> ## Documentation Index
> Fetch the complete documentation index at: https://docs.withwhile.com/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Install with `pip install whileai`; import as `import whileai as wai`.
> Run the offline path first (`simulator=False`, `wai.seeded_agent`, a callable judge); no key is needed for it.
> Report every pass rate with its interval and n, as `scored.pass_at` prints it.

# Constitution

> What whileai is, what we believe, and where each belief is enforced in the code. Read it before you add a public name, write a page, or run a recipe.

What `whileai` is, what we believe, and how that shows up in the code.
Read it before you add a public name, write a page, or run a recipe. The
routines that maintain the repository read it too. The text of record is
[CONSTITUTION.md](https://github.com/whilehq/whileai-sdk/blob/main/CONSTITUTION.md).

## What we are

`whileai` is a scientific post-training library for language models: SFT
and RL, on open models, with the measurement that says whether training
helped. Simulate, grade, measure with intervals, select, train, prove on a
held-out set, serve, and feed the new traces back in. Build self-improving
systems.

It is for AI researchers, ML engineers and applied-AI developers, and the
goal is that it sits in every applied-AI and research department the way
PyTorch does. The platform (`whileai.platform`) is a separate, optional
service for hosted training and serving. The library needs no account.

## What we believe

<Steps>
  <Step title="Repeatable science">
    A number is a result only with its interval, its noise floor, its seed
    and the versions that produced it. A mean alone is not a result. A flat
    result is a result. (`pass_at`, `eval_variance`, `delta_report`,
    `holdout_size`.)
  </Step>

  <Step title="Replicated papers are the proof">
    We show the library works by reproducing recent post-training research
    in it, one recipe per paper, under an hour on one GPU, with the number
    it moved and the number it did not. Every reproduced paper is a post.
    The proof point is the recipe, not the pitch. (`recipes/papers/`.)
  </Step>

  <Step title="The book is the map, the paper is the citation">
    Every default is named, sourced and tunable from the call.
    [rlhfbook.com](https://rlhfbook.com) (Lambert) is the map of the
    field; the originating paper is the reference. A default with no
    source says "convention, untested". (`defaults.py`,
    `scripts/check_no_hardcoding.py`.)
  </Step>

  <Step title="Bring your own keys">
    Your models, your compute, your accounts. Modal and Prime Intellect are
    first-class: a `whileai` environment becomes a `verifiers` environment
    and back, selected rows become a trainer's prompt set, eval results
    flow back into measurement with intervals. Nothing in the loop requires
    our hosting.
  </Step>

  <Step title="Developer ergonomics are the product">
    The code reads like PyTorch, DSPy and Unsloth: one import, objects
    carry configuration, calls carry data, reports print themselves, errors
    name the fix, and a first-time reader can guess the next line. Rigor
    lives behind a default, never behind a flag. ([Style](/reference/style),
    the ratchet test.)
  </Step>

  <Step title="Plain words, then the mechanism, then the proof">
    Every page, every docstring, every README section in that order. Book
    vocabulary stays in the docstring that cites the chapter, never in a
    public name.
  </Step>

  <Step title="Mass experimentation">
    A PhD or an engineer runs many experiments from one import, on their
    own compute, and every run leaves a record that a person can decide
    from.
  </Step>

  <Step title="Never big-bang">
    The internals carry the science and the tests. Change the front door,
    migrate callers mechanically, keep the old name working for one release
    with a warning that says the new one.
  </Step>
</Steps>

## How it shows up

| Belief              | Where it is enforced                                                                                                                                                    |
| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Repeatable science  | `recipes/papers/check.py` refuses "moved" without an interval that excludes zero, three base re-runs, a clean holdout, and a proxy-vs-target verdict                    |
| Replicated papers   | `recipes/papers/README.md`: one paper, one recipe, one command, one `post.md`                                                                                           |
| Sourced defaults    | `scripts/check_no_hardcoding.py` in CI; `tests/api/test_readme_defaults.py`                                                                                             |
| Ergonomics          | [Style](/reference/style); `tests/api/test_style_ratchet.py` pins the retired shapes                                                                                    |
| Docs order          | This site; the docs routine's one PR a day                                                                                                                              |
| Bring your own keys | `wai.configure(agent=, judge=, api_key=)`, backend objects whose repr names the key source; the Modal and Prime Intellect researcher routines run on their own accounts |

## Who reads this

People: contributors, before their first public name. Agents: the style
guide routine, the docs and site routines, the paper recipes routine, and
the researcher routines, at the top of every run. When this file and
another file disagree, this file wins and the other file gets a PR.