ai-box-lib 0.1.9

Python library for NXP Edge AI Industrial Platform

AI Box Library

Python library for the NXP Edge AI Industrial Platform.

Overview

ai-box-lib provides thin clients for component-to-component communication:

• DataCollectorClient for publishing collector payloads
• PreProcessorClient for subscribing collector payloads and publishing features
• ContextEngineClient for publishing context messages

Installation

Install from PyPI:

pip install ai-box-lib

Quick Start

1) Publish data from a data collector

from ai_box_lib.data_collector_client import DataCollectorClient

client = DataCollectorClient[dict]()
client.connect()
client.publish_timestream({"random_number": "42"})

2) Subscribe and publish from a pre-processor

from ai_box_lib.pre_processor_client import PreProcessorClient

client = PreProcessorClient[dict, dict]()
client.connect()

def handle_raw(message: dict) -> None:
	processed = {"feature_a": [1.0, 2.0, 3.0]}
	client.publish_data(processed)

unsubscribe = client.subscribe_timestream(handle_raw)

3) Publish context output

from ai_box_lib.context_engine_client import ContextEngineClient

client = ContextEngineClient[dict]()
client.connect()
client.publish_data({"state": "ok"})

API Summary

• DataCollectorClient.publish_timestream(data)
• DataCollectorClient.publish_audio(data)
• PreProcessorClient.subscribe_timestream(handler)
• PreProcessorClient.subscribe_audio(handler)
• PreProcessorClient.publish_data(data)
• ContextEngineClient.publish_data(data)

Validation and Limits

• Clients must call connect() before publish/subscribe operations.
• DataCollectorClient validates message keys against CHANNELS.
• PreProcessorClient validates feature keys and feature shapes against FEATURES.
• Maximum publish payload size is 2 MB.

License

See LICENSE.