Getting started
Core concepts, projects, and how authentication works with project API keys.
Labelty documentation
Label data, train models, and ship inference APIs — from your first project to production.
What you can learn here
Section titled “What you can learn here”These docs are written for someone who has never used Labelty before. Follow them in order, or jump to the area you need.
Python SDK
Install labelty-sdk, connect with an API key, manage assets, models, and predictions.
Training
Preview a dataset, start a SageMaker training run, monitor metrics, and build an inference package.
Inference workflows
Deploy a Python workflow and call a synchronous REST run API with an image.
Notebooks
Open a per-project SageMaker JupyterLab space with the SDK already wired in.
Reference
Environment variables, troubleshooting tables, and known documentation gaps.
Recommended path for a new developer
Section titled “Recommended path for a new developer”- Read What is Labelty? and Core concepts.
- Create a project API key.
- Install and connect with the Python SDK.
- Label data in the web app (or via the SDK), then train a model.
- Either open a notebook for experimentation, or deploy a workflow for production inference.