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chore(repo): retire duplicate nested source mirror

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Jens
2026-08-30 05:59:32 +02:00
parent d39816a4ca
commit b93d926b94
1157 changed files with 108 additions and 209568 deletions
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.gitignore
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@@ -4,6 +4,8 @@ __pycache__/
.venv/
venv/
.env
.env.*
!.env.example
*.egg-info/
.pytest_cache/
.ruff_cache/
@@ -35,6 +37,9 @@ build/
!/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/**
!/artifacts/evidence/accuracy/P2/
!/artifacts/evidence/accuracy/P2/**
!/artifacts/evidence/accuracy/model-training/
/artifacts/evidence/accuracy/model-training/*
!/artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json
/.cache/
/datasets/raw/*
/datasets/processed/*
backend/tests/test_repository_layout.py
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@@ -0,0 +1,25 @@
from __future__ import annotations
import importlib.util
from pathlib import Path
ROOT = Path(__file__).resolve().parents[2]
SCRIPT = ROOT / "scripts" / "verify_repository_layout.py"
SPEC = importlib.util.spec_from_file_location("verify_repository_layout", SCRIPT)
assert SPEC and SPEC.loader
MODULE = importlib.util.module_from_spec(SPEC)
SPEC.loader.exec_module(MODULE)
def test_nested_repository_mirror_is_absent() -> None:
assert MODULE.nested_mirror_markers(ROOT) == []
def test_nested_repository_mirror_is_detected(tmp_path: Path) -> None:
for marker in MODULE.CANONICAL_MARKERS:
path = tmp_path / "geointel" / marker
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text("fixture", encoding="utf-8")
assert MODULE.nested_mirror_markers(tmp_path) == list(MODULE.CANONICAL_MARKERS)
docs/accuracy-program/13-nested-mirror-retirement.md
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@@ -0,0 +1,33 @@
# Retirement of the tracked `geointel/` mirror
## Decision
The repository root is the only canonical GeoIntel source tree. The stale,
tracked copy below `geointel/` was removed during the full-platform remediation
because it duplicated backend, frontend, scripts, tests and documentation and
could make local tools inspect or execute the wrong implementation.
## Recovery evidence
- Source commit: `d39816a4ca1a23a7b90bcf01e5f2b01fd5fb57c4`.
- Source tree object: `b66d5987f7e2b1f8180acd3b4c768586993c7d5a`.
- Tracked files: `1,153`.
- The two mirror-only PNG assets remain recoverable from that immutable Git
commit; the canonical frontend already contains the current SVG/PNG/WebP
icon and wordmark assets used by the application.
- Recovery command, if historical inspection is required:
`git restore --source d39816a4ca1a23a7b90bcf01e5f2b01fd5fb57c4 -- geointel`.
The migration deletes no production data, model weights, source datasets or
runtime storage. After the tracked mirror was retired, 207 untracked runtime
files (about 0.04 GiB) remained below that directory. They were moved intact,
without content rewriting, to the ignored recovery directory
`.codex-artifacts/retired-nested-runtime-20260830/`. Nothing from that recovery
directory is packaged or deployed. Docker already excluded the former mirror,
so production runtime paths remain unchanged.
## Prevention gate
`python scripts/verify_repository_layout.py` fails when canonical source
markers appear under a new nested `geointel/` directory. The release-readiness
workflow runs this check so repository ambiguity cannot silently return.
geointel/.dockerignore
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@@ -1,23 +0,0 @@
.git
.venv
venv
__pycache__
*.pyc
.pytest_cache
frontend/node_modules
frontend/dist
frontend/*.tsbuildinfo
backend/.pytest_cache
backend/**/*.pyc
backend/**/__pycache__
storage
postgres-data
datasets/raw
datasets/processed
datasets/cache
exports
models
.env
geointel/.env.example
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@@ -1,173 +0,0 @@
# Backend
GEOINTEL_ENV=development
GEOINTEL_API_PREFIX=/api/v1
DATABASE_URL=postgresql+psycopg://geointel:geointel@localhost:5432/geointel?connect_timeout=1
STORAGE_ROOT=./storage
MAX_UPLOAD_MB=500
CORS_ORIGINS=http://localhost:1202,http://127.0.0.1:1202
# Optional single-operator access gate. Store only a PBKDF2-SHA256 hash and
# a unique 32+ character signing secret. Guest access requires this gate and
# should be enabled only on a dedicated demo-safe instance.
GEOINTEL_AUTH_ENABLED=false
GEOINTEL_AUTH_USERNAME=
GEOINTEL_AUTH_PASSWORD_HASH=
GEOINTEL_AUTH_SESSION_SECRET=
GEOINTEL_AUTH_SESSION_TTL_SECONDS=43200
GEOINTEL_GUEST_ACCESS_ENABLED=false
GEOINTEL_GUEST_DISPLAY_NAME=Gast
GEOINTEL_GUEST_SESSION_TTL_SECONDS=7200
ORTHOPHOTO_ENABLED=true
ORTHOPHOTO_WMS_URL=https://geo.api.vlaanderen.be/OMWRGBMRVL/wms
SPW_ORTHOPHOTO_WMS_URL=https://geoservices.wallonie.be/arcgis/services/IMAGERIE/ORTHO_LAST/MapServer/WMSServer
BRUSSELS_ORTHOPHOTO_WMS_URL=https://geoservices-grid.irisnet.be/geoserver/urbisgrid/ows
ORTHOPHOTO_WMS_LAYER=Ortho
ORTHOPHOTO_RESOLUTION_M=1.0
ORTHOPHOTO_MIN_SIDE_M=128
ORTHOPHOTO_MAX_SIDE_M=1024
ORTHOPHOTO_CACHE_TTL_HOURS=24
SOURCE_CATALOG_PROBE_ENABLED=true
SOURCE_CATALOG_GRB_WFS_URL=https://geo.api.vlaanderen.be/GRB/wfs
GRB_ENABLED=true
GRB_OGC_API_URL=https://geo.api.vlaanderen.be/GRB/ogc/features/v1
GRB_MIN_SIDE_M=10
GRB_MAX_SIDE_M=20000
GRB_PAGE_SIZE=1000
GRB_MAX_PAGES=200
GRB_MAX_FEATURES=150000
GRB_TIMEOUT_SECONDS=180
GRB_MAX_RESPONSE_MB=20
GRB_MAX_TOTAL_RESPONSE_MB=256
GRB_CACHE_TTL_HOURS=24
OFFICIAL_VECTOR_ENABLED=true
BWK_WFS_URL=https://geo.api.vlaanderen.be/BWK/wfs
DOV_SOIL_WFS_URL=https://www.dov.vlaanderen.be/geoserver/wfs
SPW_PICC_ENABLED=true
SPW_PICC_MAPSERVER_URL=https://geoservices.wallonie.be/arcgis/rest/services/TOPOGRAPHIE/PICC_VDIFF/MapServer
SPW_FLOOD_HAZARD_ENABLED=true
SPW_FLOOD_HAZARD_MAPSERVER_URL=https://geoservices.wallonie.be/arcgis/rest/services/EAU/ALEA_INOND/MapServer
URBIS_ENABLED=true
URBIS_WFS_URL=https://geoservices-vector.irisnet.be/geoserver/urbisvector/ows
OFFICIAL_VECTOR_MIN_SIDE_M=10
OFFICIAL_VECTOR_MAX_SIDE_M=20000
OFFICIAL_VECTOR_PAGE_SIZE=1000
OFFICIAL_VECTOR_MAX_PAGES=200
OFFICIAL_VECTOR_MAX_FEATURES=100000
OFFICIAL_VECTOR_TIMEOUT_SECONDS=180
OFFICIAL_VECTOR_MAX_RESPONSE_MB=20
OFFICIAL_VECTOR_MAX_TOTAL_RESPONSE_MB=256
OFFICIAL_VECTOR_CACHE_TTL_HOURS=24
SOURCE_CATALOG_STATBEL_DCAT_URL=https://doc.statbel.be/publications/DCAT/DCAT_opendata_datasets.ttl
SOURCE_CATALOG_STATBEL_MAX_RESPONSE_MB=5
SOURCE_CATALOG_ALZ_RELEASE_URL=https://landbouwcijfers.vlaanderen.be/open-geodata-landbouwgebruikspercelen
SOURCE_CATALOG_PROBE_TIMEOUT_SECONDS=10
SOURCE_CATALOG_PROBE_MAX_RESPONSE_MB=2
SOURCE_CATALOG_PROBE_CACHE_TTL_SECONDS=900
DHMV_ENABLED=true
DHMV_WCS_URL=https://geo.api.vlaanderen.be/DHMV/wcs
DHMV_RESOLUTION_M=5.0
DHMV_MIN_SIDE_M=10
DHMV_MAX_SIDE_M=20000
DHMV_MAX_PIXELS=12000000
DHMV_TIMEOUT_SECONDS=300
DHMV_MAX_RESPONSE_MB=160
FLOOD_HAZARD_ENABLED=true
FLOOD_HAZARD_WCS_URL=https://geoservice.waterinfo.be/OGRK/wcs
FLOOD_HAZARD_RESOLUTION_M=5.0
FLOOD_HAZARD_MIN_SIDE_M=10
FLOOD_HAZARD_MAX_SIDE_M=20000
FLOOD_HAZARD_MAX_PIXELS=12000000
FLOOD_HAZARD_TIMEOUT_SECONDS=300
FLOOD_HAZARD_MAX_RESPONSE_MB=160
BATHYMETRY_PROFILES_ENABLED=true
BATHYMETRY_PROFILES_LAYER_URL=https://vha.waterinfo.be/arcgis/rest/services/digitale_atlas/MapServer/0
BATHYMETRY_WATERCOURSE_LAYER_URL=https://vha.waterinfo.be/arcgis/rest/services/digitale_atlas/MapServer/1
BATHYMETRY_PROFILES_PAGE_SIZE=1000
BATHYMETRY_PROFILES_MAX_FEATURES=50000
BATHYMETRY_PROFILES_TIMEOUT_SECONDS=120
BATHYMETRY_PROFILES_MAX_RESPONSE_MB=32
MDK_BATHYMETRY_PROBE_ENABLED=true
MDK_BATHYMETRY_WCS_URL=https://bathy.agentschapmdk.be/spatialfusionserver/services/ows/wcs/EL_wcs
MDK_BATHYMETRY_PROBE_TIMEOUT_SECONDS=20
MDK_BATHYMETRY_PROBE_MAX_RESPONSE_MB=4
# Bounded MDK acquisition stays fail-closed until the readiness probe reports
# "reachable" and an advertised coverage id is configured explicitly.
MDK_BATHYMETRY_ACQUISITION_ENABLED=false
MDK_BATHYMETRY_COVERAGE_ID=
MDK_BATHYMETRY_REQUEST_CRS=EPSG:4326
MDK_BATHYMETRY_MAX_BBOX_DEG2=0.25
MDK_BATHYMETRY_ACQUISITION_TIMEOUT_SECONDS=120
MDK_BATHYMETRY_ACQUISITION_MAX_RESPONSE_MB=160
THEMATIC_RASTER_ENABLED=true
THEMATIC_RASTER_WCS_URL=https://www.mercator.vlaanderen.be/raadpleegdienstenmercatorpubliek/wcs
THEMATIC_RASTER_MIN_SIDE_M=100
THEMATIC_RASTER_MAX_SIDE_M=60000
THEMATIC_RASTER_MAX_PIXELS=30000000
THEMATIC_RASTER_TIMEOUT_SECONDS=300
THEMATIC_RASTER_MAX_RESPONSE_MB=160
WALOUS_ENABLED=true
WALOUS_SOURCE_DIR=/app/storage/source-cache/walous
WALOUS_ANALYSIS_RESOLUTION_M=10
WALOUS_MAX_SIDE_M=60000
WALOUS_MAX_PIXELS=36000000
YOLO_ENABLED=false
YOLO_MODELS_DIR=/app/models
YOLO_MODEL_PATH=
YOLO_MODEL_ID=yolo-configured
YOLO_MODEL_DISPLAY_NAME=Configured YOLO detector
YOLO_MODEL_VERSION=
YOLO_MODEL_CLASSES=building
YOLO_ENFORCE_VALIDATION_SCOPE=false
YOLO_VALIDATED_AREA_NAMES=Mol,Kempen
YOLO_CONFIG_DIR=./storage/ultralytics
YOLO_DEVICE=cpu
YOLO_REQUIRE_CUDA=false
YOLO_IMAGE_SIZE=640
YOLO_MAX_TILES=100
YOLO_MAX_DETECTIONS=1000
YOLO_DUPLICATE_IOU_THRESHOLD=0.5
YOLO_BATCH_SIZE=1
# Local segmentation models. GeoIntel never downloads model weights
# automatically; point these to existing local files to enable inference.
YOLO_SEG_ENABLED=false
YOLO_SEG_MODEL_PATH=
YOLO_SEG_MODEL_ID=yolo-seg-configured
YOLO_SEG_MODEL_DISPLAY_NAME=Configured YOLO segmentation
YOLO_SEG_MODEL_VERSION=
SAM_ENABLED=false
SAM_MODEL_PATH=
SAM_MODEL_ID=sam-configured
SAM_MODEL_DISPLAY_NAME=Configured SAM segmentation
SAM_MODEL_VERSION=
SEGMENTATION_MAX_MASKS_PER_TILE=300
SEGMENTATION_DUPLICATE_IOU_THRESHOLD=0.5
ENABLE_GRB_WFS=false
GRB_WFS_URL=
OSM_OVERPASS_URL=https://overpass-api.de/api/interpreter
# Install backend raster dependencies when needed:
# python -m pip install rasterio
# Frontend
VITE_API_BASE_URL=
VITE_API_PROXY_TARGET=http://localhost:8000
# Leave empty to use the local/demo OpenStreetMap fallback with visible attribution.
# Set this to a managed MapLibre style URL for production or heavier tile traffic.
VITE_MAP_STYLE_URL=
# Docker Compose / Unraid
GEOINTEL_FRONTEND_PORT=1202
GEOINTEL_BACKEND_PORT=8000
GEOINTEL_INSTALL_AI=false
GEOINTEL_STORAGE_PATH=./storage
GEOINTEL_BACKUPS_PATH=./backups
GEOINTEL_MODELS_PATH=./models
GEOINTEL_POSTGIS_DATA_PATH=./postgres-data
GEOINTEL_POSTGRES_DB=geointel
GEOINTEL_POSTGRES_USER=geointel
GEOINTEL_POSTGRES_PASSWORD=geointel
GEOINTEL_CORS_ORIGINS=http://localhost:1202,http://127.0.0.1:1202
GEOINTEL_MAX_UPLOAD_MB=500
GEOINTEL_AOI_WORKER_ENABLED=false
GEOINTEL_AOI_WORKER_POLL_SECONDS=2
geointel/.gitattributes
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@@ -1,13 +0,0 @@
*.sh text eol=lf
deploy/unraid/gosu-setpriv text eol=lf
*.py text eol=lf
*.yml text eol=lf
*.yaml text eol=lf
*.toml text eol=lf
*.ini text eol=lf
Dockerfile text eol=lf
*.md text eol=lf
*.tsx text eol=lf
*.ts text eol=lf
*.css text eol=lf
*.json text eol=lf
geointel/.gitea/workflows/release-gates.yml
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@@ -1,141 +0,0 @@
name: GeoIntel release gates
on:
push:
branches: [main, develop, "codex/**", "build/**"]
pull_request:
branches: [main, develop]
workflow_dispatch:
permissions:
contents: read
concurrency:
group: geointel-release-${{ gitea.ref }}
cancel-in-progress: true
jobs:
quality:
name: Compile, test, contracts and builds
runs-on: ubuntu-latest
timeout-minutes: 45
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: pip
cache-dependency-path: backend/requirements-ci.lock
- uses: actions/setup-node@v4
with:
node-version: "20"
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Install locked backend dependencies
run: |
python -m pip install --disable-pip-version-check --require-hashes -r backend/requirements-ci.lock
python -m pip install --disable-pip-version-check --no-deps -e backend
- name: Install locked frontend dependencies
working-directory: frontend
run: npm ci
- name: Verify dependency lock policy
run: python scripts/verify_python_lock.py
- name: Run complete release readiness gate
env:
PYTHON_BIN: python
run: bash scripts/run_readiness_check.sh
- name: Render migration and Compose evidence
run: |
mkdir -p artifacts
cd backend
python -m alembic upgrade head --sql > ../artifacts/alembic-upgrade.sql
cd ..
docker compose config > artifacts/docker-compose.resolved.yml
- name: Publish quality evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: quality-evidence
path: |
artifacts/alembic-upgrade.sql
artifacts/docker-compose.resolved.yml
if-no-files-found: warn
retention-days: 30
dependency-audit:
name: Python and npm vulnerability policy
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: pip
cache-dependency-path: backend/requirements-ci.lock
- uses: actions/setup-node@v4
with:
node-version: "20"
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Audit locked Python dependencies
run: |
mkdir -p artifacts
python -m pip install --disable-pip-version-check pip-audit==2.10.1
bash scripts/audit_python_dependencies.sh
- name: Audit locked frontend dependencies
working-directory: frontend
run: |
npm ci
npm audit --audit-level=high --json > ../artifacts/npm-audit.json
- name: Publish dependency evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: dependency-audits
path: |
artifacts/pip-audit-full.json
artifacts/pip-audit-policy.json
artifacts/npm-audit.json
if-no-files-found: warn
retention-days: 30
container:
name: GIS image, SBOM and container scan
runs-on: ubuntu-latest
timeout-minutes: 60
steps:
- uses: actions/checkout@v4
- name: Build non-AI release image
env:
RELEASE_SHA: ${{ gitea.sha }}
run: |
mkdir -p artifacts
BUILD_TIME="$(date -u +%Y-%m-%dT%H:%M:%SZ)"
docker build \
-f deploy/unraid/Dockerfile.all-in-one \
--build-arg GEOINTEL_INSTALL_AI=false \
--build-arg GEOINTEL_BUILD_SHA="$RELEASE_SHA" \
--build-arg GEOINTEL_BUILD_TIME="$BUILD_TIME" \
-t "geointel-ci:$RELEASE_SHA-gis" \
.
docker image inspect "geointel-ci:$RELEASE_SHA-gis" > artifacts/image-inspect.json
- name: Generate SPDX SBOM
env:
RELEASE_SHA: ${{ gitea.sha }}
run: bash scripts/generate_container_sbom.sh "geointel-ci:$RELEASE_SHA-gis"
- name: Enforce container vulnerability policy
env:
RELEASE_SHA: ${{ gitea.sha }}
run: bash scripts/scan_container_image.sh "geointel-ci:$RELEASE_SHA-gis"
- name: Publish container evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: container-evidence
path: |
artifacts/image-inspect.json
artifacts/geointel-sbom.spdx.json
artifacts/geointel-container-vulnerabilities.json
if-no-files-found: warn
retention-days: 30
geointel/.github/ISSUE_TEMPLATE/bug_report.md
Vendored
-43
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@@ -1,43 +0,0 @@
---
name: Bug report
about: Report a reproducible defect
---
## Summary
## Steps to reproduce
1.
2.
3.
## Expected behavior
## Actual behavior
## Affected module
- [ ] Backend
- [ ] Frontend
- [ ] Database
- [ ] Raster
- [ ] Vector
- [ ] AI/Detection
- [ ] QA/QC
- [ ] Export
- [ ] Docs
## Logs/screenshots
## Data involved
- Dataset:
- CRS:
- Geometry type:
## Risk
- [ ] Blocks build
- [ ] Data correctness issue
- [ ] UX issue
- [ ] Documentation issue
geointel/.github/ISSUE_TEMPLATE/feature_request.md
Vendored
-26
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@@ -1,26 +0,0 @@
---
name: Feature request
about: Propose an improvement without breaking scope
---
## Problem
## Proposed solution
## Scope category
- [ ] V1 in scope
- [ ] V1 adjacent
- [ ] V2+
- [ ] RFC required
## Affected modules
## Acceptance criteria
- [ ]
- [ ]
## Risks
## Notes
geointel/.github/pull_request_template.md
Vendored
-21
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@@ -1,21 +0,0 @@
# Summary
## Changed files
## Acceptance criteria
- [ ] Meets pass prompt
- [ ] Meets M6 quality gates
- [ ] Tests run
- [ ] Docs updated
- [ ] No architecture drift
## Tests
```bash
# commands
```
## Known limitations
## Next pass recommendation
geointel/.github/workflows/release-gates.yml
Vendored
-141
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@@ -1,141 +0,0 @@
name: GeoIntel release gates
on:
push:
branches: [main, develop, "codex/**", "build/**"]
pull_request:
branches: [main, develop]
workflow_dispatch:
permissions:
contents: read
concurrency:
group: geointel-release-${{ github.ref }}
cancel-in-progress: true
jobs:
quality:
name: Compile, test, contracts and builds
runs-on: ubuntu-latest
timeout-minutes: 45
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: pip
cache-dependency-path: backend/requirements-ci.lock
- uses: actions/setup-node@v4
with:
node-version: "20"
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Install locked backend dependencies
run: |
python -m pip install --disable-pip-version-check --require-hashes -r backend/requirements-ci.lock
python -m pip install --disable-pip-version-check --no-deps -e backend
- name: Install locked frontend dependencies
working-directory: frontend
run: npm ci
- name: Verify dependency lock policy
run: python scripts/verify_python_lock.py
- name: Run complete release readiness gate
env:
PYTHON_BIN: python
run: bash scripts/run_readiness_check.sh
- name: Render migration and Compose evidence
run: |
mkdir -p artifacts
cd backend
python -m alembic upgrade head --sql > ../artifacts/alembic-upgrade.sql
cd ..
docker compose config > artifacts/docker-compose.resolved.yml
- name: Publish quality evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: quality-evidence
path: |
artifacts/alembic-upgrade.sql
artifacts/docker-compose.resolved.yml
if-no-files-found: warn
retention-days: 30
dependency-audit:
name: Python and npm vulnerability policy
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: pip
cache-dependency-path: backend/requirements-ci.lock
- uses: actions/setup-node@v4
with:
node-version: "20"
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Audit locked Python dependencies
run: |
mkdir -p artifacts
python -m pip install --disable-pip-version-check pip-audit==2.10.1
bash scripts/audit_python_dependencies.sh
- name: Audit locked frontend dependencies
working-directory: frontend
run: |
npm ci
npm audit --audit-level=high --json > ../artifacts/npm-audit.json
- name: Publish dependency evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: dependency-audits
path: |
artifacts/pip-audit-full.json
artifacts/pip-audit-policy.json
artifacts/npm-audit.json
if-no-files-found: warn
retention-days: 30
container:
name: GIS image, SBOM and container scan
runs-on: ubuntu-latest
timeout-minutes: 60
steps:
- uses: actions/checkout@v4
- name: Build non-AI release image
env:
RELEASE_SHA: ${{ github.sha }}
run: |
mkdir -p artifacts
BUILD_TIME="$(date -u +%Y-%m-%dT%H:%M:%SZ)"
docker build \
-f deploy/unraid/Dockerfile.all-in-one \
--build-arg GEOINTEL_INSTALL_AI=false \
--build-arg GEOINTEL_BUILD_SHA="$RELEASE_SHA" \
--build-arg GEOINTEL_BUILD_TIME="$BUILD_TIME" \
-t "geointel-ci:$RELEASE_SHA-gis" \
.
docker image inspect "geointel-ci:$RELEASE_SHA-gis" > artifacts/image-inspect.json
- name: Generate SPDX SBOM
env:
RELEASE_SHA: ${{ github.sha }}
run: bash scripts/generate_container_sbom.sh "geointel-ci:$RELEASE_SHA-gis"
- name: Enforce container vulnerability policy
env:
RELEASE_SHA: ${{ github.sha }}
run: bash scripts/scan_container_image.sh "geointel-ci:$RELEASE_SHA-gis"
- name: Publish container evidence
if: always()
uses: actions/upload-artifact@v4
with:
name: container-evidence
path: |
artifacts/image-inspect.json
artifacts/geointel-sbom.spdx.json
artifacts/geointel-container-vulnerabilities.json
if-no-files-found: warn
retention-days: 30
geointel/.gitignore
-56
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@@ -1,56 +0,0 @@
# Python
__pycache__/
*.py[cod]
.venv/
venv/
.env
*.egg-info/
.pytest_cache/
.ruff_cache/
# Node
node_modules/
dist/
build/
*.tsbuildinfo
# Large local data
/artifacts/
/.cache/
/datasets/raw/*
/datasets/processed/*
/datasets/cache/*
/storage/uploads/*
/storage/tiles/*
/storage/masks/*
/storage/reports/*
/storage/exports/*
/storage/rasters/*
/storage/models/*
/storage/operator-data/*
/storage/operator-evidence/*
/storage/release-evidence/*
/storage/previews/*
/storage/training/*
/storage/ultralytics/*
/exports/*
/models/*
/backend/storage/uploads/*
/backend/storage/tiles/*
/backend/storage/masks/*
/backend/storage/reports/*
/backend/storage/exports/*
/backups/*
/postgres-data/*
# Keep folder placeholders
!**/.gitkeep
!**/README.md
# Runtime-generated operator documentation is not repository documentation.
/storage/operator-data/README.md
# OS/editor
.DS_Store
.vscode/
.idea/
geointel/.gitkeep
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geointel/AGENTS.md
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# AI Agent Instructions for GeoIntel
## Project identity
GeoIntel is a GeoAI Workbench for Belgium and the Belgian North Sea, not a
generic CRUD app and not a generic dashboard. Mol and the Kempen remain golden
regression areas, not the product boundary.
