Merge pull request 'Version 9b' (#1) from develop into main
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Reviewed-on: #1
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Lars 2026-03-19 08:04:01 +01:00
commit 9d15336144
18 changed files with 3311 additions and 1651 deletions

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# ── Datenbank ──────────────────────────────────────────────────
# v9 (PostgreSQL):
DB_PASSWORD=sicheres_passwort_hier
# v8 (SQLite, legacy):
# DATA_DIR=/app/data
# ── Datenbank (PostgreSQL v9b+) ────────────────────────────────
DB_HOST=postgres
DB_PORT=5432
DB_NAME=mitai
DB_USER=mitai
DB_PASSWORD=mitaiDB-PostgreSQL-Neckar-strong
# ── KI ─────────────────────────────────────────────────────────
# OpenRouter (empfohlen):

3
.gitignore vendored
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# Temp
tmp/
*.tmp
#.claude Konfiguration
.claude/

633
CLAUDE.md
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@ -1,33 +1,32 @@
# Mitai Jinkendo Entwickler-Kontext für Claude Code
## Projekt-Übersicht
**Mitai Jinkendo** ist eine selbst-gehostete PWA für Körper-Tracking (Gewicht, Körperfett, Umfänge, Ernährung, Aktivität) mit KI-Auswertung. Teil der **Jinkendo**-App-Familie (人拳道 Der menschliche Weg der Kampfkunst).
**Mitai Jinkendo** (身体 Jinkendo) ist eine selbst-gehostete PWA für Körper-Tracking (Gewicht, Körperfett, Umfänge, Ernährung, Aktivität) mit KI-Auswertung. Teil der **Jinkendo**-App-Familie (人拳道 Der menschliche Weg der Kampfkunst).
**Produktfamilie:** body · fight · guard · train · mind (alle unter jinkendo.de)
**Produktfamilie:** mitai · miken · ikigai · shinkan · kenkou (alle unter jinkendo.de)
## Tech-Stack
| Komponente | Technologie | Version |
|-----------|-------------|---------|
| Frontend | React 18 + Vite + PWA | Node 20 |
| Backend | FastAPI (Python) | Python 3.12 |
| Datenbank | PostgreSQL | 16 (Ziel: v9) / SQLite (aktuell: v8) |
| Datenbank | PostgreSQL 16 (Alpine) | v9b |
| Container | Docker + Docker Compose | - |
| Webserver | nginx (Reverse Proxy + HTTPS) | Alpine |
| Auth | Token-basiert (eigene Impl.) | - |
| Webserver | nginx (Reverse Proxy) | Alpine |
| Auth | Token-basiert + bcrypt | - |
| KI | OpenRouter API (claude-sonnet-4) | - |
## Ports
| Service | Intern | Extern (Dev) |
|---------|--------|-------------|
| Frontend | 80 (nginx) | 3002 |
| Backend | 8000 (uvicorn) | 8002 |
| PostgreSQL | 5432 | nicht exponiert |
| Service | Prod | Dev |
|---------|------|-----|
| Frontend | 3002 | 3099 |
| Backend | 8002 | 8099 |
## Verzeichnisstruktur
```
mitai-jinkendo/
├── backend/
│ ├── main.py # FastAPI App, alle Endpoints
│ ├── main.py # FastAPI App, alle Endpoints (~2000 Zeilen)
│ ├── requirements.txt
│ └── Dockerfile
├── frontend/
@ -38,113 +37,159 @@ mitai-jinkendo/
│ │ │ ├── AuthContext.jsx # Session, Login, Logout
│ │ │ └── ProfileContext.jsx # Aktives Profil
│ │ ├── pages/ # Alle Screens
│ │ ├── utils/
│ │ │ ├── api.js # Alle API-Calls (injiziert Token + ProfileId)
│ │ │ ├── calc.js # Körperfett-Formeln
│ │ │ ├── interpret.js # Regelbasierte Auswertung
│ │ │ ├── Markdown.jsx # Eigener MD-Renderer
│ │ │ └── guideData.js # Messanleitungen
│ │ └── main.jsx
│ ├── public/ # Icons (Jinkendo Ensō-Logo)
│ ├── index.html
│ ├── vite.config.js
│ └── Dockerfile
├── nginx/
│ └── nginx.conf
├── docker-compose.yml # Produktion
├── docker-compose.dev.yml # Entwicklung (Hot-Reload)
├── .env.example
└── CLAUDE.md # Diese Datei
│ │ └── utils/
│ │ ├── api.js # Alle API-Calls (injiziert Token automatisch)
│ │ ├── calc.js # Körperfett-Formeln
│ │ ├── interpret.js # Regelbasierte Auswertung
│ │ ├── Markdown.jsx # Eigener MD-Renderer
│ │ └── guideData.js # Messanleitungen
│ └── public/ # Icons (Jinkendo Ensō-Logo)
├── .gitea/workflows/
│ ├── deploy-prod.yml # Auto-Deploy bei Push auf main
│ ├── deploy-dev.yml # Auto-Deploy bei Push auf develop
│ └── test.yml # Build-Test bei jedem Push
├── docker-compose.yml # Produktion (Ports 3002/8002)
├── docker-compose.dev-env.yml # Development (Ports 3099/8099)
└── CLAUDE.md # Diese Datei
```
## Aktuelle Version: v8
## Aktuelle Version: v9b
### Was implementiert ist:
- ✅ Multi-User mit PIN/Passwort-Auth + Token-Sessions
- ✅ Multi-User mit E-Mail + Passwort Login (bcrypt)
- ✅ Auth-Middleware auf ALLE Endpoints (60+ Endpoints geschützt)
- ✅ Rate Limiting (Login: 5/min, Reset: 3/min)
- ✅ CORS konfigurierbar via ALLOWED_ORIGINS in .env
- ✅ Admin/User Rollen, KI-Limits, Export-Berechtigungen
- ✅ Gewicht, Umfänge, Caliper (4 Formeln), Ernährung, Aktivität
- ✅ FDDB CSV-Import (Ernährung), Apple Health CSV-Import (Aktivität)
- ✅ KI-Analyse: 6 Einzel-Prompts + 3-stufige Pipeline (parallel)
- ✅ Konfigurierbare Prompts mit Template-Variablen
- ✅ Konfigurierbare Prompts mit Template-Variablen (Admin kann bearbeiten)
- ✅ Verlauf mit 5 Tabs + Zeitraumfilter + KI pro Sektion
- ✅ Dashboard mit Kennzahlen, Zielfortschritt, Combo-Chart
- ✅ Assistent-Modus (Schritt-für-Schritt Messung)
- ✅ PWA (iPhone Home Screen), Jinkendo-Icon
- ✅ PWA (iPhone Home Screen), Jinkendo Ensō-Logo
- ✅ E-Mail (SMTP) für Password-Recovery
- ✅ Admin-Panel: User verwalten, KI-Limits, E-Mail-Test
- ✅ Admin-Panel: User verwalten, KI-Limits, E-Mail-Test, PIN/Email setzen
- ✅ Multi-Environment: Prod (mitai.jinkendo.de) + Dev (dev.mitai.jinkendo.de)
- ✅ Gitea CI/CD mit Auto-Deploy auf Raspberry Pi 5
- ✅ PostgreSQL 16 Migration (vollständig von SQLite migriert)
- ✅ Export: CSV, JSON, ZIP (mit Fotos)
- ✅ Automatische SQLite→PostgreSQL Migration bei Container-Start
### Was in v9 kommt:
- 🔲 PostgreSQL Migration (aktuell: SQLite)
- 🔲 Auth-Middleware auf ALLE Endpoints
- 🔲 bcrypt statt SHA256
- 🔲 Rate Limiting
- 🔲 CORS auf Domain beschränken
### Was in v9c kommt:
- 🔲 Selbst-Registrierung mit E-Mail-Bestätigung
- 🔲 Freemium Tier-System (free/basic/premium/selfhosted)
- 🔲 Login via E-Mail statt Profil-Liste
- 🔲 nginx + Let's Encrypt
- 🔲 14-Tage Trial automatisch
- 🔲 Einladungslinks für Beta-Nutzer
- 🔲 Admin kann Tiers manuell setzen
## Datenbank-Schema (SQLite, v8)
### Was in v9d kommt:
- 🔲 OAuth2-Grundgerüst für Fitness-Connectoren
- 🔲 Strava Connector
- 🔲 Withings Connector (Waage)
- 🔲 Garmin Connector
## Deployment
### Infrastruktur
```
Internet → privat.stommer.com (Fritz!Box DynDNS)
→ Synology NAS (Reverse Proxy + Let's Encrypt)
→ Raspberry Pi 5 (192.168.2.49, Docker)
```
### Git Workflow
```
develop branch → Auto-Deploy → dev.mitai.jinkendo.de (Port 3099/8099)
main branch → Auto-Deploy → mitai.jinkendo.de (Port 3002/8002)
```
### Deployment-Befehle (manuell falls nötig)
```bash
# Prod
cd /home/lars/docker/bodytrack
docker compose -f docker-compose.yml build --no-cache
docker compose -f docker-compose.yml up -d
# Dev
cd /home/lars/docker/bodytrack-dev
docker compose -f docker-compose.dev-env.yml build --no-cache
docker compose -f docker-compose.dev-env.yml up -d
```
## Datenbank-Schema (PostgreSQL 16, v9b)
### Wichtige Tabellen:
- `profiles` Nutzer mit Auth (role, pin_hash, auth_type, ai_enabled, export_enabled)
- `profiles` Nutzer (role, pin_hash/bcrypt, email, auth_type, ai_enabled, tier)
- `sessions` Auth-Tokens mit Ablaufdatum
- `weight_log` Gewichtseinträge (profile_id, date, weight)
- `circumference_log` 8 Umfangspunkte
- `caliper_log` Hautfaltenmessung, 4 Methoden
- `nutrition_log` Kalorien + Makros (aus FDDB-CSV)
- `activity_log` Training (aus Apple Health oder manuell)
- `photos` Progress Photos
- `ai_insights` KI-Auswertungen (scope = prompt-slug)
- `ai_prompts` Konfigurierbare Prompts mit Templates
- `ai_prompts` Konfigurierbare Prompts mit Templates (11 Prompts)
- `ai_usage` KI-Calls pro Tag pro Profil
