The audit imports the FastAPI app, compares implemented GET/POST/PATCH/ DELETE routes with active API contract headings and tracks the explicit non-envelope exceptions (/health and export downloads). It fails when a route exists without docs or when docs claim an endpoint that is not implemented.

Verify the browser-facing Docker/LAN runtime:

bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202
bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202

Verify the explicit demo workflow plus export artifact path:

bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202

The demo/export smoke is intentionally mutating and idempotent: it seeds the offline fixture demo if needed, verifies the project area GeoJSON, fixture datasets, vector FeatureCollection content, vector feature summary, persisted QA/QC metrics, creates metadata/report/vector GeoJSON exports, lists exports and downloads the JSON/GeoJSON/HTML artifacts through the frontend proxy. The persisted QA/QC result is compared against fixtures/golden/expected_qa_metrics.json so runtime demo precision, recall, F1, mean IoU and false-positive/negative counts cannot drift silently.

Verify that the browser-facing workbench can populate the default demo start state through the frontend proxy:

bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202

This smoke is dependency-light and intentionally idempotent: it seeds the offline demo workflow, then verifies that GeoIntel Demo - Building QA exposes the Demo AOI - Geel buildings map geometry, 2/2 ready demo datasets and a persisted QA/QC result through canonical data.items envelopes. Pair it with a Codex/browser screenshot pass when checking visual layout or overflow.

Verify the backing state for the core workbench interactions:

bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202

This smoke validates the state behind project switching, AOI/map selection, dataset selection, QA refresh and export refresh through the same frontend proxy used by the browser. The frontend also exposes stable data-testid anchors for Codex/browser click checks on those controls.

Verify the deterministic QA/QC golden benchmark:

bash scripts/verify_golden_qa_benchmark.sh
python scripts/run_golden_qa_benchmark.py --json

The benchmark uses only explicit local fixtures under fixtures/golden, executes the existing QA/QC matching logic, verifies the expected precision, recall, F1, mean IoU and false-positive/false-negative counts, and checks that QualityCheck plus Metric rows would be persisted. The main readiness gate runs this benchmark so QA metric drift fails before a release.

Verify a configured local YOLO model without running inference:

python scripts/yolo_preflight.py --model-path /absolute/path/to/model.pt --tile-manifest-path /absolute/path/to/manifest.json --check-model-load --json

Against the Docker runtime:

docker compose exec -T backend python scripts/yolo_preflight.py --model-path /absolute/path/to/model.pt --tile-manifest-path /absolute/path/to/manifest.json --check-model-load --json

The model-load smoke is opt-in, requires real optional AI dependencies, refuses --assume-dependencies, loads only the supplied local file and does not download weights or run prediction.

Clean old offline demo export artifacts without touching uploaded source data:

python scripts/cleanup_demo_artifacts.py
python scripts/cleanup_demo_artifacts.py --keep-latest 10 --export-type project_report_html
python scripts/cleanup_demo_artifacts.py --keep-latest 10 --max-delete 100 --apply

Against the Docker runtime, run the backend-container entrypoint:

docker compose exec -T backend python scripts/cleanup_demo_artifacts.py
docker compose exec -T backend python scripts/cleanup_demo_artifacts.py --keep-latest 10 --export-type project_report_html
docker compose exec -T backend python scripts/cleanup_demo_artifacts.py --keep-latest 10 --max-delete 100 --apply

The cleanup script is dry-run by default. It only targets the explicit GeoIntel Demo - Building QA project unless --project-name is provided, keeps the newest exports per matching project, deletes only exports rows/files when --apply is set, and refuses to remove files outside the configured STORAGE_ROOT. --max-delete defaults to 25 and blocks large cleanup runs until the operator raises it after reviewing dry-run output. Repeat --export-type to limit cleanup to specific artifact kinds such as project_report_html or project_metadata_json.

Verify the cleanup path against a running backend without deleting anything:

bash scripts/verify_demo_cleanup_dry_run.sh
CLEANUP_MODE=compose bash scripts/verify_demo_cleanup_dry_run.sh
CLEANUP_MODE=container CLEANUP_CONTAINER=geointel bash scripts/verify_demo_cleanup_dry_run.sh

The smoke runs the cleanup command without --apply, expects dry_run=true, expects deleted_export_count=0, verifies candidate fields are present and prints the matched/type-filtered/selected counts. Use KEEP_LATEST, MAX_DELETE and EXPORT_TYPE environment variables to adjust the dry-run thresholds without changing the script. The main readiness gate checks this script's syntax; run it explicitly against Docker/PostGIS when validating a live deployment.

Tower deployment

Push the local branch to Gitea, then rebuild the Unraid/Tower Docker runtime:

bash scripts/deploy_tower.sh

From the Codex Windows workspace, use the PowerShell wrapper:

.\scripts\deploy_tower.ps1

For the first deployment into an existing non-Git appdata folder, bootstrap the checkout explicitly:

DEPLOY_BOOTSTRAP=1 bash scripts/deploy_tower.sh

.\scripts\deploy_tower.ps1 -Bootstrap

Useful overrides:

REMOTE_HOST=root@192.168.10.150
REMOTE_PATH=/mnt/user/appdata/geointel
REMOTE_REPO=gitea-widefrog:NuklearRabbit/geointel.git
FRONTEND_URL=http://192.168.10.150:1202