## Required behavior
- Read `docs/CODEX_BOOTSTRAP_PROMPT.md` first.
- Respect `docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md`.
- Use `docs/API_CONTRACTS.md` as source of truth for endpoints.
- Use `docs/DATABASE_IMPLEMENTATION_PLAN.md` as source of truth for persistence.
- Use `docs/DEFINITION_OF_DONE.md` to decide whether work is complete.
## Agent roles
### Architecture Agent
Owns repository layout, API contracts, database migrations and service boundaries.
### GIS Agent
Owns GeoPandas, Shapely, Rasterio, CRS, clipping, buffering, spatial joins and metadata extraction.
### AI Agent
Owns YOLO/SAM abstractions, inference contracts, model configuration, detection/segmentation persistence and `not_configured` behavior.
### QA Agent
Owns tests, QA/QC metrics, regression checks and acceptance criteria.
### Frontend Agent
Owns React, TypeScript, MapLibre, API client, UI states and workbench UX.
## Never do this
- Do not fake production AI outputs.
- Do not silently skip geospatial validation.
- Do not add auth/multi-user/LiDAR/training before V1 foundation is stable.
- Do not remove documentation to avoid conflicts.
geointel/CHANGELOG.md
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geointel/CODEX_START.md
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# CODEX START — Use This First
This is the shortest possible entry point for the first implementation run.
## Mandatory order
1. Read `docs/00-start/START_HERE.md`.
2. Read `docs/30-codex-optimization/CODEX_RUN_CHECKLIST.md`.
3. Read `docs/30-codex-optimization/PROMPT_DISCIPLINE.md`.
4. Read `docs/20-run-readiness/RUN_READINESS_FINAL.md`.
5. Read `docs/20-run-readiness/CODEX_TOMORROW_RUNBOOK.md`.
6. Use `prompts/codex/m14/CODEX_FIRST_DAY_MASTER_PROMPT.md` as the first Codex prompt.
7. Follow `docs/20-run-readiness/PASS_SEQUENCE_FINAL.md` exactly.
8. Select the relevant skill from `skills/` for the active pass.
## First build objective
Build the V1 foundation vertical slice:
Project → Area → Dataset metadata → Reference polygons → Predicted detections → QA/QC → GeoJSON export → Minimal UI.
Do not start with heavy AI inference, LiDAR, training, MLOps, Sentinel automation, or advanced report generation before the foundation passes.
## Pass completion rule
A pass is not done until:
- commands were run;
- tests/smoke checks were attempted;
- docs/status were updated;
- limitations are explicit;
- next pass is clear.
## M13 additions
Before implementing, Codex must respect:
- `docs/30-codex-optimization/CODEX_OPTIMIZATION_OVERVIEW.md`
- `docs/30-codex-optimization/TOKEN_BUDGET_POLICY.md`
- `docs/30-codex-optimization/SECRETS_AND_ENV_POLICY.md`
- `docs/30-codex-optimization/PARALLEL_AGENT_STRATEGY.md` when using multiple agents/worktrees
- `docs/30-codex-optimization/CODEX_SKILLS_INDEX.md`
The preferred first prompt is now:
- `prompts/codex/m14/CODEX_FIRST_DAY_MASTER_PROMPT.md`
## M14 launch controls
Before the first implementation pass, Codex must read:
- `docs/40-build-launch/SPRINT_1_SCOPE_FREEZE.md`
- `docs/40-build-launch/BUILD_SUCCESS_DEFINITION.md`
- `docs/40-build-launch/BUILD_ORDER_GRAPH.md`
- `docs/40-build-launch/CODEX_STOP_RULES.md`
- `docs/40-build-launch/MODULE_ACCEPTANCE_CRITERIA.md`
The first implementation run is Sprint 1 only. Do not implement detection, segmentation, Sentinel, LiDAR, training, AI Copilot or advanced reports during Sprint 1.
geointel/M10_UPDATE_MANIFEST.txt
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docs/18-ultra-prep/README.md
docs/18-ultra-prep/AUTONOMOUS_BUILD_CHARTER.md
docs/18-ultra-prep/BUILD_PASS_TEMPLATE.md
docs/18-ultra-prep/CRITICAL_PATH_TO_V1.md
docs/18-ultra-prep/CODEX_START_HERE.md
prompts/codex/M10_MASTER_AUTONOMOUS_PROMPT.md
prompts/codex/M10_PASS_SEQUENCE.md
docs/18-ultra-prep/FEATURE_FLAG_STRATEGY.md
docs/18-ultra-prep/ERROR_TAXONOMY.md
docs/18-ultra-prep/GEOMETRY_CONTRACTS.md
docs/18-ultra-prep/CRS_POLICY.md
docs/18-ultra-prep/SECURITY_AND_SECRET_HANDLING.md
docs/18-ultra-prep/PERFORMANCE_BUDGETS.md
docs/18-ultra-prep/OBSERVABILITY_PLAN.md
docs/18-ultra-prep/CONNECTOR_IMPLEMENTATION_GUIDE.md
docs/18-ultra-prep/MODEL_ADAPTER_GUIDE.md
docs/18-ultra-prep/QA_QC_MATCHING_ALGORITHM.md
docs/18-ultra-prep/FRONTEND_STATE_MACHINE.md
docs/18-ultra-prep/UI_COPY_BANK.md
docs/18-ultra-prep/REPO_HYGIENE_RULES.md
docs/18-ultra-prep/RELEASE_GATE_V1.md
docs/18-ultra-prep/KNOWN_LIMITATIONS_TEMPLATE.md
docs/18-ultra-prep/FINAL_PRE_CODEX_CHECKLIST.md
tickets/TICKET_INDEX.md
tickets/T-001-backend-skeleton.md
tickets/T-002-database-foundation.md
tickets/T-003-project-area-domain.md
tickets/T-010-dataset-manager.md
tickets/T-011-vector-processing.md
tickets/T-012-raster-processing.md
tickets/T-020-frontend-foundation.md
tickets/T-021-map-workbench.md
tickets/T-022-dataset-ui.md
tickets/T-030-detection-adapter.md
tickets/T-031-qaqc-engine.md
tickets/T-032-export-engine.md
tickets/T-033-demo-workflow.md
contracts/api/examples/project_create.json
contracts/api/examples/area_create.geojson
contracts/api/examples/error_feature_disabled.json
contracts/api/examples/qaqc_result.json
scripts/smoke_m10.sh
docs/TODO.md
RELEASE_NOTES/M10_ultra_preparation.md
geointel/M11_UPDATE_MANIFEST.txt
-23
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@@ -1,23 +0,0 @@
M11 Architect Audit & Control Layer
Added:
- docs/00-start/START_HERE.md
- docs/governance/GEOINTEL_CONSTITUTION.md
- docs/governance/FORBIDDEN_DECISIONS.md
- docs/governance/ARCHITECTURE_INVARIANTS.md
- docs/governance/DECISION_PRECEDENCE.md
- docs/specs/CANONICAL_DOMAIN_MODELS.md
- docs/specs/GIS_STANDARDS.md
- docs/specs/RASTER_STANDARDS.md
- docs/specs/STATE_MACHINES.md
- docs/specs/DATA_LIFECYCLE.md
- docs/specs/ERROR_CATALOG.md
- docs/specs/PERFORMANCE_BUDGETS_CANONICAL.md
- docs/workflows/GOLDEN_PATHS.md
- docs/build/BUILD_ORDER_DEPENDENCY_GRAPH.md
- docs/build/CODEX_OPERATING_SYSTEM.md
- docs/19-architect-audit/ARCHITECT_AUDIT_REPORT_M11.md
- prompts/codex/M11_ARCHITECT_MASTER_PROMPT.md
Changed:
- README.md now points to the single canonical M11 start path.
geointel/M12_UPDATE_MANIFEST.txt
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M12 Final Run Readiness Layer
Added:
- CODEX_START.md
- docs/20-run-readiness/RUN_READINESS_FINAL.md
- docs/20-run-readiness/PASS_SEQUENCE_FINAL.md
- docs/20-run-readiness/CODEX_TOMORROW_RUNBOOK.md
- docs/20-run-readiness/IMPLEMENTATION_READINESS_CHECKLIST.md
- docs/20-run-readiness/REPO_CONFLICT_RESOLUTION.md
- prompts/codex/final/DAY_1_MASTER_PROMPT.md
- prompts/codex/final/PASS_00_REPO_AUDIT_FINAL.md
- prompts/codex/final/PASS_01_BACKEND_FOUNDATION_FINAL.md
- prompts/codex/final/PASS_02_DOMAIN_DATABASE_FINAL.md
- scripts/preimplementation_audit.py
- scripts/run_readiness_check.sh
- Makefile
- RELEASE_NOTES/v0.12-m12-final-run-readiness.md
Changed:
- README.md
geointel/M13_UPDATE_MANIFEST.txt
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M13 — Codex Optimization Pack
Purpose:
- Improve Codex execution quality after M12 final run readiness.
- Add reusable skills, prompt discipline, token policy, secrets policy, parallel agent strategy and pass completion prompts.
Added:
- docs/30-codex-optimization/CODEX_OPTIMIZATION_OVERVIEW.md
- docs/30-codex-optimization/CODEX_RUN_CHECKLIST.md
- docs/30-codex-optimization/PROMPT_DISCIPLINE.md
- docs/30-codex-optimization/TOKEN_BUDGET_POLICY.md
- docs/30-codex-optimization/SECRETS_AND_ENV_POLICY.md
- docs/30-codex-optimization/PARALLEL_AGENT_STRATEGY.md
- docs/30-codex-optimization/CODEX_SKILLS_INDEX.md
- docs/30-codex-optimization/M13_HANDOFF_SUMMARY.md
- skills/*/SKILL.md
- prompts/codex/m13/*.md
- scripts/validate_m13_codex_assets.py
Updated:
- README.md
- CODEX_START.md
- Makefile
- scripts/run_readiness_check.sh
- CHANGELOG.md
geointel/M14_UPDATE_MANIFEST.txt
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M14 Build Launch Package
Added:
- docs/40-build-launch/BUILD_SUCCESS_DEFINITION.md
- docs/40-build-launch/SPRINT_1_SCOPE_FREEZE.md
- docs/40-build-launch/DATA_ACQUISITION_PLAYBOOK.md
- docs/40-build-launch/GOLDEN_DATASET_PACKAGE.md
- docs/40-build-launch/BUILD_ORDER_GRAPH.md
- docs/40-build-launch/MODULE_ACCEPTANCE_CRITERIA.md
- docs/40-build-launch/CODEX_STOP_RULES.md
- docs/40-build-launch/RELEASE_STRATEGY.md
- docs/40-build-launch/RISK_REGISTER.md
- docs/40-build-launch/BACKLOG_PRIORITIES_MOSCOW.md
- docs/40-build-launch/FOLDER_OWNERSHIP.md
- prompts/codex/m14/CODEX_FIRST_DAY_MASTER_PROMPT.md
- checklists/SPRINT_1_OPERATOR_CHECKLIST.md
- release/v0.1-foundation-target.md
- scripts/validate_m14_launch_assets.py
Updated:
- README.md
- CODEX_START.md
- docs/00-start/START_HERE.md
- Makefile
- scripts/run_readiness_check.sh
geointel/M5_UPDATE_MANIFEST.txt
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docs/OBSERVABILITY_PLAN.md
docs/TROUBLESHOOTING_RUNBOOK.md
docs/RELEASE_PROCESS.md
docs/ROLLBACK_AND_RECOVERY.md
docs/DEPENDENCY_LOCK_PLAN.md
docs/SECURITY_CHECKLIST.md
docs/DATA_PRIVACY_AND_LICENSING.md
docs/EXTERNAL_SERVICES_ADAPTERS.md
docs/GEOSPATIAL_VALIDATION_RULES.md
docs/BUILD_GOVERNANCE.md
docs/M5_OPERATIONAL_READINESS.md
docs/CI_CD_SPECIFICATION.md
docs/HEALTHCHECK_CONTRACTS.md
docs/CODEX_PASS_0_REPO_AUDIT.md
docs/CODEX_PASS_1_BACKEND_FOUNDATION.md
docs/CODEX_PASS_2_DATABASE_AND_MODELS.md
docs/CODEX_PASS_3_DATASET_MANAGER.md
docs/CODEX_PASS_4_RASTER_VECTOR_CORE.md
docs/CODEX_PASS_5_FRONTEND_WORKBENCH_SHELL.md
docs/CODEX_PASS_6_DETECTION_QA_SKELETON.md
docs/CODEX_PROMPT_M5_LONG_AUTONOMOUS_BUILD.md
scripts/check_repo_structure.sh
scripts/smoke_backend_import.sh
scripts/smoke_docs.py
scripts/smoke_contracts.py
scripts/validate_fixtures.py
RELEASE_NOTES/v0.5-m5-operational-readiness.md
CHANGELOG.md
docs/TODO.md
geointel/M9_UPDATE_MANIFEST.txt
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@@ -1,23 +0,0 @@
# M9 Update Manifest
New/changed files:
- `docs/17-max-prep/M9_MAX_PREPARATION_PACK.md`
- `prompts/codex/M9_DAY_ONE_MASTER_PROMPT.md`
- `docs/17-max-prep/M9_AUTONOMOUS_BUILD_DOCTRINE.md`
- `docs/17-max-prep/M9_PASS_SCORECARDS.md`
- `docs/17-max-prep/M9_BUILD_BLOCKERS_AND_RECOVERY.md`
- `docs/17-max-prep/M9_REAL_VS_DEMO_DATA_POLICY.md`
- `docs/17-max-prep/M9_DATA_CONTRACTS_DETAILED.md`
- `docs/17-max-prep/M9_GEOSPATIAL_EDGE_CASES.md`
- `docs/17-max-prep/M9_UI_STATE_SPEC.md`
- `docs/17-max-prep/M9_API_VALIDATION_EXAMPLES.md`
- `docs/17-max-prep/M9_IMPLEMENTATION_REVIEW_SCRIPT.md`
- `docs/17-max-prep/M9_REGRESSION_MAP.md`
- `docs/17-max-prep/M9_GAP_TO_TASK_CONVERSION.md`
- `docs/17-max-prep/M9_MODULE_DATAFLOW_CHECKLIST.md`
- `docs/17-max-prep/M9_FINAL_PRE_CODE_CHECKLIST.md`
- `docs/17-max-prep/M9_LONG_FORM_CODEX_PROMPT_VARIANTS.md`
- `docs/IMPLEMENTATION_GAP_REPORT.md`
- `RELEASE_NOTES/v0.9-m9-max-preparation.md`
- `CHANGELOG.md`
geointel/Makefile
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PYTHON_BIN := $(shell command -v python3 >/dev/null 2>&1 && echo python3 || echo python)
.PHONY: readiness docs fixtures preflight backend-install backend-test backend-dev frontend-install frontend-typecheck frontend-build m13 m14
readiness:
bash scripts/run_readiness_check.sh
backend-install:
cd backend && \
$(PYTHON_BIN) -m pip install -e .[dev]
backend-test:
cd backend && \
$(PYTHON_BIN) -m pytest
backend-dev:
cd backend && \
$(PYTHON_BIN) -m uvicorn app.main:app --reload
frontend-install:
cd frontend && \
npm install
frontend-typecheck:
cd frontend && \
npm run typecheck
frontend-build:
cd frontend && \
npm run build
docs:
$(PYTHON_BIN) scripts/smoke_docs.py
fixtures:
$(PYTHON_BIN) scripts/validate_fixtures.py
preflight:
bash scripts/codex_preflight.sh || true
$(PYTHON_BIN) scripts/preimplementation_audit.py
.PHONY: m13
m13:
$(PYTHON_BIN) scripts/validate_m13_codex_assets.py
.PHONY: m14
m14:
$(PYTHON_BIN) scripts/validate_m14_launch_assets.py
geointel/README.md
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# GeoIntel Belgium and the Belgian North Sea
GeoIntel is a map-first GeoAI Workbench for Belgium and the Belgian North Sea.
It combines governed official-source coverage, raster/vector processing,
historical comparison, computer vision, QA/QC and geospatial exports.
Mol and the Kempen remain deep regression and model-validation references. The
release scope is all of Belgium plus legally labelled Belgian maritime zones;
source coverage remains explicit per theme and jurisdiction.
GeoIntel is not a generic dashboard or chatbot. The core product is:
> data → processing → geospatial output → QA/QC → export
## Current milestone
**v1.0.0 - Belgium/North Sea release**
The canonical release controls are:
- `docs/00-start/START_HERE.md`
- `docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md`
- `docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md`
- `docs/RELEASE_RUNBOOK.md`
- `docs/KNOWN_LIMITATIONS.md`
- `docs/DEFINITION_OF_DONE.md`
Older milestone and sprint handoff files remain historical evidence. They do
not override the active national/maritime scope freeze or RC roadmap.
## Core V1 vertical slice
The first implementation target is:
1. Project + Area creation.
2. Dataset registration/upload and metadata extraction.
3. Reference building layer loading.
4. Predicted detection layer loading/import.
5. QA/QC matching against reference polygons.
6. Metrics and false positive/false negative outputs.
7. GeoJSON export.
8. Minimal map/workbench UI.
## Primary stack
- Frontend: React, TypeScript, MapLibre GL, Deck.gl, Tailwind.
- Backend: FastAPI, Python.
- Database: PostgreSQL + PostGIS.
- GIS processing: GeoPandas, Shapely, Rasterio, PyProj, GDAL.
- AI: PyTorch, Ultralytics YOLO, SAM-compatible architecture.
- Jobs: Redis + RQ.
- Storage: local filesystem first, MinIO-compatible later.
## Codex instructions
Codex must start with:
1. `docs/00-start/START_HERE.md`
2. `prompts/codex/M11_ARCHITECT_MASTER_PROMPT.md`
Then follow the build order in:
- `docs/build/BUILD_ORDER_DEPENDENCY_GRAPH.md`
- `docs/build/CODEX_OPERATING_SYSTEM.md`
Before every implementation pass, run available preflight/smoke scripts where applicable.
## Repo principle
This is a documentation-driven engineering repo. The documentation is not decorative; it is the control system for autonomous implementation.
## Fastest Day 1 command path
```bash
make readiness
```
## Unraid / Tower deployment
GeoIntel runs on Unraid as an all-in-one DockerMan-native container. The container embeds PostGIS, runs the FastAPI backend internally, and serves the frontend through nginx on one editable web port.
Unraid template assets live in:
- `deploy/unraid/geointel.env.example`
- `deploy/unraid/geointel-unraid-template.xml`
- `deploy/unraid/geointel-icon.svg`
- `deploy/unraid/geointel-icon.png`
- `docker-compose.unraid.yml`
Copy the Unraid env template to `.env` in the checkout and edit ports/paths there:
```bash
cd /mnt/user/appdata/geointel
cp deploy/unraid/geointel.env.example .env
nano .env
docker build -f deploy/unraid/Dockerfile.all-in-one -t geointel-all-in-one:latest .
bash deploy/unraid/run-dockerman-container.sh
```
Common editable values:
```env
GEOINTEL_FRONTEND_PORT=1202
GEOINTEL_STORAGE_PATH=/mnt/user/appdata/geointel/storage
GEOINTEL_POSTGIS_DATA_PATH=/mnt/user/appdata/geointel/postgres-data
```
### Optional guest demonstration access
Guest access is disabled by default. On a dedicated demonstration installation,
it can be enabled alongside the operator gate:
```env
GEOINTEL_AUTH_ENABLED=true
GEOINTEL_AUTH_USERNAME=operator
GEOINTEL_AUTH_PASSWORD_HASH=pbkdf2_sha256$...
GEOINTEL_AUTH_SESSION_SECRET=<independent-random-secret-of-at-least-32-characters>
GEOINTEL_GUEST_ACCESS_ENABLED=true
GEOINTEL_GUEST_DISPLAY_NAME=Gast
GEOINTEL_GUEST_SESSION_TTL_SECONDS=7200
```
The login page then offers **Als gast verkennen**. A guest receives a
short-lived, read-only session scoped to the seeded demo project and sees only
the map and existing quality evidence. This is not multi-user authorization or
tenant isolation. Do not enable it on an installation containing private or
operational datasets; use a separate demo instance instead.
The backend and PostGIS ports are intentionally not exposed to the LAN in the all-in-one runtime. See `deploy/unraid/README.md` for full setup, port-change and cleanup notes.
On Tower/Unraid, `scripts/deploy_tower.ps1` and `scripts/deploy_tower.sh` validate the Compose reference but build with plain `docker build`, then automatically install the editable DockerMan template as `/boot/config/plugins/dockerMan/templates-user/my-geointel.xml`, install the PNG icon as `/boot/config/plugins/dockerMan/images/geointel-icon.png`, remove any old Compose-owned `geointel` container and start the final container with DockerMan labels.
## Sprint 2 quick start
- Update dependencies:
```bash
python -m pip install -e backend/.[dev]
cd frontend && npm install
```
- Run full readiness checks (with no scope expansion):
```bash
python -m compileall backend/app
cd backend && python -m pytest
cd ../frontend && npm run typecheck && npm run build
bash scripts/run_readiness_check.sh
```
- Raster workflow validation command (backend only):
```bash
bash scripts/smoke_backend_import.sh
cd backend && python -c "from app.main import app; print(app.title)"
```
If `rasterio` is not installed, raster metadata endpoints return `RASTER_PROCESSING_UNAVAILABLE` and the frontend displays the
state as failed until the dependency is added.
## Sprint 4 raster foundation
- Raster operations now support:
- raster metadata extraction,
- raster preview generation,
- raster clip by area (with provenance on derived datasets),
- raster tile generation with manifest output.
- Raster services are dependency-aware:
- if `rasterio` is unavailable, endpoints return `RASTER_PROCESSING_UNAVAILABLE`.
- if preview dependencies (`numpy`, `pillow`) are unavailable, preview generation is unavailable with a clear error.
- Enable raster stack explicitly when needed:
```bash
cd backend && python -m pip install -e .[dev,raster]
```
## Sprint 5 raster analytics hardening
- Added raster band statistics (min/max/mean/std, nodata ratio/count, valid pixel count, dtype, optional histograms).
- Added raster reproject workflow with CRS validation and provenance persistence.
- Extended tile manifest expectations (`tile_set_id`, `tile_size`, `overlap`, `bounds`, `source_raster_id`, `tile_paths`, `tile_server`).
- Clarified raster operation availability in frontend/backend docs (`RASTER_PROCESSING_UNAVAILABLE` and invalid-CRS cases).