## Auth-Flow (aktuell v8)
**Schema-Datei:** `backend/schema.sql` (vollständiges PostgreSQL-Schema)
**Migration-Script:** `backend/migrate_to_postgres.py` (SQLite→PostgreSQL, automatisch)
## Auth-Flow (v9b)
```
Login-Screen → Profil-Liste → PIN/Passwort → Token im localStorage
Login-Screen → E-Mail + Passwort → Token im localStorage
Token → X-Auth-Token Header → Backend require_auth()
Profile-Id → aus Session (nicht aus Header!)
SHA256 Passwörter → automatisch zu bcrypt migriert beim Login
```
## API-Konventionen
- Alle Endpoints: `/api/...`
- Auth-Header: `X-Auth-Token: <token>`
- Profile-Header: `X-Profile-Id: <uuid>` (nur wo noch nicht migriert)
- Responses: immer JSON
- Fehler: `{"detail": "Fehlermeldung"}`
- Rate Limit überschritten: HTTP 429
## Umgebungsvariablen (.env)
```
OPENROUTER_API_KEY= # KI-Calls
# Database (PostgreSQL)
DB_HOST=postgres
DB_PORT=5432
DB_NAME=mitai_prod
DB_USER=mitai_prod
DB_PASSWORD= # REQUIRED
# AI
OPENROUTER_API_KEY= # KI-Calls (optional, alternativ ANTHROPIC_API_KEY)
OPENROUTER_MODEL=anthropic/claude-sonnet-4
ANTHROPIC_API_KEY= # Alternative zu OpenRouter
SMTP_HOST= # E-Mail
ANTHROPIC_API_KEY= # Direkte Anthropic API (optional)
# Email
SMTP_HOST= # E-Mail (für Recovery)
SMTP_PORT=587
SMTP_USER=
SMTP_PASS=
SMTP_FROM=
APP_URL= # Für Links in E-Mails
DATA_DIR=/app/data # SQLite-Pfad (v8)
PHOTOS_DIR=/app/photos
# v9 (PostgreSQL):
DATABASE_URL=postgresql://jinkendo:password@db/jinkendo
DB_PASSWORD=
```
## Deployment (aktuell)
```bash
# Heimserver (Raspberry Pi 5, lars@raspberrypi5)
cd /home/lars/docker/bodytrack
docker compose build --no-cache [frontend|backend]
docker compose up -d
docker logs mitai-api --tail 30
# App
APP_URL=https://mitai.jinkendo.de
ALLOWED_ORIGINS=https://mitai.jinkendo.de
DATA_DIR=/app/data
PHOTOS_DIR=/app/photos
ENVIRONMENT=production
```
## Wichtige Hinweise für Claude Code
1. **Ports immer 3002/8002** nie ändern
1. **Ports immer 3002/8002 (Prod) oder 3099/8099 (Dev)** nie ändern
2. **npm install** (nicht npm ci) kein package-lock.json vorhanden
3. **SQLite safe_alters** neue Spalten immer via _safe_alters() hinzufügen
3. **PostgreSQL-Migrations** Schema-Änderungen in `backend/schema.sql`, dann Container neu bauen
4. **Pipeline-Prompts** haben slug-Prefix `pipeline_` nie als Einzelanalyse zeigen
5. **dayjs.week()** braucht Plugin stattdessen native JS Wochenberechnung
6. **useNavigate()** nur in React-Komponenten (Großbuchstabe), nicht in Helper-Functions
7. **Bar fill=function** in Recharts nicht unterstützt nur statische Farben
5. **dayjs.week()** braucht Plugin stattdessen native JS ISO-Wochenberechnung
6. **useNavigate()** nur in React-Komponenten, nicht in Helper-Functions
7. **api.js nutzen** für alle API-Calls injiziert Token automatisch
8. **bcrypt** für alle neuen Passwort-Operationen verwenden
9. **session=Depends(require_auth)** als separater Parameter nie in Header() einbetten
10. **RealDictCursor verwenden** `get_cursor(conn)` statt `conn.cursor()` für dict-like row access
## Code-Style
- React: Functional Components, Hooks
@ -152,3 +197,453 @@ docker logs mitai-api --tail 30
- API-Calls: immer über `api.js` (injiziert Token automatisch)
- Kein TypeScript (bewusst, für Einfachheit)
- Python: keine Type-Hints Pflicht, aber bei neuen Funktionen erwünscht
## Design-System
### Farben (CSS-Variablen)
```css
--accent: #1D9E75 /* Jinkendo Grün Buttons, Links, Akzente */
--accent-dark: #085041 /* Dunkelgrün Icon-Hintergrund, Header */
--accent-light: #E1F5EE /* Hellgrün Hintergründe, Badges */
--bg: /* Seitenhintergrund (hell/dunkel auto) */
--surface: /* Card-Hintergrund */
--surface2: /* Sekundäre Fläche */
--border: /* Rahmen */
--text1: /* Primärer Text */
--text2: /* Sekundärer Text */
--text3: /* Muted Text, Labels */
--danger: #D85A30 /* Fehler, Warnungen */
```
### CSS-Klassen
```css
.card /* Weißer Container, border-radius 12px, box-shadow */
.btn /* Basis-Button */
.btn-primary /* Grüner Button (#1D9E75) */
.btn-secondary /* Grauer Button */
.btn-full /* 100% Breite */
.form-input /* Eingabefeld, volle Breite */
.form-label /* Feldbezeichnung, klein, uppercase */
.form-row /* Label + Input + Unit nebeneinander */
.form-unit /* Einheit rechts (kg, cm, etc.) */
.section-gap /* margin-bottom zwischen Sektionen */
.spinner /* Ladekreis, animiert */
```
### Abstände & Größen
```
Seiten-Padding: 16px seitlich
Card-Padding: 16-20px
Border-Radius: 12px (Cards), 8px (Buttons/Inputs), 50% (Avatare)
Icon-Größe: 16-20px inline, 24px standalone
Font-Größe: 12px (Labels), 14px (Body), 16-18px (Subtitel), 20-24px (Titel)
Font-Weight: 400 (normal), 600 (semi-bold), 700 (bold)
Bottom-Padding: 80px (für Mobile-Navigation)
```
### Komponenten-Muster
**Titelzeile einer Seite:**
```jsx
<div style={{display:'flex',alignItems:'center',
justifyContent:'space-between',marginBottom:20}}>
<div style={{fontSize:20,fontWeight:700,color:'var(--text1)'}}>
Seitentitel
</div>
<button className="btn btn-primary">Aktion</button>
</div>
```
**Ladezustand:**
```jsx
if (loading) return (
<div style={{display:'flex',justifyContent:'center',padding:40}}>
<div className="spinner"/>
</div>
)
```
**Fehlerzustand:**
```jsx
if (error) return (
<div style={{color:'var(--danger)',padding:16,textAlign:'center'}}>
{error}
</div>
)
```
**Leerer Zustand:**
```jsx
{items.length === 0 && (
<div style={{textAlign:'center',padding:40,color:'var(--text3)'}}>
<div style={{fontSize:32,marginBottom:8}}>📭</div>
<div>Noch keine Einträge</div>
</div>
)}
```
**Metric Card:**
```jsx
<div className="card" style={{padding:16,textAlign:'center'}}>
<div style={{fontSize:12,color:'var(--text3)',marginBottom:4}}>LABEL</div>
<div style={{fontSize:24,fontWeight:700,color:'var(--accent)'}}>
{value}
</div>
<div style={{fontSize:12,color:'var(--text3)'}}>Einheit</div>
</div>
```
### Jinkendo Logo-System
```
Grundelement: Ensō-Kreis (offen, Lücke 4-5 Uhr)
Farbe Ensō: #1D9E75
Hintergrund: #085041 (dunkelgrün)
Kern-Symbol: #5DCAA5 (mintgrün)
Wortmarke: Jin(light) + ken(bold #1D9E75) + do(light)
```
### Verfügbare Custom Commands
```
/deploy → Commit + Push vorbereiten
/merge-to-prod → develop → main mergen
/test → Manuelle Tests durchführen
/new-feature → Neues Feature-Template
/ui-component → Neue Komponente erstellen
/ui-page → Neue Seite erstellen
/fix-bug → Bug analysieren und beheben
/add-endpoint → Neuen API-Endpoint hinzufügen
/db-add-column → Neue DB-Spalte hinzufügen
```
## Jinkendo App-Familie & Markenarchitektur
### Philosophie
**Jinkendo** (人拳道) = Jin (人 Mensch) + Ken (拳 Faust) + Do (道 Weg)
"Der menschliche Weg der Kampfkunst" ruhig aber kraftvoll, Selbstwahrnehmung, Meditation, Zielorientiert
### App-Familie (Subdomain-Architektur)
```
mitai.jinkendo.de → Körper-Tracker (身体 = eigener Körper) ← DIESE APP
miken.jinkendo.de → Meditation (眉間 = drittes Auge)
ikigai.jinkendo.de → Lebenssinn/Ziele (生き甲斐)
shinkan.jinkendo.de → Kampfsport (真観 = wahre Wahrnehmung)
kenkou.jinkendo.de → Gesundheit allgemein (健康) für später aufsparen
```
### Registrierte Domains
- jinkendo.de, jinkendo.com, jinkendo.life alle registriert bei Strato
## v9b Detailplan Freemium Tier-System
### Tier-Modell
```
free → Selbst-Registrierung, 14-Tage Trial, eingeschränkt
basic → Kernfunktionen (Abo Stufe 1)
premium → Alles inkl. KI und Connectoren (Abo Stufe 2)
selfhosted → Lars' Heimversion, keine Einschränkungen
```
### Geplante DB-Erweiterungen (profiles Tabelle)
```sql
tier TEXT DEFAULT 'free'
trial_ends_at TEXT -- ISO datetime
sub_valid_until TEXT -- ISO datetime
email_verified INTEGER DEFAULT 0
email_verify_token TEXT
invited_by TEXT -- profile_id FK
invitation_token TEXT
