.env example

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bunker-admin 2026-02-16 19:27:45 -07:00
parent a7978de5a0
commit cd19f8c0b9
9 changed files with 836 additions and 32 deletions

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.env.example Normal file
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# ==============================================================================
# Changemaker Lite v2 — Environment Variables
# Copy this file to .env and fill in the values
# Generate secrets with: openssl rand -hex 32
# ==============================================================================
#
# SECURITY WARNING:
# - All passwords marked REQUIRED_STRONG_PASSWORD_CHANGE_THIS MUST be changed
# - Use strong, unique passwords (20+ characters recommended)
# - Generate secrets with: openssl rand -hex 32
# - NEVER commit .env to version control
# ==============================================================================
# --- General ---
NODE_ENV=development
# Root domain serves MkDocs documentation site only
# All application routes (admin + public) accessible at app.${DOMAIN}
DOMAIN=cmlite.org
USER_ID=1000
GROUP_ID=1000
DOCKER_GROUP_ID=984
# --- V2 PostgreSQL ---
V2_POSTGRES_USER=changemaker
V2_POSTGRES_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
V2_POSTGRES_DB=changemaker_v2
V2_POSTGRES_PORT=5433
# --- JWT Auth ---
JWT_ACCESS_SECRET=GENERATE_WITH_openssl_rand_hex_32
JWT_REFRESH_SECRET=GENERATE_WITH_openssl_rand_hex_32
JWT_ACCESS_EXPIRY=15m
JWT_REFRESH_EXPIRY=7d
# Encryption key for DB-stored secrets (SMTP password, etc.)
# REQUIRED in production — must NOT reuse JWT_ACCESS_SECRET
# Generate with: openssl rand -hex 32
ENCRYPTION_KEY=GENERATE_WITH_openssl_rand_hex_32
# --- Initial Super Admin User (auto-created during database seeding) ---
# These credentials are used to create the initial super admin account
# Change these before running the seed script in production
INITIAL_ADMIN_EMAIL=admin@cmlite.org
INITIAL_ADMIN_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
# --- API ---
API_PORT=4000
API_URL=http://localhost:4000
CORS_ORIGINS=http://localhost:3000,http://localhost
# --- Admin GUI ---
ADMIN_PORT=3000
ADMIN_URL=http://localhost:3000
# --- Nginx ---
NGINX_HTTP_PORT=80
NGINX_HTTPS_PORT=443
# --- SMTP / Email ---
SMTP_HOST=mailhog-changemaker
SMTP_PORT=1025
SMTP_USER=
SMTP_PASS=
SMTP_FROM=noreply@cmlite.org
SMTP_FROM_NAME=Changemaker Lite
EMAIL_TEST_MODE=true
TEST_EMAIL_RECIPIENT=admin@cmlite.org
# --- Listmonk ---
LISTMONK_PORT=9001
LISTMONK_DB_PORT=5432
LISTMONK_DB_USER=listmonk
LISTMONK_DB_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
LISTMONK_DB_NAME=listmonk
# Web admin login (for the Listmonk dashboard at :9001)
LISTMONK_WEB_ADMIN_USER=admin
LISTMONK_WEB_ADMIN_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
# API user (auto-created by listmonk-init container, used by V2 API for sync)
# Generate token: openssl rand -hex 16
LISTMONK_API_USER=v2-api
LISTMONK_API_TOKEN=GENERATE_WITH_openssl_rand_hex_16
LISTMONK_ADMIN_USER=v2-api
LISTMONK_ADMIN_PASSWORD=SAME_AS_LISTMONK_API_TOKEN
LISTMONK_SYNC_ENABLED=false
LISTMONK_PROXY_PORT=9002
# Listmonk SMTP — MailHog for development (production SMTP added as second provider if credentials set)
LISTMONK_SMTP_HOST=mailhog-changemaker
LISTMONK_SMTP_PORT=1025
LISTMONK_SMTP_USER=
LISTMONK_SMTP_PASSWORD=
LISTMONK_SMTP_TLS_TYPE=none
LISTMONK_SMTP_FROM=Changemaker Lite <noreply@cmlite.org>
# Production SMTP (uncomment and set for real email delivery):
# LISTMONK_SMTP_HOST=smtp.protonmail.ch
# LISTMONK_SMTP_PORT=587
# LISTMONK_SMTP_USER=your@email.com
# LISTMONK_SMTP_PASSWORD=your-password
# LISTMONK_SMTP_TLS_TYPE=STARTTLS
# --- Represent API (Canadian electoral data) ---
REPRESENT_API_URL=https://represent.opennorth.ca
# --- NocoDB v2 (read-only data browser) ---
# NocoDB uses its own database (nocodb_meta) to avoid conflicts with Prisma
# The database is auto-created by init-nocodb-db.sh on first PostgreSQL startup
NOCODB_V2_PORT=8091
NOCODB_URL=http://changemaker-v2-nocodb:8080
NOCODB_PORT=8091
NC_ADMIN_EMAIL=admin@cmlite.org
NC_ADMIN_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
# --- Redis ---
# Shared Redis (v2 uses authenticated connection)
REDIS_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
REDIS_URL=redis://:${REDIS_PASSWORD}@redis-changemaker:6379
# --- Media Management ---
ENABLE_MEDIA_FEATURES=false
MEDIA_API_PORT=4100
MEDIA_API_PUBLIC_URL=http://media-api:4100
MEDIA_ROOT=/media/library
MEDIA_UPLOADS=/media/uploads
MAX_UPLOAD_SIZE_GB=10
VIDEO_PLAYER_DEBUG=false