- Raster workflow command set (where available):
```bash
cd backend
python -m pip install -e .[dev,raster]
python -m pytest
cd ../frontend
npm run typecheck
npm run build
```
Then give Codex the prompt in:
- `prompts/codex/final/DAY_1_MASTER_PROMPT.md`
## M13 Codex optimization
For the first serious Codex build run, use:
- `prompts/codex/m13/DAY_1_OPTIMIZED_MASTER_PROMPT.md`
Codex should also use the relevant reusable skill under `skills/` for each implementation pass. Validate the optimization assets with:
```bash
make m13
```
The full readiness path remains:
```bash
make readiness
```
## M14 Build Launch
For the first serious implementation run, use:
- `docs/40-build-launch/SPRINT_1_SCOPE_FREEZE.md`
- `docs/40-build-launch/BUILD_SUCCESS_DEFINITION.md`
- `docs/40-build-launch/CODEX_STOP_RULES.md`
- `prompts/codex/m14/CODEX_FIRST_DAY_MASTER_PROMPT.md`
Validate launch assets with:
```bash
make m14
```
Full readiness remains:
```bash
make readiness
```
## Sprint 1 execution (Sprint 1 only)
From a clean machine:
```bash
cd backend && python -m pip install -e .[dev]
cd ..
make backend-install
make frontend-install
make readiness
```
Copy `.env.example` to `.env` only when you want local overrides. Docker Compose has safe defaults for the local PostGIS/backend/frontend stack and does not require a root `.env` file to exist.
With Docker Compose, open the workbench at `http://localhost:1202`.
The Docker frontend is served by nginx and proxies `/api` and `/health` to the backend container, so browser clients should use the frontend URL only, for example `http://192.168.10.150:1202` on a LAN host.
Runtime containers include healthchecks for PostGIS, backend and frontend. After
startup, inspect them with:
```bash
docker compose ps
```
Verify the browser-facing API proxy after rebuilding Docker images:
```bash
bash scripts/verify_browser_runtime.sh http://localhost:1202 http://localhost:8000/health
```
Verify the Docker GIS runtime after rebuilding the backend image:
```bash
bash scripts/verify_gis_runtime.sh http://localhost:1202
```
On the LAN host use the published browser URL, for example:
```bash
bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202
```
Load the explicit offline demo workflow:
```bash
curl -X POST http://192.168.10.150:1202/api/v1/demo/workflow
```
If `/api/v1/projects` returns frontend HTML instead of a JSON envelope, rebuild
and restart the frontend container.
Useful direct verification commands:
```bash
python -m compileall backend/app
cd backend && python -c "from app.main import app; print(app.title)"
python -m pytest
cd ../frontend && npm run typecheck
cd ../frontend && npm run build
docker compose config
bash scripts/run_readiness_check.sh
```
If `make` or `docker` are unavailable in your shell, run the equivalent script entrypoints directly:
```bash
bash scripts/backend_install.sh
bash scripts/backend_test.sh
bash scripts/frontend_install.sh
bash scripts/frontend_typecheck.sh
bash scripts/frontend_build.sh
bash scripts/run_readiness_check.sh
```
geointel/RELEASE_NOTES/M10_ultra_preparation.md
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# M10 Ultra Preparation
M10 adds a stronger Codex autonomy layer:
- autonomous build charter;
- Codex start-here guide;
- pass sequence;
- master prompt;
- geometry contracts;
- CRS policy;
- security and secret handling;
- performance budgets;
- observability plan;
- connector guide;
- model adapter guide;
- QA/QC matching algorithm;
- frontend state machine;
- UI copy bank;
- repo hygiene rules;
- V1 release gate;
- implementation tickets;
- API example payloads;
- final pre-Codex checklist.
This milestone aims to make tomorrow's Codex build significantly more autonomous while preserving strict product boundaries.
geointel/RELEASE_NOTES/v0.0-M2.md
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@@ -1,11 +0,0 @@
# Release Notes — v0.0 M2 Engineering Package
This is not an application release. It is a repository preparation milestone for autonomous Codex development.
## Main value
Codex now has fewer architecture choices to invent. The repo contains decision records, contracts, engineering rules, fixtures, and build prompts.
## Next recommended action
Run Codex Pass 01 using `prompts/codex/PASS_01_BACKEND_FOUNDATION.md`.
geointel/RELEASE_NOTES/v0.0-M3.md
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# Release Notes — v0.0 M3 Implementation Readiness
This is a documentation and repository preparation release.
## Added
- implementation epics
- build tickets
- migration plan
- seed data plan
- local dev runbook
- backend package map
- frontend route map
- module contracts
- job lifecycle
- Codex pass matrix
- additional Codex prompts
- known limitations
## Purpose
Prepare the repository for Codex-driven implementation without requiring major architecture decisions during coding.
geointel/RELEASE_NOTES/v0.11-m11-architect-audit-control-layer.md
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# v0.11 — M11 Architect Audit & Control Layer
This release turns the GeoIntel preparation repo into a stricter architecture-controlled implementation repo.
## Highlights
- One canonical `START_HERE` document.
- Constitution, forbidden decisions and architecture invariants.
- Canonical domain model definitions.
- GIS/raster standards.
- State machines and data lifecycle.
- Golden paths and build dependency graph.
- Error catalog and canonical performance budgets.
- M11 Codex architect master prompt.
## Purpose
The goal is to reduce Codex ambiguity before implementation starts. Older handoff documents remain available, but M11 defines the precedence and operating model.
geointel/RELEASE_NOTES/v0.12-m12-final-run-readiness.md
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# v0.12 — M12 Final Run Readiness Layer
This release turns the M11 architect audit repo into a directly executable Codex preparation package.
## Added
- Root `CODEX_START.md` as the shortest canonical entry point.
- Final run-readiness docs under `docs/20-run-readiness/`.
- Final Day 1 Codex master prompt under `prompts/codex/final/`.
- Final pass prompts for Pass 00, Pass 01 and Pass 02.
- `scripts/preimplementation_audit.py`.
- `scripts/run_readiness_check.sh`.
- Root `Makefile` with `make readiness`.
## Changed
- README now points to M12 and the final run path.
## Intent
Reduce manual work tomorrow by giving Codex one obvious entry point, one pass sequence, one first prompt, and a simple readiness command.
geointel/RELEASE_NOTES/v0.4-m4-autonomous-build-readiness.md
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@@ -1,17 +0,0 @@
# v0.4 — M4 Autonomous Build Readiness
This release adds the documentation and fixtures required for longer autonomous Codex implementation passes.
## Highlights
- Clear sprint board.
- Module build contracts.
- Acceptance tests.
- Service IO contracts.
- UI route/state contracts.
- Job lifecycle contract.
- Demo model registry seed.
- Geel demo fixtures.
- Codex prompts per pass.
## Next
M5 should add concrete migration SQL, OpenAPI draft, component prop contracts and test skeletons.
geointel/RELEASE_NOTES/v0.5-m5-operational-readiness.md
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# GeoIntel v0.5 — M5 Operational Readiness
## Toegevoegd
- Operational readiness documentatie.
- CI/CD-specificatie.
- Healthcheck-contracten.
- Observability plan.
- Troubleshooting runbook.
- Releaseproces.
- Rollback- en recoveryregels.
- Dependency lock plan.
- Security checklist.
- Data privacy en licensing notities.
- External services adaptercontracten.
- Geospatial validation rules.
- Build governance.
- Codex passdocumenten voor Pass 0 tot Pass 6.
- Long autonomous Codex build prompt.
- Smoke scripts voor repo/docs/contracts/backend import.
## Volgende logische stap
M6 kan zich richten op echte code-scaffolding: backend app, database migrations, API schemas, frontend shell en eerste project/dataset flows.
geointel/RELEASE_NOTES/v0.9-m9-max-preparation.md
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# GeoIntel v0.9 — M9 Max Preparation
This release adds a heavy preparation layer intended to maximize Codex autonomy before implementation.
## Added
- M9 max preparation pack.
- Day-one Codex master prompt.
- Autonomous build doctrine.
- Build pass scorecards.
- Build blocker and recovery guide.
- Real vs demo data policy.
- Detailed data contracts.
- Geospatial edge case catalog.
- UI state specification.
- API validation examples.
- Implementation review script.
- Regression map.
- Gap-to-task conversion rules.
- Module dataflow checklist.
- Final pre-code checklist.
- Long-form Codex prompt variants.
- Implementation gap report template.
## Purpose
Make the repository as ready as possible for a long autonomous Codex build session.
geointel/VERSION
-1
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@@ -1 +0,0 @@
1.0.0
geointel/adr/ADR-001-technology-stack.md
-25
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@@ -1,25 +0,0 @@
# ADR-001 — Technology Stack
## Status
Accepted for V1.
## Context
GeoIntel Kempen must demonstrate modern web development, geospatial processing, and GeoAI engineering. The stack must be realistic for a portfolio project while remaining close to professional workflows.
## Decision
Use:
- Frontend: React + TypeScript.
- Map UI: MapLibre GL with Deck.gl where advanced overlays are useful.
- Backend: FastAPI.
- Database: PostgreSQL + PostGIS.
- Processing: GeoPandas, Shapely, Rasterio, PyProj, GDAL-compatible tools.
- AI: PyTorch with Ultralytics YOLO first; SAM/segmentation later.
- Jobs: Redis + RQ for V1.
- Storage: local filesystem with explicit storage abstraction.
## Consequences
This stack keeps the first build achievable while matching the vacancy profile closely: Python, raster/vector processing, computer vision, AI pipelines, and GIS outputs.
## Non-goals
Do not introduce Django, Flask, MongoDB, Firebase, or a second frontend framework unless a future ADR explicitly replaces this decision.
geointel/adr/ADR-002-postgis-choice.md
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@@ -1,27 +0,0 @@
# ADR-002 — PostGIS as Spatial Source of Truth
## Status
Accepted for V1.
## Context
GeoIntel stores areas, datasets, AI detections, segmentations, QA geometries, and exports. Spatial operations need to be queryable and persistent.
## Decision
Use PostgreSQL with PostGIS as the canonical database for:
- project areas,
- dataset spatial bounds,
- vector features,
- detection polygons/boxes,
- segmentation polygons,
- QA/QC geometries,
- spatial metadata,
- analysis outputs.
Raw rasters, tiles, masks, and large binary artifacts stay on disk/object storage. PostGIS stores metadata and vectorized results.
## Consequences
The backend can do spatial filtering, intersections, bounding-box queries, and QA matching without reloading every file. The portfolio visibly demonstrates professional GIS database skills.
## Non-goals
Do not store full large rasters as database blobs in V1.
geointel/adr/ADR-003-grb-strategy.md
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@@ -1,23 +0,0 @@
# ADR-003 — GRB as Authoritative Reference Dataset
## Status
Accepted for V1 research and implementation planning.
## Context
The Basiskaart Vlaanderen / GRB is a professional Flemish geospatial reference dataset. GeoIntel is scoped to the Kempen, so Flemish official data is highly relevant.
## Decision
Treat GRB as the primary QA/QC reference where available. Use it for building/reference geometry validation and later for roads, water, and other base-map objects.
V1 integration strategy:
1. Implement a GRB provider abstraction.
2. Start with WFS or downloaded sample/cache depending on practical availability.
3. Normalize GRB features into a common `reference_features` model.
4. Compare AI detections against GRB with IoU/overlap metrics.
## Consequences
GeoIntel becomes more relevant to real Flemish GeoAI workflows than a generic OSM-only demo. GRB validation becomes a portfolio killer feature.
## Non-goals
Do not block the entire build on live GRB integration. Provide fixtures and provider interfaces first, then connect real GRB when endpoint details are tested.
geointel/adr/ADR-004-storage-strategy.md
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@@ -1,27 +0,0 @@
# ADR-004 — Storage Strategy
## Status
Accepted for V1.
## Context
GeoIntel stores multiple artifact types: uploaded rasters, vector uploads, generated tiles, model outputs, masks, exports, and reports.
## Decision
Use local filesystem storage for V1 with a strict directory convention:
- `storage/uploads/` for original user uploads,
- `storage/originals/` for normalized source copies,
- `storage/tiles/` for generated raster tiles,
- `storage/masks/` for segmentation masks,
- `storage/derived/` for processed artifacts,
- `storage/exports/` for GeoJSON/COCO/YOLO exports,
- `storage/reports/` for reports,
- `storage/models/` for model artifacts.
Database rows reference files by relative path and content hash.
## Consequences
Simple local development and predictable repo behavior. Future MinIO/S3 migration remains possible because storage calls must go through a service boundary.
## Non-goals
No direct random file writes from routes or frontend-specific paths.
geointel/adr/ADR-005-ai-model-strategy.md
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# ADR-005 — AI Model Strategy
## Status
Accepted for V1.
## Context
The vacancy emphasizes PyTorch, object detection, segmentation, and GeoAI. A portfolio build should show a real inference pipeline, not only AI text generation.
## Decision
Use Ultralytics YOLO as the first object detection runtime because it is practical, PyTorch-based, well documented, and fast to integrate. Add segmentation through YOLO-seg or SAM after the detection pipeline is reliable.
Model execution must be wrapped behind `ModelRegistryService` and `DetectionService` interfaces so the UI and API do not depend directly on Ultralytics internals.
## Consequences
GeoIntel can demonstrate model inference, georeferencing, output conversion, confidence thresholds, and QA/QC against GRB.
## Non-goals
Do not train a custom model in V1. Fine-tuning becomes V2/V3 after annotation and dataset export exist.
geointel/adr/ADR-006-job-processing.md
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@@ -1,25 +0,0 @@
# ADR-006 — Job Processing
## Status
Accepted for V1.
## Context
Raster tiling, detection, segmentation, QA, and exports can take longer than a normal HTTP request.
## Decision
Use Redis + RQ for V1 background jobs. Every long-running operation creates an `analysis_run` or `job` record, updates status, stores outputs, and emits events.
Supported statuses:
- pending,
- queued,
- running,
- completed,
- failed,
- cancelled.
## Consequences
The UI can show progress and status without blocking. RQ is easier than Celery for an initial solo/portfolio project.
## Non-goals
No Kubernetes-native queues, no Airflow, no full workflow engine in V1.
geointel/adr/ADR-007-api-design.md
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@@ -1,28 +0,0 @@
# ADR-007 — API Design
## Status
Accepted for V1.
## Context
The frontend must be API-driven and Codex must not invent inconsistent response shapes.
## Decision
Use REST-style FastAPI endpoints with typed Pydantic schemas. Responses use stable envelopes for long-running jobs and direct resources for simple CRUD operations.
Errors use a common structure:
```json
{
"error": {
"code": "DATASET_NOT_FOUND",
"message": "Dataset not found.",
"details": {}
}
}
```
## Consequences
Frontend API clients, tests, and docs stay consistent.
## Non-goals
No GraphQL in V1.
geointel/backend/.dockerignore
-10
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@@ -1,10 +0,0 @@
__pycache__
*.pyc
.pytest_cache
.mypy_cache
.ruff_cache
geointel_backend.egg-info
storage
dist
node_modules
.env
geointel/backend/.gitkeep
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geointel/backend/Dockerfile
-36
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FROM python:3.12-slim
WORKDIR /app
ARG GEOINTEL_INSTALL_AI=false
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
gdal-bin \
libgl1 \
libglib2.0-0 \
libgdal-dev \
libgeos-dev \
libproj-dev \
libpq-dev \
libsm6 \
libx11-6 \
libxcb1 \
libxext6 \
libxrender1 \
proj-bin \
&& rm -rf /var/lib/apt/lists/*
COPY pyproject.toml README.md /app/
COPY app /app/app
RUN pip install --no-cache-dir --upgrade pip setuptools
RUN extras=".[gis]" \
&& if [ "$GEOINTEL_INSTALL_AI" = "true" ]; then extras=".[gis,ai]"; fi \
&& pip install --no-cache-dir "$extras"
COPY . /app
RUN python scripts/gis_import_smoke.py
EXPOSE 8000
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
geointel/backend/README.md
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geointel/backend/alembic.ini
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[alembic]
script_location = alembic
prepend_sys_path = .
sqlalchemy.url = postgresql+psycopg://geointel:geointel@localhost:5432/geointel
[loggers]
keys = root,sqlalchemy,alembic
[handlers]
keys = console
[formatters]
keys = generic
[logger_root]
level = WARNING
handlers = console
qualname =
[logger_sqlalchemy]
level = INFO
handlers =
qualname = sqlalchemy.engine
[logger_alembic]
level = INFO
handlers =
qualname = alembic
[handler_console]
class = StreamHandler
args = (sys.stderr,)
level = NOTSET
formatter = generic
[formatter_generic]
format = %(levelname)-5.5s [%(name)s] %(message)s
class_ = logging.Formatter
geointel/backend/alembic/env.py
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@@ -1,48 +0,0 @@
from __future__ import annotations
import os
import sys
from logging.config import fileConfig
from alembic import context
from sqlalchemy import engine_from_config, pool
sys.path.append(os.path.realpath(os.path.join(os.path.dirname(__file__), '..')))
from app.core.config import get_settings
from app.db.base import Base
import app.models.entities # noqa: F401
settings = get_settings()
config = context.config
if config.config_file_name is not None:
fileConfig(config.config_file_name)
config.set_main_option("sqlalchemy.url", settings.database_url)
target_metadata = Base.metadata
def run_migrations_offline() -> None:
url = config.get_main_option("sqlalchemy.url")
context.configure(url=url, target_metadata=target_metadata, literal_binds=True)
with context.begin_transaction():
context.run_migrations()
def run_migrations_online() -> None:
connectable = engine_from_config(
config.get_section(config.config_ini_section, {}),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
with connectable.connect() as connection:
context.configure(connection=connection, target_metadata=target_metadata)
with context.begin_transaction():
context.run_migrations()
if context.is_offline_mode():
run_migrations_offline()
else:
run_migrations_online()
geointel/backend/alembic/script.py.mako
-20
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@@ -1,20 +0,0 @@
"""
${message}
"""
from alembic import op
import sqlalchemy as sa
${imports}
revision = ${repr(revision)}
down_revision = ${repr(down_revision)}
branch_labels = ${repr(branch_labels)}
depends_on = ${repr(depends_on)}
def upgrade():
${upgrades if upgrades else "pass"}
def downgrade():
${downgrades if downgrades else "pass"}
geointel/backend/alembic/versions/202601110001_initial.py
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@@ -1,108 +0,0 @@
"""Initial PostGIS schema for Sprint 1 foundation."""
from alembic import op
import sqlalchemy as sa
from geoalchemy2 import Geometry
revision = "202601110001"
down_revision = None
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute("CREATE EXTENSION IF NOT EXISTS postgis")
op.execute("CREATE EXTENSION IF NOT EXISTS postgis_topology")
op.execute('CREATE EXTENSION IF NOT EXISTS "uuid-ossp"')
op.create_table(
"projects",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("name", sa.Text(), nullable=False),
sa.Column("description", sa.Text(), nullable=True),
sa.Column("region", sa.Text(), nullable=False, server_default="Kempen"),
sa.Column("status", sa.Text(), nullable=False, server_default="active"),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_table(
"areas",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("name", sa.Text(), nullable=False),
sa.Column("geometry", Geometry("MULTIPOLYGON", srid=4326), nullable=False),
sa.Column("original_crs", sa.Text(), nullable=True),
sa.Column("area_m2", sa.Float(), nullable=True),
sa.Column("bbox", Geometry("POLYGON", srid=4326), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_table(
"datasets",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("area_id", sa.UUID(as_uuid=True), sa.ForeignKey("areas.id", ondelete="SET NULL"), nullable=True),
sa.Column("name", sa.Text(), nullable=False),
sa.Column("dataset_type", sa.Text(), nullable=False),
sa.Column("source", sa.Text(), nullable=False),
sa.Column("storage_path", sa.Text(), nullable=True),
sa.Column("derived_from_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("crs", sa.Text(), nullable=True),
sa.Column("bounds_json", sa.JSON(), nullable=True),
sa.Column("resolution_json", sa.JSON(), nullable=True),
sa.Column("bands_json", sa.JSON(), nullable=True),
sa.Column("metadata_json", sa.JSON(), nullable=True),
sa.Column("status", sa.Text(), nullable=False, server_default="created"),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_table(
"dataset_versions",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False),
sa.Column("version", sa.Integer(), nullable=False, server_default="1"),
sa.Column("storage_path", sa.Text(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_table(
"analysis_runs",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("area_id", sa.UUID(as_uuid=True), sa.ForeignKey("areas.id", ondelete="SET NULL"), nullable=True),
sa.Column("analysis_type", sa.Text(), nullable=False),
sa.Column("status", sa.Text(), nullable=False),
sa.Column("parameters_json", sa.JSON(), nullable=False),
sa.Column("started_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("finished_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("error_message", sa.Text(), nullable=True),
)
op.create_table(
"exports",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
sa.Column("export_type", sa.Text(), nullable=False),
sa.Column("storage_path", sa.Text(), nullable=False),
sa.Column("metadata_json", sa.JSON(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_index("ix_areas_geometry", "areas", ["geometry"], postgresql_using="gist")
op.create_index("ix_areas_project_id", "areas", ["project_id"])
op.create_index("ix_datasets_project_id", "datasets", ["project_id"])
def downgrade() -> None:
op.drop_index("ix_datasets_project_id", table_name="datasets")
op.drop_index("ix_areas_project_id", table_name="areas")
op.drop_index("ix_areas_geometry", table_name="areas", postgresql_using="gist")
op.drop_table("exports")
op.drop_table("analysis_runs")
op.drop_table("dataset_versions")
op.drop_table("datasets")
op.drop_table("areas")
op.drop_table("projects")
geointel/backend/alembic/versions/202601120001_dataset_storage_metadata.py
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@@ -1,27 +0,0 @@
"""Add dataset storage metadata columns."""
from alembic import op
import sqlalchemy as sa
revision = "202601120001"
down_revision = "202601110001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("datasets", sa.Column("original_filename", sa.Text(), nullable=True))
op.add_column("datasets", sa.Column("stored_filename", sa.Text(), nullable=True))
op.add_column("datasets", sa.Column("content_type", sa.Text(), nullable=True))
op.add_column("datasets", sa.Column("size_bytes", sa.Integer(), nullable=True))
op.add_column("datasets", sa.Column("checksum_sha256", sa.Text(), nullable=True))
op.alter_column("datasets", "status", server_default="uploaded")
def downgrade() -> None:
op.drop_column("datasets", "checksum_sha256")
op.drop_column("datasets", "size_bytes")
op.drop_column("datasets", "content_type")
op.drop_column("datasets", "stored_filename")
op.drop_column("datasets", "original_filename")
geointel/backend/alembic/versions/20260611212435_add_jobs_table.py
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@@ -1,38 +0,0 @@
"""Add lightweight job table for sprint-3 async architecture foundation."""
from alembic import op
import sqlalchemy as sa
revision = "20260611212435"
down_revision = "202601120001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"jobs",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("job_type", sa.Text(), nullable=False),
sa.Column("status", sa.Text(), nullable=False, server_default="queued"),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("input_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("output_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("parameters_json", sa.JSON(), nullable=False),
sa.Column("result_json", sa.JSON(), nullable=True),
sa.Column("error_message", sa.Text(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
sa.Column("started_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("finished_at", sa.DateTime(timezone=True), nullable=True),
)
op.create_index("ix_jobs_project_id", "jobs", ["project_id"])
op.create_index("ix_jobs_status", "jobs", ["status"])
def downgrade() -> None:
op.drop_index("ix_jobs_status", table_name="jobs")
op.drop_index("ix_jobs_project_id", table_name="jobs")
op.drop_table("jobs")
geointel/backend/alembic/versions/202606120001_add_dataset_reference_metadata.py
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@@ -1,28 +0,0 @@
"""Add dataset reference and provenance metadata columns."""
from alembic import op
import sqlalchemy as sa
revision = "202606120001"
down_revision = "20260611212435"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("datasets", sa.Column("dataset_role", sa.Text(), nullable=False, server_default="source"))
op.add_column("datasets", sa.Column("source_name", sa.Text(), nullable=True))
op.add_column("datasets", sa.Column("reference_layer_name", sa.Text(), nullable=True))
op.add_column("datasets", sa.Column("source_metadata", sa.JSON(), nullable=True))
op.add_column("datasets", sa.Column("provenance_metadata", sa.JSON(), nullable=True))
op.add_column("datasets", sa.Column("imported_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()"), nullable=False))
def downgrade() -> None:
op.drop_column("datasets", "imported_at")
op.drop_column("datasets", "provenance_metadata")
op.drop_column("datasets", "source_metadata")
op.drop_column("datasets", "reference_layer_name")
op.drop_column("datasets", "source_name")
op.drop_column("datasets", "dataset_role")
geointel/backend/alembic/versions/202606120700_sprint7a_persistence_foundation.py
-76
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@@ -1,76 +0,0 @@
"""Add Sprint 7A vector feature and QA persistence foundation."""
