aiq.front_ends.fastapi.fastapi_front_end_config

Attributes

logger

Classes

AIQEvaluateRequest	Request model for the evaluate endpoint.
AIQEvaluateResponse	Response model for the evaluate endpoint.
AIQEvaluateStatusResponse	Response model for the evaluate status endpoint.
FastApiFrontEndConfig	A FastAPI based front end that allows an AIQ Toolkit workflow to be served as a microservice.

Module Contents

logger

class AIQEvaluateRequest(/, **data: Any)

Bases: pydantic.BaseModel

Request model for the evaluate endpoint.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

config_file: str = None

job_id: str | None = None

reps: int = None

expiry_seconds: int = None

class AIQEvaluateResponse(/, **data: Any)

Bases: pydantic.BaseModel

Response model for the evaluate endpoint.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

job_id: str = None

status: str = None

class AIQEvaluateStatusResponse(/, **data: Any)

Bases: pydantic.BaseModel

Response model for the evaluate status endpoint.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

job_id: str = None

status: str = None

config_file: str = None

error: str | None = None

output_path: str | None = None

created_at: datetime.datetime = None

updated_at: datetime.datetime = None

expires_at: datetime.datetime | None = None

class FastApiFrontEndConfig(/, **data: Any)

Bases: aiq.data_models.front_end.FrontEndBaseConfig

A FastAPI based front end that allows an AIQ Toolkit workflow to be served as a microservice.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

class EndpointBase(/, **data: Any)

Bases: pydantic.BaseModel

method: Literal['GET', 'POST', 'PUT', 'DELETE']

description: str

path: str | None = None

websocket_path: str | None = None

openai_api_path: str | None = None

class Endpoint(/, **data: Any)

Bases: EndpointBase

function_name: str = None

class CrossOriginResourceSharing(/, **data: Any)

Bases: pydantic.BaseModel

allow_origins: list[str] | None = None

allow_origin_regex: str | None = None

allow_methods: list[str] | None = None

allow_headers: list[str] | None = None

allow_credentials: bool | None = None

expose_headers: list[str] | None = None

max_age: int | None = None

root_path: str = None

host: str = None

port: int = None

reload: bool = None

workers: int = None

step_adaptor: aiq.data_models.step_adaptor.StepAdaptorConfig

workflow: Annotated[FastApiFrontEndConfig.EndpointBase, Field(description='Endpoint for the default workflow.')]

evaluate: Annotated[FastApiFrontEndConfig.EndpointBase, Field(description='Endpoint for evaluating workflows.')]

endpoints: list[FastApiFrontEndConfig.Endpoint] = None

cors: FastApiFrontEndConfig.CrossOriginResourceSharing = None

use_gunicorn: bool = None

runner_class: str | None = None