# Video Analytics (Feb 2026)
VIDEO_ANALYTICS_RETENTION_DAYS=90
VIDEO_ANALYTICS_IP_HASHING_ENABLED=true
# Video Scheduling (Feb 2026)
VIDEO_SCHEDULE_DEFAULT_TIMEZONE=UTC
VIDEO_SCHEDULE_NOTIFICATION_ENABLED=true
# Preview Links (Feb 2026)
VIDEO_PREVIEW_LINK_EXPIRY_HOURS=24
# --- Gitea ---
GITEA_URL=http://gitea-changemaker:3000
GITEA_PORT=3030
GITEA_WEB_PORT=3030
GITEA_SSH_PORT=2222
GITEA_DB_TYPE=mysql
GITEA_DB_HOST=gitea-db:3306
GITEA_DB_NAME=gitea
GITEA_DB_USER=gitea
GITEA_DB_PASSWD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
GITEA_DB_ROOT_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
GITEA_ROOT_URL=https://git.cmlite.org
GITEA_DOMAIN=git.cmlite.org
# --- n8n ---
N8N_URL=http://n8n-changemaker:5678
N8N_PORT=5678
N8N_HOST=n8n.cmlite.org
N8N_ENCRYPTION_KEY=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
N8N_USER_EMAIL=admin@example.com
N8N_USER_PASSWORD=REQUIRED_STRONG_PASSWORD_CHANGE_THIS
GENERIC_TIMEZONE=UTC
# --- MkDocs ---
# Port mapping for MkDocs container (host:container)
# This also controls the Vite dev proxy in local development
# Change this port to use a different local port, and the admin dev server will automatically use it
MKDOCS_PORT=4003
MKDOCS_SITE_SERVER_PORT=4001
BASE_DOMAIN=https://cmlite.org
MKDOCS_PREVIEW_URL=http://mkdocs:8000
MKDOCS_DOCS_PATH=/mkdocs/docs
# --- Code Server ---
CODE_SERVER_PORT=8888
CODE_SERVER_URL=http://code-server:8080
USER_NAME=coder
# --- Homepage ---
HOMEPAGE_PORT=3010
HOMEPAGE_VAR_BASE_URL=http://localhost
# --- Mini QR ---
MINI_QR_PORT=8089
MINI_QR_URL=http://mini-qr:8080
MINI_QR_EMBED_PORT=8885
# --- Excalidraw (Collaborative Whiteboard) ---
EXCALIDRAW_PORT=8090
EXCALIDRAW_URL=http://excalidraw-changemaker:80
EXCALIDRAW_EMBED_PORT=8886
EXCALIDRAW_WS_URL=wss://draw.cmlite.org
# --- MailHog ---
MAILHOG_SMTP_PORT=1025
MAILHOG_WEB_PORT=8025
# --- NAR (National Address Register) ---
# Path to extracted NAR data (contains YYYYMM/Addresses/ and YYYYMM/Locations/)
# Download from: https://www150.statcan.gc.ca/n1/pub/46-26-0002/462600022022001-eng.htm
NAR_DATA_DIR=/data
# --- Overpass / Area Import ---
# OpenStreetMap Overpass API endpoint (use a private instance for heavy usage)
OVERPASS_API_URL=https://overpass-api.de/api/interpreter
# Minimum delay between Overpass requests (ms) — public API requires 30s
OVERPASS_MIN_DELAY_MS=30000
# Maximum reverse geocode grid points for area import fill-in
AREA_IMPORT_MAX_GRID_POINTS=500
# --- Geocoding ---
# Optional Mapbox API key for improved geocoding accuracy
# Free tier: 100,000 requests/month
# Sign up: https://www.mapbox.com/pricing
MAPBOX_API_KEY=
# Rate limit delay between provider requests (milliseconds)
GEOCODING_RATE_LIMIT_MS=1100
# Redis-backed persistent cache settings
GEOCODING_CACHE_ENABLED=true
GEOCODING_CACHE_TTL_HOURS=24
# Phase 2: Performance & Accuracy
# Google Maps API (optional, most accurate but costs $0.005/request after 100k/month)
GOOGLE_MAPS_API_KEY=
GOOGLE_MAPS_ENABLED=false
# Parallel geocoding for bulk imports (10x speedup)
GEOCODING_PARALLEL_ENABLED=true
GEOCODING_BATCH_SIZE=10
# Bulk Re-Geocoding (Phase 3)
BULK_GEOCODE_ENABLED=true
BULK_GEOCODE_MAX_BATCH=5000
# --- Pangolin Tunnel ---
# Server: self-hosted Pangolin instance
PANGOLIN_API_URL=https://api.bnkserve.org/v1
PANGOLIN_API_KEY=
PANGOLIN_ORG_ID=
# Populated after setup (via admin GUI or API)
PANGOLIN_SITE_ID=
PANGOLIN_ENDPOINT=https://pangolin.bnkserve.org
PANGOLIN_NEWT_ID=
PANGOLIN_NEWT_SECRET=
# --- Monitoring (only used with --profile monitoring) ---
PROMETHEUS_PORT=9090
GRAFANA_PORT=3001
GRAFANA_ADMIN_PASSWORD=admin
GRAFANA_ROOT_URL=http://localhost:3001
CADVISOR_PORT=8080
NODE_EXPORTER_PORT=9100
REDIS_EXPORTER_PORT=9121
ALERTMANAGER_PORT=9093
GOTIFY_PORT=8889
GOTIFY_ADMIN_USER=admin
GOTIFY_ADMIN_PASSWORD=admin

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.gitignore vendored
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@ -21,6 +21,7 @@ node_modules/
.env
.env*
!.env.example
/configs/cloudflare/*.json
/configs/cloudflare/*.yaml
@ -34,3 +35,12 @@ node_modules/
# NAR data directory (large voter registry files)
/data/
# Media files (managed by Docker volumes, not git)
/media/
# Build output
/admin/dist/
# MkDocs core binary
/mkdocs/core

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admin/.env.example Normal file
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@ -0,0 +1,9 @@
# API Configuration
# For Docker: http://changemaker-v2-api:4000
# For local dev: http://localhost:4000
VITE_API_URL=http://localhost:4000
# MkDocs Configuration
# For Docker: http://mkdocs-changemaker:8000
# For local dev: http://localhost:4003
VITE_MKDOCS_URL=http://localhost:4003

