feat(ray): add help functions for ray model

.pylint.ini

@@ -7,7 +7,7 @@ extension-pkg-whitelist=
 
 # Add files or directories to the blacklist. They should be base names, not
 # paths.
-ignore=CVS,protogen
+ignore=CVS,protogen,protobufs
 
 # Add files or directories matching the regex patterns to the blacklist. The
 # regex matches against base names, not paths.

instill/configuration/__init__.py

@@ -6,6 +6,9 @@
 import yaml
 from pydantic import BaseModel
 
+CLOUD_RAY_ADDRESS = "ray://core_ray_server:10001"
+CORE_RAY_ADDRESS = "ray://ray_server:10001"
+
 CONFIG_DIR = Path(
     os.getenv(
         "INSTILL_SYSTEM_CONFIG_PATH",

instill/helpers/protobufs/ray_pb2.pyi

@@ -0,0 +1,256 @@
+"""
+@generated by mypy-protobuf.  Do not edit manually!
+isort:skip_file
+"""
+import builtins
+import collections.abc
+import google.protobuf.descriptor
+import google.protobuf.internal.containers
+import google.protobuf.message
+import sys
+
+if sys.version_info >= (3, 8):
+    import typing as typing_extensions
+else:
+    import typing_extensions
+
+DESCRIPTOR: google.protobuf.descriptor.FileDescriptor
+
+@typing_extensions.final
+class ModelReadyRequest(google.protobuf.message.Message):
+    """ModelReadyRequest represents a request to check if a model is ready"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    NAME_FIELD_NUMBER: builtins.int
+    VERSION_FIELD_NUMBER: builtins.int
+    name: builtins.str
+    """model id"""
+    version: builtins.str
+    """model tag verion"""
+    def __init__(
+        self,
+        *,
+        name: builtins.str = ...,
+        version: builtins.str = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "version", b"version"]) -> None: ...
+
+global___ModelReadyRequest = ModelReadyRequest
+
+@typing_extensions.final
+class ModelReadyResponse(google.protobuf.message.Message):
+    """ModelReadyResponse represents a response to check if a model is ready"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    READY_FIELD_NUMBER: builtins.int
+    ready: builtins.bool
+    """whether the model is ready or not"""
+    def __init__(
+        self,
+        *,
+        ready: builtins.bool = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["ready", b"ready"]) -> None: ...
+
+global___ModelReadyResponse = ModelReadyResponse
+
+@typing_extensions.final
+class ModelMetadataRequest(google.protobuf.message.Message):
+    """ModelMetadataRequest represents a request to get the model metadata"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    NAME_FIELD_NUMBER: builtins.int
+    VERSION_FIELD_NUMBER: builtins.int
+    name: builtins.str
+    """model id"""
+    version: builtins.str
+    """model tag verion"""
+    def __init__(
+        self,
+        *,
+        name: builtins.str = ...,
+        version: builtins.str = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["name", b"name", "version", b"version"]) -> None: ...
+
+global___ModelMetadataRequest = ModelMetadataRequest
+
+@typing_extensions.final
+class InferTensor(google.protobuf.message.Message):
+    """tensor for inference"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    NAME_FIELD_NUMBER: builtins.int
+    DATATYPE_FIELD_NUMBER: builtins.int
+    SHAPE_FIELD_NUMBER: builtins.int
+    name: builtins.str
+    """tensor name."""
+    datatype: builtins.str
+    """tensor data type."""
+    @property
+    def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]:
+        """tensor shape."""
+    def __init__(
+        self,
+        *,
+        name: builtins.str = ...,
+        datatype: builtins.str = ...,
+        shape: collections.abc.Iterable[builtins.int] | None = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["datatype", b"datatype", "name", b"name", "shape", b"shape"]) -> None: ...
+
+global___InferTensor = InferTensor
+
+@typing_extensions.final
+class ModelMetadataResponse(google.protobuf.message.Message):
+    """ModelMetadataResponse represents a response to get the model metadata"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    @typing_extensions.final
+    class TensorMetadata(google.protobuf.message.Message):
+        """metadata for a tensor"""
+
+        DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+        NAME_FIELD_NUMBER: builtins.int
+        DATATYPE_FIELD_NUMBER: builtins.int
+        SHAPE_FIELD_NUMBER: builtins.int
+        name: builtins.str
+        """tensor name"""
+        datatype: builtins.str
+        """tensor data type"""
+        @property
+        def shape(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]:
+            """tensor shape"""
+        def __init__(
+            self,
+            *,
+            name: builtins.str = ...,
+            datatype: builtins.str = ...,
+            shape: collections.abc.Iterable[builtins.int] | None = ...,
+        ) -> None: ...
+        def ClearField(self, field_name: typing_extensions.Literal["datatype", b"datatype", "name", b"name", "shape", b"shape"]) -> None: ...
+
+    NAME_FIELD_NUMBER: builtins.int
+    VERSIONS_FIELD_NUMBER: builtins.int
