OneX Observability SDK
The OneX SDK provides framework-agnostic utilities to monitor neural signals and export them to the OneX observability platform. It detects popular machine learning frameworks (PyTorch, TensorFlow, JAX) and attaches lightweight instrumentation to running models.
Installation
pip install onex-sdk
Optional extras are available for framework-specific monitoring:
# PyTorch support
pip install onex-sdk[pytorch]
# TensorFlow support
pip install onex-sdk[tensorflow]
# JAX support
pip install onex-sdk[jax]
Quick Start
from onex import OneXMonitor
monitor = OneXMonitor(api_key="your-api-key")
model = monitor.watch(model)
Development
Create a virtual environment and install the development requirements:
pip install -r requirements-dev.txt
Then run the tests with pytest.
Metadata
Release files for onex-sdk 0.1.44
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| onex_sdk-0.1.44.tar.gz | 62.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| onex_sdk-0.1.44-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 119.6 kB
Release files / onex_sdk-0.1.44.tar.gz
| Download URL | onex_sdk-0.1.44.tar.gz |
|---|---|
| Size | 62.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / onex_sdk-0.1.44-py3-none-any.whl
| Download URL | onex_sdk-0.1.44-py3-none-any.whl |
|---|---|
| Size | 57.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.12.9
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Security for onex-sdk 0.1.44
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