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@ -1,4 +1,4 @@
import { useState, useEffect, useRef, useCallback } from 'react';
import { useState, useEffect, useRef, useCallback, useMemo } from 'react';
import {
Steps,
Button,
@ -26,7 +26,11 @@ import {
CloseCircleOutlined,
LoadingOutlined,
MinusCircleOutlined,
WarningOutlined,
} from '@ant-design/icons';
import { MapContainer, TileLayer, Rectangle, Polygon, useMap } from 'react-leaflet';
import type { LatLngBoundsExpression } from 'leaflet';
import 'leaflet/dist/leaflet.css';
import { api } from '@/lib/api';
import type {
Cut,
@ -51,6 +55,56 @@ const SOURCE_STATUS_ICONS: Record<AreaImportSourceStatus, React.ReactNode> = {
skipped: <MinusCircleOutlined style={{ color: '#d9d9d9' }} />,
};
const ZOOM_PRESETS = [
{ value: 15, label: 'Neighborhood (zoom 15)' },
{ value: 13, label: 'District (zoom 13)' },
{ value: 10, label: 'City-wide (zoom 10)' },
{ value: 8, label: 'Region (zoom 8)' },
];
/**
* Client-side bounding box calculation from center + zoom + viewport.
* Mirrors the server-side boundsFromCenterZoom() in spatial.ts.
*/
function boundsFromCenterZoom(
lat: number,
lng: number,
zoom: number,
viewportWidth = 1024,
viewportHeight = 768,
): { minLat: number; maxLat: number; minLng: number; maxLng: number } {
const metersPerPixel = (156543.03392 * Math.cos((lat * Math.PI) / 180)) / Math.pow(2, zoom);
const halfWidthMeters = (viewportWidth / 2) * metersPerPixel;
const halfHeightMeters = (viewportHeight / 2) * metersPerPixel;
const latDelta = halfHeightMeters / 111320;
const lngDelta = halfWidthMeters / (111320 * Math.cos((lat * Math.PI) / 180));
return {
minLat: lat - latDelta,
maxLat: lat + latDelta,
minLng: lng - lngDelta,
maxLng: lng + lngDelta,
};
}
/**
* Approximate area in sq km from a bounding box.
*/
function areaSqKm(bounds: { minLat: number; maxLat: number; minLng: number; maxLng: number }): number {
const latMeters = (bounds.maxLat - bounds.minLat) * 111320;
const avgLat = (bounds.minLat + bounds.maxLat) / 2;
const lngMeters = (bounds.maxLng - bounds.minLng) * 111320 * Math.cos((avgLat * Math.PI) / 180);
return (latMeters * lngMeters) / 1_000_000;
}
/** Fit the map to given bounds whenever they change. */
function FitBoundsUpdater({ bounds }: { bounds: LatLngBoundsExpression }) {
const map = useMap();
useEffect(() => {
map.fitBounds(bounds, { padding: [20, 20] });
}, [map, bounds]);
return null;
}
export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardProps) {
const [currentStep, setCurrentStep] = useState(0);
@ -59,6 +113,7 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
const [selectedCutId, setSelectedCutId] = useState<string | undefined>();
const [mapSettings, setMapSettings] = useState<MapSettings | null>(null);
const [mapSettingsLoading, setMapSettingsLoading] = useState(false);
const [zoomOverride, setZoomOverride] = useState<number | null>(null);
// Step 1: Sources
const [osmEnabled, setOsmEnabled] = useState(true);
@ -78,6 +133,9 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
const [importing, setImporting] = useState(false);
const pollRef = useRef<ReturnType<typeof setInterval>>(undefined);
// Effective zoom for viewport mode (override or map settings default)
const effectiveZoom = zoomOverride ?? mapSettings?.zoom ?? 13;
// Load map settings for viewport mode
useEffect(() => {
if (areaType === 'viewport' && !mapSettings) {
@ -96,6 +154,54 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
};
}, []);
// Compute viewport bounds for preview map
const viewportBounds = useMemo(() => {
if (areaType !== 'viewport' || !mapSettings?.latitude || !mapSettings?.longitude) return null;
return boundsFromCenterZoom(
Number(mapSettings.latitude),
Number(mapSettings.longitude),
effectiveZoom,
);
}, [areaType, mapSettings?.latitude, mapSettings?.longitude, effectiveZoom]);
const viewportAreaSqKm = viewportBounds ? areaSqKm(viewportBounds) : null;
// Parse cut polygon for preview map
const selectedCutGeoJson = useMemo(() => {
if (areaType !== 'cut' || !selectedCutId) return null;
const cut = cuts.find((c) => c.id === selectedCutId);
if (!cut?.geojson) return null;
try {
const parsed = JSON.parse(cut.geojson);
// GeoJSON coordinates are [lng, lat] — Leaflet Polygon needs [lat, lng]
if (parsed.type === 'Polygon' && parsed.coordinates) {
return parsed.coordinates[0].map((c: number[]) => [c[1], c[0]] as [number, number]);
}
if (parsed.type === 'MultiPolygon' && parsed.coordinates) {
// Just use the first polygon ring for preview
return parsed.coordinates[0][0].map((c: number[]) => [c[1], c[0]] as [number, number]);