from alembic import op
import sqlalchemy as sa
from geoalchemy2 import Geometry
revision = "202606120700"
down_revision = "202606120001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"vector_features",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False),
sa.Column("feature_class", sa.Text(), nullable=True),
sa.Column("source_feature_id", sa.Text(), nullable=True),
sa.Column("properties_json", sa.JSON(), nullable=True),
sa.Column("geometry", Geometry("GEOMETRY", srid=4326, spatial_index=False), nullable=False),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_index("ix_vector_features_dataset_id", "vector_features", ["dataset_id"])
op.create_index("ix_vector_features_geometry", "vector_features", ["geometry"], postgresql_using="gist")
op.create_table(
"quality_checks",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("job_id", sa.UUID(as_uuid=True), sa.ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True),
sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
sa.Column("candidate_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("reference_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False),
sa.Column("check_type", sa.Text(), nullable=False),
sa.Column("status", sa.Text(), nullable=False),
sa.Column("score", sa.Float(), nullable=True),
sa.Column("parameters_json", sa.JSON(), nullable=True),
sa.Column("findings_json", sa.JSON(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
)
op.create_index("ix_quality_checks_project_id", "quality_checks", ["project_id"])
op.create_index("ix_quality_checks_reference_dataset_id", "quality_checks", ["reference_dataset_id"])
op.create_index("ix_quality_checks_candidate_dataset_id", "quality_checks", ["candidate_dataset_id"])
op.create_index("ix_quality_checks_analysis_run_id", "quality_checks", ["analysis_run_id"])
op.create_table(
"metrics",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("quality_check_id", sa.UUID(as_uuid=True), sa.ForeignKey("quality_checks.id", ondelete="CASCADE"), nullable=True),
sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
sa.Column("metric_key", sa.Text(), nullable=False),
sa.Column("metric_value", sa.Float(), nullable=True),
sa.Column("metric_unit", sa.Text(), nullable=True),
sa.Column("label", sa.Text(), nullable=True),
sa.Column("metadata_json", sa.JSON(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
)
op.create_index("ix_metrics_quality_check_id", "metrics", ["quality_check_id"])
op.create_index("ix_metrics_analysis_run_id", "metrics", ["analysis_run_id"])
def downgrade() -> None:
op.drop_index("ix_metrics_analysis_run_id", table_name="metrics")
op.drop_index("ix_metrics_quality_check_id", table_name="metrics")
op.drop_table("metrics")
op.drop_index("ix_quality_checks_analysis_run_id", table_name="quality_checks")
op.drop_index("ix_quality_checks_candidate_dataset_id", table_name="quality_checks")
op.drop_index("ix_quality_checks_reference_dataset_id", table_name="quality_checks")
op.drop_index("ix_quality_checks_project_id", table_name="quality_checks")
op.drop_table("quality_checks")
op.drop_index("ix_vector_features_geometry", table_name="vector_features", postgresql_using="gist")
op.drop_index("ix_vector_features_dataset_id", table_name="vector_features")
op.drop_table("vector_features")
geointel/backend/alembic/versions/202606120800_sprint8_detection_foundation.py
-59
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@@ -1,59 +0,0 @@
"""Add Sprint 8 detection foundation."""
from alembic import op
import sqlalchemy as sa
from geoalchemy2 import Geometry
revision = "202606120800"
down_revision = "202606120700"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("analysis_runs", sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True))
op.add_column("analysis_runs", sa.Column("job_id", sa.UUID(as_uuid=True), sa.ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True))
op.add_column("analysis_runs", sa.Column("model_name", sa.String(length=255), nullable=True))
op.add_column("analysis_runs", sa.Column("model_version", sa.String(length=120), nullable=True))
op.add_column("analysis_runs", sa.Column("result_json", sa.JSON(), nullable=True))
op.add_column("analysis_runs", sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()"), nullable=False))
op.create_table(
"detections",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
sa.Column("job_id", sa.UUID(as_uuid=True), sa.ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True),
sa.Column("model_name", sa.String(length=255), nullable=False),
sa.Column("model_version", sa.String(length=120), nullable=True),
sa.Column("class_name", sa.String(length=120), nullable=False),
sa.Column("confidence", sa.Float(), nullable=False),
sa.Column("geometry", Geometry("GEOMETRY", srid=4326, spatial_index=False), nullable=False),
sa.Column("bbox_json", sa.JSON(), nullable=True),
sa.Column("source_tile_path", sa.String(length=500), nullable=True),
sa.Column("properties_json", sa.JSON(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()"), nullable=False),
)
op.create_index("ix_detections_project_id", "detections", ["project_id"])
op.create_index("ix_detections_dataset_id", "detections", ["dataset_id"])
op.create_index("ix_detections_analysis_run_id", "detections", ["analysis_run_id"])
op.create_index("ix_detections_class_name", "detections", ["class_name"])
op.create_index("ix_detections_geometry", "detections", ["geometry"], postgresql_using="gist")
def downgrade() -> None:
op.drop_index("ix_detections_geometry", table_name="detections", postgresql_using="gist")
op.drop_index("ix_detections_class_name", table_name="detections")
op.drop_index("ix_detections_analysis_run_id", table_name="detections")
op.drop_index("ix_detections_dataset_id", table_name="detections")
op.drop_index("ix_detections_project_id", table_name="detections")
op.drop_table("detections")
op.drop_column("analysis_runs", "created_at")
op.drop_column("analysis_runs", "result_json")
op.drop_column("analysis_runs", "model_version")
op.drop_column("analysis_runs", "model_name")
op.drop_column("analysis_runs", "job_id")
op.drop_column("analysis_runs", "dataset_id")
geointel/backend/alembic/versions/202606120900_sprint9_segmentation_foundation.py
-51
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@@ -1,51 +0,0 @@
"""Add Sprint 9 segmentation foundation."""
from alembic import op
import sqlalchemy as sa
from geoalchemy2 import Geometry
revision = "202606120900"
down_revision = "202606120800"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"segmentations",
sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
sa.Column("job_id", sa.UUID(as_uuid=True), sa.ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True),
sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
sa.Column("model_name", sa.String(length=255), nullable=False),
sa.Column("model_version", sa.String(length=120), nullable=True),
sa.Column("class_name", sa.String(length=120), nullable=False),
sa.Column("confidence", sa.Float(), nullable=True),
sa.Column("geometry", Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False),
sa.Column("bbox_json", sa.JSON(), nullable=True),
sa.Column("area_m2", sa.Float(), nullable=True),
sa.Column("mask_path", sa.Text(), nullable=True),
sa.Column("source_tile_path", sa.String(length=500), nullable=True),
sa.Column("tile_index", sa.Integer(), nullable=True),
sa.Column("properties_json", sa.JSON(), nullable=True),
sa.Column("provenance_json", sa.JSON(), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()"), nullable=False),
)
op.create_index("ix_segmentations_project_id", "segmentations", ["project_id"])
op.create_index("ix_segmentations_dataset_id", "segmentations", ["dataset_id"])
op.create_index("ix_segmentations_analysis_run_id", "segmentations", ["analysis_run_id"])
op.create_index("ix_segmentations_job_id", "segmentations", ["job_id"])
op.create_index("ix_segmentations_class_name", "segmentations", ["class_name"])
op.create_index("ix_segmentations_geometry", "segmentations", ["geometry"], postgresql_using="gist")
def downgrade() -> None:
op.drop_index("ix_segmentations_geometry", table_name="segmentations", postgresql_using="gist")
op.drop_index("ix_segmentations_class_name", table_name="segmentations")
op.drop_index("ix_segmentations_job_id", table_name="segmentations")
op.drop_index("ix_segmentations_analysis_run_id", table_name="segmentations")
op.drop_index("ix_segmentations_dataset_id", table_name="segmentations")
op.drop_index("ix_segmentations_project_id", table_name="segmentations")
op.drop_table("segmentations")
geointel/backend/alembic/versions/202607140001_temporal_dataset_foundation.py
-72
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@@ -1,72 +0,0 @@
"""Add temporal dataset metadata and durable dataset-version provenance."""
from alembic import op
import sqlalchemy as sa
revision = "202607140001"
down_revision = "202606120900"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("datasets", sa.Column("temporal_series_key", sa.String(length=255), nullable=True))
op.add_column("datasets", sa.Column("observed_at", sa.DateTime(timezone=True), nullable=True))
op.add_column("datasets", sa.Column("valid_from", sa.DateTime(timezone=True), nullable=True))
op.add_column("datasets", sa.Column("valid_to", sa.DateTime(timezone=True), nullable=True))
op.add_column("datasets", sa.Column("temporal_granularity", sa.String(length=32), nullable=True))
op.add_column("datasets", sa.Column("source_version", sa.String(length=120), nullable=True))
op.add_column("dataset_versions", sa.Column("source_version", sa.String(length=120), nullable=True))
op.add_column("dataset_versions", sa.Column("observed_at", sa.DateTime(timezone=True), nullable=True))
op.add_column("dataset_versions", sa.Column("valid_from", sa.DateTime(timezone=True), nullable=True))
op.add_column("dataset_versions", sa.Column("valid_to", sa.DateTime(timezone=True), nullable=True))
op.add_column("dataset_versions", sa.Column("checksum_sha256", sa.String(length=64), nullable=True))
op.add_column("dataset_versions", sa.Column("source_metadata", sa.JSON(), nullable=True))
op.add_column("dataset_versions", sa.Column("provenance_metadata", sa.JSON(), nullable=True))
op.create_index(
"ix_datasets_project_temporal_series_observed",
"datasets",
["project_id", "temporal_series_key", "observed_at"],
)
op.create_index("ix_dataset_versions_dataset_version", "dataset_versions", ["dataset_id", "version"], unique=True)
op.create_index(
"ix_vector_features_dataset_source_feature",
"vector_features",
["dataset_id", "source_feature_id"],
)
op.create_check_constraint(
"ck_datasets_temporal_valid_range",
"datasets",
"valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from",
)
op.create_check_constraint(
"ck_dataset_versions_temporal_valid_range",
"dataset_versions",
"valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from",
)
def downgrade() -> None:
op.drop_constraint("ck_dataset_versions_temporal_valid_range", "dataset_versions", type_="check")
op.drop_constraint("ck_datasets_temporal_valid_range", "datasets", type_="check")
op.drop_index("ix_vector_features_dataset_source_feature", table_name="vector_features")
op.drop_index("ix_dataset_versions_dataset_version", table_name="dataset_versions")
op.drop_index("ix_datasets_project_temporal_series_observed", table_name="datasets")
op.drop_column("dataset_versions", "provenance_metadata")
op.drop_column("dataset_versions", "source_metadata")
op.drop_column("dataset_versions", "checksum_sha256")
op.drop_column("dataset_versions", "valid_to")
op.drop_column("dataset_versions", "valid_from")
op.drop_column("dataset_versions", "observed_at")
op.drop_column("dataset_versions", "source_version")
op.drop_column("datasets", "source_version")
op.drop_column("datasets", "temporal_granularity")
op.drop_column("datasets", "valid_to")
op.drop_column("datasets", "valid_from")
op.drop_column("datasets", "observed_at")
op.drop_column("datasets", "temporal_series_key")
geointel/backend/alembic/versions/202607150001_detection_reviews.py
-64
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@@ -1,64 +0,0 @@
"""Add durable operator review decisions for detection QA evidence."""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
revision = "202607150001"
down_revision = "202607140001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"detection_reviews",
sa.Column("id", postgresql.UUID(as_uuid=True), nullable=False),
sa.Column("project_id", postgresql.UUID(as_uuid=True), nullable=False),
sa.Column("quality_check_id", postgresql.UUID(as_uuid=True), nullable=False),
sa.Column("analysis_run_id", postgresql.UUID(as_uuid=True), nullable=True),
sa.Column("evidence_role", sa.String(length=32), nullable=False),
sa.Column("evidence_feature_id", sa.String(length=255), nullable=False),
sa.Column("detection_id", postgresql.UUID(as_uuid=True), nullable=True),
sa.Column("reference_feature_id", postgresql.UUID(as_uuid=True), nullable=True),
sa.Column("decision", sa.String(length=64), server_default="unreviewed", nullable=False),
sa.Column("notes", sa.Text(), nullable=True),
sa.Column("reviewed_by", sa.String(length=120), server_default="operator", nullable=False),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
sa.CheckConstraint(
"evidence_role IN ('false_positive', 'false_negative')",
name="ck_detection_reviews_evidence_role",
),
sa.CheckConstraint(
"decision IN ('confirmed_model_false_positive', 'confirmed_model_false_negative', "
"'reference_gap_or_change', 'qa_alignment_mismatch', "
"'imagery_obscured_or_uncertain', 'uncertain', 'unreviewed')",
name="ck_detection_reviews_decision",
),
sa.ForeignKeyConstraint(["analysis_run_id"], ["analysis_runs.id"], ondelete="SET NULL"),
sa.ForeignKeyConstraint(["detection_id"], ["detections.id"], ondelete="SET NULL"),
sa.ForeignKeyConstraint(["project_id"], ["projects.id"], ondelete="CASCADE"),
sa.ForeignKeyConstraint(["quality_check_id"], ["quality_checks.id"], ondelete="CASCADE"),
sa.ForeignKeyConstraint(["reference_feature_id"], ["vector_features.id"], ondelete="SET NULL"),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint(
"quality_check_id",
"evidence_role",
"evidence_feature_id",
name="uq_detection_reviews_evidence",
),
)
op.create_index("ix_detection_reviews_project_id", "detection_reviews", ["project_id"])
op.create_index("ix_detection_reviews_quality_check_id", "detection_reviews", ["quality_check_id"])
op.create_index("ix_detection_reviews_analysis_run_id", "detection_reviews", ["analysis_run_id"])
op.create_index("ix_detection_reviews_decision", "detection_reviews", ["decision"])
def downgrade() -> None:
op.drop_index("ix_detection_reviews_decision", table_name="detection_reviews")
op.drop_index("ix_detection_reviews_analysis_run_id", table_name="detection_reviews")
op.drop_index("ix_detection_reviews_quality_check_id", table_name="detection_reviews")
op.drop_index("ix_detection_reviews_project_id", table_name="detection_reviews")
op.drop_table("detection_reviews")
geointel/backend/alembic/versions/202607160001_vector_feature_municipality_index.py
-22
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@@ -1,22 +0,0 @@
"""Index partitioned vector features by dataset and municipality."""
from alembic import op
import sqlalchemy as sa
revision = "202607160001"
down_revision = "202607150001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_index(
"ix_vector_features_dataset_municipality",
"vector_features",
["dataset_id", sa.text("(properties_json ->> 'municipality')")],
)
def downgrade() -> None:
op.drop_index("ix_vector_features_dataset_municipality", table_name="vector_features")
geointel/backend/alembic/versions/202607260001_aoi_operations.py
-65
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@@ -1,65 +0,0 @@
"""Add resumable AOI parent and partition operations."""
from alembic import op
import sqlalchemy as sa
from geoalchemy2 import Geometry
revision = "202607260001"
down_revision = "202607160001"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"aoi_operations",
sa.Column("id", sa.UUID(), primary_key=True),
sa.Column("project_id", sa.UUID(), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
sa.Column("area_id", sa.UUID(), sa.ForeignKey("areas.id", ondelete="SET NULL")),
sa.Column("parent_job_id", sa.UUID(), sa.ForeignKey("jobs.id", ondelete="SET NULL")),
sa.Column("operation_type", sa.String(128), nullable=False),
sa.Column("status", sa.String(32), nullable=False),
sa.Column("geometry", Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False),
sa.Column("request_json", sa.JSON(), nullable=False),
sa.Column("plan_json", sa.JSON(), nullable=False),
sa.Column("result_json", sa.JSON()),
sa.Column("error_message", sa.Text()),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()),
sa.Column("started_at", sa.DateTime(timezone=True)),
sa.Column("finished_at", sa.DateTime(timezone=True)),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now()),
sa.CheckConstraint("status IN ('queued', 'running', 'partial', 'success', 'failed', 'cancelled')", name="ck_aoi_operations_status"),
)
op.create_index("ix_aoi_operations_project_status", "aoi_operations", ["project_id", "status"])
op.create_index("ix_aoi_operations_geometry", "aoi_operations", ["geometry"], postgresql_using="gist")
op.create_table(
"aoi_operation_partitions",
sa.Column("id", sa.UUID(), primary_key=True),
sa.Column("operation_id", sa.UUID(), sa.ForeignKey("aoi_operations.id", ondelete="CASCADE"), nullable=False),
sa.Column("child_job_id", sa.UUID(), sa.ForeignKey("jobs.id", ondelete="SET NULL")),
sa.Column("partition_key", sa.String(255), nullable=False),
sa.Column("provider_key", sa.String(120), nullable=False),
sa.Column("product_key", sa.String(120), nullable=False),
sa.Column("ordinal", sa.Integer(), nullable=False),
sa.Column("status", sa.String(32), nullable=False),
sa.Column("geometry", Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False),
sa.Column("attempt_count", sa.Integer(), nullable=False, server_default="0"),
sa.Column("max_attempts", sa.Integer(), nullable=False, server_default="3"),
sa.Column("checkpoint_json", sa.JSON()),
sa.Column("result_json", sa.JSON()),
sa.Column("error_message", sa.Text()),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()),
sa.Column("started_at", sa.DateTime(timezone=True)),
sa.Column("finished_at", sa.DateTime(timezone=True)),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now()),
sa.CheckConstraint("status IN ('queued', 'running', 'success', 'failed', 'skipped')", name="ck_aoi_operation_partitions_status"),
sa.UniqueConstraint("operation_id", "partition_key", name="uq_aoi_operation_partition_key"),
)
op.create_index("ix_aoi_operation_partitions_operation_status", "aoi_operation_partitions", ["operation_id", "status"])
op.create_index("ix_aoi_operation_partitions_geometry", "aoi_operation_partitions", ["geometry"], postgresql_using="gist")
def downgrade() -> None:
op.drop_table("aoi_operation_partitions")
op.drop_table("aoi_operations")
geointel/backend/app/.gitkeep
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geointel/backend/app/__init__.py
-3
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@@ -1,3 +0,0 @@
from app.models.entities import AnalysisRun, Area, Dataset, Export, Project
__all__ = ["AnalysisRun", "Area", "Dataset", "Export", "Project"]
geointel/backend/app/ai/.gitkeep
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geointel/backend/app/analysis/.gitkeep
View File
geointel/backend/app/api/.gitkeep
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geointel/backend/app/api/routes/.gitkeep
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geointel/backend/app/api/routes/__init__.py
-1
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@@ -1 +0,0 @@
__all__ = ["analysis", "areas", "assistant", "auth", "datasets", "health", "projects", "exports", "jobs", "external", "qa", "temporal"]
geointel/backend/app/api/routes/analysis.py
-42
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@@ -1,42 +0,0 @@
from __future__ import annotations
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.core.errors import AppError
from app.db.session import get_db
from app.models import Dataset
from app.schemas import Envelope, JobRead
from app.schemas.analysis import ChangeDetectionRequest
from app.services.change_detection_service import ChangeDetectionService
from app.services.job_service import JobService
from app.utils.response import envelope
router = APIRouter(prefix="/analysis", tags=["analysis"])
@router.post("/change-detection", response_model=Envelope[JobRead])
def run_change_detection(
payload: ChangeDetectionRequest,
db: Session = Depends(get_db),
) -> dict:
source_dataset = db.get(Dataset, payload.source_dataset_id)
if not source_dataset:
raise AppError(code="DATASET_NOT_FOUND", message="Source dataset not found", status_code=404)
ChangeDetectionService._get_project_vector_dataset(db, payload.source_dataset_id, source_dataset.project_id, "Source")
job = JobService.run_sync_job(
db=db,
project_id=source_dataset.project_id,
job_type="analysis.change-detection",
parameters=payload.model_dump(mode="json"),
input_dataset_id=payload.source_dataset_id,
operation=lambda: ChangeDetectionService.compare_vector_datasets(
db=db,
project_id=source_dataset.project_id,
source_dataset_id=payload.source_dataset_id,
target_dataset_id=payload.target_dataset_id,
iou_threshold=payload.iou_threshold,
include_unchanged=payload.include_unchanged,
).model_dump(mode="json"),
)
return envelope(job)
geointel/backend/app/api/routes/aoi_operations.py
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from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas.aoi_operation import AoiOperationCreate, AoiOperationList, AoiOperationRead, AoiPartitionCheckpoint, AoiPartitionComplete, AoiPartitionFail, AoiPartitionRead
from app.schemas.common import Envelope
from app.services.aoi_operation_service import AoiOperationService
from app.services.aoi_operation_executor import AoiOperationExecutor
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}/aoi-operations", tags=["aoi-operations"])
@router.post("", status_code=201, response_model=Envelope[AoiOperationRead])
def create_operation(project_id: UUID, payload: AoiOperationCreate, db: Session = Depends(get_db)):
return envelope(AoiOperationService.create(db, project_id, payload))
@router.get("", response_model=Envelope[AoiOperationList])
def list_operations(project_id: UUID, limit: int = Query(default=50, ge=1, le=200), db: Session = Depends(get_db)):
return envelope(AoiOperationService.list(db, project_id, limit))
@router.get("/{operation_id}", response_model=Envelope[AoiOperationRead])
def read_operation(project_id: UUID, operation_id: UUID, db: Session = Depends(get_db)):
return envelope(AoiOperationService.read(db, project_id, operation_id))
@router.post("/{operation_id}/partitions/claim", response_model=Envelope[AoiPartitionRead | None])
def claim_partition(project_id: UUID, operation_id: UUID, db: Session = Depends(get_db)):
partition = AoiOperationService.claim_next(db, project_id, operation_id)
