llms.txt

# PyAutoFit

> PyAutoFit (package `autofit`) is a probabilistic programming library for model composition and non-linear search / Bayesian inference — `af.Model`/`af.Collection`, the `af.Analysis` interface, MCMC / nested-sampling / MLE searches, and a results aggregator and database. This file is a signpost: it points you to the right resource by intent — use the API, learn it, or work on the library itself.

## Use it (examples & tutorials)

- [autofit_workspace navigator](https://github.com/PyAutoLabs/autofit_workspace/blob/main/llms.txt): end-to-end example scripts and notebooks per task — the paste-friendly task router. Send any "how do I compose a model / run a search / inspect results?" question here.
- [HowToFit](https://github.com/PyAutoLabs/HowToFit): from-first-principles lecture series on model fitting and Bayesian inference.

## API reference & docs

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

## Work on it (contributors / coding agents)

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

## Ecosystem

- Built on PyAutoNerves (config); used by PyAutoGalaxy and PyAutoLens, which build `Analysis` subclasses on it.