OpenInference Build

The build action builds a container image for an openinference function. A Task is created by calling run() on the Function; task parameters are passed through that call.

Overview

OpenInference functions are specialized Python handlers for inference workloads. They declare model metadata and tensor schemas as part of the function specification. The build action creates an image containing the inference handler and its dependencies.

Quick example

function = dh.new_function(
    name="my-openinference-function",
    kind="openinference",
    code_src="inference.py",
    handler="predict",
    python_version="PYTHON3_10",
    model_name="text-classifier",
    inputs=[{"name": "input-0", "shape": [-1], "datatype": "BYTES"}],
    outputs=[{"name": "output-0", "shape": [-1], "datatype": "FP32"}]
)

run = function.run(
    action="build",
    instructions=["pip install transformers"]
)

Parameters

Function Parameters

Must be specified when creating the function.

Name	Type	Description
project	str	Project name. Required only when creating from the library; otherwise MUST NOT be set.
name	str	Name that identifies the object. Required.
kind	str	Function kind. Must be openinference. Required.
uuid	str	Object ID in UUID4 format.
description	str	Description of the object.
labels	list[str]	List of labels.
embedded	bool	Whether the object should be embedded in the project.
code_src	str	URI pointing to the source code.
code	str	Source code provided as plain text.
base64	str	Source code encoded as base64.
handler	str	Function entrypoint.
init_function	str	Init function name for remote execution.
python_version	str	Python version to use. Required.
lang	str	Source code language (informational).
image	str	Container image used to execute the function.
base_image	str	Base image (name:tag) used to build the execution image.
requirements	list	List of pip requirements to install into the execution image.
model_name	str	Logical model name exposed by the function.
inputs	list[dict]	Tensor definitions for the request payload.
outputs	list[dict]	Tensor definitions for the response payload.

Python Versions

The Python runtime supports versions 3.10, 3.11, 3.12, and 3.13 expressed as:

• PYTHON3_10
• PYTHON3_11
• PYTHON3_12
• PYTHON3_13

Init Function

The init function is the entrypoint used by the Nuclio init wrapper. Specify the init function name via the init_function parameter.

Base Image

The base image is the image (name:tag) used as the foundation when building the execution image for the function.

Requirements

Requirements are a list of strings representing packages to be installed by pip in the image where the function will be executed.

Tensor Schema

Each item in inputs and outputs is a tensor definition with the following fields:

Field	Type	Description
name	str	Tensor name.
shape	list[int]	Tensor shape.
datatype	str	Tensor datatype. Defaults to FP32.

Supported tensor datatypes are: BOOL, BYTES, UINT8, INT8, UINT16, INT16, UINT32, INT32, UINT64, INT64, FP16, FP32, and FP64.

Task Parameters

Can only be specified when calling function.run().

Name	Type	Description
action	str	Task action. Required. Must be build
volumes	list[dict]	List of volumes.
resources	dict	Resource limits/requests.
envs	list[dict]	Environment variables.
secrets	list[str]	List of secret names.
profile	str	Profile template.
instructions	list[str]	Additional build instructions.

Run Parameters

Can only be specified when calling function.run().

Name	Type	Description
init_parameters	dict	Parameters supplied to the init function.