return envelope(AoiPartitionRead.model_validate(partition).model_dump() if partition else None)
@router.post("/{operation_id}/execute-next", response_model=Envelope[AoiOperationRead])
def execute_next_partition(project_id: UUID, operation_id: UUID, db: Session = Depends(get_db)):
return envelope(AoiOperationExecutor.execute_next(db, project_id, operation_id))
@router.put("/{operation_id}/partitions/{partition_id}/checkpoint", response_model=Envelope[AoiPartitionRead])
def checkpoint_partition(project_id: UUID, operation_id: UUID, partition_id: UUID, payload: AoiPartitionCheckpoint, db: Session = Depends(get_db)):
partition = AoiOperationService.checkpoint(db, project_id, operation_id, partition_id, payload.checkpoint_json)
return envelope(AoiPartitionRead.model_validate(partition).model_dump())
@router.post("/{operation_id}/partitions/{partition_id}/complete", response_model=Envelope[AoiOperationRead])
def complete_partition(project_id: UUID, operation_id: UUID, partition_id: UUID, payload: AoiPartitionComplete, db: Session = Depends(get_db)):
return envelope(AoiOperationService.complete(db, project_id, operation_id, partition_id, payload.result_json, payload.skipped))
@router.post("/{operation_id}/partitions/{partition_id}/fail", response_model=Envelope[AoiOperationRead])
def fail_partition(project_id: UUID, operation_id: UUID, partition_id: UUID, payload: AoiPartitionFail, db: Session = Depends(get_db)):
return envelope(AoiOperationService.fail(db, project_id, operation_id, partition_id, payload.error_message, payload.retryable, payload.details))
geointel/backend/app/api/routes/areas.py
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from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, Query
from fastapi import HTTPException
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.models import Area
from app.schemas import Envelope
from app.schemas.area import AreaCreate, AreaList, AreaRead, AreaUpdate, MunicipalitySearchList
from app.services.area_service import AreaService
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}/areas", tags=["areas"])
@router.get("", response_model=Envelope[AreaList])
def list_areas(
project_id: UUID,
limit: int = Query(default=50, ge=1, le=200),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
):
areas, total = AreaService.list_areas(db, project_id=project_id, limit=limit, offset=offset)
return envelope({"items": [AreaService.serialize_area(area) for area in areas], "total": total, "limit": limit, "offset": offset})
@router.post("", status_code=201, response_model=Envelope[AreaRead])
def create_area(project_id: UUID, payload: AreaCreate, db: Session = Depends(get_db)):
area = AreaService.create_area(db, project_id, payload)
return envelope(AreaService.serialize_area(area))
@router.get("/municipalities", response_model=Envelope[MunicipalitySearchList])
def search_municipalities(
project_id: UUID,
query: str = Query(default="", max_length=120),
limit: int = Query(default=20, ge=1, le=50),
db: Session = Depends(get_db),
):
items, total = AreaService.search_municipalities(db, project_id, query, limit)
return envelope({"items": items, "total": total})
@router.post("/municipalities/{niscode}/activate", response_model=Envelope[AreaRead])
def activate_municipality(project_id: UUID, niscode: str, db: Session = Depends(get_db)):
area = AreaService.activate_municipality(db, project_id, niscode)
return envelope(AreaService.serialize_area(area))
@router.get("/{area_id}", response_model=Envelope[AreaRead])
def get_area(
project_id: UUID,
area_id: UUID,
db: Session = Depends(get_db),
):
area = AreaService.get_area(db, area_id)
if area.project_id != project_id:
raise HTTPException(status_code=404, detail="Area not found")
return envelope(AreaService.serialize_area(area))
@router.patch("/{area_id}", response_model=Envelope[AreaRead])
def update_area(
project_id: UUID,
area_id: UUID,
payload: AreaUpdate,
db: Session = Depends(get_db),
):
existing = db.get(Area, area_id)
if not existing or existing.project_id != project_id:
raise HTTPException(status_code=404, detail="Area not found")
area = AreaService.update_area(db, area_id, payload)
return envelope(AreaService.serialize_area(area))
geointel/backend/app/api/routes/assistant.py
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from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope
from app.schemas.assistant import (
AssistantModelList,
AssistantQueryRequest,
AssistantQueryResponse,
AssistantStatus,
)
from app.services.geo_assistant_service import GeoAssistantService
from app.utils.response import envelope
router = APIRouter(tags=["assistant"])
@router.get("/assistant/status", response_model=Envelope[AssistantStatus])
def assistant_status() -> dict:
return envelope(GeoAssistantService().status().model_dump())
@router.get("/assistant/models", response_model=Envelope[AssistantModelList])
def assistant_models() -> dict:
service = GeoAssistantService()
models = service.list_models()
return envelope(
{
"items": [model.model_dump() for model in models],
"total": len(models),
"default_model": service.settings.ollama_default_model,
}
)
@router.post(
"/projects/{project_id}/assistant/query",
response_model=Envelope[AssistantQueryResponse],
)
def assistant_query(
project_id: UUID,
payload: AssistantQueryRequest,
db: Session = Depends(get_db),
) -> dict:
return envelope(GeoAssistantService().query(db, project_id=project_id, payload=payload).model_dump())
geointel/backend/app/api/routes/auth.py
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from __future__ import annotations
from datetime import UTC, datetime
from fastapi import APIRouter, Depends, Request, Response, status
from sqlalchemy.orm import Session
from app.core.config import get_settings
from app.core.errors import AppError
from app.db.session import get_db
from app.schemas.auth import AuthLoginRequest, AuthSession, AuthSessionEnvelope
from app.services.auth_service import AuthPrincipal, AuthService
from app.services.demo_workflow_service import DemoWorkflowService
router = APIRouter(prefix="/auth", tags=["auth"])
COOKIE_NAME = "geointel_session"
def _session_from_principal(principal: AuthPrincipal, *, guest_access_enabled: bool) -> AuthSession:
return AuthSession(
authentication_required=True,
authenticated=True,
username=principal.username,
expires_at=datetime.fromtimestamp(principal.expires_at, tz=UTC),
role=principal.role,
guest_access_enabled=guest_access_enabled,
guest_project_id=principal.project_id,
)
def _session_payload(request: Request) -> AuthSession:
settings = get_settings()
guest_access_enabled = settings.auth_enabled and settings.guest_access_enabled
if not settings.auth_enabled:
return AuthSession(
authentication_required=False,
authenticated=True,
guest_access_enabled=False,
)
principal = AuthService.verify_session_token(request.cookies.get(COOKIE_NAME), settings)
if principal is None:
return AuthSession(
authentication_required=True,
authenticated=False,
guest_access_enabled=guest_access_enabled,
)
return _session_from_principal(
principal,
guest_access_enabled=guest_access_enabled,
)
def _set_session_cookie(
*,
request: Request,
response: Response,
token: str,
max_age: int,
) -> None:
forwarded_proto = request.headers.get("x-forwarded-proto", "").split(",", 1)[0].strip().lower()
response.set_cookie(
key=COOKIE_NAME,
value=token,
max_age=max_age,
httponly=True,
secure=forwarded_proto == "https" or request.url.scheme == "https",
samesite="strict",
path="/",
)
@router.get("/session", response_model=AuthSessionEnvelope)
def session(request: Request) -> AuthSessionEnvelope:
return AuthSessionEnvelope(data=_session_payload(request))
@router.post("/login", response_model=AuthSessionEnvelope)
def login(payload: AuthLoginRequest, request: Request, response: Response) -> AuthSessionEnvelope:
settings = get_settings()
if not settings.auth_enabled:
raise AppError(
code="AUTHENTICATION_DISABLED",
message="Operator authentication is not enabled on this runtime",
status_code=status.HTTP_409_CONFLICT,
)
client_host = request.client.host if request.client else "unknown"
throttle_key = f"{client_host}:{payload.username.casefold()}"
retry_after = AuthService.retry_after_seconds(throttle_key)
if retry_after:
raise AppError(
code="LOGIN_RATE_LIMITED",
message="Te veel mislukte aanmeldpogingen. Probeer later opnieuw.",
details={"retry_after_seconds": retry_after},
status_code=status.HTTP_429_TOO_MANY_REQUESTS,
)
if not AuthService.credentials_match(payload.username, payload.password, settings):
AuthService.record_failure(throttle_key)
raise AppError(
code="INVALID_CREDENTIALS",
message="Gebruikersnaam of wachtwoord is onjuist.",
status_code=status.HTTP_401_UNAUTHORIZED,
)
AuthService.clear_failures(throttle_key)
token = AuthService.create_session_token(payload.username, settings)
principal = AuthService.verify_session_token(token, settings)
if principal is None: # pragma: no cover - defensive invariant
raise AppError(
code="SESSION_CREATION_FAILED",
message="De beveiligde sessie kon niet worden aangemaakt.",
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
)
_set_session_cookie(
request=request,
response=response,
token=token,
max_age=settings.auth_session_ttl_seconds,
)
return AuthSessionEnvelope(
data=_session_from_principal(
principal,
guest_access_enabled=settings.guest_access_enabled,
)
)
@router.post("/guest", response_model=AuthSessionEnvelope)
def guest_login(
request: Request,
response: Response,
db: Session = Depends(get_db),
) -> AuthSessionEnvelope:
settings = get_settings()
if not settings.auth_enabled or not settings.guest_access_enabled:
raise AppError(
code="GUEST_ACCESS_DISABLED",
message="Gasttoegang is niet ingeschakeld op deze GeoIntel-installatie.",
status_code=status.HTTP_403_FORBIDDEN,
)
demo = DemoWorkflowService.seed(db)
token = AuthService.create_session_token(
settings.guest_display_name,
settings,
role="guest",
project_id=demo.project_id,
ttl_seconds=settings.guest_session_ttl_seconds,
)
principal = AuthService.verify_session_token(token, settings)
if principal is None: # pragma: no cover - defensive invariant
raise AppError(
code="SESSION_CREATION_FAILED",
message="De tijdelijke gastensessie kon niet worden aangemaakt.",
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
)
_set_session_cookie(
request=request,
response=response,
token=token,
max_age=settings.guest_session_ttl_seconds,
)
return AuthSessionEnvelope(
data=_session_from_principal(
principal,
guest_access_enabled=True,
)
)
@router.post("/logout", response_model=AuthSessionEnvelope)
def logout(response: Response) -> AuthSessionEnvelope:
settings = get_settings()
response.delete_cookie(key=COOKIE_NAME, path="/", httponly=True, samesite="strict")
return AuthSessionEnvelope(
data=AuthSession(
authentication_required=settings.auth_enabled,
authenticated=not settings.auth_enabled,
guest_access_enabled=settings.auth_enabled and settings.guest_access_enabled,
)
)
geointel/backend/app/api/routes/datasets.py
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geointel/backend/app/api/routes/demo.py
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from __future__ import annotations
from fastapi import APIRouter, Depends, status
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope
from app.schemas.demo import DemoWorkflowResponse
from app.services.demo_workflow_service import DemoWorkflowService
from app.utils.response import envelope
router = APIRouter(prefix="/demo", tags=["demo"])
@router.post(
"/workflow",
status_code=status.HTTP_201_CREATED,
response_model=Envelope[DemoWorkflowResponse],
)
def seed_demo_workflow(db: Session = Depends(get_db)) -> dict:
result: DemoWorkflowResponse = DemoWorkflowService.seed(db)
return envelope(result.model_dump())
geointel/backend/app/api/routes/detection.py
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from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import (
AnalysisQaResponse,
DetectionListResponse,
DetectionModelsResponse,
DetectionQaRequest,
DetectionRead,
DetectionRunListResponse,
DetectionRunRead,
DetectionRunRequest,
DetectionRunResponse,
Envelope,
GeoJsonFeatureCollection,
ModelAssetListResponse,
YoloPreflightResponse,
)
from app.services.detection_service import DetectionService
from app.services.model_asset_catalog_service import ModelAssetCatalogService
from app.services.model_registry_service import ModelRegistryService
from app.services.yolo_preflight_service import YoloPreflightService
from app.utils.response import envelope
router = APIRouter(prefix="/detection", tags=["detection"])
@router.get("/models", response_model=Envelope[DetectionModelsResponse])
def list_detection_models() -> dict:
return envelope({"models": [model.model_dump() for model in ModelRegistryService.list_model_capabilities()]})
@router.get("/model-assets", response_model=Envelope[ModelAssetListResponse])
def list_detection_model_assets() -> dict:
return envelope(ModelAssetCatalogService.list_assets().model_dump())
@router.get("/yolo/preflight", response_model=Envelope[YoloPreflightResponse])
def get_yolo_preflight(
tile_manifest_path: str | None = None,
check_model_load: bool = False,
model_asset_id: str | None = None,
) -> dict:
return envelope(
YoloPreflightService.run(
tile_manifest_path=tile_manifest_path,
check_model_load=check_model_load,
model_asset_id=model_asset_id,
)
)
@router.post("/run", response_model=Envelope[DetectionRunResponse])
def run_detection(payload: DetectionRunRequest, db: Session = Depends(get_db)) -> dict:
result = DetectionService.run_detection(
db=db,
project_id=payload.project_id,
dataset_id=payload.dataset_id,
model_id=payload.model_id,
model_asset_id=payload.model_asset_id,
confidence_threshold=payload.confidence_threshold,
class_filter=payload.class_filter,
tile_manifest_path=payload.tile_manifest_path,
parameters_json=payload.parameters_json,
)
return envelope(result.model_dump())
@router.get("/runs", response_model=Envelope[DetectionRunListResponse])
def list_detection_runs(
project_id: UUID | None = None,
dataset_id: UUID | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(DetectionService.list_runs(db, project_id=project_id, dataset_id=dataset_id).model_dump())
@router.get("/runs/{analysis_run_id}", response_model=Envelope[DetectionRunRead])
def get_detection_run(analysis_run_id: UUID, db: Session = Depends(get_db)) -> dict:
return envelope(DetectionService.get_run(db, analysis_run_id).model_dump())
@router.get(
"/runs/{analysis_run_id}/detections",
response_model=Envelope[DetectionListResponse],
)
def list_detection_run_detections(
analysis_run_id: UUID,
dataset_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.list_detections(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
).model_dump()
)
@router.get(
"/datasets/{dataset_id}/detections",
response_model=Envelope[DetectionListResponse],
)
def list_dataset_detections(
dataset_id: UUID,
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.list_detections(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
).model_dump()
)
@router.get("/detections/{detection_id}", response_model=Envelope[DetectionRead])
def get_detection(detection_id: UUID, db: Session = Depends(get_db)) -> dict:
return envelope(DetectionService.get_detection(db, detection_id).model_dump())
@router.get(
"/runs/{analysis_run_id}/geojson",
response_model=Envelope[GeoJsonFeatureCollection],
)
def get_detection_run_geojson(
analysis_run_id: UUID,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.detections_to_geojson(
db,
analysis_run_id=analysis_run_id,
class_name=class_name,
min_confidence=min_confidence,
)
)
@router.get(
"/datasets/{dataset_id}/geojson",
response_model=Envelope[GeoJsonFeatureCollection],
)
def get_dataset_detection_geojson(
dataset_id: UUID,
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.detections_to_geojson(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
)
)
@router.post(
"/runs/{analysis_run_id}/qa/reference",
response_model=Envelope[AnalysisQaResponse],
)
def compare_detection_run_with_reference(
analysis_run_id: UUID,
payload: DetectionQaRequest,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.compare_detections_with_reference(
db=db,
analysis_run_id=analysis_run_id,
reference_dataset_id=payload.reference_dataset_id,
iou_threshold=payload.iou_threshold,
class_name=payload.class_name,
min_confidence=payload.min_confidence,
)
)
geointel/backend/app/api/routes/exports.py
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@@ -1,100 +0,0 @@
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, Query
from fastapi.responses import FileResponse
from sqlalchemy.orm import Session
from app.core.errors import AppError
from app.db.session import get_db
from app.schemas import Envelope
from app.schemas.export import (
ExportContentResponse,
ExportCreateResponse,
ExportListResponse,
ExportRead,
GeoJsonExportRequest,
MapResultExportRequest,
MetadataExportRequest,
ReportExportRequest,
)
from app.services.export_service import ExportService
from app.utils.response import envelope
router = APIRouter(prefix="/exports", tags=["exports"])
@router.post("/geojson", response_model=Envelope[ExportCreateResponse])
def export_geojson(payload: GeoJsonExportRequest, db: Session = Depends(get_db)):
if payload.export_kind == "vector_selection" and payload.dataset_id is not None and payload.bbox is not None:
return envelope(
ExportService.export_vector_selection_geojson(
db,
payload.dataset_id,
payload.bbox.model_dump(),
area_id=payload.area_id,
limit=payload.limit,
name=payload.name,
).model_dump(mode="json")
)
if payload.export_kind == "detection_run" and payload.analysis_run_id is not None:
return envelope(
ExportService.export_detection_run_geojson(db, payload.analysis_run_id, payload.name).model_dump(mode="json")
)
if payload.export_kind == "segmentation_run" and payload.analysis_run_id is not None:
return envelope(
ExportService.export_segmentation_run_geojson(db, payload.analysis_run_id, payload.name).model_dump(mode="json")
)
if payload.dataset_id is not None:
return envelope(ExportService.export_dataset_geojson(db, payload.dataset_id, payload.name).model_dump(mode="json"))
raise AppError(
code="INVALID_EXPORT_REQUEST",
message="GeoJSON export request does not match any supported export target",
status_code=422,
)
@router.post("/metadata", response_model=Envelope[ExportCreateResponse])
def export_project_metadata(payload: MetadataExportRequest, db: Session = Depends(get_db)):
return envelope(ExportService.export_project_metadata(db, payload.project_id, payload.name).model_dump(mode="json"))
@router.post("/report", response_model=Envelope[ExportCreateResponse])
def export_project_report(payload: ReportExportRequest, db: Session = Depends(get_db)):
return envelope(ExportService.export_project_report(db, payload.project_id, payload.name).model_dump(mode="json"))
@router.post("/map-result", response_model=Envelope[ExportCreateResponse])
def export_map_result(payload: MapResultExportRequest, db: Session = Depends(get_db)):
return envelope(ExportService.export_map_result(db, payload).model_dump(mode="json"))
@router.get(
"/projects/{project_id}/exports",
response_model=Envelope[ExportListResponse],
)
def list_project_exports(
project_id: UUID,
limit: int = Query(default=50, ge=1, le=100),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
):
return envelope(ExportService.list_project_exports(db, project_id, limit=limit, offset=offset).model_dump(mode="json"))
@router.get("/{export_id}", response_model=Envelope[ExportRead])
def get_export(export_id: UUID, db: Session = Depends(get_db)):
return envelope(ExportService.get_export(db, export_id).model_dump(mode="json"))
@router.get("/{export_id}/download")
def download_export(export_id: UUID, db: Session = Depends(get_db)):
path = ExportService.get_export_download_path(db, export_id)
media_type = "text/html" if path.suffix.lower() in {".html", ".htm"} else "application/json"
return FileResponse(path, filename=path.name, media_type=media_type)
@router.get("/{export_id}/content", response_model=Envelope[ExportContentResponse])
def get_export_content(export_id: UUID, db: Session = Depends(get_db)):
return envelope(ExportService.get_export_content(db, export_id).model_dump(mode="json"))
geointel/backend/app/api/routes/external.py
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from __future__ import annotations
from fastapi import APIRouter, Depends, Request
from sqlalchemy.orm import Session
from app.core.errors import AppError
from app.db.session import get_db
from app.models import Area, Project
from app.providers.registry import fetch_provider_data, get_provider, import_provider_dataset, list_provider_capabilities
from app.schemas import (
CoverageCatalogResponse,
CoverageResolveRequest,
CoverageResolveResponse,
Envelope,
ExternalFetchRequest,
ExternalFetchResponse,
ProviderCapabilitiesResponse,
ProviderCapabilityResponse,
ProviderImportRequest,
ProviderImportResponse,
ProviderLayersResponse,
ProviderStatusResponse,
)
from app.services.coverage_registry_service import CoverageRegistryService
from app.utils.response import envelope
router = APIRouter(prefix="/external", tags=["external"])
def _validate_area_in_project(db: Session, project_id, area_id: str | None) -> None:
if area_id is None:
return
area = db.get(Area, area_id)
if not area:
raise AppError(code="AREA_NOT_FOUND", message="Area not found", status_code=404)
if area.project_id != project_id:
raise AppError(code="INVALID_DATASET_SCOPE", message="Area does not belong to this project", status_code=400)
def _assert_project_exists(db: Session, project_id):
project = db.get(Project, project_id)
if not project:
raise AppError(code="PROJECT_NOT_FOUND", message="Project not found", status_code=404)
def _assert_guest_project_scope(request: Request, project_id) -> None:
principal = getattr(request.state, "auth_principal", None)
if (
getattr(principal, "role", None) == "guest"
and getattr(principal, "project_id", None) != project_id
):
raise AppError(
code="GUEST_PROJECT_SCOPE_REQUIRED",
message="Deze gastensessie heeft alleen toegang tot de GeoIntel-demowerkruimte.",
status_code=403,
)
def _normalize_layer_input(layers: list[str] | None) -> list[str]:
return [layer.strip() for layer in (layers or []) if isinstance(layer, str) and layer.strip()]
def _provider_payload(provider_name: str) -> dict:
return get_provider(provider_name).capability.to_dict()
@router.get("/providers", response_model=Envelope[ProviderCapabilitiesResponse])
def list_external_providers() -> dict:
return envelope({
"providers": [provider.to_dict() for provider in list_provider_capabilities()],
})
@router.get("/coverage/catalog", response_model=Envelope[CoverageCatalogResponse])
def get_coverage_catalog() -> dict:
return envelope(CoverageRegistryService.catalog().model_dump())
@router.post("/coverage/resolve", response_model=Envelope[CoverageResolveResponse])
def resolve_project_coverage(
payload: CoverageResolveRequest,
request: Request,
db: Session = Depends(get_db),
) -> dict:
_assert_guest_project_scope(request, payload.project_id)