}
// If it's just an array of coordinate rings (legacy format)
if (Array.isArray(parsed) && Array.isArray(parsed[0])) {
return parsed[0].map((c: number[]) => [c[1], c[0]] as [number, number]);
}
} catch { /* ignore parse errors */ }
return null;
}, [areaType, selectedCutId, cuts]);
// Cut bounds for fitBounds
const cutPreviewBounds = useMemo((): LatLngBoundsExpression | null => {
if (!selectedCutGeoJson || selectedCutGeoJson.length === 0) return null;
let minLat = Infinity, maxLat = -Infinity, minLng = Infinity, maxLng = -Infinity;
for (const [lat, lng] of selectedCutGeoJson) {
if (lat < minLat) minLat = lat;
if (lat > maxLat) maxLat = lat;
if (lng < minLng) minLng = lng;
if (lng > maxLng) maxLng = lng;
}
return [[minLat, minLng], [maxLat, maxLng]];
}, [selectedCutGeoJson]);
const buildRequestBody = useCallback(() => {
const sources: Record<string, unknown> = {
osm: osmEnabled,
@ -114,11 +220,11 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
lat: mapSettings?.latitude ? Number(mapSettings.latitude) : 53.5,
lng: mapSettings?.longitude ? Number(mapSettings.longitude) : -113.5,
};
body.zoom = mapSettings?.zoom ?? 13;
body.zoom = effectiveZoom;
}
return body;
}, [areaType, selectedCutId, mapSettings, osmEnabled, narEnabled, narResidentialOnly, rgEnabled, rgSpacing, rgMaxPoints]);
}, [areaType, selectedCutId, mapSettings, effectiveZoom, osmEnabled, narEnabled, narResidentialOnly, rgEnabled, rgSpacing, rgMaxPoints]);
const fetchPreview = async () => {
setPreviewLoading(true);
@ -162,6 +268,94 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
const canProceedStep0 = areaType === 'cut' ? !!selectedCutId : (!!mapSettings?.latitude && !!mapSettings?.longitude);
const canProceedStep1 = osmEnabled || narEnabled || rgEnabled;
// ─── Mini Map Preview ─────────────────────────────────────────────
const renderPreviewMap = () => {
// Viewport mode: show rectangle
if (areaType === 'viewport' && viewportBounds) {
const mapBounds: LatLngBoundsExpression = [
[viewportBounds.minLat, viewportBounds.minLng],
[viewportBounds.maxLat, viewportBounds.maxLng],
];
return (
<Card size="small" title="Import Area Preview" style={{ marginTop: 12 }}>
<div style={{ height: 250 }}>
<MapContainer
bounds={mapBounds}
style={{ width: '100%', height: '100%' }}
zoomControl={false}
dragging={false}
scrollWheelZoom={false}
doubleClickZoom={false}
touchZoom={false}
boxZoom={false}
keyboard={false}
attributionControl={false}
>
<TileLayer url="https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png" />
<FitBoundsUpdater bounds={mapBounds} />
<Rectangle
bounds={mapBounds}
pathOptions={{
color: '#1890ff',
weight: 2,
dashArray: '6 4',
fillColor: '#1890ff',
fillOpacity: 0.1,
}}
/>
</MapContainer>
</div>
</Card>
);
}
// Cut mode: show polygon
if (areaType === 'cut' && selectedCutGeoJson && cutPreviewBounds) {
return (
<Card size="small" title="Import Area Preview" style={{ marginTop: 12 }}>
<div style={{ height: 250 }}>
<MapContainer
bounds={cutPreviewBounds}
style={{ width: '100%', height: '100%' }}
zoomControl={false}
dragging={false}
scrollWheelZoom={false}
doubleClickZoom={false}
touchZoom={false}
boxZoom={false}
keyboard={false}
attributionControl={false}
>
<TileLayer url="https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png" />
<FitBoundsUpdater bounds={cutPreviewBounds} />
<Polygon
positions={selectedCutGeoJson}
pathOptions={{
color: '#1890ff',
weight: 2,
fillColor: '#1890ff',
fillOpacity: 0.15,
}}
/>
</MapContainer>
</div>
</Card>
);
}
// No area configured yet
return (
<Card size="small" style={{ marginTop: 12 }}>
<Text type="secondary" style={{ display: 'block', textAlign: 'center', padding: 16 }}>
Select an area type above to see preview
</Text>
</Card>
);
};
// ─── Steps ─────────────────────────────────────────────────────────
const steps = [
{
title: 'Define Area',
@ -202,22 +396,56 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
{mapSettingsLoading ? (
<Spin size="small" />
) : mapSettings?.latitude && mapSettings?.longitude ? (
<Card size="small">
<Row gutter={16}>
<Col span={8}>
<Statistic title="Center Lat" value={Number(mapSettings.latitude).toFixed(4)} valueStyle={{ fontSize: 16 }} />
</Col>
<Col span={8}>
<Statistic title="Center Lng" value={Number(mapSettings.longitude).toFixed(4)} valueStyle={{ fontSize: 16 }} />
</Col>
<Col span={8}>
<Statistic title="Zoom" value={mapSettings.zoom ?? 13} valueStyle={{ fontSize: 16 }} />
</Col>
</Row>
<Text type="secondary" style={{ fontSize: 12, marginTop: 8, display: 'block' }}>
A bounding box will be derived from the map center and zoom level.
