bvandeusen
22cdf0f334
Switch every prediction READER off the JSON column onto the normalized
image_prediction table. Parity by construction: each reader loads the same
{raw_name: {category, confidence}} dict it consumed before (via small
_load_predictions helpers), so all downstream threshold/alias/merge/consensus
logic is byte-identical — only the data source changed.
- suggestions.SuggestionService.for_image (and for_selection via it)
- ml.apply_allowlist_tags (iterates images that have prediction rows)
- importer re-import reset deletes the image's prediction rows
The tagger_predictions JSON column is still dual-written (step 1) so it stays
valid during transition; the backfill task's NULL check still works. Removing
the JSON write + DROP column + retiring the #764 prune is the cleanup
follow-up (needs a quiesced-worker window for the DROP lock).
Tests: shared tests/_prediction_helpers.seed_predictions seeds the table;
read-path tests (suggestions, bulk consensus, allowlist apply, API) seed there
instead of ImageRecord.tagger_predictions.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
22 lines
796 B
Python
22 lines
796 B
Python
"""#768 test helper: seed image_prediction rows.
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Read-path tests used to seed ImageRecord(tagger_predictions={...}); predictions
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now live in the normalized image_prediction table, so seed there instead.
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"""
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from backend.app.models import ImagePrediction
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async def seed_predictions(session, image_id: int, predictions: dict) -> None:
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"""Insert image_prediction rows from a {raw_name: {category, confidence}}
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dict (the old JSON shape). Caller commits/flushes as needed; this flushes."""
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session.add_all([
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ImagePrediction(
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image_record_id=image_id,
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raw_name=name,
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category=p.get("category", "general"),
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score=float(p.get("confidence", 0.0)),
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)
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for name, p in predictions.items()
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])
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await session.flush()
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