```
### Tier-Limits (geplant)
| Feature | free | basic | premium | selfhosted |
|---------|------|-------|---------|------------|
| Gewicht-Einträge | 30 | unbegrenzt | unbegrenzt | unbegrenzt |
| KI-Analysen/Monat | 0 | 3 | unbegrenzt | unbegrenzt |
| Ernährung Import | ❌ | ✅ | ✅ | ✅ |
| Export | ❌ | ✅ | ✅ | ✅ |
| Fitness-Connectoren | ❌ | ❌ | ✅ | ✅ |
### Registrierungs-Flow (geplant)
```
1. Selbst-Registrierung: Name + E-Mail + Passwort
2. Auto-Trial: tier='free', trial_ends_at=now+14d
3. E-Mail-Bestätigung → email_verified=1
4. Trial läuft ab → Upgrade-Prompt
5. Einladungslinks: Admin generiert Token → direkt basic-Tier
6. Stripe Integration: später (v9b ohne Stripe, nur Tier-Logik)
```
## Infrastruktur Details
### Heimnetzwerk
```
Internet
→ Fritz!Box 7530 AX (DynDNS: privat.stommer.com)
→ Synology NAS (192.168.2.63, Reverse Proxy + Let's Encrypt)
→ Raspberry Pi 5 (192.168.2.49, Docker)
→ MiniPC (192.168.2.144, Gitea auf Port 3000)
```
### Synology Reverse Proxy Regeln
```
mitai.jinkendo.de → HTTP 192.168.2.49:3002 (Prod Frontend)
dev.mitai.jinkendo.de → HTTP 192.168.2.49:3099 (Dev Frontend)
```
### AdGuard DNS Rewrites (für internes Routing)
```
mitai.jinkendo.de → 192.168.2.63
dev.mitai.jinkendo.de → 192.168.2.63
```
### Fritz!Box DNS-Rebind Ausnahmen
```
jinkendo.de
mitai.jinkendo.de
```
### Pi Verzeichnisstruktur
```
/home/lars/docker/
├── bodytrack/ → Prod (main branch, docker-compose.yml)
└── bodytrack-dev/ → Dev (develop branch, docker-compose.dev-env.yml)
```
### Gitea Runner
```
Runner: raspberry-pi (auf Pi installiert)
Service: /etc/systemd/system/gitea-runner.service
Binary: /home/lars/gitea-runner/act_runner
```
### Container Namen
```
Prod: mitai-api, mitai-ui
Dev: dev-mitai-api, dev-mitai-ui
```
## Bekannte Probleme & Lösungen
### dayjs.week() NIEMALS verwenden
```javascript
// ❌ Falsch:
const week = dayjs(date).week()
// ✅ Richtig (ISO 8601):
const weekNum = (() => {
const dt = new Date(date)
dt.setHours(0,0,0,0)
dt.setDate(dt.getDate()+4-(dt.getDay()||7))
const y = new Date(dt.getFullYear(),0,1)
return Math.ceil(((dt-y)/86400000+1)/7)
})()
```
### session=Depends(require_auth) Korrekte Platzierung
```python
# ❌ Falsch (führt zu NameError oder ungeschütztem Endpoint):
def endpoint(x_profile_id: Optional[str] = Header(default=None, session=Depends(require_auth))):
# ✅ Richtig (separater Parameter):
def endpoint(x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth)):
```
### Recharts Bar fill=function nicht unterstützt
```jsx
// ❌ Falsch:
<Bar fill={(entry) => entry.color}/>
// ✅ Richtig:
<Bar fill="#1D9E75"/>
```
### PostgreSQL Boolean-Syntax
```python
# ❌ Falsch (SQLite-Syntax):
cur.execute("SELECT * FROM ai_prompts WHERE active=1")
# ✅ Richtig (PostgreSQL):
cur.execute("SELECT * FROM ai_prompts WHERE active=true")
```
### RealDictCursor für dict-like row access
```python
# ❌ Falsch:
cur = conn.cursor()
cur.execute("SELECT COUNT(*) FROM weight_log")
count = cur.fetchone()[0] # Tuple index
# ✅ Richtig:
cur = get_cursor(conn) # Returns RealDictCursor
cur.execute("SELECT COUNT(*) as count FROM weight_log")
count = cur.fetchone()['count'] # Dict key
```
## v9b Migration Lessons Learned
### PostgreSQL Migration (SQLite → PostgreSQL)
**Problem:** Docker Build hing 30+ Minuten bei `apt-get install postgresql-client`
**Lösung:** Alle apt-get dependencies entfernt, reine Python-Lösung mit psycopg2-binary
**Problem:** Leere date-Strings (`''`) führten zu PostgreSQL-Fehlern
**Lösung:** Migration-Script konvertiert leere Strings zu NULL für DATE-Spalten
**Problem:** Boolean-Felder (SQLite INTEGER 0/1 vs PostgreSQL BOOLEAN)
**Lösung:** Migration konvertiert automatisch, Backend nutzt `active=true` statt `active=1`
### API Endpoint Consistency (März 2026)
**Problem:** 11 kritische Endpoint-Mismatches zwischen Frontend und Backend gefunden
**Gelöst:**
- AI-Endpoints konsistent: `/api/insights/run/{slug}`, `/api/insights/pipeline`
- Password-Reset: `/api/auth/forgot-password`, `/api/auth/reset-password`
- Admin-Endpoints: `/permissions`, `/email`, `/pin` Sub-Routes
- Export: JSON + ZIP Endpoints hinzugefügt
- Prompt-Bearbeitung: PUT-Endpoint für Admins
**Tool:** Vollständiger Audit via Explore-Agent empfohlen bei größeren Änderungen
## Export/Import Spezifikation (v9c)
### ZIP-Export Struktur
```
mitai-export-{name}-{YYYY-MM-DD}.zip
├── README.txt ← Erklärung des Formats + Versionsnummer
├── profile.json ← Profildaten (ohne Passwort-Hash)
├── data/
│ ├── weight.csv ← Gewichtsverlauf
│ ├── circumferences.csv ← Umfänge (8 Messpunkte)
│ ├── caliper.csv ← Caliper-Messungen
│ ├── nutrition.csv ← Ernährungsdaten
│ └── activity.csv ← Aktivitäten
├── insights/
│ └── ai_insights.json ← KI-Auswertungen (alle gespeicherten)
└── photos/
├── {date}_{id}.jpg ← Progress-Fotos
└── ...
```
### CSV Format (alle Dateien)
```
- Trennzeichen: Semikolon (;) Excel/LibreOffice kompatibel
- Encoding: UTF-8 mit BOM (für Windows Excel)
- Datumsformat: YYYY-MM-DD
- Dezimaltrennzeichen: Punkt (.)
- Erste Zeile: Header
- Nullwerte: leer (nicht "null" oder "NULL")
```
### weight.csv Spalten
```
id;date;weight;note;source;created
```
### circumferences.csv Spalten
```
id;date;waist;hip;chest;neck;upper_arm;thigh;calf;forearm;note;created
```
### caliper.csv Spalten
```
id;date;chest;abdomen;thigh;tricep;subscapular;suprailiac;midaxillary;method;bf_percent;note;created
```
### nutrition.csv Spalten
```
id;date;meal_name;kcal;protein;fat;carbs;fiber;note;source;created
```
### activity.csv Spalten
```
id;date;name;type;duration_min;kcal;heart_rate_avg;heart_rate_max;distance_km;note;source;created
```
### profile.json Struktur
```json
{
"export_version": "2",
"export_date": "2026-03-18",
"app": "Mitai Jinkendo",
"profile": {
"name": "Lars",
"email": "lars@stommer.com",
"sex": "m",
"height": 178,
"birth_year": 1980,
"goal_weight": 82,
"goal_bf_pct": 14,
"avatar_color": "#1D9E75",
"auth_type": "password",
"session_days": 30,
"ai_enabled": true,
"tier": "selfhosted"
},
"stats": {
"weight_entries": 150,
"nutrition_entries": 300,
"activity_entries": 45,
"photos": 12
}
}
```
### ai_insights.json Struktur
```json
[
{
"id": "uuid",
"scope": "gesamt",
"created": "2026-03-18T10:00:00",
"result": "KI-Analyse Text..."
}
]
```
### README.txt Inhalt
```
Mitai Jinkendo Datenexport
Version: 2
Exportiert am: YYYY-MM-DD
Profil: {name}
Inhalt:
- profile.json: Profildaten und Einstellungen
- data/*.csv: Messdaten (Semikolon-getrennt, UTF-8)
- insights/: KI-Auswertungen (JSON)
- photos/: Progress-Fotos (JPEG)
Import:
Dieser Export kann in Mitai Jinkendo unter
Einstellungen → Import → "Mitai Backup importieren"
wieder eingespielt werden.
Format-Version 2 (ab v9b):
Alle CSV-Dateien sind UTF-8 mit BOM kodiert.
Trennzeichen: Semikolon (;)
Datumsformat: YYYY-MM-DD
```
### Import-Funktion (zu implementieren)
**Endpoint:** `POST /api/import/zip`
**Verhalten:**
- Akzeptiert ZIP-Datei (multipart/form-data)
- Erkennt export_version aus profile.json
- Importiert nur fehlende Einträge (kein Duplikat)
- Fotos werden nicht überschrieben falls bereits vorhanden
- Gibt Zusammenfassung zurück: wie viele Einträge je Kategorie importiert
- Bei Fehler: vollständiger Rollback (alle oder nichts)
**Duplikat-Erkennung:**
```python
# INSERT ... ON CONFLICT (profile_id, date) DO NOTHING
# weight: UNIQUE (profile_id, date)
# nutrition: UNIQUE (profile_id, date, meal_name)
# activity: UNIQUE (profile_id, date, name)
# caliper: UNIQUE (profile_id, date)
# circumferences: UNIQUE (profile_id, date)
```
**Frontend:** Neuer Button in SettingsPage:
```
[ZIP exportieren] [JSON exportieren] [Backup importieren]
```

