feat(ml): add date range validation to POST /predict/batch
- Parse start_date and end_date as datetime objects - Return HTTP 400 if end_date is before start_date - Return HTTP 400 if date range exceeds 365 days (1 year) Closes task 5.4 in code-review-fix tasks. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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- [x] 5.1 `[sonnet]` Replace `error.message` / traceback details with generic `"Internal server error"` in FastAPI exception handlers at lines 640, 778, 1091, 1134, 1199, 1296 of `services/ml/app/main.py`
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- [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`
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- [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
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- [ ] 5.4 `[sonnet]` Add date range validation (max 1 year) to `POST /predict/batch` in `services/ml/app/main.py`
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- [x] 5.4 `[sonnet]` Add date range validation (max 1 year) to `POST /predict/batch` in `services/ml/app/main.py`
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- [ ] 5.5 `[sonnet]` Add candle time-sort validation/auto-sort to `POST /predict` in `services/ml/app/main.py`
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- [ ] 5.6 `[sonnet]` Implement real health checks: `SELECT 1` for PostgreSQL, MLflow API ping in `services/ml/app/main.py:396-409`
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- [ ] 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`
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