+    FRAMEWORK_FIELD_NUMBER: builtins.int
+    INPUTS_FIELD_NUMBER: builtins.int
+    OUTPUTS_FIELD_NUMBER: builtins.int
+    name: builtins.str
+    """model name"""
+    @property
+    def versions(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]:
+        """model tag version"""
+    framework: builtins.str
+    """model inference framework"""
+    @property
+    def inputs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelMetadataResponse.TensorMetadata]:
+        """model inputs"""
+    @property
+    def outputs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelMetadataResponse.TensorMetadata]:
+        """model outputs"""
+    def __init__(
+        self,
+        *,
+        name: builtins.str = ...,
+        versions: collections.abc.Iterable[builtins.str] | None = ...,
+        framework: builtins.str = ...,
+        inputs: collections.abc.Iterable[global___ModelMetadataResponse.TensorMetadata] | None = ...,
+        outputs: collections.abc.Iterable[global___ModelMetadataResponse.TensorMetadata] | None = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["framework", b"framework", "inputs", b"inputs", "name", b"name", "outputs", b"outputs", "versions", b"versions"]) -> None: ...
+
+global___ModelMetadataResponse = ModelMetadataResponse
+
+@typing_extensions.final
+class ModelInferRequest(google.protobuf.message.Message):
+    """ModelInferRequest represents a request for model inference"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    @typing_extensions.final
+    class InferRequestedOutputTensor(google.protobuf.message.Message):
+        """An output tensor requested for an inference request."""
+
+        DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+        NAME_FIELD_NUMBER: builtins.int
+        name: builtins.str
+        """tensor name."""
+        def __init__(
+            self,
+            *,
+            name: builtins.str = ...,
+        ) -> None: ...
+        def ClearField(self, field_name: typing_extensions.Literal["name", b"name"]) -> None: ...
+
+    MODEL_NAME_FIELD_NUMBER: builtins.int
+    MODEL_VERSION_FIELD_NUMBER: builtins.int
+    INPUTS_FIELD_NUMBER: builtins.int
+    OUTPUTS_FIELD_NUMBER: builtins.int
+    RAW_INPUT_CONTENTS_FIELD_NUMBER: builtins.int
+    model_name: builtins.str
+    """name of the model to use for inferencing."""
+    model_version: builtins.str
+    """model tag version"""
+    @property
+    def inputs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___InferTensor]:
+        """input tensors for the inference."""
+    @property
+    def outputs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelInferRequest.InferRequestedOutputTensor]:
+        """The requested output tensors for the inference. Optional, if not
+        specified all outputs specified in the model config will be
+        returned.
+        """
+    @property
+    def raw_input_contents(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bytes]:
+        """raw input contents"""
+    def __init__(
+        self,
+        *,
+        model_name: builtins.str = ...,
+        model_version: builtins.str = ...,
+        inputs: collections.abc.Iterable[global___InferTensor] | None = ...,
+        outputs: collections.abc.Iterable[global___ModelInferRequest.InferRequestedOutputTensor] | None = ...,
+        raw_input_contents: collections.abc.Iterable[builtins.bytes] | None = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["inputs", b"inputs", "model_name", b"model_name", "model_version", b"model_version", "outputs", b"outputs", "raw_input_contents", b"raw_input_contents"]) -> None: ...
+
+global___ModelInferRequest = ModelInferRequest
+
+@typing_extensions.final
+class ModelInferResponse(google.protobuf.message.Message):
+    """ModelInferResponse represents a response for model inference"""
+
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    MODEL_NAME_FIELD_NUMBER: builtins.int
+    MODEL_VERSION_FIELD_NUMBER: builtins.int
+    OUTPUTS_FIELD_NUMBER: builtins.int
+    RAW_OUTPUT_CONTENTS_FIELD_NUMBER: builtins.int
+    model_name: builtins.str
+    """name of the model to use for inferencing."""
+    model_version: builtins.str
+    """model tag version"""
+    @property
+    def outputs(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___InferTensor]:
+        """output tensors"""
+    @property
+    def raw_output_contents(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.bytes]:
+        """raw output contents"""
+    def __init__(
+        self,
+        *,
+        model_name: builtins.str = ...,
+        model_version: builtins.str = ...,
+        outputs: collections.abc.Iterable[global___InferTensor] | None = ...,
+        raw_output_contents: collections.abc.Iterable[builtins.bytes] | None = ...,
+    ) -> None: ...
+    def ClearField(self, field_name: typing_extensions.Literal["model_name", b"model_name", "model_version", b"model_version", "outputs", b"outputs", "raw_output_contents", b"raw_output_contents"]) -> None: ...
+
+global___ModelInferResponse = ModelInferResponse