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.
iter_keepers read only raw per-trajectory .json -- one of three input shapes.
Add load_turns(data, hub, revision) yielding assistant-bearing turns from a raw
rollout dir (keep-filtered), a curated .jsonl corpus (one record per line), or
the published corpus via posix-sdc's load_trajectories (the in-repo data/ of a
checkout, else the Hugging Face Hub). sekft-train gains --hub and --revision and
dispatches --data by dir-vs-.jsonl; train() and inspect() use it.
Raw-rollout reading stays sekft-local; curated + Hub reuse posix-sdc's loader,
imported lazily so the raw/jsonl paths need neither posix-sdc nor huggingface_hub
installed. Unit tests cover the raw-dir and jsonl dispatch.
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.
sum(t.steps > 0 and t.meta.get("clean") for t in rows) yields the right operand
of `and` when steps>0, so a trajectory whose meta lacks the "clean" key
contributes None and sum() raises TypeError. Wrap the predicate in bool() so it
counts trajectories that operated and are clean. Surfaced by mypy once posix-sdc
began shipping py.typed (Trajectory is now typed).
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.
The trainer was nearly silent: outside an example count and a save line it
printed nothing through tokenizer load, the base-model load, example building, or
the training loop, and trajectories dropped for length or empty mask vanished
without a trace.
Add _log.py (a shared stderr logging setup so stdout stays clean for results)
and a module logger. sekft-train gains -v/--verbose and -q/--quiet. Log the run
config and each phase; report dataset accounting (keepers -> usable, with counts
dropped for over-length and empty-mask and a warning when any are dropped);
inside the build loop, a per-trajectory debug line and a progress line every 100;
raise transformers' verbosity during training so the per-step curve shows. Prints
in train() and inspect() are routed through the logger.
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.