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@ -1,7 +1,21 @@
FROM python:3.12-slim
# No system packages needed - we use Python (psycopg2-binary) for PostgreSQL checks
WORKDIR /app
# Install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application code
COPY . .
# Create directories
RUN mkdir -p /app/data /app/photos
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
# Make startup script executable
RUN chmod +x /app/startup.sh
# Use startup script instead of direct uvicorn
CMD ["/app/startup.sh"]

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backend/db.py Normal file
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"""
PostgreSQL Database Connector for Mitai Jinkendo (v9b)
Provides connection pooling and helper functions for database operations.
Compatible drop-in replacement for the previous SQLite get_db() pattern.
"""
import os
from contextlib import contextmanager
from typing import Optional, Dict, Any, List
import psycopg2
from psycopg2.extras import RealDictCursor
import psycopg2.pool
# Global connection pool
_pool: Optional[psycopg2.pool.SimpleConnectionPool] = None
def init_pool():
"""Initialize PostgreSQL connection pool."""
global _pool
if _pool is None:
_pool = psycopg2.pool.SimpleConnectionPool(
minconn=1,
maxconn=10,
host=os.getenv("DB_HOST", "postgres"),
port=int(os.getenv("DB_PORT", "5432")),
database=os.getenv("DB_NAME", "mitai"),
user=os.getenv("DB_USER", "mitai"),
password=os.getenv("DB_PASSWORD", "")
)
print(f"✓ PostgreSQL connection pool initialized ({os.getenv('DB_HOST', 'postgres')}:{os.getenv('DB_PORT', '5432')})")
@contextmanager
def get_db():
"""
Context manager for database connections.
Usage:
with get_db() as conn:
cur = conn.cursor()
cur.execute("SELECT * FROM profiles")
rows = cur.fetchall()
Auto-commits on success, auto-rolls back on exception.
"""
if _pool is None:
init_pool()
conn = _pool.getconn()
try:
yield conn
conn.commit()
except Exception:
conn.rollback()
raise
finally:
_pool.putconn(conn)
def get_cursor(conn):
"""
Get cursor with RealDictCursor for dict-like row access.
Returns rows as dictionaries: {'column_name': value, ...}
Compatible with previous sqlite3.Row behavior.
"""
return conn.cursor(cursor_factory=RealDictCursor)
def r2d(row) -> Optional[Dict[str, Any]]:
"""
Convert row to dict (compatibility helper).
Args:
row: RealDictRow from psycopg2
Returns:
Dictionary or None if row is None
"""
return dict(row) if row else None
def execute_one(conn, query: str, params: tuple = ()) -> Optional[Dict[str, Any]]:
"""
Execute query and return one row as dict.
Args:
conn: Database connection from get_db()
query: SQL query with %s placeholders
params: Tuple of parameters
Returns:
Dictionary with column:value pairs, or None if no row found
Example:
profile = execute_one(conn, "SELECT * FROM profiles WHERE id=%s", (pid,))
if profile:
print(profile['name'])
"""
with get_cursor(conn) as cur:
cur.execute(query, params)
row = cur.fetchone()
return r2d(row)
def execute_all(conn, query: str, params: tuple = ()) -> List[Dict[str, Any]]:
"""
Execute query and return all rows as list of dicts.
Args:
conn: Database connection from get_db()
query: SQL query with %s placeholders
params: Tuple of parameters
Returns:
List of dictionaries (one per row)
Example:
weights = execute_all(conn,
"SELECT * FROM weight_log WHERE profile_id=%s ORDER BY date DESC",
(pid,)
)
for w in weights:
print(w['date'], w['weight'])
"""
with get_cursor(conn) as cur:
cur.execute(query, params)
rows = cur.fetchall()
return [r2d(r) for r in rows]
def execute_write(conn, query: str, params: tuple = ()) -> None:
"""
Execute INSERT/UPDATE/DELETE query.
Args:
conn: Database connection from get_db()
query: SQL query with %s placeholders
params: Tuple of parameters
Example:
execute_write(conn,
"UPDATE profiles SET name=%s WHERE id=%s",
("New Name", pid)
)
"""
with get_cursor(conn) as cur:
cur.execute(query, params)

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#!/usr/bin/env python3
"""
Database initialization script for PostgreSQL.
Replaces psql commands in startup.sh with pure Python.
"""
import os
import sys
import time
import psycopg2
from psycopg2 import OperationalError
DB_HOST = os.getenv("DB_HOST", "localhost")
DB_PORT = os.getenv("DB_PORT", "5432")
DB_NAME = os.getenv("DB_NAME", "mitai_dev")
DB_USER = os.getenv("DB_USER", "mitai_dev")
DB_PASSWORD = os.getenv("DB_PASSWORD", "")
def get_connection():
"""Get PostgreSQL connection."""
return psycopg2.connect(
host=DB_HOST,
port=DB_PORT,
database=DB_NAME,
user=DB_USER,
password=DB_PASSWORD
)
def wait_for_postgres(max_retries=30):
"""Wait for PostgreSQL to be ready."""
print("\nChecking PostgreSQL connection...")
for i in range(1, max_retries + 1):
try:
conn = get_connection()
conn.close()
print("✓ PostgreSQL ready")
return True
except OperationalError:
print(f" Waiting for PostgreSQL... (attempt {i}/{max_retries})")
time.sleep(2)
print(f"✗ PostgreSQL not ready after {max_retries} attempts")
return False
def check_table_exists(table_name="profiles"):
"""Check if a table exists."""
try:
conn = get_connection()
cur = conn.cursor()
cur.execute("""
SELECT COUNT(*)
FROM information_schema.tables
WHERE table_schema='public' AND table_name=%s
""", (table_name,))
count = cur.fetchone()[0]
cur.close()
conn.close()
return count > 0
except Exception as e:
print(f"Error checking table: {e}")
return False
def load_schema(schema_file="/app/schema.sql"):
"""Load schema from SQL file."""
try:
with open(schema_file, 'r') as f:
schema_sql = f.read()
conn = get_connection()
cur = conn.cursor()
cur.execute(schema_sql)
conn.commit()
cur.close()
conn.close()
print("✓ Schema loaded from schema.sql")
return True
except Exception as e:
print(f"✗ Error loading schema: {e}")
return False
def get_profile_count():
"""Get number of profiles in database."""
try:
conn = get_connection()
cur = conn.cursor()
cur.execute("SELECT COUNT(*) FROM profiles")
count = cur.fetchone()[0]
cur.close()
conn.close()
return count
except Exception as e:
print(f"Error getting profile count: {e}")
return -1
if __name__ == "__main__":
print("═══════════════════════════════════════════════════════════")
print("MITAI JINKENDO - Database Initialization (v9b)")
print("═══════════════════════════════════════════════════════════")
# Wait for PostgreSQL
if not wait_for_postgres():
sys.exit(1)
# Check schema
print("\nChecking database schema...")
if not check_table_exists("profiles"):
print(" Schema not found, initializing...")
if not load_schema():
sys.exit(1)
else:
print("✓ Schema already exists")
# Check for migration
print("\nChecking for SQLite data migration...")
sqlite_db = "/app/data/bodytrack.db"
profile_count = get_profile_count()
if os.path.exists(sqlite_db) and profile_count == 0:
print(" SQLite database found and PostgreSQL is empty")
print(" Starting automatic migration...")
# Import and run migration
try:
from migrate_to_postgres import main as migrate
migrate()
except Exception as e:
print(f"✗ Migration failed: {e}")
sys.exit(1)
elif os.path.exists(sqlite_db) and profile_count > 0:
print(f"⚠ SQLite DB exists but PostgreSQL already has {profile_count} profiles")
print(" Skipping migration (already migrated)")
elif not os.path.exists(sqlite_db):
print("✓ No SQLite database found (fresh install or already migrated)")
else:
print("✓ No migration needed")
print("\n✓ Database initialization complete")