</Text>
</Card>
<>
<Card size="small">
<Row gutter={16}>
<Col span={6}>
<Statistic title="Center Lat" value={Number(mapSettings.latitude).toFixed(4)} valueStyle={{ fontSize: 16 }} />
</Col>
<Col span={6}>
<Statistic title="Center Lng" value={Number(mapSettings.longitude).toFixed(4)} valueStyle={{ fontSize: 16 }} />
</Col>
<Col span={6}>
<Statistic title="Zoom" value={effectiveZoom} valueStyle={{ fontSize: 16 }} />
</Col>
<Col span={6}>
<Statistic
title="Area"
value={viewportAreaSqKm ? viewportAreaSqKm.toFixed(0) : '—'}
suffix="km2"
valueStyle={{ fontSize: 16 }}
/>
</Col>
</Row>
</Card>
<div style={{ marginTop: 12 }}>
<Text strong style={{ display: 'block', marginBottom: 4 }}>Zoom Level Override:</Text>
<Select
value={effectiveZoom}
onChange={(val) => setZoomOverride(val)}
style={{ width: '100%' }}
options={[
{ value: mapSettings.zoom ?? 13, label: `Map Settings Default (zoom ${mapSettings.zoom ?? 13})` },
...ZOOM_PRESETS.filter((p) => p.value !== (mapSettings.zoom ?? 13)),
]}
/>
<Text type="secondary" style={{ fontSize: 12, marginTop: 4, display: 'block' }}>
Lower zoom = larger area. Use "City-wide" for full city imports.
</Text>
</div>
{viewportAreaSqKm !== null && viewportAreaSqKm < 50 && (
<Alert
message="Small Coverage Area"
description={`This covers only ${viewportAreaSqKm.toFixed(0)} km2. Consider using a lower zoom level for city-wide imports.`}
type="warning"
showIcon
icon={<WarningOutlined />}
style={{ marginTop: 12 }}
/>
)}
</>
) : (
<Alert
message="Map settings not configured"
@ -228,6 +456,8 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
)}
</div>
)}
{renderPreviewMap()}
</div>
),
},
@ -479,6 +709,9 @@ export default function AreaImportWizard({ cuts, onComplete }: AreaImportWizardP
{sp.candidatesFound > 0 && (
<Text type="secondary">{sp.candidatesFound} found</Text>
)}
{sp.failedQuadrants && sp.failedQuadrants > 0 && (
<Tag color="warning">{sp.failedQuadrants} quadrant(s) failed</Tag>
)}
</Space>
{sp.message && (
<Text type="secondary" style={{ display: 'block', marginLeft: 24, fontSize: 12 }}>

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@ -198,7 +198,7 @@ export default function VolunteerMapPage() {
};
// Zoom-based limits (from v1 optimization)
const limit = zoom >= 15 ? 2000 : zoom >= 12 ? 1000 : 500;
const limit = zoom >= 15 ? 5000 : zoom >= 12 ? 3000 : 1500;
clearTimeout(fetchTimerRef.current);
fetchTimerRef.current = setTimeout(() => {

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@ -1286,6 +1286,7 @@ export type AreaImportSourceStatus = 'pending' | 'running' | 'complete' | 'faile
export interface AreaImportSourceProgress {
status: AreaImportSourceStatus;
candidatesFound: number;
failedQuadrants?: number;
message?: string;
error?: string;
}

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@ -22,6 +22,7 @@ export type SourceStatus = 'pending' | 'running' | 'complete' | 'failed' | 'skip
export interface AreaImportSourceProgress {
status: SourceStatus;
candidatesFound: number;
failedQuadrants?: number;
message?: string;
error?: string;
}
@ -333,24 +334,28 @@ export const areaImportService = {
progress.sources.osm.status = 'running';
await updateProgress();
try {
const osmCandidates = await overpassService.queryArea(bounds, (msg) => {
const osmResult = await overpassService.queryArea(bounds, (msg) => {
progress.sources.osm.message = msg;
writeProgress(importId, progress).catch(() => {});
});
// Filter by cut polygon if applicable
let filtered = osmCandidates;
let filtered = osmResult.candidates;
if (cutPolygons && cutPolygons.length > 0) {
filtered = osmCandidates.filter((c) =>
filtered = osmResult.candidates.filter((c) =>
cutPolygons.some((ring) => isPointInPolygon(c.latitude, c.longitude, ring)),
);
}
allCandidates.push(...filtered);
for (const c of filtered) allCandidates.push(c);
progress.sources.osm.status = 'complete';
progress.sources.osm.candidatesFound = filtered.length;
if (osmResult.failedQuadrants > 0) {
progress.sources.osm.failedQuadrants = osmResult.failedQuadrants;
progress.sources.osm.message = `${filtered.length} found, ${osmResult.failedQuadrants} quadrant(s) failed`;
}
await updateProgress();
logger.info(`OSM source: ${filtered.length} candidates (${osmCandidates.length} pre-filter)`);
logger.info(`OSM source: ${filtered.length} candidates (${osmResult.candidates.length} pre-filter, ${osmResult.failedQuadrants} failed quadrants)`);
} catch (err) {
const msg = err instanceof Error ? err.message : 'Unknown error';
progress.sources.osm.status = 'failed';
@ -469,7 +474,7 @@ export const areaImportService = {
}
}
allCandidates.push(...narCandidates);
for (const c of narCandidates) allCandidates.push(c);
progress.sources.nar.status = 'complete';
progress.sources.nar.candidatesFound = narCandidates.length;
await updateProgress();
@ -564,7 +569,7 @@ export const areaImportService = {
await new Promise((resolve) => setTimeout(resolve, 1100));
}
allCandidates.push(...rgCandidates);
for (const c of rgCandidates) allCandidates.push(c);
progress.sources.reverseGeocode.status = 'complete';
progress.sources.reverseGeocode.candidatesFound = rgCandidates.length;
await updateProgress();

View File

@ -172,11 +172,12 @@ export const overpassService = {
/**
* Query all address data within a bounding box.
