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feat: add candle time-sort and duplicate timestamp validation to POST /predict

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Sort incoming candles by their time field in ascending chronological order
before processing to ensure correct feature engineering regardless of input
order. Also validate that no duplicate timestamps are present, returning
HTTP 400 with details if duplicates are found.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Marko Djordjevic 2026-02-18 11:28:02 +01:00
parent ff952aa083
commit d75b05b585
2 changed files with 16 additions and 3 deletions
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2
openspec/changes/code-review-fix/tasks.md
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@ -45,7 +45,7 @@
- [x] 5.2 `[opus]` Add SHA256 model integrity check: create `models/checksums.sha256` manifest, verify hash before `joblib.load()` in `services/ml/app/main.py:266`
- [x] 5.3 `[sonnet]` Add `_model_swap_lock` to prediction reads (not just writes) in `services/ml/app/main.py` for thread-safe model access
- [x] 5.4 `[sonnet]` Add date range validation (max 1 year) to `POST /predict/batch` in `services/ml/app/main.py`
- [ ] 5.5 `[sonnet]` Add candle time-sort validation/auto-sort to `POST /predict` in `services/ml/app/main.py`
- [x] 5.5 `[sonnet]` Add candle time-sort validation/auto-sort to `POST /predict` in `services/ml/app/main.py`
- [ ] 5.6 `[sonnet]` Implement real health checks: `SELECT 1` for PostgreSQL, MLflow API ping in `services/ml/app/main.py:396-409`
- [ ] 5.7 `[sonnet]` Add training resource limits: 500MB dataset size check, 30-minute timeout with status update on expiry in `services/ml/app/main.py:907-1030`
- [ ] 5.8 `[haiku]` Add `run_id` format validation to `DELETE /training/runs/{run_id}` and `GET /training/runs/{run_id}` endpoints