Weekly retrain pipeline + hourly accuracy tracking#3
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- scripts/run_full_pipeline.py: single entrypoint that scrapes, retrains all 3 models, predicts next 7 days, and logs each hour. Used by both train_weekly.bat (local Friday) and daily_predict.yml (GH Actions). - train_weekly.bat: Windows one-click wrapper that pulls main, runs the pipeline, then commits and pushes the new models. Designed to be triggered weekly via a Friday 23:00 IST calendar reminder. - .github/workflows/daily_predict.yml: predict-only workflow (no training) that runs daily at 00:30 UTC. Replaces scheduler.yml which is now deprecated to workflow_dispatch only. - prediction_log_hourly table: 24 rows per (date, model) capturing predicted vs actual at hourly granularity. Powers a 6-month org-readable evaluation dashboard. - /api/v1/dashboard/hourly-accuracy: returns per-hour entries plus a hour-of-day rollup of MAPE/MAE/interval coverage. - /api/v1/admin/trigger-pipeline: kicks the GH Actions workflow via workflow_dispatch (needs GITHUB_PAT env var on Render). Wired to a 'Run Daily Pipeline' button in the admin page header. - Refreshed daily and hourly champions on full data through 2026-06-09. Reported CV MAPE: 5-min 0.18%, hourly (XGBoost) 0.52%, daily 2.70%.
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Summary
train_weekly.bat) that scrapes, retrains all 3 models, predicts the next 7 days, commits and pushesdaily_predict.ymlrunning daily 00:30 UTC for predict + log only (no training — fits the free tier)prediction_log_hourlytable +/api/v1/dashboard/hourly-accuracyendpoint for the 6-month org evaluationTraining results (this run, full data through 2026-06-09)
Data refresh
Operating cadence
train_weekly.bat— full retrain, ~15-20 min, auto-commits and pushes new models--no-trainmode — scrape + predict + logSetup required after merge
GITHUB_PAT(a personal access token withworkflowscope) to enable the admin Run-Pipeline button/api/v1/health/readyevery 5 min to keep Render warmTest plan
daily_predict.ymlruns successfully in GH Actions (after merge)GITHUB_PATis set on Render