result = CoverageRegistryService.resolve(
db,
project_id=payload.project_id,
bbox=payload.bbox,
themes=payload.themes,
)
return envelope(result.model_dump())
@router.get(
"/providers/capabilities",
response_model=Envelope[ProviderCapabilitiesResponse],
)
def get_external_provider_capabilities() -> dict:
return envelope({
"providers": [provider.to_dict() for provider in list_provider_capabilities()],
})
@router.get(
"/providers/{provider_name}",
response_model=Envelope[ProviderCapabilityResponse],
)
def get_external_provider(provider_name: str) -> dict:
return envelope(_provider_payload(provider_name))
@router.get(
"/providers/{provider_name}/layers",
response_model=Envelope[ProviderLayersResponse],
)
def get_external_provider_layers(provider_name: str) -> dict:
provider = get_provider(provider_name)
return envelope({
"provider_name": provider.provider_name,
"layers": provider.supported_layers,
})
@router.get(
"/providers/{provider_name}/status",
response_model=Envelope[ProviderStatusResponse],
)
def get_external_provider_status(provider_name: str) -> dict:
provider = get_provider(provider_name)
return envelope({
"provider_name": provider.provider_name,
"configured": provider.is_configured,
"status": provider.capability.status,
"limitation_message": provider.limitation_message,
})
@router.post(
"/providers/{provider_name}/import",
response_model=Envelope[ProviderImportResponse],
)
def import_external_provider_dataset(provider_name: str, payload: ProviderImportRequest) -> dict:
result = import_provider_dataset(
provider_name=provider_name,
project_id=payload.project_id,
area_id=payload.area_id,
layers=_normalize_layer_input(payload.layers),
requested_dataset_role=payload.dataset_role,
)
return envelope(result.model_dump())
def _run_fetch(payload: ExternalFetchRequest, provider_name: str) -> ExternalFetchResponse:
area_id_str = str(payload.area_id) if payload.area_id else None
response = fetch_provider_data(
provider_name=provider_name,
project_id=str(payload.project_id),
area_id=area_id_str,
layers=_normalize_layer_input(payload.layers),
)
return ExternalFetchResponse(
provider=provider_name,
status=response.get("status", "not_configured"),
message=response.get("message", "Provider fetch executed."),
requested_layers=_normalize_layer_input(payload.layers),
project_id=payload.project_id,
area_id=payload.area_id,
)
@router.post("/osm/fetch", response_model=Envelope[ExternalFetchResponse])
def fetch_osm(payload: ExternalFetchRequest, db: Session = Depends(get_db)) -> dict:
_assert_project_exists(db, payload.project_id)
_validate_area_in_project(db, payload.project_id, payload.area_id)
return envelope(_run_fetch(payload, "osm").model_dump())
@router.post("/grb/fetch", response_model=Envelope[ExternalFetchResponse])
def fetch_grb(payload: ExternalFetchRequest, db: Session = Depends(get_db)) -> dict:
_assert_project_exists(db, payload.project_id)
_validate_area_in_project(db, payload.project_id, payload.area_id)
return envelope(_run_fetch(payload, "grb").model_dump())
geointel/backend/app/api/routes/health.py
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from __future__ import annotations
from importlib import import_module
from pathlib import Path
from tempfile import NamedTemporaryFile
from alembic.config import Config
from alembic.script import ScriptDirectory
from fastapi import APIRouter, Response, status
from sqlalchemy import text
from app.core.config import get_settings
from app.db.session import get_engine
from app.providers.registry import list_provider_capabilities
from app.schemas.health import (
HealthResponse,
SystemCapabilities,
SystemCapabilitiesEnvelope,
)
from app.services.model_registry_service import ModelRegistryService
router = APIRouter()
def _dependency_enabled(module: str) -> bool:
try:
import_module(module)
return True
except Exception:
return False
def _expected_migration_heads() -> list[str]:
backend_root = Path(__file__).resolve().parents[3]
config = Config(str(backend_root / "alembic.ini"))
config.set_main_option("script_location", str(backend_root / "alembic"))
return list(ScriptDirectory.from_config(config).get_heads())
def _database_checks() -> dict[str, str]:
checks = {
"database": "degraded",
"postgis": "degraded",
"migration": "degraded",
}
try:
with get_engine().connect() as connection:
connection.execute(text("SELECT 1"))
checks["database"] = "ok"
postgis_version = connection.execute(
text("SELECT PostGIS_Version()")
).scalar_one()
checks["postgis"] = f"ok:{postgis_version}"
database_head = connection.execute(
text("SELECT version_num FROM alembic_version")
).scalar_one()
expected_heads = _expected_migration_heads()
if len(expected_heads) == 1 and database_head == expected_heads[0]:
checks["migration"] = f"ok:{database_head}"
else:
checks["migration"] = (
f"degraded:database={database_head};"
f"expected={','.join(expected_heads) or 'none'}"
)
except Exception:
return checks
return checks
def _storage_check(storage_root: str) -> str:
root = Path(storage_root).expanduser()
try:
root.mkdir(parents=True, exist_ok=True)
with NamedTemporaryFile(
prefix=".geointel-readiness-",
dir=root,
delete=True,
) as handle:
handle.write(b"ok")
handle.flush()
return "ok"
except OSError:
return "degraded"
def _readiness_payload() -> HealthResponse:
settings = get_settings()
checks = _database_checks()
checks["storage"] = _storage_check(settings.storage_root)
ready = all(
value == "ok" or value.startswith("ok:")
for value in checks.values()
)
return HealthResponse(
status="ok" if ready else "degraded",
service="geointel-backend",
version=settings.app_version,
build_sha=settings.build_sha,
build_time=settings.build_time,
database=checks["database"],
postgis=checks["postgis"],
migration=checks["migration"],
storage=checks["storage"],
checks=checks,
)
@router.get("/health/live", response_model=HealthResponse)
def liveness() -> HealthResponse:
settings = get_settings()
return HealthResponse(
status="ok",
service="geointel-backend",
version=settings.app_version,
build_sha=settings.build_sha,
build_time=settings.build_time,
)
def _readiness_response(response: Response) -> HealthResponse:
payload = _readiness_payload()
if payload.status != "ok":
response.status_code = status.HTTP_503_SERVICE_UNAVAILABLE
return payload
@router.get("/health", response_model=HealthResponse)
def readiness(response: Response) -> HealthResponse:
return _readiness_response(response)
@router.get("/health/ready", response_model=HealthResponse)
def readiness_explicit(response: Response) -> HealthResponse:
return _readiness_response(response)
@router.get(
"/api/v1/system/capabilities",
response_model=SystemCapabilitiesEnvelope,
)
def capabilities() -> SystemCapabilitiesEnvelope:
settings = get_settings()
providers = [item.to_dict() for item in list_provider_capabilities()]
configured_yolo = ModelRegistryService.get_model_capability(
settings.yolo_model_id,
settings=settings,
)
yolo_configured = bool(configured_yolo and configured_yolo.configured)
yolo_status = configured_yolo.status if configured_yolo else "not_configured"
configured_sam = ModelRegistryService.get_model_capability(
settings.sam_model_id,
settings=settings,
task_type="segmentation",
)
postgis_ready = _database_checks()["postgis"].startswith("ok:")
return SystemCapabilitiesEnvelope(
data=SystemCapabilities(
postgis=postgis_ready,
rasterio=_dependency_enabled("rasterio"),
geopandas=_dependency_enabled("geopandas"),
yolo=yolo_configured,
yolo_status=yolo_status,
sam=bool(configured_sam and configured_sam.configured),
grb="bounded",
sentinel="planned",
version=settings.app_version,
build_sha=settings.build_sha,
providers=providers,
)
)
geointel/backend/app/api/routes/jobs.py
-67
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from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope, JobCreate, JobList, JobRead, JobStatus
from app.services.job_service import JobService
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}", tags=["jobs"])
@router.post("/jobs", status_code=201, response_model=Envelope[JobRead])
def create_job(
project_id: UUID,
payload: JobCreate,
db: Session = Depends(get_db),
):
if payload.project_id != project_id:
raise HTTPException(status_code=400, detail="project_id mismatch")
return envelope(JobService.create_job(db, payload).model_dump())
@router.get("/jobs", response_model=Envelope[JobList])
def list_jobs(
project_id: UUID,
dataset_id: UUID | None = Query(default=None),
limit: int = Query(default=50, ge=1, le=200),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
):
items, total = JobService.list_jobs(
db,
project_id=project_id,
dataset_id=dataset_id,
limit=limit,
offset=offset,
)
return envelope(JobList(items=items, total=total, limit=limit, offset=offset).model_dump())
@router.get("/jobs/{job_id}", response_model=Envelope[JobRead])
def read_job(
project_id: UUID,
job_id: UUID,
db: Session = Depends(get_db),
):
job = JobService.get_job(db, job_id)
if job.project_id != project_id:
raise HTTPException(status_code=404, detail="Job not found")
return envelope(job.model_dump())
@router.get("/jobs/{job_id}/status", response_model=Envelope[JobStatus])
def read_job_status(
project_id: UUID,
job_id: UUID,
db: Session = Depends(get_db),
):
status_row = JobService.get_job_status(db, job_id)
if status_row["project_id"] != str(project_id):
raise HTTPException(status_code=404, detail="Job not found")
return envelope(JobStatus(**status_row).model_dump())
geointel/backend/app/api/routes/projects.py
-88
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@@ -1,88 +0,0 @@
from __future__ import annotations
from typing import Literal
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Query, Request, status
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope
from app.schemas.project import ProjectCreate, ProjectDeleteResult, ProjectList, ProjectRead, ProjectUpdate
from app.services.project_service import ProjectService
from app.utils.response import envelope
router = APIRouter(prefix="/projects", tags=["projects"])
@router.get("", response_model=Envelope[ProjectList])
def list_projects(
request: Request,
limit: int = Query(default=50, ge=1, le=200),
offset: int = Query(default=0, ge=0),
name: str | None = Query(default=None, min_length=1, max_length=255),
project_status: Literal["active", "archived", "all"] = Query(default="active", alias="status"),
db: Session = Depends(get_db),
):
principal = getattr(request.state, "auth_principal", None)
if principal is not None and principal.role == "guest":
project = ProjectService.get_project(db, principal.project_id)
status_matches = bool(
project is not None
and (project_status == "all" or project.status == project_status)
)
name_matches = bool(
project is not None
and (name is None or name.casefold() in project.name.casefold())
)
matches = project is not None and status_matches and name_matches
visible = [project] if matches and offset == 0 else []
return envelope(
{
"items": [ProjectRead.model_validate(item).model_dump() for item in visible[:limit]],
"total": 1 if matches else 0,
"limit": limit,
"offset": offset,
}
)
projects, total = ProjectService.list_projects(
db,
limit=limit,
offset=offset,
name=name,
project_status=project_status,
)
return envelope({"items": [ProjectRead.model_validate(item).model_dump() for item in projects], "total": total, "limit": limit, "offset": offset})
@router.post("", status_code=status.HTTP_201_CREATED, response_model=Envelope[ProjectRead])
def create_project(payload: ProjectCreate, db: Session = Depends(get_db)):
project = ProjectService.create_project(db, payload)
return envelope(ProjectRead.model_validate(project).model_dump())
@router.get("/{project_id}", response_model=Envelope[ProjectRead])
def get_project(project_id: UUID, db: Session = Depends(get_db)):
project = ProjectService.get_project(db, project_id)
if not project:
raise HTTPException(status_code=404, detail="Project not found")
return envelope(ProjectRead.model_validate(project).model_dump())
@router.patch("/{project_id}", response_model=Envelope[ProjectRead])
def update_project(project_id: UUID, payload: ProjectUpdate, db: Session = Depends(get_db)):
project = ProjectService.update_project(db, project_id, payload)
if not project:
raise HTTPException(status_code=404, detail="Project not found")
return envelope(ProjectRead.model_validate(project).model_dump())
@router.delete(
"/{project_id}",
status_code=status.HTTP_200_OK,
response_model=Envelope[ProjectDeleteResult],
)
def delete_project(project_id: UUID, db: Session = Depends(get_db)):
if not ProjectService.delete_project(db, project_id):
raise HTTPException(status_code=404, detail="Project not found")
return envelope({"deleted": True})
geointel/backend/app/api/routes/qa.py
-83
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@@ -1,83 +0,0 @@
from __future__ import annotations
import uuid
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.core.errors import AppError
from app.models import Dataset, Job
from app.schemas import Envelope, JobRead, QaProviderComparisonRequest
from app.services.qa_service import QaService
from app.services.job_service import JobService
from app.services.quality_service import QualityService
from app.utils.response import envelope
router = APIRouter(prefix="/qa", tags=["qa"])
@router.post("/detections-vs-reference", response_model=Envelope[JobRead])
def compare_candidate_with_reference(
payload: QaProviderComparisonRequest,
db: Session = Depends(get_db),
) -> dict:
candidate_dataset = db.get(Dataset, payload.candidate_dataset_id)
if not candidate_dataset:
raise AppError(code="DATASET_NOT_FOUND", message="Candidate dataset not found", status_code=404)
job = JobService.run_sync_job(
db=db,
project_id=candidate_dataset.project_id,
job_type="qa.compare-candidate-with-reference",
parameters=payload.model_dump(mode="json"),
input_dataset_id=candidate_dataset.id,
operation=lambda: QaService.compare_candidate_with_reference(
db=db,
project_id=candidate_dataset.project_id,
candidate_dataset_id=payload.candidate_dataset_id,
reference_dataset_id=payload.reference_dataset_id,
iou_threshold=payload.iou_threshold,
area_id=payload.area_id,
).model_dump(mode="json"),
)
result_json = job.get("result_json") if isinstance(job, dict) else None
if isinstance(result_json, dict) and job.get("status") == "success":
quality_check = QualityService.persist_quality_check(
db=db,
project_id=candidate_dataset.project_id,
job_id=uuid.UUID(str(job["id"])),
candidate_dataset_id=payload.candidate_dataset_id,
reference_dataset_id=payload.reference_dataset_id,
check_type="candidate_vs_reference",
status=str(result_json.get("status", "ok")),
score=result_json.get("f1_score"),
parameters=payload.model_dump(mode="json"),
findings={
"matches": result_json.get("matches"),
"false_positives": result_json.get("false_positives"),
"false_negatives": result_json.get("false_negatives"),
"warnings": result_json.get("warnings", []),
"unsupported_geometry": result_json.get("unsupported_geometry", False),
"unsupported_geometries": result_json.get("unsupported_geometries", []),
"match_evidence": result_json.get("match_evidence", []),
"false_positive_evidence": result_json.get("false_positive_evidence", []),
"false_negative_evidence": result_json.get("false_negative_evidence", []),
},
metrics={
"precision": result_json.get("precision"),
"recall": result_json.get("recall"),
"f1": result_json.get("f1_score"),
"mean_iou": result_json.get("mean_iou"),
"false_positive_count": result_json.get("false_positives"),
"false_negative_count": result_json.get("false_negatives"),
},
)
result_json["quality_check_id"] = str(quality_check.id)
job_record = db.get(Job, uuid.UUID(str(job["id"])))
if job_record:
job_record.result_json = result_json
db.add(job_record)
db.commit()
return envelope(job)
geointel/backend/app/api/routes/quality_checks.py
-93
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@@ -1,93 +0,0 @@
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope, QualityEvidenceResponse
from app.schemas.detection_review import DetectionReviewList, DetectionReviewRead, DetectionReviewUpsert
from app.schemas.qa import QualityCheckList
from app.services.detection_review_service import DetectionReviewService
from app.services.quality_evidence_service import QualityEvidenceService
from app.services.quality_check_service import QualityCheckService
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}", tags=["quality-checks"])
@router.get("/quality-checks", response_model=Envelope[QualityCheckList])
def list_quality_checks(
project_id: UUID,
limit: int = Query(default=50, ge=1, le=200),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
items, total = QualityCheckService.list_quality_checks(
db,
project_id=project_id,
limit=limit,
offset=offset,
)
return envelope(QualityCheckList(items=items, total=total, limit=limit, offset=offset).model_dump())
@router.get(
"/quality-checks/{quality_check_id}/evidence/geojson",
response_model=Envelope[QualityEvidenceResponse],
)
def get_quality_check_evidence_geojson(
project_id: UUID,
quality_check_id: UUID,
db: Session = Depends(get_db),
) -> dict:
return envelope(QualityEvidenceService.evidence_geojson(db, project_id=project_id, quality_check_id=quality_check_id))
@router.get(
"/quality-checks/{quality_check_id}/reviews",
response_model=Envelope[DetectionReviewList],
)
def list_detection_reviews(
project_id: UUID,
quality_check_id: UUID,
evidence_role: str | None = Query(default=None, pattern="^(false_positive|false_negative)$"),
decision: str | None = Query(default=None, max_length=64),
reviewed: bool | None = Query(default=None),
limit: int = Query(default=50, ge=1, le=200),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionReviewService.list_reviews(
db,
project_id=project_id,
quality_check_id=quality_check_id,
evidence_role=evidence_role,
decision=decision,
reviewed=reviewed,
limit=limit,
offset=offset,
).model_dump()
)
@router.post(
"/quality-checks/{quality_check_id}/reviews",
response_model=Envelope[DetectionReviewRead],
)
def upsert_detection_review(
project_id: UUID,
quality_check_id: UUID,
payload: DetectionReviewUpsert,
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionReviewService.upsert_review(
db,
project_id=project_id,
quality_check_id=quality_check_id,
payload=payload,
).model_dump()
)
geointel/backend/app/api/routes/segmentation.py
-172
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@@ -1,172 +0,0 @@
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import (
AnalysisQaResponse,
Envelope,
GeoJsonFeatureCollection,
SegmentationListResponse,
SegmentationModelsResponse,
SegmentationQaRequest,
SegmentationRead,
SegmentationRunListResponse,
SegmentationRunRead,
SegmentationRunRequest,
SegmentationRunResponse,
)
from app.services.model_registry_service import ModelRegistryService
from app.services.segmentation_service import SegmentationService
from app.utils.response import envelope
router = APIRouter(prefix="/segmentation", tags=["segmentation"])
@router.get("/models", response_model=Envelope[SegmentationModelsResponse])
def list_segmentation_models() -> dict:
return envelope({"models": [model.model_dump() for model in ModelRegistryService.list_model_capabilities(task_type="segmentation")]})
@router.post("/run", response_model=Envelope[SegmentationRunResponse])
def run_segmentation(payload: SegmentationRunRequest, db: Session = Depends(get_db)) -> dict:
result = SegmentationService.run_segmentation(
db=db,
project_id=payload.project_id,
dataset_id=payload.dataset_id,
model_id=payload.model_id,
confidence_threshold=payload.confidence_threshold,
class_filter=payload.class_filter,
tile_manifest_path=payload.tile_manifest_path,
parameters_json=payload.parameters_json,
)
return envelope(result.model_dump())
@router.get("/runs", response_model=Envelope[SegmentationRunListResponse])
def list_segmentation_runs(
project_id: UUID | None = None,
dataset_id: UUID | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(SegmentationService.list_runs(db, project_id=project_id, dataset_id=dataset_id).model_dump())
@router.get("/runs/{analysis_run_id}", response_model=Envelope[SegmentationRunRead])
def get_segmentation_run(analysis_run_id: UUID, db: Session = Depends(get_db)) -> dict:
return envelope(SegmentationService.get_run(db, analysis_run_id).model_dump())
@router.get(
"/runs/{analysis_run_id}/segmentations",
response_model=Envelope[SegmentationListResponse],
)
def list_segmentation_run_outputs(
analysis_run_id: UUID,
dataset_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.list_segmentations(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
).model_dump()
)
@router.get(
"/datasets/{dataset_id}/segmentations",
response_model=Envelope[SegmentationListResponse],
)
def list_dataset_segmentations(
dataset_id: UUID,
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.list_segmentations(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
).model_dump()
)
@router.get("/segmentations/{segmentation_id}", response_model=Envelope[SegmentationRead])
def get_segmentation(segmentation_id: UUID, db: Session = Depends(get_db)) -> dict:
return envelope(SegmentationService.get_segmentation(db, segmentation_id).model_dump())
@router.get(
"/runs/{analysis_run_id}/geojson",
response_model=Envelope[GeoJsonFeatureCollection],
)
def get_segmentation_run_geojson(
analysis_run_id: UUID,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.segmentations_to_geojson(
db,
analysis_run_id=analysis_run_id,
class_name=class_name,
min_confidence=min_confidence,
)
)
@router.get(
"/datasets/{dataset_id}/geojson",
response_model=Envelope[GeoJsonFeatureCollection],
)
def get_dataset_segmentation_geojson(
dataset_id: UUID,
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.segmentations_to_geojson(
db,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
)
)
@router.post(
"/runs/{analysis_run_id}/qa/reference",
response_model=Envelope[AnalysisQaResponse],
)
def compare_segmentation_run_with_reference(
analysis_run_id: UUID,
payload: SegmentationQaRequest,
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.compare_segmentations_with_reference(
db=db,
analysis_run_id=analysis_run_id,
reference_dataset_id=payload.reference_dataset_id,
iou_threshold=payload.iou_threshold,
class_name=payload.class_name,
min_confidence=payload.min_confidence,
)
)
geointel/backend/app/api/routes/selection_partitions.py
-87
View File
@@ -1,87 +0,0 @@
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.core.errors import AppError
from app.db.session import get_db
from app.models import Area, Dataset
from app.schemas.common import Envelope
from app.schemas.operations import VectorSelectionResponse
from app.schemas.selection_partitions import VectorPartitionSelectionRequest
from app.services.vector_feature_service import VectorFeatureService
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}", tags=["selection-partitions"])
def _product_identity(dataset: Dataset) -> str:
metadata = dataset.source_metadata if isinstance(dataset.source_metadata, dict) else {}
return str(metadata.get("product_key") or dataset.reference_layer_name or "")
