Source code for bentoml._internal.io_descriptors.base

from __future__ import annotations

import typing as t
from abc import ABC
from abc import abstractmethod
from functools import update_wrapper

from ...exceptions import InvalidArgument

    from types import UnionType

    import pyarrow
    import pyspark.sql.types
    from starlette.requests import Request
    from starlette.responses import Response
    from starlette.responses import StreamingResponse

    from bentoml.grpc.types import ProtoField

    from ..context import ServiceContext as Context
    from ..service.openapi.specification import Reference
    from ..service.openapi.specification import Schema
    from ..types import LazyType

    InputType = (
        | t.Type[t.Any]
        | LazyType[t.Any]
        | dict[str, t.Type[t.Any] | UnionType | LazyType[t.Any]]
    OpenAPIResponse = dict[str, str | dict[str, t.Any]]
    F = t.Callable[..., t.Any]

IO_DESCRIPTOR_REGISTRY: dict[str, type[IODescriptor[t.Any]]] = {}

IOType = t.TypeVar("IOType")

def from_spec(spec: dict[str, t.Any]) -> IODescriptor[t.Any]:
    if "id" not in spec:
        raise InvalidArgument(f"IO descriptor spec ({spec}) missing ID.")

    if spec["id"] is None:
        raise InvalidArgument("No IO descriptor spec found.")

    return IO_DESCRIPTOR_REGISTRY[spec["id"]].from_spec(spec)

class _OpenAPIMeta:
    def openapi_schema(self) -> Schema | Reference:
        raise NotImplementedError

    def openapi_components(self) -> dict[str, t.Any] | None:
        raise NotImplementedError

    def openapi_example(self) -> t.Any | None:
        raise NotImplementedError

    def openapi_request_body(self) -> dict[str, t.Any]:
        raise NotImplementedError

    def openapi_responses(self) -> dict[str, t.Any]:
        raise NotImplementedError

[docs]class IODescriptor(ABC, _OpenAPIMeta, t.Generic[IOType]): """ IODescriptor describes the input/output data format of an InferenceAPI defined in a :code:`bentoml.Service`. This is an abstract base class for extending new HTTP endpoint IO descriptor types in BentoServer. """ if t.TYPE_CHECKING: # Populated by subclasses. Makes pyright happy. def __init__(self, **kwargs: t.Any) -> None: ... __slots__ = ( "_mime_type", "proto_fields", "descriptor_id", "from_sample", "_sample", ) HTTP_METHODS = ("POST",) _mime_type: str descriptor_id: str | None proto_fields: tuple[ProtoField] def __init_subclass__( cls, *, descriptor_id: str | None = None, proto_fields: tuple[ProtoField] | None = None, ): if descriptor_id is not None: if descriptor_id in IO_DESCRIPTOR_REGISTRY: raise ValueError( f"Descriptor ID {descriptor_id} already registered to {IO_DESCRIPTOR_REGISTRY[descriptor_id]}." ) IO_DESCRIPTOR_REGISTRY[descriptor_id] = cls cls.descriptor_id = descriptor_id cls.proto_fields = proto_fields or t.cast("tuple[ProtoField]", ()) cls._sample: IOType | None = None def _() -> F: def impl( cl_: type[IODescriptor[t.Any]], sample: t.Any, **kwargs: t.Any ) -> IODescriptor[t.Any]: klass = cl_(**kwargs) klass.sample = klass._from_sample(sample) return klass impl.__doc__ = cls._from_sample.__doc__ return update_wrapper(impl, cls._from_sample) cls.from_sample = classmethod(_()) def __repr__(self) -> str: return self.__class__.__qualname__ @property def sample(self) -> IOType | None: return self._sample @sample.setter def sample(self, value: IOType) -> None: self._sample = value if t.TYPE_CHECKING: @classmethod def from_sample(cls, sample: t.Any, **attrs: t.Any) -> t.Self: ... @abstractmethod def _from_sample(self, sample: t.Any) -> IOType: """ Creates a new instance of the IO Descriptor from given sample. Args: sample: The sample to create the instance from. **kwargs: Additional keyword arguments to pass to the constructor. Returns: An instance of the IODescriptor. """ raise NotImplementedError @property def mime_type(self) -> str: return self._mime_type def to_spec(self) -> dict[str, t.Any] | None: return None @classmethod def from_spec(cls, spec: dict[str, t.Any]) -> t.Self: raise NotImplementedError @abstractmethod def input_type(self) -> InputType: raise NotImplementedError @abstractmethod async def from_http_request(self, request: Request) -> IOType: raise NotImplementedError @abstractmethod async def to_http_response( self, obj: IOType, ctx: Context | None = None ) -> Response | StreamingResponse: raise NotImplementedError @abstractmethod async def from_proto(self, field: t.Any) -> IOType: raise NotImplementedError @abstractmethod async def to_proto(self, obj: IOType) -> t.Any: raise NotImplementedError def from_arrow(self, batch: pyarrow.RecordBatch) -> IOType: raise NotImplementedError( "This IO descriptor does not currently support batch inference." ) def to_arrow(self, obj: IOType) -> pyarrow.RecordBatch: raise NotImplementedError( "This IO descriptor does not currently support batch inference." ) def spark_schema(self) -> pyspark.sql.types.StructType: raise NotImplementedError( "This IO descriptor does not currently support batch inference." )