feat: from_sample classmethod [skip ci]

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

pyproject.toml

@@ -35,6 +35,7 @@ dependencies = [
   "deepmerge",
   "fs",
   "numpy",
+  "filetype",
   "opentelemetry-api>=1.9.0",
   "opentelemetry-instrumentation==0.33b0",
   "opentelemetry-instrumentation-aiohttp-client==0.33b0",

src/bentoml/_internal/bento/build_dev_bentoml_whl.py

@@ -29,9 +29,8 @@ def build_bentoml_editable_wheel(target_path: str) -> None:
         return
 
     try:
-        from build.env import IsolatedEnvBuilder
-
-        from build import ProjectBuilder
+        from build.env import IsolatedEnvBuilder  # isort: skip
+        from build import ProjectBuilder  # isort: skip
     except ModuleNotFoundError as e:
         raise MissingDependencyException(_exc_message) from e
 

src/bentoml/_internal/io_descriptors/base.py

@@ -19,16 +19,16 @@
     from ..types import LazyType
     from ..context import InferenceApiContext as Context
     from ..service.openapi.specification import Schema
-    from ..service.openapi.specification import Response as OpenAPIResponse
+    from ..service.openapi.specification import MediaType
     from ..service.openapi.specification import Reference
-    from ..service.openapi.specification import RequestBody
 
     InputType = (
         UnionType
         | t.Type[t.Any]
         | LazyType[t.Any]
         | dict[str, t.Type[t.Any] | UnionType | LazyType[t.Any]]
     )
+    OpenAPIResponse = dict[str, str | dict[str, MediaType] | dict[str, t.Any]]
 
 
 IO_DESCRIPTOR_REGISTRY: dict[str, type[IODescriptor[t.Any]]] = {}
@@ -54,6 +54,7 @@ class IODescriptor(ABC, t.Generic[IOType]):
     _mime_type: str
     _rpc_content_type: str = "application/grpc"
     _proto_fields: tuple[ProtoField]
+    _sample_input: IOType | None = None
     descriptor_id: str | None
 
     def __init_subclass__(cls, *, descriptor_id: str | None = None):
@@ -65,6 +66,14 @@ def __init_subclass__(cls, *, descriptor_id: str | None = None):
             IO_DESCRIPTOR_REGISTRY[descriptor_id] = cls
         cls.descriptor_id = descriptor_id
 
+    @property
+    def sample_input(self) -> IOType | None:
+        return self._sample_input
+
+    @sample_input.setter
+    def sample_input(self, value: IOType) -> None:
+        self._sample_input = value
+
     @abstractmethod
     def to_spec(self) -> dict[str, t.Any]:
         raise NotImplementedError
@@ -90,7 +99,7 @@ def openapi_components(self) -> dict[str, t.Any] | None:
         raise NotImplementedError
 
     @abstractmethod
-    def openapi_request_body(self) -> RequestBody:
+    def openapi_request_body(self) -> dict[str, t.Any]:
         raise NotImplementedError
 
     @abstractmethod
@@ -114,3 +123,8 @@ async def from_proto(self, field: t.Any) -> IOType:
     @abstractmethod
     async def to_proto(self, obj: IOType) -> t.Any:
         ...
+
+    @classmethod
+    @abstractmethod
+    def from_sample(cls, sample_input: IOType, **kwargs: t.Any) -> Self:
+        ...

src/bentoml/_internal/io_descriptors/file.py

@@ -14,18 +14,20 @@
 from ..types import FileLike
 from ..utils.http import set_cookies
 from ...exceptions import BadInput
+from ...exceptions import InvalidArgument
 from ...exceptions import BentoMLException
 from ..service.openapi import SUCCESS_DESCRIPTION
 from ..service.openapi.specification import Schema
-from ..service.openapi.specification import Response as OpenAPIResponse
 from ..service.openapi.specification import MediaType
-from ..service.openapi.specification import RequestBody
 
 logger = logging.getLogger(__name__)
 
 if TYPE_CHECKING:
+    from typing_extensions import Self
+
     from bentoml.grpc.v1alpha1 import service_pb2 as pb
 
+    from .base import OpenAPIResponse
     from ..context import InferenceApiContext as Context
 
     FileKind: t.TypeAlias = t.Literal["binaryio", "textio"]
@@ -110,9 +112,7 @@ async def predict(input_pdf: io.BytesIO[Any]) -> NDArray[Any]:
 
     _proto_fields = ("file",)
 
-    def __new__(  # pylint: disable=arguments-differ # returning subclass from new
-        cls, kind: FileKind = "binaryio", mime_type: str | None = None
-    ) -> File:
+    def __new__(cls, kind: FileKind = "binaryio", mime_type: str | None = None) -> File:
         mime_type = mime_type if mime_type is not None else "application/octet-stream"
         if kind == "binaryio":
             res = object.__new__(BytesIOFile)
@@ -121,8 +121,14 @@ def __new__(  # pylint: disable=arguments-differ # returning subclass from new
         res._mime_type = mime_type
         return res
 
