Release v4.32.0 (#1859)

Author: alexmojaki

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Release Notes
 
+## [v4.32.0] (2026-04-10)
+
+* Add `push_dataset` helpers to the experimental API client by @dmontagu in [#1848](https://github.com/pydantic/logfire/pull/1848)
+
 ## [v4.31.2] (2026-04-10)
 
 * fix: Show token badges for OpenAI streaming logs by @alexmojaki in [#1857](https://github.com/pydantic/logfire/pull/1857)
@@ -1105,3 +1109,4 @@ First release from new repo!
 [v4.31.0]: https://github.com/pydantic/logfire/compare/v4.30.0...v4.31.0
 [v4.31.1]: https://github.com/pydantic/logfire/compare/v4.31.0...v4.31.1
 [v4.31.2]: https://github.com/pydantic/logfire/compare/v4.31.1...v4.31.2
+[v4.32.0]: https://github.com/pydantic/logfire/compare/v4.31.2...v4.32.0

logfire-api/logfire_api/experimental/api_client.pyi

@@ -6,7 +6,7 @@ from logfire._internal.config import get_base_url_from_token as get_base_url_fro
 from pydantic_evals import Case, Dataset
 from pydantic_evals.evaluators import Evaluator
 from types import TracebackType
-from typing import Any, Generic, TypeVar, overload
+from typing import Any, Generic, Literal, TypeVar, overload
 from typing_extensions import Self
 
 Case = Any
@@ -42,8 +42,9 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
     Example usage:
         ```python skip-run="true" skip-reason="external-connection"
         from dataclasses import dataclass
+        from pydantic_evals import Case, Dataset
+
         from logfire.experimental.api_client import LogfireAPIClient
-        from pydantic_evals import Case
 
 
         @dataclass
@@ -56,21 +57,17 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             answer: str
 
 
-        with LogfireAPIClient(api_key=\'your-api-key\') as client:
-            # Create typed dataset
-            dataset = client.create_dataset(
-                name=\'qa-dataset\',
-                input_type=MyInput,
-                output_type=MyOutput,
-            )
+        local_dataset = Dataset[MyInput, MyOutput, None](
+            name=\'qa-dataset\',
+            cases=[
+                Case(name=\'q1\', inputs=MyInput(\'Hello?\'), expected_output=MyOutput(\'Hi!\')),
+            ],
+        )
 
-            # Add cases using pydantic-evals Case objects
-            client.add_cases(
-                dataset[\'id\'],
-                cases=[
-                    Case(name=\'q1\', inputs=MyInput(\'Hello?\'), expected_output=MyOutput(\'Hi!\')),
-                ],
-            )
+
+        with LogfireAPIClient(api_key=\'your-api-key\') as client:
+            # Publish the local dataset to hosted
+            client.push_dataset(local_dataset)
 
             # Get as pydantic-evals Dataset
             dataset = client.get_dataset(\'qa-dataset\', MyInput, MyOutput)
@@ -93,7 +90,7 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
         Returns:
             List of dataset summaries with id, name, description, case_count, etc.
         """
-    def create_dataset(self, name: str, *, input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = None, guidance: str | None = None, ai_managed_guidance: bool = False) -> dict[str, Any]:
+    def create_dataset(self, name: str, *, input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = None) -> dict[str, Any]:
         '''Create a new dataset with optional type schemas.
 
         Args:
@@ -102,8 +99,6 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             output_type: Type for expected outputs. JSON schema will be generated from this type.
             metadata_type: Type for case metadata. JSON schema will be generated from this type.
             description: Optional description of the dataset.
-            guidance: Instructions for AI-assisted population.
-            ai_managed_guidance: Whether guidance is managed by AI.
 
         Returns:
             The created dataset.
@@ -130,7 +125,7 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             )
             ```
         '''
-    def update_dataset(self, id_or_name: str, *, name: str = ..., input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = ..., guidance: str | None = ..., ai_managed_guidance: bool | None = None) -> dict[str, Any]:
+    def update_dataset(self, id_or_name: str, *, name: str = ..., input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = ...) -> dict[str, Any]:
         """Update an existing dataset.
 
         Args:
@@ -140,8 +135,6 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             output_type: New output type (generates schema).
             metadata_type: New metadata type (generates schema).
             description: New description. Pass None to clear.
-            guidance: New guidance instructions. Pass None to clear.
-            ai_managed_guidance: Whether guidance is managed by AI.
 
         Returns:
             The updated dataset.
@@ -158,12 +151,11 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
         Raises:
             DatasetNotFoundError: If the dataset does not exist.
         """
-    def list_cases(self, dataset_id_or_name: str, *, tags: list[str] | None = None) -> list[dict[str, Any]]:
+    def list_cases(self, dataset_id_or_name: str) -> list[dict[str, Any]]:
         """List all cases in a dataset.
 
         Args:
             dataset_id_or_name: The dataset ID (UUID) or name.
-            tags: Optional list of tags to filter cases by.
 