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#!/usr/bin/env python3
"""
SQLite PostgreSQL Migration Script für Mitai Jinkendo (v9a v9b)
Migrates all data from SQLite to PostgreSQL with type conversions and validation.
Usage:
# Inside Docker container:
python migrate_to_postgres.py
# Or locally with custom paths:
DATA_DIR=./data DB_HOST=localhost python migrate_to_postgres.py
Environment Variables:
SQLite Source:
DATA_DIR (default: ./data)
PostgreSQL Target:
DB_HOST (default: postgres)
DB_PORT (default: 5432)
DB_NAME (default: mitai)
DB_USER (default: mitai)
DB_PASSWORD (required)
"""
import os
import sys
import sqlite3
from pathlib import Path
from typing import Dict, Any, List, Optional
import psycopg2
from psycopg2.extras import execute_values, RealDictCursor
# ================================================================
# CONFIGURATION
# ================================================================
# SQLite Source
DATA_DIR = Path(os.getenv("DATA_DIR", "./data"))
SQLITE_DB = DATA_DIR / "bodytrack.db"
# PostgreSQL Target
PG_CONFIG = {
'host': os.getenv("DB_HOST", "postgres"),
'port': int(os.getenv("DB_PORT", "5432")),
'database': os.getenv("DB_NAME", "mitai"),
'user': os.getenv("DB_USER", "mitai"),
'password': os.getenv("DB_PASSWORD", "")
}
# Tables to migrate (in order - respects foreign keys)
TABLES = [
'profiles',
'sessions',
'ai_usage',
'ai_prompts',
'weight_log',
'circumference_log',
'caliper_log',
'nutrition_log',
'activity_log',
'photos',
'ai_insights',
]
# Columns that need INTEGER (0/1) → BOOLEAN conversion
BOOLEAN_COLUMNS = {
'profiles': ['ai_enabled', 'export_enabled'],
'ai_prompts': ['active'],
}
# ================================================================
# CONVERSION HELPERS
# ================================================================
def convert_value(value: Any, column: str, table: str) -> Any:
"""
Convert SQLite value to PostgreSQL-compatible format.
Args:
value: Raw value from SQLite
column: Column name
table: Table name
Returns:
Converted value suitable for PostgreSQL
"""
# NULL values pass through
if value is None:
return None
# Empty string → NULL for DATE columns (PostgreSQL doesn't accept '' for DATE type)
if isinstance(value, str) and value.strip() == '' and column == 'date':
return None
# INTEGER → BOOLEAN conversion
if table in BOOLEAN_COLUMNS and column in BOOLEAN_COLUMNS[table]:
return bool(value)
# All other values pass through
# (PostgreSQL handles TEXT timestamps, UUIDs, and numerics automatically)
return value
def convert_row(row: Dict[str, Any], table: str) -> Dict[str, Any]:
"""
Convert entire row from SQLite to PostgreSQL format.
Args:
row: Dictionary with column:value pairs from SQLite
table: Table name
Returns:
Converted dictionary
"""
return {
column: convert_value(value, column, table)
for column, value in row.items()
}
# ================================================================
# MIGRATION LOGIC
# ================================================================
def get_sqlite_rows(table: str) -> List[Dict[str, Any]]:
"""
Fetch all rows from SQLite table.
Args:
table: Table name
Returns:
List of dictionaries (one per row)
"""
conn = sqlite3.connect(SQLITE_DB)
conn.row_factory = sqlite3.Row
cur = conn.cursor()
try:
rows = cur.execute(f"SELECT * FROM {table}").fetchall()
return [dict(row) for row in rows]
except sqlite3.OperationalError as e:
# Table doesn't exist in SQLite (OK, might be new in v9b)
print(f" ⚠ Table '{table}' not found in SQLite: {e}")
return []
finally:
conn.close()
def migrate_table(pg_conn, table: str) -> Dict[str, int]:
"""
Migrate one table from SQLite to PostgreSQL.
Args:
pg_conn: PostgreSQL connection
table: Table name
Returns:
Dictionary with stats: {'sqlite_count': N, 'postgres_count': M}
"""
print(f" Migrating '{table}'...", end=' ', flush=True)
# Fetch from SQLite
sqlite_rows = get_sqlite_rows(table)
sqlite_count = len(sqlite_rows)
if sqlite_count == 0:
print("(empty)")
return {'sqlite_count': 0, 'postgres_count': 0}
# Convert rows
converted_rows = [convert_row(row, table) for row in sqlite_rows]
# Get column names
columns = list(converted_rows[0].keys())
cols_str = ', '.join(columns)
placeholders = ', '.join(['%s'] * len(columns))
# Insert into PostgreSQL
pg_cur = pg_conn.cursor()
# Build INSERT query
query = f"INSERT INTO {table} ({cols_str}) VALUES %s"
# Prepare values (list of tuples)
values = [
tuple(row[col] for col in columns)
for row in converted_rows
]
# Batch insert with execute_values (faster than executemany)
try:
execute_values(pg_cur, query, values, page_size=100)
except psycopg2.Error as e:
print(f"\n ✗ Insert failed: {e}")
raise
# Verify row count
pg_cur.execute(f"SELECT COUNT(*) FROM {table}")
postgres_count = pg_cur.fetchone()[0]
print(f"{sqlite_count} rows → {postgres_count} rows")
return {
'sqlite_count': sqlite_count,
'postgres_count': postgres_count
}
def verify_migration(pg_conn, stats: Dict[str, Dict[str, int]]):
"""
Verify migration integrity.
Args:
pg_conn: PostgreSQL connection
stats: Migration stats per table
"""
print("\n═══════════════════════════════════════════════════════════")
print("VERIFICATION")
print("═══════════════════════════════════════════════════════════")
all_ok = True
for table, counts in stats.items():
sqlite_count = counts['sqlite_count']
postgres_count = counts['postgres_count']
status = "" if sqlite_count == postgres_count else ""
print(f" {status} {table:20s} SQLite: {sqlite_count:5d} → PostgreSQL: {postgres_count:5d}")
if sqlite_count != postgres_count:
all_ok = False
# Sample some data
print("\n───────────────────────────────────────────────────────────")
print("SAMPLE DATA (first profile)")
print("───────────────────────────────────────────────────────────")
cur = pg_conn.cursor(cursor_factory=RealDictCursor)
cur.execute("SELECT * FROM profiles LIMIT 1")
profile = cur.fetchone()
if profile:
for key, value in dict(profile).items():
print(f" {key:20s} = {value}")
else:
print(" (no profiles found)")
print("\n───────────────────────────────────────────────────────────")
print("SAMPLE DATA (latest weight entry)")
print("───────────────────────────────────────────────────────────")
cur.execute("SELECT * FROM weight_log ORDER BY date DESC LIMIT 1")
weight = cur.fetchone()
if weight:
for key, value in dict(weight).items():
print(f" {key:20s} = {value}")
else:
print(" (no weight entries found)")
print("\n═══════════════════════════════════════════════════════════")
if all_ok:
print("✓ MIGRATION SUCCESSFUL - All row counts match!")
else:
print("✗ MIGRATION FAILED - Row count mismatch detected!")
sys.exit(1)
# ================================================================
# MAIN
# ================================================================
def main():
print("═══════════════════════════════════════════════════════════")
print("MITAI JINKENDO - SQLite → PostgreSQL Migration (v9a → v9b)")
print("═══════════════════════════════════════════════════════════\n")
# Check SQLite DB exists
if not SQLITE_DB.exists():
print(f"✗ SQLite database not found: {SQLITE_DB}")
print(f" Set DATA_DIR environment variable if needed.")
sys.exit(1)
print(f"✓ SQLite source: {SQLITE_DB}")
print(f"✓ PostgreSQL target: {PG_CONFIG['user']}@{PG_CONFIG['host']}:{PG_CONFIG['port']}/{PG_CONFIG['database']}\n")
# Check PostgreSQL password
if not PG_CONFIG['password']:
print("✗ DB_PASSWORD environment variable not set!")
sys.exit(1)
# Connect to PostgreSQL
print("Connecting to PostgreSQL...", end=' ', flush=True)
try:
pg_conn = psycopg2.connect(**PG_CONFIG)
print("")
except psycopg2.Error as e:
print(f"\n✗ Connection failed: {e}")
print("\nTroubleshooting:")
print(" - Is PostgreSQL running? (docker compose ps)")
print(" - Is DB_PASSWORD correct?")
print(" - Is the schema initialized? (schema.sql loaded?)")
sys.exit(1)
# Check if schema is initialized
print("Checking PostgreSQL schema...", end=' ', flush=True)
cur = pg_conn.cursor()
cur.execute("""
SELECT COUNT(*) FROM information_schema.tables
WHERE table_schema = 'public' AND table_name = 'profiles'
""")
if cur.fetchone()[0] == 0:
print("\n✗ Schema not initialized!")
print("\nRun this first:")
print(" docker compose exec backend python -c \"from main import init_db; init_db()\"")
print(" Or manually load schema.sql")
sys.exit(1)
print("")
# Check if PostgreSQL is empty
print("Checking if PostgreSQL is empty...", end=' ', flush=True)
cur.execute("SELECT COUNT(*) FROM profiles")
existing_profiles = cur.fetchone()[0]
if existing_profiles > 0:
print(f"\n⚠ WARNING: PostgreSQL already has {existing_profiles} profiles!")
response = input(" Continue anyway? This will create duplicates! (yes/no): ")
if response.lower() != 'yes':
print("Migration cancelled.")
sys.exit(0)
else:
print("")
print("\n───────────────────────────────────────────────────────────")
print("MIGRATION")
print("───────────────────────────────────────────────────────────")
stats = {}
try:
for table in TABLES:
stats[table] = migrate_table(pg_conn, table)
# Commit all changes
pg_conn.commit()
print("\n✓ All changes committed to PostgreSQL")
except Exception as e:
print(f"\n✗ Migration failed: {e}")
print("Rolling back...")
pg_conn.rollback()
pg_conn.close()
sys.exit(1)
# Verification
verify_migration(pg_conn, stats)
# Cleanup
pg_conn.close()
print("\n✓ Migration complete!")
print("\nNext steps:")
print(" 1. Test login with existing credentials")
print(" 2. Check Dashboard (weight chart, stats)")
print(" 3. Verify KI-Analysen work")
print(" 4. If everything works: commit + push to develop")
if __name__ == '__main__':
main()

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@ -7,3 +7,4 @@ aiofiles==23.2.1
pydantic==2.7.1
bcrypt==4.1.3
slowapi==0.1.9
psycopg2-binary==2.9.9

263
backend/schema.sql Normal file
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-- ================================================================
-- MITAI JINKENDO v9b PostgreSQL Schema
-- ================================================================
-- Migration from SQLite to PostgreSQL
-- Includes v9b Tier System features
-- ================================================================
-- Enable UUID Extension
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
-- ================================================================
-- CORE TABLES
-- ================================================================
-- ── Profiles Table ──────────────────────────────────────────────
-- User/Profile management with auth and permissions
CREATE TABLE IF NOT EXISTS profiles (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
name VARCHAR(255) NOT NULL DEFAULT 'Nutzer',
avatar_color VARCHAR(7) DEFAULT '#1D9E75',
photo_id UUID,
sex VARCHAR(1) DEFAULT 'm' CHECK (sex IN ('m', 'w', 'd')),
dob DATE,
height NUMERIC(5,2) DEFAULT 178,
goal_weight NUMERIC(5,2),
goal_bf_pct NUMERIC(4,2),
-- Auth & Permissions
role VARCHAR(20) DEFAULT 'user' CHECK (role IN ('user', 'admin')),
pin_hash TEXT,
auth_type VARCHAR(20) DEFAULT 'pin' CHECK (auth_type IN ('pin', 'email')),
session_days INTEGER DEFAULT 30,
ai_enabled BOOLEAN DEFAULT TRUE,
ai_limit_day INTEGER,
export_enabled BOOLEAN DEFAULT TRUE,
email VARCHAR(255) UNIQUE,
-- v9b: Tier System
tier VARCHAR(20) DEFAULT 'free' CHECK (tier IN ('free', 'basic', 'premium', 'selfhosted')),
tier_expires_at TIMESTAMP WITH TIME ZONE,
trial_ends_at TIMESTAMP WITH TIME ZONE,
invited_by UUID REFERENCES profiles(id),
-- Timestamps
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_profiles_email ON profiles(email) WHERE email IS NOT NULL;
CREATE INDEX IF NOT EXISTS idx_profiles_tier ON profiles(tier);
-- ── Sessions Table ──────────────────────────────────────────────
-- Auth token management
CREATE TABLE IF NOT EXISTS sessions (
token VARCHAR(64) PRIMARY KEY,
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
expires_at TIMESTAMP WITH TIME ZONE NOT NULL,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_sessions_profile_id ON sessions(profile_id);
CREATE INDEX IF NOT EXISTS idx_sessions_expires_at ON sessions(expires_at);
-- ── AI Usage Tracking ───────────────────────────────────────────
-- Daily AI call limits per profile
CREATE TABLE IF NOT EXISTS ai_usage (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
call_count INTEGER DEFAULT 0,
UNIQUE(profile_id, date)
);
CREATE INDEX IF NOT EXISTS idx_ai_usage_profile_date ON ai_usage(profile_id, date);
-- ================================================================
-- TRACKING TABLES
-- ================================================================
-- ── Weight Log ──────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS weight_log (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
weight NUMERIC(5,2) NOT NULL,
note TEXT,
source VARCHAR(20) DEFAULT 'manual',
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_weight_log_profile_date ON weight_log(profile_id, date DESC);
CREATE UNIQUE INDEX IF NOT EXISTS idx_weight_log_profile_date_unique ON weight_log(profile_id, date);
-- ── Circumference Log ───────────────────────────────────────────
CREATE TABLE IF NOT EXISTS circumference_log (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
c_neck NUMERIC(5,2),
c_chest NUMERIC(5,2),
c_waist NUMERIC(5,2),
c_belly NUMERIC(5,2),
c_hip NUMERIC(5,2),
c_thigh NUMERIC(5,2),
c_calf NUMERIC(5,2),
c_arm NUMERIC(5,2),
notes TEXT,
photo_id UUID,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_circumference_profile_date ON circumference_log(profile_id, date DESC);
-- ── Caliper Log ─────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS caliper_log (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
sf_method VARCHAR(20) DEFAULT 'jackson3',
sf_chest NUMERIC(5,2),
sf_axilla NUMERIC(5,2),
sf_triceps NUMERIC(5,2),
sf_subscap NUMERIC(5,2),
sf_suprailiac NUMERIC(5,2),
sf_abdomen NUMERIC(5,2),
sf_thigh NUMERIC(5,2),
sf_calf_med NUMERIC(5,2),
sf_lowerback NUMERIC(5,2),
sf_biceps NUMERIC(5,2),
body_fat_pct NUMERIC(4,2),
lean_mass NUMERIC(5,2),
fat_mass NUMERIC(5,2),
notes TEXT,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_caliper_profile_date ON caliper_log(profile_id, date DESC);
-- ── Nutrition Log ───────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS nutrition_log (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
kcal NUMERIC(7,2),
protein_g NUMERIC(6,2),
fat_g NUMERIC(6,2),
carbs_g NUMERIC(6,2),
source VARCHAR(20) DEFAULT 'csv',
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_nutrition_profile_date ON nutrition_log(profile_id, date DESC);
-- ── Activity Log ────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS activity_log (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
start_time TIME,
end_time TIME,
activity_type VARCHAR(50) NOT NULL,
duration_min NUMERIC(6,2),
kcal_active NUMERIC(7,2),
kcal_resting NUMERIC(7,2),
hr_avg NUMERIC(5,2),
hr_max NUMERIC(5,2),
distance_km NUMERIC(7,2),
rpe INTEGER CHECK (rpe >= 1 AND rpe <= 10),
source VARCHAR(20) DEFAULT 'manual',
notes TEXT,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_activity_profile_date ON activity_log(profile_id, date DESC);
-- ── Photos ──────────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS photos (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
meas_id UUID, -- Legacy: reference to measurement (circumference/caliper)
date DATE,
path TEXT NOT NULL,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_photos_profile_date ON photos(profile_id, date DESC);
-- ================================================================
-- AI TABLES
-- ================================================================
-- ── AI Insights ─────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS ai_insights (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
scope VARCHAR(50) NOT NULL,
content TEXT NOT NULL,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_ai_insights_profile_scope ON ai_insights(profile_id, scope, created DESC);
-- ── AI Prompts ──────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS ai_prompts (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
name VARCHAR(255) NOT NULL,
slug VARCHAR(100) NOT NULL UNIQUE,
description TEXT,
template TEXT NOT NULL,
active BOOLEAN DEFAULT TRUE,
sort_order INTEGER DEFAULT 0,
created TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX IF NOT EXISTS idx_ai_prompts_slug ON ai_prompts(slug);
CREATE INDEX IF NOT EXISTS idx_ai_prompts_active_sort ON ai_prompts(active, sort_order);
-- ================================================================
-- TRIGGERS
-- ================================================================
-- Auto-update timestamp trigger for profiles
CREATE OR REPLACE FUNCTION update_updated_timestamp()
RETURNS TRIGGER AS $$
BEGIN
NEW.updated = CURRENT_TIMESTAMP;
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
DROP TRIGGER IF EXISTS trigger_profiles_updated ON profiles;
CREATE TRIGGER trigger_profiles_updated
BEFORE UPDATE ON profiles
FOR EACH ROW
EXECUTE FUNCTION update_updated_timestamp();
DROP TRIGGER IF EXISTS trigger_ai_prompts_updated ON ai_prompts;
CREATE TRIGGER trigger_ai_prompts_updated
BEFORE UPDATE ON ai_prompts
FOR EACH ROW
EXECUTE FUNCTION update_updated_timestamp();
-- ================================================================
-- COMMENTS (Documentation)
-- ================================================================
COMMENT ON TABLE profiles IS 'User profiles with auth, permissions, and tier system';
COMMENT ON TABLE sessions IS 'Active auth tokens';
COMMENT ON TABLE ai_usage IS 'Daily AI call tracking per profile';
COMMENT ON TABLE weight_log IS 'Weight measurements';
COMMENT ON TABLE circumference_log IS 'Body circumference measurements (8 points)';
COMMENT ON TABLE caliper_log IS 'Skinfold measurements with body fat calculations';
COMMENT ON TABLE nutrition_log IS 'Daily nutrition intake (calories + macros)';
COMMENT ON TABLE activity_log IS 'Training sessions and activities';
COMMENT ON TABLE photos IS 'Progress photos';
COMMENT ON TABLE ai_insights IS 'AI-generated analysis results';
COMMENT ON TABLE ai_prompts IS 'Configurable AI prompt templates';
COMMENT ON COLUMN profiles.tier IS 'Subscription tier: free, basic, premium, selfhosted';
COMMENT ON COLUMN profiles.trial_ends_at IS 'Trial expiration timestamp (14 days from registration)';
COMMENT ON COLUMN profiles.tier_expires_at IS 'Paid tier expiration timestamp';
COMMENT ON COLUMN profiles.invited_by IS 'Profile ID of inviter (for beta invitations)';

