pyproject declares posix-sdc[hub]; Pipfile [packages] pulls posix-sdc from the private index and [dev-packages] from git develop; Pipfile.lock committed and consistent; tree clean after commit.
sft.load_turns(data, hub, revision) yields turns from a raw rollout dir (keep-filtered), a curated .jsonl file, or the published corpus via posix-sdc load_trajectories (lazy import; Hub fallback) - verified the hub path yields all 787 trajectories via the editable checkout's data/; sekft-train gains --hub/--revision and dispatches --data by dir-vs-.jsonl; train()+inspect() use it; 9 tests pass (3 new for raw-dir/jsonl/reject); mypy strict clean (5 files). No submodule changes.
sft.load_turns(data, hub, revision) yields turns from a raw rollout dir (keep-filtered), a curated .jsonl file, or the published corpus via posix-sdc load_trajectories (Hub fallback), imported lazily; sekft-train gains --hub and --revision and dispatches --data by dir-vs-.jsonl; train() and inspect() use it; unit tests cover the raw-dir and jsonl paths; existing tests stay green; mypy strict clean.
bool() wraps the operate_rate predicate in eval.py and resident.py so the sum counts cleanly-operated trajectories without summing None; mypy strict clean across the whole package (5 files); 6 tests pass.
operate_rate in eval.py and resident.py wraps the steps>0 and meta.get('clean') predicate in bool() so the sum counts cleanly-operated trajectories without summing None; mypy strict clean across the whole package (5 files); tests pass.
sekft-train logs run config and each phase (tokenizer/model load, build, training, save) via a sekft.train logger to stderr; -v/--verbose and -q/--quiet added; dataset accounting reports keepers->usable with over-length/empty-mask drop counts and a warning; build loop logs per-trajectory (debug) and every 100 (info); transformers verbosity raised so the per-step curve shows; inspect() logs likewise; 6 tests pass; mypy strict clean on sft.py + _log.py (verified loop logging fires with FakeTok). No submodule changes.
sekft-train logs run config and each phase (tokenizer load, model load, training, save) via a module logger to stderr; -v/--verbose and -q/--quiet control level; dataset accounting reports keepers->usable with counts dropped for length and empty-mask and warns when any are dropped; transformers verbosity raised so the per-step curve shows during training; inspect() logs likewise; existing sft tests stay green; mypy strict clean.
mypy --strict src tests passes (no issues, 6 files); ML/posix-sdc imports ignored via overrides; sft/eval/resident/tests fully annotated; mypy is a declared dev dep; py.typed ships in the package.
README describes the trainer/eval/resident, the posix-sdc dependency, install via the gpu extra, the chat-template render contract, and console-script usage; module docstrings reference sekft-train/eval/resident and apply_chat_template, not the old flat scripts.
tests/unit and tests/smoke pass under pytest; the mask test proves assistant-only training and raises on non-additive templates; entry-point smoke tests pass without torch.
Resident loads the base once; fit trains an adapter and unloads it; evaluate attaches an adapter (or the base baseline) and renders via the shared chat-template canonicalisation.
eval reuses the posix-sdc rollout with a local operator; renders via apply_chat_template + normalize_for_template; reports command-mode, terminate, and verified rates over held-out scenarios.
sft renders via apply_chat_template; normalize_for_template folds system and merges consecutive turns; the loss mask trains assistant turns only and raises on a non-additive template; --inspect reports mask stats.
tiararodney.sekft imports; sekft-train/eval/resident console scripts resolve; pyproject declares posix-sdc as a dependency with torch et al. behind a gpu extra; Pipfile carries the local editable posix-sdc override; tox envs exist.
