release(1.0.0): add changelog

First release: the trainer (assistant-only mask, train=serve render), the
three-source data loader (raw dir / curated jsonl / Hub), eval, resident, and
structured logging. Packaged, typed, [gpu] extra, depends on posix-sdc[hub].
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# Changelog
All notable changes to sekft, the shell-operator SFT trainer behind the
[posix-sdc](https://huggingface.co/datasets/tiararodney/posix-sdc) experiment,
are documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and the project follows [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [1.0.0] - 2026-06-18
First release: the training and evaluation pipeline that turns posix-sdc
trajectories into a fine-tuned shell operator.
### Added
- `sekft-train`: LoRA / QLoRA supervised fine-tuning of a base model on
shell-operation trajectories, with an **assistant-only loss mask** derived by
token-prefix differencing — the commands and the terminal `exit` / `panic`
token are trained; the environment turns (orientation, prompts, command
output) are masked to `-100`. The render uses the tokenizer's own
`apply_chat_template`, so training matches what the serving harness sends
(train = serve), with `normalize_for_template` canonicalising trajectories for
instruct templates that have no system role and require strict user/assistant
alternation.
- Three sources of training data: a directory of raw rollout `.json`
(keep-filtered), a curated `.jsonl` corpus, or the published posix-sdc corpus
over the Hugging Face Hub (`--hub`).
- `--inspect` for mask and token statistics without training, and structured
stderr logging across every phase (`-v` / `-q`): per-trajectory and progress
lines while the corpus is tokenized, dataset accounting that warns on dropped
(over-length / empty-mask) trajectories, and the per-step training curve.
- `sekft-eval`: behavioural evaluation that drops the tuned model into held-out
scenarios with no scaffold and scores whether it operates and terminates.
- `sekft-resident`: a resident-base harness that loads the base model once and
fits several adapters without reloading, for paired / STaR-style runs.
- Packaging: the `tiararodney.sekft` namespace package with `sekft-train`,
`sekft-eval`, and `sekft-resident` console scripts; a typed (`py.typed`),
mypy-strict codebase; an optional `[gpu]` extra (torch / transformers / peft);
and a dependency on `posix-sdc[hub]`. Released under GPL-2.0.
[1.0.0]: https://git.code.tiararodney.com/tiara/sekft/releases/tag/v1.0.0