19
backend/startup.sh Normal file
View File

@ -0,0 +1,19 @@
#!/bin/bash
set -e
# Run database initialization with Python (no psql needed!)
python /app/db_init.py
if [ $? -ne 0 ]; then
echo "✗ Database initialization failed"
exit 1
fi
# ── Start Application ──────────────────────────────────────────
echo ""
echo "═══════════════════════════════════════════════════════════"
echo "Starting FastAPI application..."
echo "═══════════════════════════════════════════════════════════"
echo ""
exec uvicorn main:app --host 0.0.0.0 --port 8000

View File

@ -1,24 +1,56 @@
services:
postgres-dev:
image: postgres:16-alpine
container_name: dev-mitai-postgres
restart: unless-stopped
environment:
POSTGRES_DB: mitai_dev
POSTGRES_USER: mitai_dev
POSTGRES_PASSWORD: dev_password_change_me
volumes:
- mitai_dev_postgres_data:/var/lib/postgresql/data
ports:
- "127.0.0.1:5433:5432"
healthcheck:
test: ["CMD-SHELL", "pg_isready -U mitai_dev"]
interval: 10s
timeout: 5s
retries: 5
backend:
build: ./backend
container_name: dev-mitai-api
restart: unless-stopped
ports:
- "8099:8000"
depends_on:
postgres-dev:
condition: service_healthy
volumes:
- bodytrack_bodytrack-data:/app/data
- bodytrack_bodytrack-photos:/app/photos
environment:
# Database
- DB_HOST=postgres-dev
- DB_PORT=5432
- DB_NAME=mitai_dev
- DB_USER=mitai_dev
- DB_PASSWORD=dev_password_change_me
# AI
- OPENROUTER_API_KEY=${OPENROUTER_API_KEY}
- OPENROUTER_MODEL=${OPENROUTER_MODEL:-anthropic/claude-sonnet-4}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
# Email
- SMTP_HOST=${SMTP_HOST}
- SMTP_PORT=${SMTP_PORT:-587}
- SMTP_USER=${SMTP_USER}
- SMTP_PASS=${SMTP_PASS}
- SMTP_FROM=${SMTP_FROM}
# App
- APP_URL=${APP_URL_DEV:-https://dev.mitai.jinkendo.de}
- DATA_DIR=/app/data
- PHOTOS_DIR=/app/photos
- ALLOWED_ORIGINS=${ALLOWED_ORIGINS_DEV:-*}
- ENVIRONMENT=development
@ -33,6 +65,7 @@ services:
- backend
volumes:
mitai_dev_postgres_data:
bodytrack_bodytrack-data:
external: true
bodytrack_bodytrack-photos:

View File

@ -1,22 +1,55 @@
services:
postgres:
image: postgres:16-alpine
container_name: mitai-db
restart: unless-stopped
environment:
POSTGRES_DB: mitai_prod
POSTGRES_USER: mitai_prod
POSTGRES_PASSWORD: ${DB_PASSWORD:-change_me_in_production}
volumes:
- mitai_postgres_data:/var/lib/postgresql/data
ports:
- "127.0.0.1:5432:5432"
healthcheck:
test: ["CMD-SHELL", "pg_isready -U mitai_prod"]
interval: 10s
timeout: 5s
retries: 5
backend:
build: ./backend
container_name: mitai-api
restart: unless-stopped
ports:
- "8002:8000"
depends_on:
postgres:
condition: service_healthy
volumes:
- bodytrack_bodytrack-data:/app/data
- bodytrack_bodytrack-photos:/app/photos
environment:
# Database
- DB_HOST=postgres
- DB_PORT=5432
- DB_NAME=mitai_prod
- DB_USER=mitai_prod
- DB_PASSWORD=${DB_PASSWORD:-change_me_in_production}
# AI
- OPENROUTER_API_KEY=${OPENROUTER_API_KEY}
- OPENROUTER_MODEL=${OPENROUTER_MODEL:-anthropic/claude-sonnet-4}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
# Email
- SMTP_HOST=${SMTP_HOST}
- SMTP_PORT=${SMTP_PORT:-587}
- SMTP_USER=${SMTP_USER}
- SMTP_PASS=${SMTP_PASS}
- SMTP_FROM=${SMTP_FROM}
# App
- APP_URL=${APP_URL}
- DATA_DIR=/app/data
- PHOTOS_DIR=/app/photos
@ -33,6 +66,7 @@ services:
- backend
volumes:
mitai_postgres_data:
bodytrack_bodytrack-data:
external: true
bodytrack_bodytrack-photos:

View File

@ -150,8 +150,11 @@ export default function Analysis() {
}
const savePrompt = async (promptId, data) => {
const token = localStorage.getItem('bodytrack_token')||''
await fetch(`/api/prompts/${promptId}`, {
method:'PUT', headers:{'Content-Type':'application/json'}, body:JSON.stringify(data)
method:'PUT',
headers:{'Content-Type':'application/json', 'X-Auth-Token': token},
body:JSON.stringify(data)
})
setEditing(null); await loadAll()
}
@ -176,6 +179,10 @@ export default function Analysis() {
const activePrompts = prompts.filter(p=>p.active && !p.slug.startsWith('pipeline_'))
// Pipeline is available if the "pipeline" prompt is active
const pipelinePrompt = prompts.find(p=>p.slug==='pipeline')
const pipelineAvailable = pipelinePrompt?.active ?? true // Default to true if not found (backwards compatibility)
return (
<div>
<h1 className="page-title">KI-Analyse</h1>
@ -218,36 +225,38 @@ export default function Analysis() {
</div>
)}
{/* Pipeline button */}
<div className="card" style={{marginBottom:16,borderColor:'var(--accent)',borderWidth:2}}>
<div style={{display:'flex',alignItems:'flex-start',gap:12}}>
<div style={{flex:1}}>
<div style={{fontWeight:700,fontSize:15,color:'var(--accent)'}}>🔬 Mehrstufige Gesamtanalyse</div>
<div style={{fontSize:12,color:'var(--text2)',marginTop:3,lineHeight:1.5}}>
3 spezialisierte KI-Calls parallel (Körper + Ernährung + Aktivität),
dann Synthese + Zielabgleich. Detaillierteste Auswertung.
</div>
{allInsights.find(i=>i.scope==='pipeline') && (
<div style={{fontSize:11,color:'var(--text3)',marginTop:3}}>
Letzte Analyse: {dayjs(allInsights.find(i=>i.scope==='pipeline').created).format('DD.MM.YYYY, HH:mm')}
{/* Pipeline button - only if all sub-prompts are active */}
{pipelineAvailable && (
<div className="card" style={{marginBottom:16,borderColor:'var(--accent)',borderWidth:2}}>
<div style={{display:'flex',alignItems:'flex-start',gap:12}}>
<div style={{flex:1}}>
<div style={{fontWeight:700,fontSize:15,color:'var(--accent)'}}>🔬 Mehrstufige Gesamtanalyse</div>
<div style={{fontSize:12,color:'var(--text2)',marginTop:3,lineHeight:1.5}}>
3 spezialisierte KI-Calls parallel (Körper + Ernährung + Aktivität),
dann Synthese + Zielabgleich. Detaillierteste Auswertung.
</div>
)}
{allInsights.find(i=>i.scope==='pipeline') && (
<div style={{fontSize:11,color:'var(--text3)',marginTop:3}}>
Letzte Analyse: {dayjs(allInsights.find(i=>i.scope==='pipeline').created).format('DD.MM.YYYY, HH:mm')}
</div>
)}
</div>
<button className="btn btn-primary" style={{flexShrink:0,minWidth:100}}
onClick={runPipeline} disabled={!!loading||pipelineLoading}>
{pipelineLoading
? <><div className="spinner" style={{width:13,height:13}}/> Läuft</>
: <><Brain size={13}/> Starten</>}
</button>
{!canUseAI && <div style={{fontSize:11,color:'#D85A30',marginTop:4}}>🔒 KI nicht freigeschaltet</div>}
</div>
<button className="btn btn-primary" style={{flexShrink:0,minWidth:100}}
onClick={runPipeline} disabled={!!loading||pipelineLoading}>
{pipelineLoading
? <><div className="spinner" style={{width:13,height:13}}/> Läuft</>
: <><Brain size={13}/> Starten</>}
</button>
{!canUseAI && <div style={{fontSize:11,color:'#D85A30',marginTop:4}}>🔒 KI nicht freigeschaltet</div>}
{pipelineLoading && (
<div style={{marginTop:10,padding:'8px 12px',background:'var(--accent-light)',
borderRadius:8,fontSize:12,color:'var(--accent-dark)'}}>
Stufe 1: 3 parallele Analyse-Calls dann Synthese dann Zielabgleich
</div>
)}
</div>
{pipelineLoading && (
<div style={{marginTop:10,padding:'8px 12px',background:'var(--accent-light)',
borderRadius:8,fontSize:12,color:'var(--accent-dark)'}}>
Stufe 1: 3 parallele Analyse-Calls dann Synthese dann Zielabgleich
</div>
)}
</div>
)}
{!canUseAI && (
<div style={{padding:'14px 16px',background:'#FCEBEB',borderRadius:10,
@ -345,21 +354,26 @@ export default function Analysis() {
Einzelanalysen
</div>
{singlePrompts.map(p=>(
<div key={p.id} className="card section-gap">
<div key={p.id} className="card section-gap" style={{opacity:p.active?1:0.6}}>
<div style={{display:'flex',alignItems:'center',gap:10}}>
<div style={{flex:1}}>
<div style={{fontWeight:600,fontSize:14,display:'flex',alignItems:'center',gap:8}}>
{SLUG_LABELS[p.slug]||p.name}
{!p.active && <span style={{fontSize:10,color:'var(--text3)',
background:'var(--surface2)',padding:'1px 6px',borderRadius:4}}>Inaktiv</span>}
{!p.active && <span style={{fontSize:10,color:'#D85A30',
background:'#FCEBEB',padding:'2px 8px',borderRadius:4,fontWeight:600}}> Deaktiviert</span>}
</div>
{p.description && <div style={{fontSize:12,color:'var(--text3)',marginTop:1}}>{p.description}</div>}
</div>
<button className="btn btn-secondary" style={{padding:'5px 8px',fontSize:12}}
onClick={()=>fetch(`/api/prompts/${p.id}`,{method:'PUT',
headers:{'Content-Type':'application/json'},
body:JSON.stringify({active:p.active?0:1})}).then(loadAll)}>
{p.active?'Deaktiv.':'Aktiv.'}
onClick={()=>{
const token = localStorage.getItem('bodytrack_token')||''
fetch(`/api/prompts/${p.id}`,{
method:'PUT',
headers:{'Content-Type':'application/json','X-Auth-Token':token},
body:JSON.stringify({active:!p.active})
}).then(loadAll)
}}>
{p.active?'Deaktivieren':'Aktivieren'}
</button>
<button className="btn btn-secondary" style={{padding:'5px 8px'}}
onClick={()=>setEditing(p)}><Pencil size={13}/></button>
@ -372,26 +386,60 @@ export default function Analysis() {
))}
{/* Pipeline prompts */}
<div style={{fontSize:12,fontWeight:700,color:'var(--text3)',
textTransform:'uppercase',letterSpacing:'0.05em',margin:'20px 0 8px'}}>
Mehrstufige Pipeline
</div>
<div style={{padding:'10px 12px',background:'var(--warn-bg)',borderRadius:8,
fontSize:12,color:'var(--warn-text)',marginBottom:12,lineHeight:1.6}}>
<strong>Hinweis:</strong> Pipeline-Stage-1-Prompts müssen valides JSON zurückgeben.
Halte das JSON-Format im Prompt erhalten. Stage 2 + 3 können frei angepasst werden.
<div style={{display:'flex',alignItems:'center',justifyContent:'space-between',margin:'20px 0 8px'}}>
<div style={{fontSize:12,fontWeight:700,color:'var(--text3)',
textTransform:'uppercase',letterSpacing:'0.05em'}}>
Mehrstufige Pipeline
</div>
{(() => {
const pipelinePrompt = prompts.find(p=>p.slug==='pipeline')
return pipelinePrompt && (
<button className="btn btn-secondary" style={{padding:'5px 12px',fontSize:12}}
onClick={()=>{
const token = localStorage.getItem('bodytrack_token')||''
fetch(`/api/prompts/${pipelinePrompt.id}`,{
method:'PUT',
headers:{'Content-Type':'application/json','X-Auth-Token':token},
body:JSON.stringify({active:!pipelinePrompt.active})
}).then(loadAll)
}}>
{pipelinePrompt.active ? 'Gesamte Pipeline deaktivieren' : 'Gesamte Pipeline aktivieren'}
</button>
)
})()}
</div>
{(() => {
const pipelinePrompt = prompts.find(p=>p.slug==='pipeline')
const isPipelineActive = pipelinePrompt?.active ?? true
return (
<div style={{padding:'10px 12px',
background: isPipelineActive ? 'var(--warn-bg)' : '#FCEBEB',
borderRadius:8,fontSize:12,
color: isPipelineActive ? 'var(--warn-text)' : '#D85A30',
marginBottom:12,lineHeight:1.6}}>
{isPipelineActive ? (
<> <strong>Hinweis:</strong> Pipeline-Stage-1-Prompts müssen valides JSON zurückgeben.
Halte das JSON-Format im Prompt erhalten. Stage 2 + 3 können frei angepasst werden.</>
) : (
<> <strong>Pipeline deaktiviert:</strong> Die mehrstufige Gesamtanalyse ist aktuell nicht verfügbar.
Aktiviere sie mit dem Schalter oben, um sie auf der Analyse-Seite zu nutzen.</>
)}
</div>
)
})()}
{pipelinePrompts.map(p=>{
const isJson = jsonSlugs.includes(p.slug)
return (
<div key={p.id} className="card section-gap"
style={{borderLeft:`3px solid ${isJson?'var(--warn)':'var(--accent)'}`}}>
style={{borderLeft:`3px solid ${isJson?'var(--warn)':'var(--accent)'}`,opacity:p.active?1:0.6}}>
<div style={{display:'flex',alignItems:'center',gap:10}}>
<div style={{flex:1}}>
<div style={{fontWeight:600,fontSize:14,display:'flex',alignItems:'center',gap:8}}>
{p.name}
{isJson && <span style={{fontSize:10,background:'var(--warn-bg)',
color:'var(--warn-text)',padding:'1px 6px',borderRadius:4}}>JSON-Output</span>}
{!p.active && <span style={{fontSize:10,color:'#D85A30',
background:'#FCEBEB',padding:'2px 8px',borderRadius:4,fontWeight:600}}> Deaktiviert</span>}
</div>
{p.description && <div style={{fontSize:12,color:'var(--text3)',marginTop:1}}>{p.description}</div>}
</div>

View File

@ -147,7 +147,7 @@ function PeriodSelector({ value, onChange }) {
}
// Body Section (Weight + Composition combined)
function BodySection({ weights, calipers, circs, profile, insights, onRequest, loadingSlug }) {
function BodySection({ weights, calipers, circs, profile, insights, onRequest, loadingSlug, filterActiveSlugs }) {
const [period, setPeriod] = useState(90)
const sex = profile?.sex||'m'
const height = profile?.height||178
@ -394,14 +394,14 @@ function BodySection({ weights, calipers, circs, profile, insights, onRequest, l
</div>
)}
<InsightBox insights={insights} slugs={['pipeline','koerper','gesundheit','ziele']}
<InsightBox insights={insights} slugs={filterActiveSlugs(['pipeline','koerper','gesundheit','ziele'])}
onRequest={onRequest} loading={loadingSlug}/>
</div>
)
}
// Nutrition Section
function NutritionSection({ nutrition, weights, profile, insights, onRequest, loadingSlug }) {
function NutritionSection({ nutrition, weights, profile, insights, onRequest, loadingSlug, filterActiveSlugs }) {
const [period, setPeriod] = useState(30)
if (!nutrition?.length) return (
<EmptySection text="Noch keine Ernährungsdaten." to="/nutrition" toLabel="FDDB importieren"/>
@ -579,13 +579,13 @@ function NutritionSection({ nutrition, weights, profile, insights, onRequest, lo
<div style={{fontSize:12,fontWeight:600,color:'var(--text3)',marginBottom:8}}>BEWERTUNG</div>
{macroRules.map((item,i)=><RuleCard key={i} item={item}/>)}
</div>
<InsightBox insights={insights} slugs={['ernaehrung']} onRequest={onRequest} loading={loadingSlug}/>
<InsightBox insights={insights} slugs={filterActiveSlugs(['ernaehrung'])} onRequest={onRequest} loading={loadingSlug}/>
</div>
)
}
// Activity Section
function ActivitySection({ activities, insights, onRequest, loadingSlug }) {
function ActivitySection({ activities, insights, onRequest, loadingSlug, filterActiveSlugs }) {
const [period, setPeriod] = useState(30)
if (!activities?.length) return (
<EmptySection text="Noch keine Aktivitätsdaten." to="/activity" toLabel="Aktivität erfassen"/>
@ -657,13 +657,13 @@ function ActivitySection({ activities, insights, onRequest, loadingSlug }) {
<div style={{fontSize:12,fontWeight:600,color:'var(--text3)',marginBottom:8}}>BEWERTUNG</div>
{actRules.map((item,i)=><RuleCard key={i} item={item}/>)}
</div>
<InsightBox insights={insights} slugs={['aktivitaet']} onRequest={onRequest} loading={loadingSlug}/>
<InsightBox insights={insights} slugs={filterActiveSlugs(['aktivitaet'])} onRequest={onRequest} loading={loadingSlug}/>
</div>
)
}
// Correlation Section
function CorrelationSection({ corrData, insights, profile, onRequest, loadingSlug }) {
function CorrelationSection({ corrData, insights, profile, onRequest, loadingSlug, filterActiveSlugs }) {
const filtered = (corrData||[]).filter(d=>d.kcal&&d.weight)
if (filtered.length < 5) return (
<EmptySection text="Für Korrelationen werden Gewichts- und Ernährungsdaten benötigt (mind. 5 gemeinsame Tage)."/>
@ -852,7 +852,7 @@ function CorrelationSection({ corrData, insights, profile, onRequest, loadingSlu
</div>
)}
<InsightBox insights={insights} slugs={['gesamt','ziele']} onRequest={onRequest} loading={loadingSlug}/>
<InsightBox insights={insights} slugs={filterActiveSlugs(['gesamt','ziele'])} onRequest={onRequest} loading={loadingSlug}/>
</div>
)
}
@ -903,6 +903,7 @@ export default function History() {
const [activities, setActivities] = useState([])
const [corrData, setCorrData] = useState([])
const [insights, setInsights] = useState([])
const [prompts, setPrompts] = useState([])
const [profile, setProfile] = useState(null)
const [loading, setLoading] = useState(true)
const [loadingSlug,setLoadingSlug]= useState(null)
@ -911,10 +912,12 @@ export default function History() {
api.listWeight(365), api.listCaliper(), api.listCirc(),
api.listNutrition(90), api.listActivity(200),
api.nutritionCorrelations(), api.latestInsights(), api.getProfile(),
]).then(([w,ca,ci,n,a,corr,ins,p])=>{
api.listPrompts(),
]).then(([w,ca,ci,n,a,corr,ins,p,pr])=>{
setWeights(w); setCalipers(ca); setCircs(ci)
setNutrition(n); setActivities(a); setCorrData(corr)
setInsights(Array.isArray(ins)?ins:[]); setProfile(p)
setPrompts(Array.isArray(pr)?pr:[])
setLoading(false)
})
@ -923,17 +926,23 @@ export default function History() {
const requestInsight = async (slug) => {
setLoadingSlug(slug)
try {
const pid=localStorage.getItem('bodytrack_active_profile')||''
const r=await api.runInsight(slug)
if(!r.ok) throw new Error(await r.text())
const ins=await api.latestInsights()
const result = await api.runInsight(slug)
// result is already JSON, not a Response object
const ins = await api.latestInsights()
setInsights(Array.isArray(ins)?ins:[])
} catch(e){ alert('KI-Fehler: '+e.message) }
} catch(e){
alert('KI-Fehler: '+e.message)
}
finally{ setLoadingSlug(null) }
}
if(loading) return <div className="empty-state"><div className="spinner"/></div>
const sp={insights,onRequest:requestInsight,loadingSlug}
// Filter active prompts
const activeSlugs = prompts.filter(p=>p.active).map(p=>p.slug)
const filterActiveSlugs = (slugs) => slugs.filter(s=>activeSlugs.includes(s))
const sp={insights,onRequest:requestInsight,loadingSlug,filterActiveSlugs}
return (
<div>