* Automatically splits large areas into sub-quadrants.
* Returns candidates and the number of quadrants that failed.
*/
async queryArea(
bounds: { minLat: number; maxLat: number; minLng: number; maxLng: number },
onProgress?: (msg: string) => void,
): Promise<CandidateLocation[]> {
): Promise<{ candidates: CandidateLocation[]; failedQuadrants: number }> {
const area = areaSqDeg(bounds);
// If area is too large, split into quadrants and query each
@ -184,20 +185,23 @@ export const overpassService = {
const quadrants = splitBounds(bounds);
const allCandidates: CandidateLocation[] = [];
const totalQuadrants = quadrants.length;
let failedQuadrants = 0;
for (let i = 0; i < totalQuadrants; i++) {
onProgress?.(`Querying OSM quadrant ${i + 1}/${totalQuadrants}`);
try {
const subCandidates = await this.queryArea(quadrants[i]!, onProgress);
allCandidates.push(...subCandidates);
const result = await this.queryArea(quadrants[i]!, onProgress);
for (const c of result.candidates) allCandidates.push(c);
failedQuadrants += result.failedQuadrants;
} catch (err) {
const msg = err instanceof Error ? err.message : 'Unknown error';
logger.warn(`Overpass quadrant ${i + 1} failed: ${msg}`);
failedQuadrants++;
// Continue with other quadrants
}
}
return allCandidates;
return { candidates: allCandidates, failedQuadrants };
}
const bbox = `${bounds.minLat},${bounds.minLng},${bounds.maxLat},${bounds.maxLng}`;
@ -206,6 +210,6 @@ export const overpassService = {
onProgress?.('Querying OSM addresses...');
const data = await queryOverpass<OverpassResponse>(query);
return parseElements(data.elements);
return { candidates: parseElements(data.elements), failedQuadrants: 0 };
},
};

291
media-manager/.env.example Normal file
View File

@ -0,0 +1,291 @@
# =============================================================================
# REQUIRED SECRETS - You MUST change these before starting!
# =============================================================================
# PostgreSQL password - REQUIRED
# Generate: openssl rand -base64 24
POSTGRES_PASSWORD=CHANGE_ME_REQUIRED
# JWT secret for authentication - REQUIRED (min 32 characters)
# Generate: openssl rand -hex 32
JWT_SECRET=CHANGE_ME_REQUIRED_MIN_32_CHARS
# Initial admin account (created on first startup if no admin exists)
INITIAL_ADMIN_EMAIL=admin@example.com
INITIAL_ADMIN_PASSWORD=ChangeMe123!