         Returns:
             List of cases with full details.
@@ -185,7 +177,79 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             DatasetNotFoundError: If the dataset does not exist.
             CaseNotFoundError: If the case does not exist.
         """
-    def add_cases(self, dataset_id_or_name: str, cases: Sequence[Case[InputsT, OutputT, MetadataT]] | Sequence[dict[str, Any]], *, tags: list[str] | None = None, on_conflict: str = 'update') -> list[dict[str, Any]]:
+    def push_dataset(self, dataset: Dataset[InputsT, OutputT, MetadataT], *, name: str | None = None, description: str | None = ..., on_case_conflict: Literal['update', 'error'] = 'update') -> dict[str, Any]:
+        '''Publish a local `pydantic_evals.Dataset` to the hosted datasets API.
+
+        This is the high-level "push my dataset to hosted" helper. It creates a
+        hosted dataset when one does not exist yet, updates the hosted dataset
+        when one already exists with the same name, uploads all local cases
+        through the existing import/upsert API, and finally returns hosted
+        dataset metadata.
+
+        The JSON schemas for inputs, expected outputs, and metadata are
+        inferred from the `Dataset[InputsT, OutputT, MetadataT]` generic
+        parameters of the dataset you pass in — instantiate your local dataset
+        with the types you want hosted.
+
+        Args:
+            dataset: The local `pydantic_evals.Dataset` to publish. Case-level
+                evaluators are uploaded with their cases. Dataset-level
+                `evaluators` and `report_evaluators` are not supported yet and
+                will raise `ValueError`.
+            name: Optional hosted dataset name override. Defaults to
+                `dataset.name`.
+            description: Hosted dataset description. Omit this argument to leave
+                the existing description unchanged when updating an existing
+                dataset. Pass `None` to clear the description on update. On
+                initial create, `None` means no description is set.
+            on_case_conflict: Conflict behavior for uploaded cases. The default
+                `\'update\'` makes repeated pushes idempotent for named cases.
+                Pass `\'error\'` to fail instead of updating an existing case with
+                the same name.
+
+        Returns:
+            Hosted dataset metadata as returned by
+            `get_dataset(..., include_cases=False)`.
+
+        Raises:
+            ValueError: If neither `dataset.name` nor `name` is provided, or if
+                the dataset contains unsupported dataset-level evaluators.
+            DatasetApiError: If the API returns an error other than the expected
+                `409` conflict used to trigger an update flow.
+            DatasetNotFoundError: If the hosted dataset cannot be fetched after
+                the push completes.
+
+        Example:
+            ```python skip-run="true" skip-reason="external-connection"
+            from dataclasses import dataclass
+
+            from pydantic_evals import Case, Dataset
+
+
+            @dataclass
+            class MyInput:
+                question: str
+
+
+            @dataclass
+            class MyOutput:
+                answer: str
+
+
+            local_dataset = Dataset[MyInput, MyOutput, None](
+                name=\'qa-dataset\',
+                cases=[
+                    Case(name=\'q1\', inputs=MyInput(\'Hello?\'), expected_output=MyOutput(\'Hi!\')),
+                ],
+            )
+
+            dataset_info = client.push_dataset(
+                local_dataset,
+                description=\'Golden test cases for the Q&A task\',
+            )
+            ```
+        '''
+    def add_cases(self, dataset_id_or_name: str, cases: Sequence[Case[InputsT, OutputT, MetadataT]] | Sequence[dict[str, Any]], *, on_conflict: str = 'update') -> list[dict[str, Any]]:
         '''Add cases to a dataset.
 
         Accepts either pydantic-evals Case objects or plain dicts.
@@ -197,7 +261,6 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
         Args:
             dataset_id_or_name: The dataset ID (UUID) or name.
             cases: A sequence of pydantic-evals Case objects or dicts.
-            tags: Optional list of tags to associate with all cases.
             on_conflict: Conflict resolution strategy: `\'update\'` (default) to
                 upsert cases with matching names, or `\'error\'` to fail on conflicts.
 
@@ -220,7 +283,7 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             )
             ```
         '''
-    def update_case(self, dataset_id_or_name: str, case_id: str, *, name: str | None = ..., inputs: Any | None = None, expected_output: Any | None = ..., metadata: Any | None = ..., evaluators: Sequence[Evaluator[Any, Any, Any]] | None = ..., tags: list[str] | None = ...) -> dict[str, Any]:
+    def update_case(self, dataset_id_or_name: str, case_id: str, *, name: str | None = ..., inputs: Any | None = None, expected_output: Any | None = ..., metadata: Any | None = ..., evaluators: Sequence[Evaluator[Any, Any, Any]] | None = ...) -> dict[str, Any]:
         """Update an existing case.
 
         Args:
@@ -231,7 +294,6 @@ class LogfireAPIClient(_BaseLogfireAPIClient[Client]):
             expected_output: New expected output (dict or typed object). Pass None to clear.
             metadata: New metadata (dict or typed object). Pass None to clear.
             evaluators: New evaluators. Pass None to clear.
-            tags: New tags for the case. Pass None to clear.
 
