Add curator-to-SFT JSONL converter#62
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Add cosmos_framework.scripts.curator_to_sft_jsonl, which converts cosmos-curator splitting-pipeline metas_jsonl output directly into the SFT training JSONL format, applying the same hard filters sft_dataset.py applies silently at train time (duration > 61.0s, per-window frames < 61, optional short-edge) so dataset counts match what training consumes. Emits a sidecar <output>.summary.json with per-reason drop counts and rewrites vision_path relative to the JSONL so datasets stay portable across mounts. Document the path as a new "Create Dataset from a Cosmos-Curator output directory" section in docs/dataset_jsonl.md. Ported from imaginaire4 MR 9217: cosmos3.scripts -> cosmos_framework.scripts, OSS SPDX header, and stale sft_dataset.py line refs corrected to 548-550. Verified: 24/24 tests pass, ruff check/format clean, CLI --help imports. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Add cosmos_framework.scripts.curator_to_sft_jsonl, which converts cosmos-curator splitting-pipeline metas_jsonl output directly into the SFT training JSONL format, applying the same hard filters sft_dataset.py applies silently at train time (duration > 61.0s, per-window frames < 61, optional short-edge) so dataset counts match what training consumes. Emits a sidecar .summary.json with per-reason drop counts and rewrites vision_path relative to the JSONL so datasets stay portable across mounts.
Document the path as a new "Create Dataset from a Cosmos-Curator output directory" section in docs/dataset_jsonl.md.
Ported from imaginaire4 MR 9217: cosmos3.scripts -> cosmos_framework.scripts, OSS SPDX header, and stale sft_dataset.py line refs corrected to 548-550.
Verified: 24/24 tests pass, ruff check/format clean, CLI --help imports.
from MR 9217