llms.txt

# PyAutoLens

> PyAutoLens (package `autolens`) is the open-source strong gravitational-lensing modelling library, built on PyAutoGalaxy and using JAX to accelerate lens modelling on GPUs. This file is a signpost: it points you to the right ecosystem resource depending on your intent — use the API, learn lensing, or work on the library itself.

## Use it (examples & tutorials)

- [autolens_workspace navigator](https://github.com/PyAutoLabs/autolens_workspace/blob/main/llms.txt): end-to-end example scripts and notebooks per science case — the paste-friendly task router. Send any "how do I model / simulate / analyse X?" question here.
- [autolens_assistant](https://github.com/PyAutoLabs/autolens_assistant): the PyAutoLens AI assistant — task skills, curated API reference, and a science wiki in one repo you drive by conversation (browser chat via a GitHub connector, or a local coding agent); start from its `llms.txt` front door.
- [HowToLens](https://github.com/PyAutoLabs/HowToLens): from-first-principles lecture series for beginners new to gravitational lensing.

## API reference & docs

- [PyAutoLens documentation (ReadTheDocs)](https://pyautolens.readthedocs.io/en/latest/): API reference, feature overviews, and the installation guide.

## Work on PyAutoLens itself (contributors / coding agents)

- [AGENTS.md](./AGENTS.md): build, tests, architecture, and the JAX / decorator conventions.

## Ecosystem (libraries this builds on)

- [PyAutoGalaxy](https://github.com/PyAutoLabs/PyAutoGalaxy), [PyAutoArray](https://github.com/PyAutoLabs/PyAutoArray), [PyAutoFit](https://github.com/PyAutoLabs/PyAutoFit), [PyAutoNerves](https://github.com/PyAutoLabs/PyAutoNerves): the upstream layers PyAutoLens is built on.