@router.post(
"/datasets/vector/partitions/select",
response_model=Envelope[VectorSelectionResponse],
)
def select_vector_partitions(
project_id: UUID,
payload: VectorPartitionSelectionRequest,
db: Session = Depends(get_db),
):
datasets = db.query(Dataset).filter(Dataset.id.in_(payload.dataset_ids)).all()
by_id = {dataset.id: dataset for dataset in datasets}
ordered = [by_id.get(dataset_id) for dataset_id in payload.dataset_ids]
if any(dataset is None or dataset.project_id != project_id for dataset in ordered):
raise AppError(code="DATASET_NOT_FOUND", message="One or more selection partitions were not found", status_code=404)
typed_datasets = [dataset for dataset in ordered if dataset is not None]
if any(dataset.dataset_type not in {"vector", "geojson"} or dataset.status != "ready" for dataset in typed_datasets):
raise AppError(
code="INVALID_VECTOR_PARTITIONS",
message="Every selection partition must be a ready vector dataset",
status_code=409,
)
source_names = {dataset.source_name for dataset in typed_datasets}
product_keys = {_product_identity(dataset) for dataset in typed_datasets}
if len(source_names) != 1 or len(product_keys) != 1:
raise AppError(
code="VECTOR_PARTITION_SOURCE_MISMATCH",
message="Selection partitions must belong to one governed source product",
details={"source_names": sorted(str(value) for value in source_names), "product_keys": sorted(product_keys)},
status_code=409,
)
selection_geometry = None
selection_area_id = None
if payload.area_id is not None:
selection_area = db.get(Area, payload.area_id)
if selection_area is None or selection_area.project_id != project_id:
raise AppError(code="AREA_NOT_FOUND", message="Area not found", status_code=404)
selection_geometry, _covers_full_area = VectorFeatureService.constrain_bbox_to_area(
payload.bbox.model_dump(),
selection_area.geometry,
)
selection_area_id = selection_area.id
representative = typed_datasets[0]
dataset_ids = [dataset.id for dataset in typed_datasets]
result = VectorFeatureService.select_features_by_bbox(
db,
dataset_id=representative.id,
dataset_ids=dataset_ids,
bbox=payload.bbox.model_dump(),
limit=payload.limit,
dataset=representative,
selection_geometry=selection_geometry,
selection_area_id=selection_area_id,
deduplicate_source_features=True,
)
result.update(
partition_count=len(dataset_ids),
source_name=representative.source_name,
dataset_ids=dataset_ids,
)
return envelope(VectorSelectionResponse(**result).model_dump(exclude_none=True))
geointel/backend/app/api/routes/temporal.py
-34
View File
@@ -1,34 +0,0 @@
from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.db.session import get_db
from app.schemas import Envelope, ItemList
from app.schemas.temporal import (
TemporalComparisonRequest,
TemporalComparisonResponse,
TemporalSeriesRead,
)
from app.services.temporal_analysis_service import TemporalAnalysisService
from app.utils.response import envelope
router = APIRouter(prefix="/projects/{project_id}/temporal", tags=["temporal"])
@router.get("/series", response_model=Envelope[ItemList[TemporalSeriesRead]])
def list_temporal_series(project_id: UUID, db: Session = Depends(get_db)):
series = TemporalAnalysisService.list_series(db, project_id)
return envelope({"items": [item.model_dump() for item in series], "total": len(series)})
@router.post("/compare", response_model=Envelope[TemporalComparisonResponse])
def compare_temporal_snapshots(
project_id: UUID,
payload: TemporalComparisonRequest,
db: Session = Depends(get_db),
):
return envelope(TemporalAnalysisService.compare(db, project_id=project_id, payload=payload).model_dump())
geointel/backend/app/core/.gitkeep
View File
geointel/backend/app/core/config.py
-442
View File
@@ -1,442 +0,0 @@
from pydantic import Field, field_validator, model_validator
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
model_config = SettingsConfigDict(
env_file=".env",
env_file_encoding="utf-8",
extra="ignore",
populate_by_name=True,
)
app_env: str = Field(default="development", validation_alias="GEOINTEL_ENV")
app_version: str = Field(
default="1.0.0",
validation_alias="GEOINTEL_APP_VERSION",
)
build_sha: str | None = Field(default=None, validation_alias="GEOINTEL_BUILD_SHA")
build_time: str | None = Field(default=None, validation_alias="GEOINTEL_BUILD_TIME")
api_prefix: str = Field(default="/api/v1", validation_alias="GEOINTEL_API_PREFIX")
auth_enabled: bool = Field(default=False, validation_alias="GEOINTEL_AUTH_ENABLED")
auth_username: str | None = Field(default=None, validation_alias="GEOINTEL_AUTH_USERNAME")
auth_password_hash: str | None = Field(default=None, validation_alias="GEOINTEL_AUTH_PASSWORD_HASH")
auth_session_secret: str | None = Field(default=None, validation_alias="GEOINTEL_AUTH_SESSION_SECRET")
auth_session_ttl_seconds: int = Field(
default=43_200,
ge=900,
le=604_800,
validation_alias="GEOINTEL_AUTH_SESSION_TTL_SECONDS",
)
guest_access_enabled: bool = Field(
default=False,
validation_alias="GEOINTEL_GUEST_ACCESS_ENABLED",
)
guest_display_name: str = Field(
default="Gast",
min_length=1,
max_length=64,
validation_alias="GEOINTEL_GUEST_DISPLAY_NAME",
)
guest_session_ttl_seconds: int = Field(
default=7_200,
ge=900,
le=86_400,
validation_alias="GEOINTEL_GUEST_SESSION_TTL_SECONDS",
)
database_url: str = Field(
default="postgresql+psycopg://geointel:geointel@localhost:5432/geointel?connect_timeout=1",
validation_alias="DATABASE_URL",
)
storage_root: str = Field(default="./storage", validation_alias="STORAGE_ROOT")
max_upload_mb: int = Field(default=500, validation_alias="MAX_UPLOAD_MB")
orthophoto_enabled: bool = Field(default=True, validation_alias="ORTHOPHOTO_ENABLED")
orthophoto_wms_url: str = Field(
default="https://geo.api.vlaanderen.be/OMWRGBMRVL/wms",
validation_alias="ORTHOPHOTO_WMS_URL",
)
orthophoto_wms_layer: str = Field(default="Ortho", validation_alias="ORTHOPHOTO_WMS_LAYER")
spw_orthophoto_wms_url: str = Field(
default="https://geoservices.wallonie.be/arcgis/services/IMAGERIE/ORTHO_LAST/MapServer/WMSServer",
validation_alias="SPW_ORTHOPHOTO_WMS_URL",
)
brussels_orthophoto_wms_url: str = Field(
default="https://geoservices-grid.irisnet.be/geoserver/urbisgrid/ows",
validation_alias="BRUSSELS_ORTHOPHOTO_WMS_URL",
)
orthophoto_resolution_m: float = Field(default=1.0, gt=0, validation_alias="ORTHOPHOTO_RESOLUTION_M")
orthophoto_min_side_m: float = Field(default=128.0, gt=0, validation_alias="ORTHOPHOTO_MIN_SIDE_M")
orthophoto_max_side_m: float = Field(default=1024.0, gt=0, validation_alias="ORTHOPHOTO_MAX_SIDE_M")
orthophoto_timeout_seconds: int = Field(default=120, ge=1, validation_alias="ORTHOPHOTO_TIMEOUT_SECONDS")
orthophoto_max_response_mb: int = Field(default=32, ge=1, validation_alias="ORTHOPHOTO_MAX_RESPONSE_MB")
orthophoto_cache_ttl_hours: int = Field(default=24, ge=0, validation_alias="ORTHOPHOTO_CACHE_TTL_HOURS")
source_catalog_probe_enabled: bool = Field(default=True, validation_alias="SOURCE_CATALOG_PROBE_ENABLED")
source_catalog_grb_wfs_url: str = Field(
default="https://geo.api.vlaanderen.be/GRB/wfs",
validation_alias="SOURCE_CATALOG_GRB_WFS_URL",
)
source_catalog_alz_release_url: str = Field(
default="https://landbouwcijfers.vlaanderen.be/open-geodata-landbouwgebruikspercelen",
validation_alias="SOURCE_CATALOG_ALZ_RELEASE_URL",
)
source_catalog_statbel_dcat_url: str = Field(
default="https://doc.statbel.be/publications/DCAT/DCAT_opendata_datasets.ttl",
validation_alias="SOURCE_CATALOG_STATBEL_DCAT_URL",
)
source_catalog_statbel_max_response_mb: int = Field(
default=5,
ge=1,
le=10,
validation_alias="SOURCE_CATALOG_STATBEL_MAX_RESPONSE_MB",
)
source_catalog_probe_timeout_seconds: int = Field(
default=10,
ge=1,
le=60,
validation_alias="SOURCE_CATALOG_PROBE_TIMEOUT_SECONDS",
)
source_catalog_probe_max_response_mb: int = Field(
default=2,
ge=1,
le=10,
validation_alias="SOURCE_CATALOG_PROBE_MAX_RESPONSE_MB",
)
source_catalog_probe_cache_ttl_seconds: int = Field(
default=900,
ge=0,
le=86_400,
validation_alias="SOURCE_CATALOG_PROBE_CACHE_TTL_SECONDS",
)
grb_enabled: bool = Field(default=True, validation_alias="GRB_ENABLED")
grb_ogc_api_url: str = Field(
default="https://geo.api.vlaanderen.be/GRB/ogc/features/v1",
validation_alias="GRB_OGC_API_URL",
)
grb_min_side_m: float = Field(default=10.0, gt=0, validation_alias="GRB_MIN_SIDE_M")
grb_max_side_m: float = Field(default=20_000.0, gt=0, validation_alias="GRB_MAX_SIDE_M")
grb_page_size: int = Field(default=1000, ge=1, le=1000, validation_alias="GRB_PAGE_SIZE")
grb_max_pages: int = Field(default=200, ge=1, le=1000, validation_alias="GRB_MAX_PAGES")
grb_max_features: int = Field(default=150_000, ge=1, validation_alias="GRB_MAX_FEATURES")
grb_timeout_seconds: int = Field(default=180, ge=1, le=600, validation_alias="GRB_TIMEOUT_SECONDS")
grb_max_response_mb: int = Field(default=20, ge=1, le=100, validation_alias="GRB_MAX_RESPONSE_MB")
grb_max_total_response_mb: int = Field(
default=256,
ge=1,
le=2048,
validation_alias="GRB_MAX_TOTAL_RESPONSE_MB",
)
grb_cache_ttl_hours: int = Field(default=24, ge=0, le=8760, validation_alias="GRB_CACHE_TTL_HOURS")
official_vector_enabled: bool = Field(default=True, validation_alias="OFFICIAL_VECTOR_ENABLED")
bwk_wfs_url: str = Field(
default="https://geo.api.vlaanderen.be/BWK/wfs",
validation_alias="BWK_WFS_URL",
)
dov_soil_wfs_url: str = Field(
default="https://www.dov.vlaanderen.be/geoserver/wfs",
validation_alias="DOV_SOIL_WFS_URL",
)
official_vector_min_side_m: float = Field(
default=10.0,
gt=0,
validation_alias="OFFICIAL_VECTOR_MIN_SIDE_M",
)
official_vector_max_side_m: float = Field(
default=20_000.0,
gt=0,
validation_alias="OFFICIAL_VECTOR_MAX_SIDE_M",
)
official_vector_page_size: int = Field(
default=1000,
ge=1,
le=2000,
validation_alias="OFFICIAL_VECTOR_PAGE_SIZE",
)
official_vector_max_pages: int = Field(
default=200,
ge=1,
le=1000,
validation_alias="OFFICIAL_VECTOR_MAX_PAGES",
)
official_vector_max_features: int = Field(
default=100_000,
ge=1,
validation_alias="OFFICIAL_VECTOR_MAX_FEATURES",
)
official_vector_timeout_seconds: int = Field(
default=180,
ge=1,
le=600,
validation_alias="OFFICIAL_VECTOR_TIMEOUT_SECONDS",
)
official_vector_max_response_mb: int = Field(
default=20,
ge=1,
le=100,
validation_alias="OFFICIAL_VECTOR_MAX_RESPONSE_MB",
)
official_vector_max_total_response_mb: int = Field(
default=256,
ge=1,
le=2048,
validation_alias="OFFICIAL_VECTOR_MAX_TOTAL_RESPONSE_MB",
)
official_vector_cache_ttl_hours: int = Field(
default=24,
ge=0,
le=8760,
validation_alias="OFFICIAL_VECTOR_CACHE_TTL_HOURS",
)
spw_picc_enabled: bool = Field(default=True, validation_alias="SPW_PICC_ENABLED")
spw_picc_mapserver_url: str = Field(
default=(
"https://geoservices.wallonie.be/arcgis/rest/services/"
"TOPOGRAPHIE/PICC_VDIFF/MapServer"
),
validation_alias="SPW_PICC_MAPSERVER_URL",
)
spw_flood_hazard_enabled: bool = Field(default=True, validation_alias="SPW_FLOOD_HAZARD_ENABLED")
spw_flood_hazard_mapserver_url: str = Field(
default=(
"https://geoservices.wallonie.be/arcgis/rest/services/"
"EAU/ALEA_INOND/MapServer"
),
validation_alias="SPW_FLOOD_HAZARD_MAPSERVER_URL",
)
urbis_enabled: bool = Field(default=True, validation_alias="URBIS_ENABLED")
urbis_wfs_url: str = Field(
default="https://geoservices-vector.irisnet.be/geoserver/urbisvector/ows",
validation_alias="URBIS_WFS_URL",
)
dhmv_enabled: bool = Field(default=True, validation_alias="DHMV_ENABLED")
dhmv_wcs_url: str = Field(
default="https://geo.api.vlaanderen.be/DHMV/wcs",
validation_alias="DHMV_WCS_URL",
)
dhmv_resolution_m: float = Field(default=5.0, ge=1.0, le=10.0, validation_alias="DHMV_RESOLUTION_M")
dhmv_min_side_m: float = Field(default=10.0, gt=0, validation_alias="DHMV_MIN_SIDE_M")
dhmv_max_side_m: float = Field(default=20_000.0, gt=0, validation_alias="DHMV_MAX_SIDE_M")
dhmv_max_pixels: int = Field(default=12_000_000, ge=1, validation_alias="DHMV_MAX_PIXELS")
dhmv_timeout_seconds: int = Field(default=300, ge=1, validation_alias="DHMV_TIMEOUT_SECONDS")
dhmv_max_response_mb: int = Field(default=160, ge=1, validation_alias="DHMV_MAX_RESPONSE_MB")
flood_hazard_enabled: bool = Field(default=True, validation_alias="FLOOD_HAZARD_ENABLED")
flood_hazard_wcs_url: str = Field(
default="https://geoservice.waterinfo.be/OGRK/wcs",
validation_alias="FLOOD_HAZARD_WCS_URL",
)
flood_hazard_resolution_m: float = Field(default=5.0, ge=2.0, le=20.0, validation_alias="FLOOD_HAZARD_RESOLUTION_M")
flood_hazard_min_side_m: float = Field(default=10.0, gt=0, validation_alias="FLOOD_HAZARD_MIN_SIDE_M")
flood_hazard_max_side_m: float = Field(default=20_000.0, gt=0, validation_alias="FLOOD_HAZARD_MAX_SIDE_M")
flood_hazard_max_pixels: int = Field(default=12_000_000, ge=1, validation_alias="FLOOD_HAZARD_MAX_PIXELS")
flood_hazard_timeout_seconds: int = Field(default=300, ge=1, validation_alias="FLOOD_HAZARD_TIMEOUT_SECONDS")
flood_hazard_max_response_mb: int = Field(default=160, ge=1, validation_alias="FLOOD_HAZARD_MAX_RESPONSE_MB")
bathymetry_profiles_enabled: bool = Field(default=True, validation_alias="BATHYMETRY_PROFILES_ENABLED")
bathymetry_profiles_layer_url: str = Field(
default="https://vha.waterinfo.be/arcgis/rest/services/digitale_atlas/MapServer/0",
validation_alias="BATHYMETRY_PROFILES_LAYER_URL",
)
bathymetry_watercourse_layer_url: str = Field(
default="https://vha.waterinfo.be/arcgis/rest/services/digitale_atlas/MapServer/1",
validation_alias="BATHYMETRY_WATERCOURSE_LAYER_URL",
)
bathymetry_profiles_page_size: int = Field(
default=1000,
ge=1,
le=2000,
validation_alias="BATHYMETRY_PROFILES_PAGE_SIZE",
)
bathymetry_profiles_max_features: int = Field(
default=50_000,
ge=1,
le=250_000,
validation_alias="BATHYMETRY_PROFILES_MAX_FEATURES",
)
bathymetry_profiles_timeout_seconds: int = Field(
default=120,
ge=1,
le=600,
validation_alias="BATHYMETRY_PROFILES_TIMEOUT_SECONDS",
)
bathymetry_profiles_max_response_mb: int = Field(
default=32,
ge=1,
le=256,
validation_alias="BATHYMETRY_PROFILES_MAX_RESPONSE_MB",
)
bathymetry_raster_max_pixels: int = Field(
default=30_000_000,
ge=1,
validation_alias="BATHYMETRY_RASTER_MAX_PIXELS",
)
mdk_bathymetry_probe_enabled: bool = Field(default=True, validation_alias="MDK_BATHYMETRY_PROBE_ENABLED")
mdk_bathymetry_wcs_url: str = Field(
default="https://bathy.agentschapmdk.be/spatialfusionserver/services/ows/wcs/EL_wcs",
validation_alias="MDK_BATHYMETRY_WCS_URL",
)
mdk_bathymetry_probe_timeout_seconds: int = Field(
default=20,
ge=1,
le=120,
validation_alias="MDK_BATHYMETRY_PROBE_TIMEOUT_SECONDS",
)
mdk_bathymetry_probe_max_response_mb: int = Field(
default=4,
ge=1,
le=16,
validation_alias="MDK_BATHYMETRY_PROBE_MAX_RESPONSE_MB",
)
thematic_raster_enabled: bool = Field(default=True, validation_alias="THEMATIC_RASTER_ENABLED")
thematic_raster_wcs_url: str = Field(
default="https://www.mercator.vlaanderen.be/raadpleegdienstenmercatorpubliek/wcs",
validation_alias="THEMATIC_RASTER_WCS_URL",
)
mdk_bathymetry_acquisition_enabled: bool = Field(
default=False,
validation_alias="MDK_BATHYMETRY_ACQUISITION_ENABLED",
)
mdk_bathymetry_coverage_id: str | None = Field(default=None, validation_alias="MDK_BATHYMETRY_COVERAGE_ID")
mdk_bathymetry_request_crs: str = Field(default="EPSG:4326", validation_alias="MDK_BATHYMETRY_REQUEST_CRS")
mdk_bathymetry_max_bbox_deg2: float = Field(
default=0.25,
gt=0,
validation_alias="MDK_BATHYMETRY_MAX_BBOX_DEG2",
)
mdk_bathymetry_acquisition_timeout_seconds: int = Field(
default=120,
ge=1,
validation_alias="MDK_BATHYMETRY_ACQUISITION_TIMEOUT_SECONDS",
)
mdk_bathymetry_acquisition_max_response_mb: int = Field(
default=160,
ge=1,
validation_alias="MDK_BATHYMETRY_ACQUISITION_MAX_RESPONSE_MB",
)
thematic_raster_min_side_m: float = Field(default=100.0, gt=0, validation_alias="THEMATIC_RASTER_MIN_SIDE_M")
thematic_raster_max_side_m: float = Field(default=60_000.0, gt=0, validation_alias="THEMATIC_RASTER_MAX_SIDE_M")
thematic_raster_max_pixels: int = Field(default=30_000_000, ge=1, validation_alias="THEMATIC_RASTER_MAX_PIXELS")
thematic_raster_timeout_seconds: int = Field(default=300, ge=1, validation_alias="THEMATIC_RASTER_TIMEOUT_SECONDS")
thematic_raster_max_response_mb: int = Field(default=160, ge=1, validation_alias="THEMATIC_RASTER_MAX_RESPONSE_MB")
walous_enabled: bool = Field(default=True, validation_alias="WALOUS_ENABLED")
walous_source_dir: str = Field(
default="/app/storage/source-cache/walous",
validation_alias="WALOUS_SOURCE_DIR",
)
walous_analysis_resolution_m: float = Field(
default=10.0,
ge=1.0,
le=100.0,
validation_alias="WALOUS_ANALYSIS_RESOLUTION_M",
)
walous_max_side_m: float = Field(default=60_000.0, gt=0, validation_alias="WALOUS_MAX_SIDE_M")
walous_max_pixels: int = Field(default=36_000_000, ge=1, validation_alias="WALOUS_MAX_PIXELS")
spw_terrain_enabled: bool = Field(default=True, validation_alias="SPW_TERRAIN_ENABLED")
spw_terrain_source_dir: str = Field(
default="/app/storage/source-cache/spw-terrain",
validation_alias="SPW_TERRAIN_SOURCE_DIR",
)
spw_terrain_analysis_resolution_m: float = Field(
default=5.0,
ge=1.0,
le=10.0,
validation_alias="SPW_TERRAIN_ANALYSIS_RESOLUTION_M",
)
spw_terrain_max_side_m: float = Field(default=20_000.0, gt=0, validation_alias="SPW_TERRAIN_MAX_SIDE_M")
spw_terrain_max_pixels: int = Field(default=12_000_000, ge=1, validation_alias="SPW_TERRAIN_MAX_PIXELS")
redis_url: str | None = Field(default=None, validation_alias="REDIS_URL")
log_level: str = Field(default="INFO", validation_alias="GEOINTEL_LOG_LEVEL")
sql_log_level: str = Field(default="WARNING", validation_alias="GEOINTEL_SQL_LOG_LEVEL")
reconcile_interrupted_runs_on_startup: bool = Field(
default=False,
validation_alias="GEOINTEL_RECONCILE_INTERRUPTED_RUNS_ON_STARTUP",
)
aoi_worker_enabled: bool = Field(default=False, validation_alias="GEOINTEL_AOI_WORKER_ENABLED")
aoi_worker_poll_seconds: float = Field(default=2.0, ge=0.5, le=60.0, validation_alias="GEOINTEL_AOI_WORKER_POLL_SECONDS")
database_statement_timeout_ms: int = Field(default=5_000, validation_alias="DATABASE_STATEMENT_TIMEOUT_MS")
yolo_enabled: bool = Field(default=False, validation_alias="YOLO_ENABLED")
yolo_models_dir: str = Field(default="/app/models", validation_alias="YOLO_MODELS_DIR")
yolo_model_path: str | None = Field(default=None, validation_alias="YOLO_MODEL_PATH")
yolo_model_id: str = Field(default="yolo-configured", validation_alias="YOLO_MODEL_ID")
yolo_model_display_name: str = Field(default="Configured YOLO detector", validation_alias="YOLO_MODEL_DISPLAY_NAME")
yolo_model_version: str | None = Field(default=None, validation_alias="YOLO_MODEL_VERSION")
yolo_model_classes: str = Field(default="building", validation_alias="YOLO_MODEL_CLASSES")
yolo_enforce_validation_scope: bool = Field(default=False, validation_alias="YOLO_ENFORCE_VALIDATION_SCOPE")
yolo_validated_area_names: str = Field(default="Mol,Kempen", validation_alias="YOLO_VALIDATED_AREA_NAMES")
yolo_device: str = Field(default="cpu", validation_alias="YOLO_DEVICE")
yolo_require_cuda: bool = Field(default=False, validation_alias="YOLO_REQUIRE_CUDA")
yolo_image_size: int = Field(default=640, validation_alias="YOLO_IMAGE_SIZE")
yolo_max_tiles: int = Field(default=100, validation_alias="YOLO_MAX_TILES")
yolo_max_detections: int = Field(default=1000, validation_alias="YOLO_MAX_DETECTIONS")
yolo_duplicate_iou_threshold: float = Field(default=0.5, ge=0.0, le=1.0, validation_alias="YOLO_DUPLICATE_IOU_THRESHOLD")
yolo_batch_size: int = Field(default=1, validation_alias="YOLO_BATCH_SIZE")
yolo_seg_enabled: bool = Field(default=False, validation_alias="YOLO_SEG_ENABLED")
yolo_seg_model_path: str | None = Field(default=None, validation_alias="YOLO_SEG_MODEL_PATH")
yolo_seg_model_id: str = Field(default="yolo-seg-configured", validation_alias="YOLO_SEG_MODEL_ID")
yolo_seg_model_display_name: str = Field(
default="Configured YOLO segmentation",
validation_alias="YOLO_SEG_MODEL_DISPLAY_NAME",
)
yolo_seg_model_version: str | None = Field(default=None, validation_alias="YOLO_SEG_MODEL_VERSION")
sam_enabled: bool = Field(default=False, validation_alias="SAM_ENABLED")
sam_model_path: str | None = Field(default=None, validation_alias="SAM_MODEL_PATH")
sam_model_id: str = Field(default="sam-configured", validation_alias="SAM_MODEL_ID")
sam_model_display_name: str = Field(
default="Configured SAM segmentation",
validation_alias="SAM_MODEL_DISPLAY_NAME",
)
sam_model_version: str | None = Field(default=None, validation_alias="SAM_MODEL_VERSION")
segmentation_max_masks_per_tile: int = Field(default=300, ge=1, validation_alias="SEGMENTATION_MAX_MASKS_PER_TILE")
segmentation_duplicate_iou_threshold: float = Field(
default=0.5,
ge=0.0,
le=1.0,
validation_alias="SEGMENTATION_DUPLICATE_IOU_THRESHOLD",
)
ollama_enabled: bool = Field(default=False, validation_alias="OLLAMA_ENABLED")
ollama_base_url: str = Field(default="http://127.0.0.1:11434", validation_alias="OLLAMA_BASE_URL")
ollama_default_model: str = Field(default="qwen3.5:9b", validation_alias="OLLAMA_DEFAULT_MODEL")
ollama_timeout_seconds: int = Field(default=120, ge=5, le=600, validation_alias="OLLAMA_TIMEOUT_SECONDS")
ollama_max_output_tokens: int = Field(default=1_200, ge=100, le=4_000, validation_alias="OLLAMA_MAX_OUTPUT_TOKENS")
ollama_context_tokens: int = Field(default=16_384, ge=4_096, le=131_072, validation_alias="OLLAMA_CONTEXT_TOKENS")
cors_origins: list[str] | str = Field(
default=["http://localhost:5173", "http://127.0.0.1:5173"],
validation_alias="CORS_ORIGINS",
)
@field_validator("cors_origins", mode="before")
@classmethod
def parse_cors_origins(cls, value: object) -> list[str]:
if isinstance(value, str):
return [item.strip() for item in value.split(",") if item.strip()]
if isinstance(value, list):
return value
if value is None:
return ["http://localhost:5173", "http://127.0.0.1:5173"]
return [str(value)]
@field_validator("ollama_base_url")
@classmethod
def validate_ollama_base_url(cls, value: str) -> str:
normalized = value.strip().rstrip("/")
if not normalized.startswith(("http://", "https://")):
raise ValueError("OLLAMA_BASE_URL must use http or https")
return normalized
@model_validator(mode="after")
def validate_operator_auth(self) -> "Settings":
self.guest_display_name = self.guest_display_name.strip()
if not self.guest_display_name:
raise ValueError("GEOINTEL_GUEST_DISPLAY_NAME must not be blank")
if self.guest_access_enabled and not self.auth_enabled:
raise ValueError("GEOINTEL_GUEST_ACCESS_ENABLED requires GEOINTEL_AUTH_ENABLED=true")
if not self.auth_enabled:
return self
if not (self.auth_username or "").strip():
raise ValueError("GEOINTEL_AUTH_USERNAME is required when authentication is enabled")
if not (self.auth_password_hash or "").startswith("pbkdf2_sha256$"):
raise ValueError("GEOINTEL_AUTH_PASSWORD_HASH must be a PBKDF2-SHA256 hash")
if len(self.auth_session_secret or "") < 32:
raise ValueError("GEOINTEL_AUTH_SESSION_SECRET must contain at least 32 characters")
return self
def get_settings() -> Settings:
return Settings()
geointel/backend/app/core/errors.py
-15
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@@ -1,15 +0,0 @@
class AppError(Exception):
"""Domain error used by services to return canonical API errors."""
