feat(types): replace List[str] with SequenceNotStr in params

Author: stainless-app[bot]

src/openlayer/_utils/_transform.py

@@ -16,6 +16,7 @@
     lru_cache,
     is_mapping,
     is_iterable,
+    is_sequence,
 )
 from .._files import is_base64_file_input
 from ._typing import (
@@ -24,6 +25,7 @@
     extract_type_arg,
     is_iterable_type,
     is_required_type,
+    is_sequence_type,
     is_annotated_type,
     strip_annotated_type,
 )
@@ -184,6 +186,8 @@ def _transform_recursive(
         (is_list_type(stripped_type) and is_list(data))
         # Iterable[T]
         or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str))
+        # Sequence[T]
+        or (is_sequence_type(stripped_type) and is_sequence(data) and not isinstance(data, str))
     ):
         # dicts are technically iterable, but it is an iterable on the keys of the dict and is not usually
         # intended as an iterable, so we don't transform it.
@@ -346,6 +350,8 @@ async def _async_transform_recursive(
         (is_list_type(stripped_type) and is_list(data))
         # Iterable[T]
         or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str))
+        # Sequence[T]
+        or (is_sequence_type(stripped_type) and is_sequence(data) and not isinstance(data, str))
     ):
         # dicts are technically iterable, but it is an iterable on the keys of the dict and is not usually
         # intended as an iterable, so we don't transform it.

src/openlayer/types/inference_pipelines/data_stream_params.py

@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
-from typing import Dict, List, Union, Iterable, Optional
+from typing import Dict, Union, Iterable, Optional
 from typing_extensions import Required, Annotated, TypeAlias, TypedDict
 
+from ..._types import SequenceNotStr
 from ..._utils import PropertyInfo
 
 __all__ = [
@@ -60,7 +61,7 @@ class ConfigLlmData(TypedDict, total=False):
     provided, a unique id is generated by Openlayer.
     """
 
-    input_variable_names: Annotated[List[str], PropertyInfo(alias="inputVariableNames")]
+    input_variable_names: Annotated[SequenceNotStr[str], PropertyInfo(alias="inputVariableNames")]
     """Array of input variable names. Each input variable should be a dataset column."""
 
     latency_column_name: Annotated[str, PropertyInfo(alias="latencyColumnName")]
@@ -90,19 +91,19 @@ class ConfigLlmData(TypedDict, total=False):
 
 
 class ConfigTabularClassificationData(TypedDict, total=False):
-    class_names: Required[Annotated[List[str], PropertyInfo(alias="classNames")]]
+    class_names: Required[Annotated[SequenceNotStr[str], PropertyInfo(alias="classNames")]]
     """List of class names indexed by label integer in the dataset.
 
     E.g. ["Retained", "Exited"] when 0, 1 are in your label column.
     """
 
-    categorical_feature_names: Annotated[List[str], PropertyInfo(alias="categoricalFeatureNames")]
+    categorical_feature_names: Annotated[SequenceNotStr[str], PropertyInfo(alias="categoricalFeatureNames")]
     """Array with the names of all categorical features in the dataset.
 
     E.g. ["Age", "Geography"].
     """
 
-    feature_names: Annotated[List[str], PropertyInfo(alias="featureNames")]
+    feature_names: Annotated[SequenceNotStr[str], PropertyInfo(alias="featureNames")]
     """Array with all input feature names."""
 
     inference_id_column_name: Annotated[str, PropertyInfo(alias="inferenceIdColumnName")]
@@ -143,13 +144,13 @@ class ConfigTabularClassificationData(TypedDict, total=False):
 
 
 class ConfigTabularRegressionData(TypedDict, total=False):
-    categorical_feature_names: Annotated[List[str], PropertyInfo(alias="categoricalFeatureNames")]
+    categorical_feature_names: Annotated[SequenceNotStr[str], PropertyInfo(alias="categoricalFeatureNames")]
     """Array with the names of all categorical features in the dataset.
 
     E.g. ["Gender", "Geography"].
     """
 
-    feature_names: Annotated[List[str], PropertyInfo(alias="featureNames")]
+    feature_names: Annotated[SequenceNotStr[str], PropertyInfo(alias="featureNames")]
     """Array with all input feature names."""
 
     inference_id_column_name: Annotated[str, PropertyInfo(alias="inferenceIdColumnName")]
@@ -180,7 +181,7 @@ class ConfigTabularRegressionData(TypedDict, total=False):
 
 
 class ConfigTextClassificationData(TypedDict, total=False):
-    class_names: Required[Annotated[List[str], PropertyInfo(alias="classNames")]]
+    class_names: Required[Annotated[SequenceNotStr[str], PropertyInfo(alias="classNames")]]
     """List of class names indexed by label integer in the dataset.
 
     E.g. ["Retained", "Exited"] when 0, 1 are in your label column.

src/openlayer/types/projects/inference_pipeline_create_params.py

@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
-from typing import List, Optional
+from typing import Optional
 from typing_extensions import Literal, Required, Annotated, TypedDict
 
+from ..._types import SequenceNotStr
 from ..._utils import PropertyInfo
 
 __all__ = ["InferencePipelineCreateParams", "Project", "Workspace"]
@@ -51,4 +52,4 @@ class Workspace(TypedDict, total=False):
     saml_only_access: Annotated[bool, PropertyInfo(alias="samlOnlyAccess")]
     """Whether the workspace only allows SAML authentication."""
 
-    wildcard_domains: Annotated[List[str], PropertyInfo(alias="wildcardDomains")]
+    wildcard_domains: Annotated[SequenceNotStr[str], PropertyInfo(alias="wildcardDomains")]

src/openlayer/types/projects/test_create_params.py

@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
-from typing import List, Union, Iterable, Optional
+from typing import Union, Iterable, Optional
 from typing_extensions import Literal, Required, Annotated, TypedDict
 
+from ..._types import SequenceNotStr
 from ..._utils import PropertyInfo
 
 __all__ = ["TestCreateParams", "Threshold", "ThresholdInsightParameter"]
@@ -165,5 +166,5 @@ class Threshold(TypedDict, total=False):
     threshold_mode: Annotated[Literal["automatic", "manual"], PropertyInfo(alias="thresholdMode")]
     """Whether to use automatic anomaly detection or manual thresholds"""
 
-    value: Union[float, bool, str, List[str]]
+    value: Union[float, bool, str, SequenceNotStr[str]]
     """The value to be compared."""

src/openlayer/types/projects/test_update_params.py

@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
-from typing import List, Union, Iterable, Optional
+from typing import Union, Iterable, Optional
 from typing_extensions import Literal, Required, Annotated, TypedDict
 
+from ..._types import SequenceNotStr
 from ..._utils import PropertyInfo
 
 __all__ = ["TestUpdateParams", "Payload", "PayloadThreshold", "PayloadThresholdInsightParameter"]
@@ -82,7 +83,7 @@ class PayloadThreshold(TypedDict, total=False):
     threshold_mode: Annotated[Literal["automatic", "manual"], PropertyInfo(alias="thresholdMode")]
     """Whether to use automatic anomaly detection or manual thresholds"""
 
-    value: Union[float, bool, str, List[str]]
+    value: Union[float, bool, str, SequenceNotStr[str]]
     """The value to be compared."""