feat(api): update via SDK Studio (#274)

.stats.yml

@@ -1 +1 @@
-configured_endpoints: 12
+configured_endpoints: 13

api.md

@@ -55,12 +55,13 @@ Methods:
 Types:
 
 ```python
-from openlayer.types import InferencePipelineRetrieveResponse
+from openlayer.types import InferencePipelineRetrieveResponse, InferencePipelineUpdateResponse
 ```
 
 Methods:
 
 - <code title="get /inference-pipelines/{inferencePipelineId}">client.inference_pipelines.<a href="./src/openlayer/resources/inference_pipelines/inference_pipelines.py">retrieve</a>(inference_pipeline_id) -> <a href="./src/openlayer/types/inference_pipeline_retrieve_response.py">InferencePipelineRetrieveResponse</a></code>
+- <code title="put /inference-pipelines/{inferencePipelineId}">client.inference_pipelines.<a href="./src/openlayer/resources/inference_pipelines/inference_pipelines.py">update</a>(inference_pipeline_id, \*\*<a href="src/openlayer/types/inference_pipeline_update_params.py">params</a>) -> <a href="./src/openlayer/types/inference_pipeline_update_response.py">InferencePipelineUpdateResponse</a></code>
 - <code title="delete /inference-pipelines/{inferencePipelineId}">client.inference_pipelines.<a href="./src/openlayer/resources/inference_pipelines/inference_pipelines.py">delete</a>(inference_pipeline_id) -> None</code>
 
 ## Data

src/openlayer/resources/inference_pipelines/inference_pipelines.py

@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+from typing import Optional
+
 import httpx
 
 from .data import (
@@ -20,7 +22,12 @@
     RowsResourceWithStreamingResponse,
     AsyncRowsResourceWithStreamingResponse,
 )
+from ...types import inference_pipeline_update_params
 from ..._types import NOT_GIVEN, Body, Query, Headers, NoneType, NotGiven
+from ..._utils import (
+    maybe_transform,
+    async_maybe_transform,
+)
 from ..._compat import cached_property
 from ..._resource import SyncAPIResource, AsyncAPIResource
 from ..._response import (
@@ -38,6 +45,7 @@
     AsyncTestResultsResourceWithStreamingResponse,
 )
 from ..._base_client import make_request_options
+from ...types.inference_pipeline_update_response import InferencePipelineUpdateResponse
 from ...types.inference_pipeline_retrieve_response import InferencePipelineRetrieveResponse
 
 __all__ = ["InferencePipelinesResource", "AsyncInferencePipelinesResource"]
@@ -99,6 +107,59 @@ def retrieve(
             cast_to=InferencePipelineRetrieveResponse,
         )
 
+    def update(
+        self,
+        inference_pipeline_id: str,
+        *,
+        description: Optional[str] | NotGiven = NOT_GIVEN,
+        name: str | NotGiven = NOT_GIVEN,
+        reference_dataset_uri: Optional[str] | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> InferencePipelineUpdateResponse:
+        """
+        Update inference pipeline.
+
+        Args:
+          description: The inference pipeline description.
+
+          name: The inference pipeline name.
+
+          reference_dataset_uri: The storage uri of your reference dataset. We recommend using the Python SDK or
+              the UI to handle your reference dataset updates.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not inference_pipeline_id:
+            raise ValueError(
+                f"Expected a non-empty value for `inference_pipeline_id` but received {inference_pipeline_id!r}"
+            )
+        return self._put(
+            f"/inference-pipelines/{inference_pipeline_id}",
+            body=maybe_transform(
+                {
+                    "description": description,
+                    "name": name,
+                    "reference_dataset_uri": reference_dataset_uri,
+                },
+                inference_pipeline_update_params.InferencePipelineUpdateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=InferencePipelineUpdateResponse,
+        )
+
     def delete(
         self,
         inference_pipeline_id: str,
@@ -192,6 +253,59 @@ async def retrieve(
             cast_to=InferencePipelineRetrieveResponse,
         )
 