-    def to_spec(self):
-        raise NotImplementedError
+    @classmethod
+    def from_sample(cls, sample_input: FileType, kind: FileKind = "binaryio") -> Self:
+        import filetype
+
+        mime_type: str | None = filetype.guess_mime(sample_input)
+        kls = cls(kind=kind, mime_type=mime_type)
+        kls.sample_input = sample_input
+        return kls
 
     @classmethod
     def from_spec(cls, spec: dict[str, t.Any]) -> Self:
@@ -193,6 +199,9 @@ async def from_proto(self, field: pb.File | bytes) -> FileLike[bytes]:
     async def from_http_request(self, request: Request) -> t.IO[bytes]:
         raise NotImplementedError
 
+    def to_spec(self) -> dict[str, t.Any]:
+        raise NotImplementedError
+
 
 class BytesIOFile(File, descriptor_id=None):
     def to_spec(self) -> dict[str, t.Any]:

src/bentoml/_internal/io_descriptors/image.py

@@ -20,7 +20,6 @@
 from ...exceptions import InternalServerError
 from ..service.openapi import SUCCESS_DESCRIPTION
 from ..service.openapi.specification import Schema
-from ..service.openapi.specification import Response as OpenAPIResponse
 from ..service.openapi.specification import MediaType
 from ..service.openapi.specification import RequestBody
 
@@ -31,6 +30,7 @@
     import PIL.Image
 
     from bentoml.grpc.v1alpha1 import service_pb2 as pb
+    from .base import OpenAPIResponse
 
     from .. import external_typing as ext
     from ..context import InferenceApiContext as Context
@@ -75,7 +75,7 @@ def initialize_pillow():
         import PIL.Image
     except ImportError:
         raise InternalServerError(
-            "`Pillow` is required to use {__name__}\n Instructions: `pip install -U Pillow`"
+            f"'Pillow' is required to use {__name__}. Install Pillow with 'pip install bentoml[io-image]'"
         )
 
     PIL.Image.init()

src/bentoml/_internal/io_descriptors/numpy.py

@@ -19,16 +19,17 @@
 from ...exceptions import UnprocessableEntity
 from ..service.openapi import SUCCESS_DESCRIPTION
 from ..service.openapi.specification import Schema
-from ..service.openapi.specification import Response as OpenAPIResponse
 from ..service.openapi.specification import MediaType
 from ..service.openapi.specification import RequestBody
 
 if TYPE_CHECKING:
     import numpy as np
+    from typing_extensions import Self
 
     from bentoml.grpc.v1alpha1 import service_pb2 as pb
 
     from .. import external_typing as ext
+    from .base import OpenAPIResponse
     from ..context import InferenceApiContext as Context
 else:
     from bentoml.grpc.utils import import_generated_stubs
@@ -228,8 +229,6 @@ def __init__(
         self._enforce_dtype = enforce_dtype
         self._enforce_shape = enforce_shape
 
-        self._sample_input = None
-
         if self._enforce_dtype and not self._dtype:
             raise InvalidArgument(
                 "'dtype' must be specified when 'enforce_dtype=True'"
@@ -269,14 +268,6 @@ def from_spec(cls, spec: dict[str, t.Any]) -> Self:
         res = NumpyNdarray(**spec["args"])
         return res
 
-    @property
-    def sample_input(self) -> ext.NpNDArray | None:
-        return self._sample_input
-
-    @sample_input.setter
-    def sample_input(self, value: ext.NpNDArray) -> None:
-        self._sample_input = value
-
     def openapi_schema(self) -> Schema:
         # Note that we are yet provide
         # supports schemas for arrays that is > 2D.
@@ -407,7 +398,7 @@ def from_sample(
         sample_input: ext.NpNDArray,
         enforce_dtype: bool = True,
         enforce_shape: bool = True,
-    ) -> NumpyNdarray:
+    ) -> Self:
         """
         Create a :obj:`NumpyNdarray` IO Descriptor from given inputs.
 

src/bentoml/_internal/service/openapi/specification.py

@@ -187,7 +187,7 @@ class Operation:
     description: t.Optional[str] = None
     externalDocs: t.Optional[ExternalDocumentation] = None
     operationId: t.Optional[str] = None
-    requestBody: t.Optional[t.Union[RequestBody, Reference]] = None
+    requestBody: t.Optional[t.Union[RequestBody, Reference, t.Dict[str, t.Any]]] = None
 
     # Not yet supported: parameters, callbacks, deprecated, servers, security
 
@@ -253,7 +253,9 @@ class Components:
     schemas: t.Dict[str, t.Union[Schema, Reference]]
     responses: t.Optional[t.Dict[str, t.Union[Response, Reference]]] = None
     examples: t.Optional[t.Dict[str, t.Union[Example, Reference]]] = None
-    requestBodies: t.Optional[t.Dict[str, t.Union[RequestBody, Reference]]] = None
+    requestBodies: t.Optional[
+        t.Dict[str, t.Union[RequestBody, Reference, t.Dict[str, t.Any]]]
+    ] = None
     links: t.Optional[t.Dict[str, t.Union[Link, Reference]]] = None
 
     # Not yet supported: securitySchemes, callbacks, parameters, headers