a221f9") | ||
| UUID2 = uuid.UUID("8ad0d33c-8db1-4437-87f3-72161ca2a51a") | ||
| UUID3 = uuid.UUID("83d99755-9deb-4b16-8431-d1dff4ab0a75") | ||
|
|
||
|
|
||
| def test_near_vector(collection_factory: CollectionFactory) -> None: | ||
| collection = collection_factory( | ||
| properties=[Property(name="Name", data_type=DataType.TEXT)], | ||
| vectorizer_config=Configure.Vectorizer.text2vec_contextionary( | ||
| vectorize_collection_name=False | ||
| ), | ||
| ) | ||
| uuid_banana = collection.data.insert({"Name": "Banana"}) | ||
| collection.data.insert({"Name": "Fruit"}) | ||
| collection.data.insert({"Name": "car"}) | ||
| collection.data.insert({"Name": "Mountain"}) | ||
|
|
||
| banana = collection.query.fetch_object_by_id(uuid_banana, include_vector=True) | ||
|
|
||
| full_objects = collection.query.near_vector( | ||
| banana.vector["default"], return_metadata=MetadataQuery(distance=True, certainty=True) | ||
| ).objects | ||
| assert len(full_objects) == 4 | ||
|
|
||
| objects_distance = collection.query.near_vector( | ||
| banana.vector["default"], distance=full_objects[2].metadata.distance | ||
| ).objects | ||
| assert len(objects_distance) == 3 | ||
|
|
||
| objects_distance = collection.query.near_vector( | ||
| banana.vector["default"], certainty=full_objects[2].metadata.certainty | ||
| ).objects | ||
| assert len(objects_distance) == 3 | ||
|
|
||
|
|
||
| def test_near_vector_limit(collection_factory: CollectionFactory) -> None: | ||
| collection = collection_factory( | ||
| properties=[Property(name="Name", data_type=DataType.TEXT)], | ||
| vectorizer_config=Configure.Vectorizer.text2vec_contextionary( | ||
| vectorize_collection_name=False | ||
| ), | ||
| ) | ||
| uuid_banana = collection.data.insert({"Name": "Banana"}) | ||
| collection.data.insert({"Name": "Fruit"}) | ||
| collection.data.insert({"Name": "car"}) | ||
| collection.data.insert({"Name": "Mountain"}) | ||
|
|
||
| banana = collection.query.fetch_object_by_id(uuid_banana, include_vector=True) | ||
|
|
||
| objs = collection.query.near_vector(banana.vector["default"], limit=2).objects | ||
| assert len(objs) == 2 | ||
|
|
||
|
|
||
| def test_near_vector_offset(collection_factory: CollectionFactory) -> None: | ||
| collection = collection_factory( | ||
| properties=[Property(name="Name", data_type=DataType.TEXT)], | ||
| vectorizer_config=Configure.Vectorizer.text2vec_contextionary( | ||
| vectorize_collection_name=False | ||
| ), | ||
| ) | ||
| uuid_banana = collection.data.insert({"Name": "Banana"}) | ||
| uuid_fruit = collection.data.insert({"Name": "Fruit"}) | ||
| collection.data.insert({"Name": "car"}) | ||
| collection.data.insert({"Name": "Mountain"}) | ||
|
|
||
| banana = collection.query.fetch_object_by_id(uuid_banana, include_vector=True) | ||
|
|
||
| objs = collection.query.near_vector(banana.vector["default"], offset=1).objects | ||
| assert len(objs) == 3 | ||
| assert objs[0].uuid == uuid_fruit | ||
|
|
||
|
|
||
| def test_near_vector_group_by_argument(collection_factory: CollectionFactory) -> None: | ||
| collection = collection_factory( | ||
| properties=[ | ||
| Property(name="Name", data_type=DataType.TEXT), | ||
| Property(name="Count", data_type=DataType.INT), | ||
| ], | ||
| vectorizer_config=Configure.Vectorizer.text2vec_contextionary( | ||
| vectorize_collection_name=False | ||
| ), | ||
| ) | ||
| uuid_banana1 = collection.data.insert({"Name": "Banana", "Count": 51}) | ||
| collection.data.insert({"Name": "Banana", "Count": 72}) | ||
| collection.data.insert({"Name": "car", "Count": 12}) | ||
| collection.data.insert({"Name": "Mountain", "Count": 1}) | ||
|
|
||
| banana1 = collection.query.fetch_object_by_id(uuid_banana1, include_vector=True) | ||
|
|
||
| ret = collection.query.near_vector( | ||
| banana1.vector["default"], | ||
| group_by=GroupBy( | ||
| prop="name", | ||
| number_of_groups=4, | ||
| objects_per_group=10, | ||
| ), | ||