         Returns:
             The updated case.
@@ -266,17 +328,48 @@ class AsyncLogfireAPIClient(_BaseLogfireAPIClient[AsyncClient]):
     async def __aexit__(self, exc_type: type[BaseException] | None = None, exc_value: BaseException | None = None, traceback: TracebackType | None = None) -> None: ...
     async def list_datasets(self) -> list[dict[str, Any]]:
         """List all datasets."""
-    async def create_dataset(self, name: str, *, input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = None, guidance: str | None = None, ai_managed_guidance: bool = False) -> dict[str, Any]:
+    async def create_dataset(self, name: str, *, input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = None) -> dict[str, Any]:
         """Create a new dataset."""
-    async def update_dataset(self, id_or_name: str, *, name: str = ..., input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = ..., guidance: str | None = ..., ai_managed_guidance: bool | None = None) -> dict[str, Any]:
+    async def update_dataset(self, id_or_name: str, *, name: str = ..., input_type: type[Any] | None = None, output_type: type[Any] | None = None, metadata_type: type[Any] | None = None, description: str | None = ...) -> dict[str, Any]:
         """Update an existing dataset."""
     async def delete_dataset(self, id_or_name: str) -> None:
         """Delete a dataset."""
-    async def list_cases(self, dataset_id_or_name: str, *, tags: list[str] | None = None) -> list[dict[str, Any]]:
+    async def list_cases(self, dataset_id_or_name: str) -> list[dict[str, Any]]:
         """List all cases in a dataset."""
     async def get_case(self, dataset_id_or_name: str, case_id: str) -> dict[str, Any]:
         """Get a specific case from a dataset."""
-    async def add_cases(self, dataset_id_or_name: str, cases: Sequence[Case[InputsT, OutputT, MetadataT]] | Sequence[dict[str, Any]], *, tags: list[str] | None = None, on_conflict: str = 'update') -> list[dict[str, Any]]:
+    async def push_dataset(self, dataset: Dataset[InputsT, OutputT, MetadataT], *, name: str | None = None, description: str | None = ..., on_case_conflict: Literal['update', 'error'] = 'update') -> dict[str, Any]:
+        """Async version of `LogfireAPIClient.push_dataset`.
+
+        Args:
+            dataset: The local `pydantic_evals.Dataset` to publish. Case-level
+                evaluators are uploaded with their cases. Dataset-level
+                `evaluators` and `report_evaluators` are not supported yet and
+                will raise `ValueError`.
+            name: Optional hosted dataset name override. Defaults to
+                `dataset.name`.
+            description: Hosted dataset description. Omit this argument to leave
+                the existing description unchanged when updating an existing
+                dataset. Pass `None` to clear the description on update. On
+                initial create, `None` means no description is set.
+            on_case_conflict: Conflict behavior for uploaded cases. The default
+                `'update'` makes repeated pushes idempotent for named cases.
+                Pass `'error'` to fail instead of updating an existing case with
+                the same name.
+
+        Returns:
+            Hosted dataset metadata as returned by
+            `get_dataset(..., include_cases=False)`.
+
+        Raises:
+            ValueError: If neither `dataset.name` nor `name` is provided, or if
+                the dataset contains unsupported dataset-level evaluators.
+            DatasetApiError: If the API returns an error other than the expected
+                `409` conflict used to trigger an update flow.
+            DatasetNotFoundError: If the hosted dataset cannot be fetched after
+                the push completes.
+        """
+    async def add_cases(self, dataset_id_or_name: str, cases: Sequence[Case[InputsT, OutputT, MetadataT]] | Sequence[dict[str, Any]], *, on_conflict: str = 'update') -> list[dict[str, Any]]:
         """Add cases to a dataset.
 
         Accepts either pydantic-evals Case objects or plain dicts.
@@ -285,7 +378,7 @@ class AsyncLogfireAPIClient(_BaseLogfireAPIClient[AsyncClient]):
         case in the dataset are updated; cases without a name or with a new name
         are created. Set `on_conflict='error'` to fail on name conflicts instead.
         """
-    async def update_case(self, dataset_id_or_name: str, case_id: str, *, name: str | None = ..., inputs: Any | None = None, expected_output: Any | None = ..., metadata: Any | None = ..., evaluators: Sequence[Evaluator[Any, Any, Any]] | None = ..., tags: list[str] | None = ...) -> dict[str, Any]:
+    async def update_case(self, dataset_id_or_name: str, case_id: str, *, name: str | None = ..., inputs: Any | None = None, expected_output: Any | None = ..., metadata: Any | None = ..., evaluators: Sequence[Evaluator[Any, Any, Any]] | None = ...) -> dict[str, Any]:
         """Update an existing case."""
     async def delete_case(self, dataset_id_or_name: str, case_id: str) -> None:
         """Delete a case from a dataset."""

logfire-api/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "logfire-api"
-version = "4.31.2"
+version = "4.32.0"
 description = "Shim for the Logfire SDK which does nothing unless Logfire is installed"
 authors = [
     { name = "Pydantic Team", email = "engineering@pydantic.dev" },

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "logfire"
-version = "4.31.2"
+version = "4.32.0"
 description = "The best Python observability tool! 🪵🔥"
 requires-python = ">=3.9"
 authors = [