+    async def update(
+        self,
+        inference_pipeline_id: str,
+        *,
+        description: Optional[str] | NotGiven = NOT_GIVEN,
+        name: str | NotGiven = NOT_GIVEN,
+        reference_dataset_uri: Optional[str] | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> InferencePipelineUpdateResponse:
+        """
+        Update inference pipeline.
+
+        Args:
+          description: The inference pipeline description.
+
+          name: The inference pipeline name.
+
+          reference_dataset_uri: The storage uri of your reference dataset. We recommend using the Python SDK or
+              the UI to handle your reference dataset updates.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not inference_pipeline_id:
+            raise ValueError(
+                f"Expected a non-empty value for `inference_pipeline_id` but received {inference_pipeline_id!r}"
+            )
+        return await self._put(
+            f"/inference-pipelines/{inference_pipeline_id}",
+            body=await async_maybe_transform(
+                {
+                    "description": description,
+                    "name": name,
+                    "reference_dataset_uri": reference_dataset_uri,
+                },
+                inference_pipeline_update_params.InferencePipelineUpdateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=InferencePipelineUpdateResponse,
+        )
+
     async def delete(
         self,
         inference_pipeline_id: str,
@@ -236,6 +350,9 @@ def __init__(self, inference_pipelines: InferencePipelinesResource) -> None:
         self.retrieve = to_raw_response_wrapper(
             inference_pipelines.retrieve,
         )
+        self.update = to_raw_response_wrapper(
+            inference_pipelines.update,
+        )
         self.delete = to_raw_response_wrapper(
             inference_pipelines.delete,
         )
@@ -260,6 +377,9 @@ def __init__(self, inference_pipelines: AsyncInferencePipelinesResource) -> None
         self.retrieve = async_to_raw_response_wrapper(
             inference_pipelines.retrieve,
         )
+        self.update = async_to_raw_response_wrapper(
+            inference_pipelines.update,
+        )
         self.delete = async_to_raw_response_wrapper(
             inference_pipelines.delete,
         )
@@ -284,6 +404,9 @@ def __init__(self, inference_pipelines: InferencePipelinesResource) -> None:
         self.retrieve = to_streamed_response_wrapper(
             inference_pipelines.retrieve,
         )
+        self.update = to_streamed_response_wrapper(
+            inference_pipelines.update,
+        )
         self.delete = to_streamed_response_wrapper(
             inference_pipelines.delete,
         )
@@ -308,6 +431,9 @@ def __init__(self, inference_pipelines: AsyncInferencePipelinesResource) -> None
         self.retrieve = async_to_streamed_response_wrapper(
             inference_pipelines.retrieve,
         )
+        self.update = async_to_streamed_response_wrapper(
+            inference_pipelines.update,
+        )
         self.delete = async_to_streamed_response_wrapper(
             inference_pipelines.delete,
         )

src/openlayer/types/__init__.py

@@ -6,4 +6,6 @@
 from .project_create_params import ProjectCreateParams as ProjectCreateParams
 from .project_list_response import ProjectListResponse as ProjectListResponse
 from .project_create_response import ProjectCreateResponse as ProjectCreateResponse
+from .inference_pipeline_update_params import InferencePipelineUpdateParams as InferencePipelineUpdateParams
+from .inference_pipeline_update_response import InferencePipelineUpdateResponse as InferencePipelineUpdateResponse
 from .inference_pipeline_retrieve_response import InferencePipelineRetrieveResponse as InferencePipelineRetrieveResponse

src/openlayer/types/inference_pipeline_update_params.py

@@ -0,0 +1,25 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+from typing import Optional
+from typing_extensions import Annotated, TypedDict
+
+from .._utils import PropertyInfo
+
+__all__ = ["InferencePipelineUpdateParams"]
+
+
+class InferencePipelineUpdateParams(TypedDict, total=False):
+    description: Optional[str]
+    """The inference pipeline description."""
+
+    name: str
+    """The inference pipeline name."""
+
+    reference_dataset_uri: Annotated[Optional[str], PropertyInfo(alias="referenceDatasetUri")]
+    """The storage uri of your reference dataset.
+
+    We recommend using the Python SDK or the UI to handle your reference dataset
+    updates.
+    """

src/openlayer/types/inference_pipeline_update_response.py

@@ -0,0 +1,61 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from typing import Optional
+from datetime import datetime
+from typing_extensions import Literal
+
+from pydantic import Field as FieldInfo
+
+from .._models import BaseModel
+
+__all__ = ["InferencePipelineUpdateResponse", "Links"]
+
+
+class Links(BaseModel):
+    app: str
+
+
+class InferencePipelineUpdateResponse(BaseModel):
+    id: str
+    """The inference pipeline id."""
+
+    date_created: datetime = FieldInfo(alias="dateCreated")
+    """The creation date."""
+
+    date_last_evaluated: Optional[datetime] = FieldInfo(alias="dateLastEvaluated", default=None)
+    """The last test evaluation date."""
+
+    date_last_sample_received: Optional[datetime] = FieldInfo(alias="dateLastSampleReceived", default=None)
+    """The last data sample received date."""
+
+    date_of_next_evaluation: Optional[datetime] = FieldInfo(alias="dateOfNextEvaluation", default=None)
+    """The next test evaluation date."""
+
+    date_updated: datetime = FieldInfo(alias="dateUpdated")
+    """The last updated date."""
+
+    description: Optional[str] = None
+    """The inference pipeline description."""
+
+    failing_goal_count: int = FieldInfo(alias="failingGoalCount")
+    """The number of tests failing."""
+
+    links: Links
+
+    name: str
+    """The inference pipeline name."""
+
+    passing_goal_count: int = FieldInfo(alias="passingGoalCount")
+    """The number of tests passing."""
+
+    project_id: str = FieldInfo(alias="projectId")
+    """The project id."""
+
+    status: Literal["queued", "running", "paused", "failed", "completed", "unknown"]
+    """The status of test evaluation for the inference pipeline."""
+
+    status_message: Optional[str] = FieldInfo(alias="statusMessage", default=None)
+    """The status message of test evaluation for the inference pipeline."""
+
+    total_goal_count: int = FieldInfo(alias="totalGoalCount")
+    """The total number of tests."""