| return_metadata=MetadataQuery(distance=True, certainty=True), | ||
| ) | ||
|
|
||
| assert len(ret.objects) == 4 | ||
| assert ret.objects[0].belongs_to_group == "Banana" | ||
| assert ret.objects[1].belongs_to_group == "Banana" | ||
| assert ret.objects[2].belongs_to_group == "car" | ||
| assert ret.objects[3].belongs_to_group == "Mountain" | ||
|
|
||
|
|
||
| @pytest.mark.parametrize( | ||
| "near_vector", [[1, 0], [1.0, 0.0], np.array([1, 0]), pl.Series([1, 0]), pd.Series([1, 0])] | ||
| ) | ||
| def test_near_vector_with_other_input( | ||
| collection_factory: CollectionFactory, near_vector: Any | ||
| ) -> None: | ||
| collection = collection_factory(vectorizer_config=Configure.Vectorizer.none()) | ||
|
|
||
| uuid1 = collection.data.insert({}, vector=[1, 0]) | ||
| collection.data.insert({}, vector=[0, 1]) | ||
|
|
||
| ret = collection.query.near_vector( | ||
| near_vector, | ||
| distance=0.1, | ||
| ) | ||
| assert len(ret.objects) == 1 | ||
| assert ret.objects[0].uuid == uuid1 | ||
|
|
||
|
|
||
| @pytest.mark.parametrize( | ||
| "near_vector", | ||
| [ | ||
| {"first": [1, 0], "second": [1, 0, 0]}, | ||
| {"first": np.array([1, 0]), "second": [1, 0, 0]}, | ||
| {"first": pl.Series([1, 0]), "second": [1, 0, 0]}, | ||
| {"first": pd.Series([1, 0]), "second": [1, 0, 0]}, | ||
| [np.array([1, 0]), [1, 0, 0]], | ||
| [pl.Series([1, 0]), [1, 0, 0]], | ||
| [pd.Series([1, 0]), [1, 0, 0]], | ||
| {"first": [1.0, 0.0], "second": [1.0, 0.0, 0.0]}, | ||
| ], | ||
| ) | ||
| def test_near_vector_with_named_vector_other_input( | ||
| collection_factory: CollectionFactory, near_vector: Any | ||
| ) -> None: | ||
| dummy = collection_factory("dummy") | ||
| if dummy._connection._weaviate_version.is_lower_than(1, 26, 0): | ||
| pytest.skip("Named vectors are supported in versions higher than 1.26.0") | ||
|
|
||
| collection = collection_factory( | ||
| vectorizer_config=[ | ||
| Configure.NamedVectors.none("first"), | ||
| Configure.NamedVectors.none("second"), | ||
| ] | ||
| ) | ||
|
|
||
| uuid1 = collection.data.insert({}, vector={"first": [1, 0], "second": [1, 0, 0]}) | ||
| collection.data.insert({}, vector={"first": [0, 1], "second": [0, 0, 1]}) | ||
|
|
||
| ret = collection.query.near_vector(near_vector, distance=0.1, target_vector=["first", "second"]) | ||
| assert len(ret.objects) == 1 | ||
| assert ret.objects[0].uuid == uuid1 |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,38 @@ | ||
| from typing import Any, List | ||
|
|
||
| import numpy as np | ||
| import pandas as pd | ||
| import polars as pl | ||
| import pytest | ||
|
|
||
| from weaviate.exceptions import WeaviateInvalidInputError | ||
| from weaviate.validator import _validate_input, _ValidateArgument, _ExtraTypes | ||
|
|
||
|
|
||
| @pytest.mark.parametrize( | ||
| "inputs,expected,error", | ||
| [ | ||
| (1, [int], False), | ||
| (1.0, [int], True), | ||
| ([1, 1], [List], False), | ||
| (np.array([1, 2, 3]), [_ExtraTypes.NUMPY], False), | ||
| (np.array([1, 2, 3]), [_ExtraTypes.NUMPY, List], False), | ||
| (np.array([1, 2, 3]), [List], True), | ||
| ([1, 1], [List, _ExtraTypes.NUMPY], False), | ||
| (pd.array([1, 1]), [_ExtraTypes.PANDAS, List], False), | ||
| (pd.Series([1, 1]), [_ExtraTypes.PANDAS, List], False), | ||
| (pl.Series([1, 1]), [_ExtraTypes.POLARS, List], False), | ||
| ( | ||
| pl.Series([1, 1]), | ||
| [_ExtraTypes.POLARS, _ExtraTypes.PANDAS, _ExtraTypes.NUMPY, List], | ||
| False, | ||
| ), | ||
| (pl.Series([1, 1]), [_ExtraTypes.PANDAS, _ExtraTypes.NUMPY, List], True), | ||
| ], | ||
| ) | ||
| def test_validator(inputs: Any, expected: List[Any], error: bool) -> None: | ||
| if error: | ||
| with pytest.raises(WeaviateInvalidInputError): | ||
| _validate_input(_ValidateArgument(expected=expected, name="test", value=inputs)) | ||
| else: | ||
| _validate_input(_ValidateArgument(expected=expected, name="test", value=inputs)) |
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