Research-0697: MOS Corpus Adapter Manifests¶
Question¶
Which remaining MOS-corpus source adapters still produce durable JSONL shards without replayable input/output evidence, and what is the smallest contract that makes those shards usable as model-card evidence?
Findings¶
The downstream AI pipeline already had provenance sidecars for training reports, derived feature tables, aggregate/merge JSONL outputs, and several legacy trainer-input builders. The source MOS adapters were the weak boundary: CHUG, KoNViD, YouTube-UGC, LSVQ, LIVE-VQC, and Waterloo-IVC rows could be generated from local dataset roots, manifest CSVs, row caps, and resumable progress files, but the emitted JSONL did not preserve those run-level choices.
That matters more than normal file metadata. The same output path can represent a capped smoke subset, a full-corpus run, or a rerun after download attrition changed. Later MOS-head training, signal-mix audits, and model cards need the adapter-level counters before aggregation normalises scales or deduplicates rows.
Decision Drivers¶
- Keep row schemas stable; run-level evidence belongs beside the JSONL, not in every row.
- Reuse ADR-0661
run_provenanceso corpus source sidecars look like the rest of the AI evidence chain. - Make the sidecar automatic with
<output>.manifest.json, but expose--manifest-outfor dated experiment bundles. - Cover the full source-adapter family in one batch so mixed-corpus training does not have partial provenance.
Implementation Notes¶
ai/src/corpus/base.py now owns write_ingest_manifest(). Adapters pass their effective input paths, output paths, row caps, corpus version, and run counters into that helper after a successful JSONL run. Tests cover the shared helper and the CHUG CLI default sidecar; existing adapter tests continue to exercise row compatibility.
Follow-Up¶
Regenerate local CHUG, KoNViD, YouTube-UGC, LSVQ, LIVE-VQC, and Waterloo-IVC JSONL shards before using them as promoted MOS-head training evidence, and keep the generated sidecars with the gitignored corpus outputs.