# SMTP Configuration (required for email verification and password reset)
# Leave empty to disable email features (admin approval will be used instead)
SMTP_HOST=smtp.example.com
SMTP_PORT=587
SMTP_SECURE=false
SMTP_USER=your-smtp-username
SMTP_PASS=your-smtp-password
SMTP_FROM=noreply@example.com
SMTP_FROM_NAME=Media Manager
# Email settings
EMAIL_VERIFICATION_EXPIRY_HOURS=24
PASSWORD_RESET_EXPIRY_HOURS=1
# Application URL (used in email links)
APP_BASE_URL=http://localhost:3080
# CORS allowed origins (comma-separated)
# Add your production domains here
ALLOWED_ORIGINS=http://localhost:3080,http://localhost:8080
# Timezone for API server (logs and server-side timestamps)
# See: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
TZ=UTC
# Locale for date/time formatting (optional, defaults to browser locale)
# Examples: en-US, en-GB, de-DE, fr-FR
VITE_DEFAULT_LOCALE=
# =============================================================================
# MAXMIND GEOIP CONFIGURATION (optional)
# =============================================================================
# Provides geographic location data for session analytics
# Download GeoLite2-City.mmdb from: https://dev.maxmind.com/geoip/geolite2-free-geolocation-data
# Place the file in ./data/GeoLite2-City.mmdb (mounted to /app/data in container)
# Register for free account to download: https://www.maxmind.com/en/geolite2/signup
# =============================================================================
# CONTENT SAFETY CONFIGURATION (requires --profile safety)
# =============================================================================
# Set to false to disable LLM-based content safety checking
SAFETY_CHECK_ENABLED=true
# Admin email for high-severity content alerts (e.g., S4 Child Sexual Exploitation)
# If not set, falls back to SMTP_FROM
# Leave empty to disable high-severity email alerts
ADMIN_ALERT_EMAIL=
# =============================================================================
# OLLAMA CONFIGURATION
# =============================================================================
# Base URL for Ollama API (shared by safety and digest features)
OLLAMA_BASE_URL=http://ollama:11434
# Content Safety Model (Llama Guard for chat moderation)
OLLAMA_MODEL=llama-guard3:1b
# =============================================================================
# DIGEST FEATURE MODELS (requires --profile digest)
# =============================================================================
# Video analysis pipeline using vision-language models and speech recognition
#
# Vision Model - analyzes video frames (requires vision-language model)
# Used for: frame description, visual element detection, scene classification
# Options:
# - huihui_ai/qwen3-vl-abliterated:2b (uncensored, ~2GB VRAM) [RECOMMENDED]
# - qwen2-vl:7b (censored, ~7GB VRAM)
# - llava:7b (censored, ~7GB VRAM)
DIGEST_VISION_MODEL=huihui_ai/qwen3-vl-abliterated:2b
# Text Model - synthesizes analysis results (text-only LLM)
# Used for: tag extraction, transcript analysis, final synthesis
# Options:
# - huihui_ai/qwen3-abliterated:4b (uncensored, ~4GB VRAM) [RECOMMENDED]
# - qwen2.5:7b (censored, ~7GB VRAM)
# - llama3.1:8b (censored, ~8GB VRAM)
DIGEST_TEXT_MODEL=huihui_ai/qwen3-abliterated:4b
# Digest service URLs
DIGEST_OLLAMA_URL=http://ollama:11434
DIGEST_WHISPER_URL=http://whisper:5000
# Frame extraction interval (seconds between frames)
DIGEST_FRAME_INTERVAL=30
# =============================================================================
# JOYCAPTION VISION BACKEND (requires --profile joycaption)
# =============================================================================
# Alternative to Ollama vision models - uses JoyCaption GGUF via llama.cpp
# Better quality image captioning, fits on 6GB VRAM with Q3_K_M quantization
#
# Vision backend type: 'ollama' (default) or 'llama-server' (JoyCaption)
DIGEST_VISION_BACKEND=ollama
# JoyCaption server URL (when using llama-server backend)
JOYCAPTION_URL=http://joycaption:8080
JOYCAPTION_MODEL=llama-joycaption-beta-one-hf-llava
# Fall back to Ollama vision if JoyCaption fails
JOYCAPTION_FALLBACK_TO_OLLAMA=true
# JoyCaption model files (place in ./models directory)
# Download from: https://huggingface.co/Mungert/llama-joycaption-beta-one-hf-llava-GGUF
# Quantization options:
# - Q2_K: ~3.2GB model, ~4GB VRAM (good quality, safest for 6GB GPU)
# - Q3_K_M: ~4GB model, ~5GB VRAM (better quality, tight fit on 6GB)
# - Q4_K_M: ~5GB model, ~6GB VRAM (best quality, needs 8GB+ GPU)
JOYCAPTION_MODEL_PATH=/models/llama-joycaption-beta-one-hf-llava.Q2_K.gguf
JOYCAPTION_MMPROJ_PATH=/models/llama-joycaption-beta-one-llava-mmproj-model-f16.gguf
# llama-server configuration
JOYCAPTION_CTX_SIZE=4096
JOYCAPTION_GPU_LAYERS=999
JOYCAPTION_PARALLEL=1
# =============================================================================
# WHISPER TRANSCRIPTION
# =============================================================================
# Model sizes: tiny, base, small, medium, large-v2, large-v3
# Larger = more accurate but slower and more VRAM
WHISPER_MODEL=base
WHISPER_DEVICE=cuda
WHISPER_COMPUTE=float16
# =============================================================================
# OLLAMA AUTO-PULL MODELS
# =============================================================================
# Comma-separated list of models to pull on Ollama container startup
# Include all models needed for your enabled features
#
# Safety profile only:
# OLLAMA_MODELS=llama-guard3:1b
#
# Digest profile only:
# OLLAMA_MODELS=huihui_ai/qwen3-vl-abliterated:2b,huihui_ai/qwen3-abliterated:4b
#
# Both profiles (recommended):
OLLAMA_MODELS=llama-guard3:1b,huihui_ai/qwen3-vl-abliterated:2b,huihui_ai/qwen3-abliterated:4b