View File

@ -32,7 +32,7 @@ export default function LoginScreen() {
}
setLoading(true); setError(null)
try {
await login({ email: email.trim().toLowerCase(), pin: password })
await login({ email: email.trim().toLowerCase(), password: password })
} catch(e) {
setError(e.message || 'Ungültige E-Mail oder Passwort')
} finally { setLoading(false) }

View File

@ -1,5 +1,5 @@
import { useState } from 'react'
import { Save, Download, Trash2, Plus, Check, Pencil, X, LogOut, Shield, Key } from 'lucide-react'
import { Save, Download, Upload, Trash2, Plus, Check, Pencil, X, LogOut, Shield, Key } from 'lucide-react'
import { useProfile } from '../context/ProfileContext'
import { useAuth } from '../context/AuthContext'
import { Avatar } from './ProfileSelect'
@ -123,6 +123,73 @@ export default function SettingsPage() {
// editingId: string ID of profile being edited, or 'new' for new profile, or null
const [editingId, setEditingId] = useState(null)
const [saved, setSaved] = useState(false)
const [importing, setImporting] = useState(false)
const [importMsg, setImportMsg] = useState(null)
const handleImport = async (e) => {
const file = e.target.files?.[0]
if (!file) return
if (!confirm(`Backup "${file.name}" importieren? Vorhandene Einträge werden nicht überschrieben.`)) {
e.target.value = '' // Reset file input
return
}
setImporting(true)
setImportMsg(null)
try {
const formData = new FormData()
formData.append('file', file)
const token = localStorage.getItem('bodytrack_token')||''
const pid = localStorage.getItem('bodytrack_active_profile')||''
const res = await fetch('/api/import/zip', {
method: 'POST',
headers: {
'X-Auth-Token': token,
'X-Profile-Id': pid
},
body: formData
})
const data = await res.json()
if (!res.ok) {
throw new Error(data.detail || 'Import fehlgeschlagen')
}
// Show success message with stats
const stats = data.stats
const lines = []
if (stats.weight > 0) lines.push(`${stats.weight} Gewicht`)
if (stats.circumferences > 0) lines.push(`${stats.circumferences} Umfänge`)
if (stats.caliper > 0) lines.push(`${stats.caliper} Caliper`)
if (stats.nutrition > 0) lines.push(`${stats.nutrition} Ernährung`)
if (stats.activity > 0) lines.push(`${stats.activity} Aktivität`)
if (stats.photos > 0) lines.push(`${stats.photos} Fotos`)
if (stats.insights > 0) lines.push(`${stats.insights} KI-Analysen`)
setImportMsg({
type: 'success',
text: `✓ Import erfolgreich: ${lines.join(', ')}`
})
// Refresh data (in case new entries were added)
await refreshProfiles()
} catch (err) {
setImportMsg({
type: 'error',
text: `${err.message}`
})
} finally {
setImporting(false)
e.target.value = '' // Reset file input
setTimeout(() => setImportMsg(null), 5000)
}
}
const handleSave = async (form, profileId) => {
const data = {}
@ -291,12 +358,12 @@ export default function SettingsPage() {
)}
{canExport && <>
<button className="btn btn-primary btn-full"
onClick={()=>window.open('/api/export/zip')}>
onClick={()=>api.exportZip()}>
<Download size={14}/> ZIP exportieren
<span style={{fontSize:11,opacity:0.8,marginLeft:6}}> je eine CSV pro Kategorie</span>
</button>
<button className="btn btn-secondary btn-full"
onClick={()=>window.open('/api/export/json')}>
onClick={()=>api.exportJson()}>
<Download size={14}/> JSON exportieren
<span style={{fontSize:11,opacity:0.8,marginLeft:6}}> maschinenlesbar, alles in einer Datei</span>
</button>
@ -307,6 +374,55 @@ export default function SettingsPage() {
</p>
</div>
{/* Import */}
<div className="card section-gap">
<div className="card-title">Backup importieren</div>
<p style={{fontSize:13,color:'var(--text2)',marginBottom:12,lineHeight:1.6}}>
Importiere einen ZIP-Export zurück in <strong>{activeProfile?.name}</strong>.
Vorhandene Einträge werden nicht überschrieben.
</p>
<div style={{display:'flex',flexDirection:'column',gap:8}}>
{!canExport && (
<div style={{padding:'10px 12px',background:'#FCEBEB',borderRadius:8,
fontSize:13,color:'#D85A30',marginBottom:8}}>
🔒 Import ist für dein Profil nicht freigeschaltet. Bitte den Admin kontaktieren.
</div>
)}
{canExport && (
<>
<label className="btn btn-primary btn-full"
style={{cursor:importing?'wait':'pointer',opacity:importing?0.6:1}}>
<input type="file" accept=".zip" onChange={handleImport}
disabled={importing}
style={{display:'none'}}/>
{importing ? (
<>Importiere...</>
) : (
<>
<Upload size={14}/> ZIP-Backup importieren
</>
)}
</label>
{importMsg && (
<div style={{
padding:'10px 12px',
background: importMsg.type === 'success' ? '#E1F5EE' : '#FCEBEB',
borderRadius:8,
fontSize:12,
color: importMsg.type === 'success' ? 'var(--accent)' : '#D85A30',
lineHeight:1.4
}}>
{importMsg.text}
</div>
)}
</>
)}
</div>
<p style={{fontSize:11,color:'var(--text3)',marginTop:8}}>
Der Import erkennt automatisch das Format und importiert nur neue Einträge.
</p>
</div>
{saved && (
<div style={{position:'fixed',bottom:80,left:'50%',transform:'translateX(-50%)',
background:'var(--accent)',color:'white',padding:'8px 20px',borderRadius:20,

View File

@ -68,7 +68,10 @@ export const api = {
return fetch(`${BASE}/photos`,{method:'POST',body:fd,headers:hdrs()}).then(r=>r.json())
},
listPhotos: () => req('/photos'),
photoUrl: (pid) => `${BASE}/photos/${pid}`,
photoUrl: (pid) => {
const token = getToken()
return `${BASE}/photos/${pid}${token ? `?token=${token}` : ''}`
},
// Nutrition
importCsv: async(file)=>{
@ -88,9 +91,45 @@ export const api = {
insightPipeline: () => req('/insights/pipeline',{method:'POST'}),
listInsights: () => req('/insights'),
latestInsights: () => req('/insights/latest'),
exportZip: () => window.open(`${BASE}/export/zip`),
exportJson: () => window.open(`${BASE}/export/json`),
exportCsv: () => window.open(`${BASE}/export/csv`),
exportZip: async () => {
const res = await fetch(`${BASE}/export/zip`, {headers: hdrs()})
if (!res.ok) throw new Error('Export failed')
const blob = await res.blob()
const url = window.URL.createObjectURL(blob)
const a = document.createElement('a')
a.href = url
a.download = `mitai-export-${new Date().toISOString().split('T')[0]}.zip`
document.body.appendChild(a)
a.click()
document.body.removeChild(a)
window.URL.revokeObjectURL(url)
},
exportJson: async () => {
const res = await fetch(`${BASE}/export/json`, {headers: hdrs()})
if (!res.ok) throw new Error('Export failed')
const blob = await res.blob()
const url = window.URL.createObjectURL(blob)
const a = document.createElement('a')
a.href = url
a.download = `mitai-export-${new Date().toISOString().split('T')[0]}.json`
document.body.appendChild(a)
a.click()
document.body.removeChild(a)
window.URL.revokeObjectURL(url)
},
exportCsv: async () => {
const res = await fetch(`${BASE}/export/csv`, {headers: hdrs()})
if (!res.ok) throw new Error('Export failed')
const blob = await res.blob()
const url = window.URL.createObjectURL(blob)
const a = document.createElement('a')
a.href = url
a.download = `mitai-export-${new Date().toISOString().split('T')[0]}.csv`
document.body.appendChild(a)
a.click()
document.body.removeChild(a)
window.URL.revokeObjectURL(url)
},
// Admin
adminListProfiles: () => req('/admin/profiles'),