def __init__(
self,
code: str,
message: str,
details: dict | list | None = None,
status_code: int = 400,
) -> None:
super().__init__(message)
self.code = code
self.message = message
self.details = details or {}
self.status_code = status_code
geointel/backend/app/core/logging.py
-14
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@@ -1,14 +0,0 @@
import logging
import sys
def configure_logging(level: str = "INFO", sql_level: str = "WARNING") -> None:
logging.basicConfig(
level=level,
format="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
stream=sys.stdout,
force=True,
)
for name in ["uvicorn", "uvicorn.error", "uvicorn.access"]:
logging.getLogger(name).setLevel(level)
logging.getLogger("sqlalchemy.engine").setLevel(sql_level)
geointel/backend/app/core/request_context.py
-18
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@@ -1,18 +0,0 @@
from __future__ import annotations
from contextvars import ContextVar, Token
_request_id: ContextVar[str] = ContextVar("geointel_request_id", default="-")
def get_request_id() -> str:
return _request_id.get()
def set_request_id(value: str) -> Token:
return _request_id.set(value)
def reset_request_id(token: Token) -> None:
_request_id.reset(token)
geointel/backend/app/db/.gitkeep
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geointel/backend/app/db/__init__.py
-4
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@@ -1,4 +0,0 @@
from .base import Base
from .session import get_db, get_engine
__all__ = ["Base", "get_db", "get_engine"]
geointel/backend/app/db/base.py
-5
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@@ -1,5 +0,0 @@
from sqlalchemy.orm import DeclarativeBase
class Base(DeclarativeBase):
pass
geointel/backend/app/db/session.py
-20
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@@ -1,20 +0,0 @@
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, Session
from app.core.config import get_settings
engine = create_engine(get_settings().database_url, pool_pre_ping=True, future=True)
SessionLocal = sessionmaker(bind=engine, autocommit=False, autoflush=False, future=True)
def get_db():
db: Session = SessionLocal()
try:
yield db
finally:
db.close()
def get_engine():
return engine
geointel/backend/app/geo/.gitkeep
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geointel/backend/app/main.py
-357
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@@ -1,357 +0,0 @@
from __future__ import annotations
import logging
import asyncio
import re
import time
import uuid
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException, Request
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from app.api.routes import analysis, aoi_operations, areas, assistant, auth, datasets, demo, detection, exports, external, health, jobs, projects, qa, quality_checks, segmentation, selection_partitions, temporal
from app.core.config import get_settings
from app.core.errors import AppError
from app.core.logging import configure_logging
from app.core.request_context import reset_request_id, set_request_id
from app.db.session import SessionLocal
from app.services.runtime_reconciliation_service import RuntimeReconciliationService
from app.services.auth_service import AuthService
from app.services.aoi_operation_worker import AoiOperationWorker
logger = logging.getLogger("geointel")
SAFE_REQUEST_ID = re.compile(r"^[A-Za-z0-9._:-]{1,128}$")
UNSAFE_HOST = re.compile(r"[/\\@\s\x00-\x1f\x7f]")
def _to_error_payload(
code: str,
message: str,
details: dict | list | None = None,
request_id: str | None = None,
) -> dict:
return {
"error": code,
"message": message,
"details": details or {},
"request_id": request_id,
}
def create_app() -> FastAPI:
settings = get_settings()
configure_logging(settings.log_level, settings.sql_log_level)
@asynccontextmanager
async def lifespan(_: FastAPI):
worker_stop = asyncio.Event()
worker_task = None
if settings.reconcile_interrupted_runs_on_startup:
db = SessionLocal()
try:
result = RuntimeReconciliationService.reconcile(db)
logger.info(
"Runtime reconciliation completed: jobs=%s analysis_runs=%s resumed_aoi_partitions=%s exhausted_aoi_partitions=%s",
result.interrupted_jobs,
result.interrupted_analysis_runs,
result.resumed_aoi_partitions,
result.exhausted_aoi_partitions,
)
except Exception:
db.rollback()
logger.exception("Runtime reconciliation failed")
raise
finally:
db.close()
if settings.aoi_worker_enabled:
worker_task = asyncio.create_task(AoiOperationWorker.run(worker_stop, settings.aoi_worker_poll_seconds))
try:
yield
finally:
worker_stop.set()
if worker_task is not None:
await worker_task
app = FastAPI(
title="GeoIntel",
version=settings.app_version,
docs_url="/docs",
redoc_url="/redoc",
lifespan=lifespan,
)
app.add_middleware(
CORSMiddleware,
allow_origins=settings.cors_origins,
allow_methods=["*"],
allow_headers=["*"],
allow_credentials=True,
)
app.include_router(health.router)
app.include_router(auth.router, prefix=settings.api_prefix)
app.include_router(analysis.router, prefix=settings.api_prefix)
app.include_router(aoi_operations.router, prefix=settings.api_prefix)
app.include_router(projects.router, prefix=settings.api_prefix)
app.include_router(areas.router, prefix=settings.api_prefix)
app.include_router(datasets.router, prefix=settings.api_prefix)
app.include_router(jobs.router, prefix=settings.api_prefix)
app.include_router(quality_checks.router, prefix=settings.api_prefix)
app.include_router(exports.router, prefix=settings.api_prefix)
app.include_router(external.router, prefix=settings.api_prefix)
app.include_router(demo.router, prefix=settings.api_prefix)
app.include_router(qa.router, prefix=settings.api_prefix)
app.include_router(detection.router, prefix=settings.api_prefix)
app.include_router(segmentation.router, prefix=settings.api_prefix)
app.include_router(selection_partitions.router, prefix=settings.api_prefix)
app.include_router(temporal.router, prefix=settings.api_prefix)
app.include_router(assistant.router, prefix=settings.api_prefix)
@app.middleware("http")
async def request_identity(request: Request, call_next):
supplied_request_id = request.headers.get("x-request-id", "")
request_id = supplied_request_id if SAFE_REQUEST_ID.fullmatch(supplied_request_id) else str(uuid.uuid4())
request.state.request_id = request_id
token = set_request_id(request_id)
started_at = time.perf_counter()
raw_path = str(request.scope.get("path") or "")
try:
host = request.headers.get("host", "")
content_type = request.headers.get("content-type", "").split(";", 1)[0].strip().lower()
if not raw_path.startswith("/") or not host or UNSAFE_HOST.search(host):
response = JSONResponse(
status_code=400,
content=_to_error_payload(
"INVALID_REQUEST_TARGET",
"The request target or Host header is invalid",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
if content_type == "application/x-www-form-urlencoded":
response = JSONResponse(
status_code=415,
content=_to_error_payload(
"UNSUPPORTED_CONTENT_TYPE",
"URL-encoded form bodies are not supported",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
public_auth_paths = {
f"{settings.api_prefix}/auth/session",
f"{settings.api_prefix}/auth/login",
f"{settings.api_prefix}/auth/guest",
f"{settings.api_prefix}/auth/logout",
}
direct_loopback_request = (
request.client is not None
and request.client.host in {"127.0.0.1", "::1"}
and not request.headers.get("x-real-ip")
and not request.headers.get("x-forwarded-for")
)
if (
settings.auth_enabled
and raw_path.startswith(f"{settings.api_prefix}/")
and raw_path not in public_auth_paths
and not direct_loopback_request
):
principal = AuthService.verify_session_token(
request.cookies.get(auth.COOKIE_NAME),
settings,
)
if principal is None:
response = JSONResponse(
status_code=401,
content=_to_error_payload(
"AUTHENTICATION_REQUIRED",
"Meld u aan om de GeoIntel API te gebruiken.",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
request.state.auth_principal = principal
if principal.role == "guest":
project_path_prefix = f"{settings.api_prefix}/projects/"
guest_project_root = f"{project_path_prefix}{principal.project_id}"
if raw_path.startswith(project_path_prefix):
scoped_path = raw_path[len(project_path_prefix):]
requested_project_id = scoped_path.split("/", 1)[0]
if str(principal.project_id) != requested_project_id:
response = JSONResponse(
status_code=403,
content=_to_error_payload(
"GUEST_PROJECT_SCOPE_REQUIRED",
"Deze gastensessie heeft alleen toegang tot de GeoIntel-demowerkruimte.",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
query_project_id = request.query_params.get("project_id")
if query_project_id and query_project_id != str(principal.project_id):
response = JSONResponse(
status_code=403,
content=_to_error_payload(
"GUEST_PROJECT_SCOPE_REQUIRED",
"Deze gastensessie heeft alleen toegang tot de GeoIntel-demowerkruimte.",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
guest_safe_read_paths = {
f"{settings.api_prefix}/projects",
f"{settings.api_prefix}/external/providers",
}
normalized_path = raw_path.rstrip("/") or "/"
guest_project_read = (
normalized_path == guest_project_root
or normalized_path.startswith(f"{guest_project_root}/")
)
is_read_request = request.method in {"GET", "HEAD", "OPTIONS"}
if is_read_request:
if normalized_path not in guest_safe_read_paths and not guest_project_read:
response = JSONResponse(
status_code=403,
content=_to_error_payload(
"GUEST_ROUTE_NOT_AVAILABLE",
"Deze API-route maakt geen deel uit van de afgeschermde GeoIntel-demo.",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
else:
guest_safe_post_paths = {
f"{settings.api_prefix}/demo/workflow",
f"{settings.api_prefix}/external/coverage/resolve",
}
guest_safe_post_suffixes = (
"/vector/select",
"/raster/bathymetry/select",
"/raster/terrain/select",
"/raster/flood-hazard/select",
"/raster/thematic/select",
"/raster/walous/select",
"/temporal/compare",
"/datasets/vector/partitions/select",
"/datasets/bathymetry/profiles/partitions/select",
)
is_guest_safe_post = request.method == "POST" and (
raw_path in guest_safe_post_paths
or (
raw_path.startswith(project_path_prefix)
and raw_path.endswith(guest_safe_post_suffixes)
)
)
if not is_guest_safe_post:
response = JSONResponse(
status_code=403,
content=_to_error_payload(
"GUEST_READ_ONLY",
"Gasttoegang is een tijdelijke, alleen-lezen demo. Meld u aan als operator om gegevens te wijzigen of taken te starten.",
request_id=request_id,
),
)
response.headers["x-request-id"] = request_id
return response
response = await call_next(request)
response.headers["x-request-id"] = request_id
logger.info(
"request_complete request_id=%s method=%s path=%s status=%s duration_ms=%.1f",
request_id,
request.method,
raw_path,
response.status_code,
(time.perf_counter() - started_at) * 1000,
)
return response
finally:
reset_request_id(token)
@app.exception_handler(AppError)
async def app_error(request: Request, exc: AppError): # noqa: ARG001
return JSONResponse(
status_code=exc.status_code,
content=_to_error_payload(
exc.code,
exc.message,
exc.details,
request_id=request.state.request_id,
),
)
@app.exception_handler(HTTPException)
async def http_error(request: Request, exc: HTTPException): # noqa: ARG001
code = "HTTP_ERROR"
message = str(exc.detail)
details = {}
if isinstance(exc.detail, dict):
code = str(exc.detail.get("error") or exc.detail.get("code") or code)
message = str(exc.detail.get("message") or message)
raw_details = exc.detail.get("details")
details = raw_details if isinstance(raw_details, (dict, list)) else {}
return JSONResponse(
status_code=exc.status_code,
content=_to_error_payload(
code,
message,
details,
request_id=request.state.request_id,
),
)
@app.exception_handler(RequestValidationError)
async def validation_error(request: Request, exc: RequestValidationError): # noqa: ARG001
return JSONResponse(
status_code=422,
content=_to_error_payload(
"VALIDATION_ERROR",
"Validation failed",
exc.errors(),
request_id=request.state.request_id,
),
)
@app.exception_handler(Exception)
async def unexpected_error(request: Request, exc: Exception):
logger.exception(
"Unhandled request error request_id=%s method=%s path=%s",
request.state.request_id,
request.method,
str(request.scope.get("path") or ""),
)
return JSONResponse(
status_code=500,
content=_to_error_payload(
"INTERNAL_ERROR",
"Unexpected server error",
{"type": exc.__class__.__name__},
request_id=request.state.request_id,
),
)
return app
app = create_app()
def main() -> None:
import uvicorn
settings = get_settings()
uvicorn.run(
"app.main:app",
host="0.0.0.0",
port=8000,
reload=settings.app_env == "development",
)
geointel/backend/app/models.py
-1
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@@ -1 +0,0 @@
from app.models import *
geointel/backend/app/models/.gitkeep
View File
geointel/backend/app/models/__init__.py
-19
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@@ -1,19 +0,0 @@
from .entities import AoiOperation, AoiOperationPartition, AnalysisRun, Area, Dataset, DatasetVersion, Detection, DetectionReview, Export, Job, Metric, Project, QualityCheck, Segmentation, VectorFeature
__all__ = [
"AnalysisRun",
"AoiOperation",
"AoiOperationPartition",
"Area",
"Dataset",
"DatasetVersion",
"Detection",
"DetectionReview",
"Export",
"Job",
"Metric",
"Project",
"QualityCheck",
"Segmentation",
"VectorFeature",
]
geointel/backend/app/models/entities.py
-423
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@@ -1,423 +0,0 @@
from __future__ import annotations
import uuid
from datetime import datetime
from geoalchemy2 import Geometry
from sqlalchemy import CheckConstraint, DateTime, ForeignKey, Float, Index, JSON, String, Text, UniqueConstraint, func, text
from sqlalchemy.sql.sqltypes import Integer
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.orm import Mapped, mapped_column, relationship
from app.db.base import Base
class Project(Base):
__tablename__ = "projects"
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
name: Mapped[str] = mapped_column(String(255), nullable=False)
description: Mapped[str | None] = mapped_column(Text, nullable=True)
region: Mapped[str] = mapped_column(String(120), default="Belgium and Belgian North Sea")
status: Mapped[str] = mapped_column(String(32), default="active")
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
areas: Mapped[list["Area"]] = relationship("Area", back_populates="project", cascade="all, delete-orphan")
datasets: Mapped[list["Dataset"]] = relationship("Dataset", back_populates="project", cascade="all, delete-orphan")
class Area(Base):
__tablename__ = "areas"
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
name: Mapped[str] = mapped_column(String(255), nullable=False)
geometry: Mapped[str] = mapped_column(Geometry("MultiPolygon", srid=4326), nullable=False)
original_crs: Mapped[str | None] = mapped_column(String(64), nullable=True)
area_m2: Mapped[float | None] = mapped_column(Float, nullable=True)
bbox: Mapped[str | None] = mapped_column(Geometry("Polygon", srid=4326), nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
project: Mapped[Project] = relationship("Project", back_populates="areas")
class Dataset(Base):
__tablename__ = "datasets"
__table_args__ = (
CheckConstraint(
"valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from",
name="ck_datasets_temporal_valid_range",
),
Index(
"ix_datasets_project_temporal_series_observed",
"project_id",
"temporal_series_key",
"observed_at",
),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
area_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("areas.id", ondelete="SET NULL"), nullable=True)
name: Mapped[str] = mapped_column(String(255), nullable=False)
dataset_type: Mapped[str] = mapped_column(String(64), nullable=False)
source: Mapped[str] = mapped_column(String(120), nullable=False)
storage_path: Mapped[str | None] = mapped_column(String(500), nullable=True)
original_filename: Mapped[str | None] = mapped_column(String(255), nullable=True)
stored_filename: Mapped[str | None] = mapped_column(String(255), nullable=True)
content_type: Mapped[str | None] = mapped_column(String(120), nullable=True)
size_bytes: Mapped[int | None] = mapped_column(Integer, nullable=True)
checksum_sha256: Mapped[str | None] = mapped_column(String(64), nullable=True)
derived_from_dataset_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("datasets.id", ondelete="SET NULL"),
nullable=True,
)
crs: Mapped[str | None] = mapped_column(String(64), nullable=True)
bounds_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
resolution_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
bands_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
metadata_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
dataset_role: Mapped[str] = mapped_column(String(32), nullable=False, default="source", server_default="source")
source_name: Mapped[str | None] = mapped_column(String(120), nullable=True)
reference_layer_name: Mapped[str | None] = mapped_column(String(120), nullable=True)
source_metadata: Mapped[dict | None] = mapped_column(JSON, nullable=True)
provenance_metadata: Mapped[dict | None] = mapped_column(JSON, nullable=True)
imported_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
temporal_series_key: Mapped[str | None] = mapped_column(String(255), nullable=True)
observed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
valid_from: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
valid_to: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
temporal_granularity: Mapped[str | None] = mapped_column(String(32), nullable=True)
source_version: Mapped[str | None] = mapped_column(String(120), nullable=True)
status: Mapped[str] = mapped_column(String(32), default="uploaded")
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
project: Mapped[Project] = relationship("Project", back_populates="datasets")
versions: Mapped[list["DatasetVersion"]] = relationship(
"DatasetVersion",
back_populates="dataset",
cascade="all, delete-orphan",
)
vector_features: Mapped[list["VectorFeature"]] = relationship(
"VectorFeature",
back_populates="dataset",
cascade="all, delete-orphan",
)
class DatasetVersion(Base):
__tablename__ = "dataset_versions"
__table_args__ = (
CheckConstraint(
"valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from",
name="ck_dataset_versions_temporal_valid_range",
),
Index("ix_dataset_versions_dataset_version", "dataset_id", "version", unique=True),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
dataset_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False)
version: Mapped[int] = mapped_column(Integer, default=1)
storage_path: Mapped[str | None] = mapped_column(String(500), nullable=True)
source_version: Mapped[str | None] = mapped_column(String(120), nullable=True)
observed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
valid_from: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
valid_to: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
checksum_sha256: Mapped[str | None] = mapped_column(String(64), nullable=True)
source_metadata: Mapped[dict | None] = mapped_column(JSON, nullable=True)
provenance_metadata: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
dataset: Mapped[Dataset] = relationship("Dataset", back_populates="versions")
class VectorFeature(Base):
__tablename__ = "vector_features"
__table_args__ = (
Index("ix_vector_features_dataset_id", "dataset_id"),
Index("ix_vector_features_geometry", "geometry", postgresql_using="gist"),
Index("ix_vector_features_dataset_source_feature", "dataset_id", "source_feature_id"),
Index(
"ix_vector_features_dataset_municipality",
"dataset_id",
text("(properties_json ->> 'municipality')"),
),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
dataset_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False)
feature_class: Mapped[str | None] = mapped_column(String(120), nullable=True)
source_feature_id: Mapped[str | None] = mapped_column(String(255), nullable=True)
properties_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
geometry: Mapped[str] = mapped_column(Geometry("Geometry", srid=4326, spatial_index=False), nullable=False)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
dataset: Mapped[Dataset] = relationship("Dataset", back_populates="vector_features")
class AnalysisRun(Base):
__tablename__ = "analysis_runs"
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
area_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("areas.id", ondelete="SET NULL"), nullable=True)
dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
analysis_type: Mapped[str] = mapped_column(String(64), nullable=False)
status: Mapped[str] = mapped_column(String(32), nullable=False)
model_name: Mapped[str | None] = mapped_column(String(255), nullable=True)
model_version: Mapped[str | None] = mapped_column(String(120), nullable=True)
parameters_json: Mapped[dict] = mapped_column(JSON, nullable=False)
result_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
class Detection(Base):
__tablename__ = "detections"
__table_args__ = (
Index("ix_detections_project_id", "project_id"),
Index("ix_detections_dataset_id", "dataset_id"),
Index("ix_detections_analysis_run_id", "analysis_run_id"),
Index("ix_detections_class_name", "class_name"),
Index("ix_detections_geometry", "geometry", postgresql_using="gist"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True)
job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
model_name: Mapped[str] = mapped_column(String(255), nullable=False)
model_version: Mapped[str | None] = mapped_column(String(120), nullable=True)
class_name: Mapped[str] = mapped_column(String(120), nullable=False)
confidence: Mapped[float] = mapped_column(Float, nullable=False)
geometry: Mapped[str] = mapped_column(Geometry("Geometry", srid=4326, spatial_index=False), nullable=False)
bbox_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
source_tile_path: Mapped[str | None] = mapped_column(String(500), nullable=True)
properties_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
class Segmentation(Base):
__tablename__ = "segmentations"
__table_args__ = (
Index("ix_segmentations_project_id", "project_id"),
Index("ix_segmentations_dataset_id", "dataset_id"),
Index("ix_segmentations_analysis_run_id", "analysis_run_id"),
Index("ix_segmentations_job_id", "job_id"),
Index("ix_segmentations_class_name", "class_name"),
Index("ix_segmentations_geometry", "geometry", postgresql_using="gist"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True)
model_name: Mapped[str] = mapped_column(String(255), nullable=False)
model_version: Mapped[str | None] = mapped_column(String(120), nullable=True)
class_name: Mapped[str] = mapped_column(String(120), nullable=False)
confidence: Mapped[float | None] = mapped_column(Float, nullable=True)
geometry: Mapped[str] = mapped_column(Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False)
bbox_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
area_m2: Mapped[float | None] = mapped_column(Float, nullable=True)
mask_path: Mapped[str | None] = mapped_column(Text, nullable=True)
source_tile_path: Mapped[str | None] = mapped_column(String(500), nullable=True)
tile_index: Mapped[int | None] = mapped_column(Integer, nullable=True)
properties_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
provenance_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
class QualityCheck(Base):
__tablename__ = "quality_checks"
__table_args__ = (
Index("ix_quality_checks_project_id", "project_id"),
Index("ix_quality_checks_reference_dataset_id", "reference_dataset_id"),
Index("ix_quality_checks_candidate_dataset_id", "candidate_dataset_id"),
Index("ix_quality_checks_analysis_run_id", "analysis_run_id"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True)
candidate_dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
reference_dataset_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False)
check_type: Mapped[str] = mapped_column(String(120), nullable=False)
status: Mapped[str] = mapped_column(String(32), nullable=False)
score: Mapped[float | None] = mapped_column(Float, nullable=True)
parameters_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
findings_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
completed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
class Metric(Base):
__tablename__ = "metrics"
__table_args__ = (
Index("ix_metrics_quality_check_id", "quality_check_id"),
Index("ix_metrics_analysis_run_id", "analysis_run_id"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
quality_check_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("quality_checks.id", ondelete="CASCADE"), nullable=True)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True)
metric_key: Mapped[str] = mapped_column(String(120), nullable=False)
metric_value: Mapped[float | None] = mapped_column(Float, nullable=True)
metric_unit: Mapped[str | None] = mapped_column(String(64), nullable=True)
label: Mapped[str | None] = mapped_column(String(120), nullable=True)
metadata_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
class DetectionReview(Base):
__tablename__ = "detection_reviews"
__table_args__ = (
CheckConstraint(
"evidence_role IN ('false_positive', 'false_negative')",
name="ck_detection_reviews_evidence_role",
),
CheckConstraint(
"decision IN ('confirmed_model_false_positive', 'confirmed_model_false_negative', "
"'reference_gap_or_change', 'qa_alignment_mismatch', "
"'imagery_obscured_or_uncertain', 'uncertain', 'unreviewed')",
name="ck_detection_reviews_decision",
),
UniqueConstraint(
"quality_check_id",
"evidence_role",
"evidence_feature_id",
name="uq_detection_reviews_evidence",
),
Index("ix_detection_reviews_project_id", "project_id"),
Index("ix_detection_reviews_quality_check_id", "quality_check_id"),
Index("ix_detection_reviews_analysis_run_id", "analysis_run_id"),
Index("ix_detection_reviews_decision", "decision"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
quality_check_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("quality_checks.id", ondelete="CASCADE"),
nullable=False,
)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("analysis_runs.id", ondelete="SET NULL"),
nullable=True,
)
evidence_role: Mapped[str] = mapped_column(String(32), nullable=False)
evidence_feature_id: Mapped[str] = mapped_column(String(255), nullable=False)
detection_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("detections.id", ondelete="SET NULL"),
nullable=True,
)
reference_feature_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("vector_features.id", ondelete="SET NULL"),
nullable=True,
)
decision: Mapped[str] = mapped_column(String(64), nullable=False, default="unreviewed", server_default="unreviewed")
notes: Mapped[str | None] = mapped_column(Text, nullable=True)
reviewed_by: Mapped[str] = mapped_column(String(120), nullable=False, default="operator", server_default="operator")
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
class Export(Base):
__tablename__ = "exports"
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
analysis_run_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True)
export_type: Mapped[str] = mapped_column(String(64), nullable=False)
storage_path: Mapped[str] = mapped_column(String(500), nullable=False)
metadata_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
class Job(Base):
__tablename__ = "jobs"
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
job_type: Mapped[str] = mapped_column(String(128), nullable=False)
status: Mapped[str] = mapped_column(String(32), nullable=False, default="queued")
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
input_dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
output_dataset_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True)
parameters_json: Mapped[dict] = mapped_column(JSON, nullable=False, default=dict)
result_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
class AoiOperation(Base):
__tablename__ = "aoi_operations"
__table_args__ = (
CheckConstraint(
"status IN ('queued', 'running', 'partial', 'success', 'failed', 'cancelled')",
name="ck_aoi_operations_status",
),
Index("ix_aoi_operations_project_status", "project_id", "status"),
Index("ix_aoi_operations_geometry", "geometry", postgresql_using="gist"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
project_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("projects.id", ondelete="CASCADE"), nullable=False)
area_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("areas.id", ondelete="SET NULL"), nullable=True)
parent_job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
operation_type: Mapped[str] = mapped_column(String(128), nullable=False)
status: Mapped[str] = mapped_column(String(32), nullable=False, default="queued")
geometry: Mapped[str] = mapped_column(Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False)
request_json: Mapped[dict] = mapped_column(JSON, nullable=False, default=dict)
plan_json: Mapped[dict] = mapped_column(JSON, nullable=False, default=dict)
result_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
class AoiOperationPartition(Base):
__tablename__ = "aoi_operation_partitions"
__table_args__ = (
CheckConstraint(
"status IN ('queued', 'running', 'success', 'failed', 'skipped')",
name="ck_aoi_operation_partitions_status",
),
UniqueConstraint("operation_id", "partition_key", name="uq_aoi_operation_partition_key"),
Index("ix_aoi_operation_partitions_operation_status", "operation_id", "status"),
Index("ix_aoi_operation_partitions_geometry", "geometry", postgresql_using="gist"),
)
id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
operation_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), ForeignKey("aoi_operations.id", ondelete="CASCADE"), nullable=False)
child_job_id: Mapped[uuid.UUID | None] = mapped_column(UUID(as_uuid=True), ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True)
partition_key: Mapped[str] = mapped_column(String(255), nullable=False)
provider_key: Mapped[str] = mapped_column(String(120), nullable=False)
product_key: Mapped[str] = mapped_column(String(120), nullable=False)
ordinal: Mapped[int] = mapped_column(Integer, nullable=False)
status: Mapped[str] = mapped_column(String(32), nullable=False, default="queued")
geometry: Mapped[str] = mapped_column(Geometry("MultiPolygon", srid=4326, spatial_index=False), nullable=False)
attempt_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
max_attempts: Mapped[int] = mapped_column(Integer, nullable=False, default=3)
checkpoint_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
result_json: Mapped[dict | None] = mapped_column(JSON, nullable=True)
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
geointel/backend/app/providers/.gitkeep
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