# =============================================================================
# JOB QUEUE CONFIGURATION
# =============================================================================
# GPU resource management for preventing job conflicts
# The system automatically queues GPU-intensive jobs to prevent VRAM exhaustion
# Maximum GPU VRAM in MB (default: 6000 for RTX 4050)
# Adjust based on your GPU: RTX 3090 = 24000, RTX 4080 = 16000, etc.
MAX_GPU_VRAM=6000
# =============================================================================
# FFMPEG ENCODING CONCURRENCY
# =============================================================================
# Number of parallel FFmpeg encode sessions for clip/scene generation.
# NVENC supports 3-5 concurrent sessions on consumer RTX GPUs (~200-400MB VRAM each).
# Set to 1 to restore sequential behavior.
FFMPEG_ENCODE_CONCURRENCY=2
# Disable job queue for immediate execution (legacy behavior)
# Set to 'true' to bypass the queue manager entirely
# DISABLE_JOB_QUEUE=false
# =============================================================================
# INBOX FILE WATCHER CONFIGURATION
# =============================================================================
# Automatically watches inbox directory for new video files.
# When a new file is fully written, it's scanned into the library
# and optionally triggers auto-digest if auto_digest_enabled is true.
# Enable/disable file watcher (default: false, can also enable via admin UI)
# Set to 'true' to auto-detect new files added to inbox directory
FILE_WATCHER_ENABLED=false
# Time in ms to wait for file size to stabilize before processing (default: 2000)
# Increase for slower network drives or when copying large files
FILE_WATCHER_DEBOUNCE_MS=2000
# =============================================================================
# CONTAINER LIFECYCLE CONFIGURATION
# =============================================================================
# By default, the system starts AI containers on-demand and stops them after use
# to minimize VRAM usage. Set to 'true' to disable this behavior when all AI
# containers are configured to run continuously (e.g., models fit in VRAM).
#
# When enabled:
# - ensureContainerRunning() only checks health, doesn't start containers
# - stopContainer() becomes a no-op, containers keep running
# - You must manually start containers: docker compose --profile ai up -d
DISABLE_CONTAINER_LIFECYCLE=false
# =============================================================================
# COMBINED SCENE DETECTION CONFIGURATION
# =============================================================================
# Uses three methods: TransNetV2 (neural), PySceneDetect (histogram), CLIP (semantic)
# Results are merged using configurable strategies for more accurate scene boundaries.
#
# Enable/disable combined detection (default: true)
# When disabled, falls back to PySceneDetect only
ENABLE_COMBINED_SCENE_DETECTION=true
# Merge strategy for combining cuts from multiple detectors
# Options: weighted (default), union, intersection, majority
# - weighted: Uses detector confidence weights (best balance)
# - union: Include all cuts (most comprehensive, may over-segment)
# - intersection: Only cuts from all 3 detectors (highest confidence)
# - majority: Cuts from 2+ detectors
SCENE_MERGE_STRATEGY=weighted
# Tolerance window for grouping cuts (seconds)
# Cuts within this window are considered "the same" cut
SCENE_MERGE_TOLERANCE=0.75
# Run GPU detectors in parallel (requires >12GB VRAM)
# When false (default), runs sequentially: PyScene -> TransNet -> CLIP
SCENE_DETECTION_PARALLEL=false
# Detector weights for weighted merge strategy
# Higher weight = more trusted detector
SCENE_WEIGHT_TRANSNET=1.0 # Neural network, best for soft transitions
SCENE_WEIGHT_PYSCENEDETECT=0.8 # Histogram-based, fast, good for hard cuts
SCENE_WEIGHT_CLIP=0.9 # Visual embeddings, semantic/content changes
# CLIP boundary detection configuration
# Extracts frames at interval, computes embeddings, detects similarity drops
CLIP_BOUNDARY_FRAME_INTERVAL=0.5 # Seconds between frames (0.5 = 2 fps)
CLIP_BOUNDARY_SIMILARITY_THRESHOLD=0.7 # Below this = scene boundary (0-1)
CLIP_BOUNDARY_MIN_GAP=2.0 # Minimum seconds between boundaries
# CLIP embeddings GPU batch size (default: 128)
# Higher = faster processing, more VRAM usage
# RTX 4050 6GB: safe up to 512, recommended 256
# RTX 3090 24GB: can use 1024+
CLIP_GPU_BATCH_SIZE=256
# Database path (inside container)
DATABASE_URL=/app/data/library.db
# Media library paths (host paths)
MEDIA_ROOT=/media/bunker-admin/Internal/plex/xxx/media
MEDIA_LOCAL=/media/bunker-admin/Internal/plex/xxx/media/local
MEDIA_PUBLIC=/media/bunker-admin/Internal/plex/xxx/media/public
STUDIOS_PATH=/media/bunker-admin/Internal/plex/xxx/media/local/studios
GIFS_PATH=/media/bunker-admin/Internal/plex/xxx/media/local/gifs
PLAYBACK_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/playback
COMPILATIONS_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/compilations
PUBLIC_CURATED_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/curated
QUICKIES_PATH=/media/bunker-admin/Internal/plex/xxx/media/public/quickies
# =============================================================================
# PAYMENT SYSTEM CONFIGURATION
# =============================================================================
# IMAP settings for automatic e-transfer email parsing
# Leave empty to disable automatic payment polling (manual entry only)
#
# For Proton Mail: Requires Proton Mail Bridge running locally
# PAYMENT_IMAP_HOST=127.0.0.1 (or host.docker.internal from container)
# PAYMENT_IMAP_PORT=1143
# PAYMENT_IMAP_TLS=false (Bridge uses STARTTLS)
#
# For Gmail: Enable "Less secure app access" or use App Password
# PAYMENT_IMAP_HOST=imap.gmail.com
# PAYMENT_IMAP_PORT=993
# PAYMENT_IMAP_TLS=true
#
PAYMENT_IMAP_HOST=
PAYMENT_IMAP_PORT=993
PAYMENT_IMAP_USER=
PAYMENT_IMAP_PASS=
PAYMENT_IMAP_TLS=true
# How often to check for new payment emails (milliseconds)
# Default: 60000 (1 minute)
PAYMENT_POLL_INTERVAL_MS=60000
# Folder to move processed emails to (created automatically)
PAYMENT_PROCESSED_FOLDER=Processed