Module: ai_availability_status

Purpose

Thread-safe status tracker for the AI engine lifecycle (downloading, converting, uploading, enabled, warning, error).

Public Interface

Enum: AIAvailabilityEnum

Value	Name	Meaning
0	NONE	Initial state, not yet initialized
10	DOWNLOADING	Model download in progress
20	CONVERTING	ONNX-to-TensorRT conversion in progress
30	UPLOADING	Converted model upload in progress
200	ENABLED	Engine ready for inference
300	WARNING	Operational with warnings
500	ERROR	Failed, not operational

Class: AIAvailabilityStatus

Field	Type	Description
`status`	AIAvailabilityEnum	Current status
`error_message`	str or None	Error/warning details

Method	Signature	Description
`__init__`	`()`	Sets status=NONE, error_message=None
`__str__`	`() -> str`	Thread-safe formatted string: `"StatusText ErrorText"`
`serialize`	`() -> bytes`	Thread-safe msgpack serialization `{s: status, m: error_message}` (legacy — not called in current codebase)
`set_status`	`(AIAvailabilityEnum status, str error_message=None) -> void`	Thread-safe status update; logs via constants_inf (error or info)

Internal Logic

All public methods acquire a threading.Lock before reading/writing status fields. set_status logs the transition: errors go to constants_inf.logerror, normal transitions go to constants_inf.log.

Dependencies

External: msgpack, threading
Internal: constants_inf (logging)

Consumers

inference — creates instance, calls set_status during engine lifecycle, exposes ai_availability_status for health checks
main — reads ai_availability_status via inference for /health endpoint

Data Models

AIAvailabilityEnum — status enum
AIAvailabilityStatus — stateful status holder

Configuration

None.

External Integrations