geograsim/App/sims/weltkueche/scripts/generate-onboarding-images.py

#!/usr/bin/env python3
"""Generiert die 5 Tutorial-Step-Bilder für das Weltküche-Onboarding.
Flat-Scandinavian-Stil, ersetzen die alten Emojis im Tutorial-Overlay.
Output: App/sims/weltkueche/assets/img/onboarding/<key>.webp (320x320)"""
import json, os, subprocess, sys, tempfile, base64
from pathlib import Path

KEY = None
env_path = 'C:/xampp/htdocs/geograsim/App/.env.local'
with open(env_path, 'r', encoding='utf-8') as f:
    for line in f:
        if line.startswith('OPENAI_API_KEY='):
            KEY = line.split('=', 1)[1].strip().strip('"').strip("'")
            break
if not KEY:
    sys.exit('OPENAI_API_KEY nicht in .env.local')

OUT_DIR  = Path('C:/xampp/htdocs/geograsim/App/sims/weltkueche/assets/img/onboarding')
ORIG_DIR = OUT_DIR / '_original'
OUT_DIR.mkdir(parents=True, exist_ok=True)
ORIG_DIR.mkdir(parents=True, exist_ok=True)

PROMPT_BASE = ("CRITICAL STYLE: flat vector illustration, children's-book / Scandinavian poster art, "
               "NO photography, NO 3D rendering, NO realistic shading, NO photographic textures, NO gradients. "
               "Wide-shape silhouettes with flat solid color fills, clean cut edges, simple geometric forms. "
               "Strict palette: dark forest green #1f4b37, sage green #4a7c4e, yellow-mustard #e8c547, "
               "warm beige #e8e4d8, white highlights, optional small red-orange accent #c97b5a. "
               "COMPOSITION: a single centered iconographic motif (one strong shape), filling about 75% of the square frame, "
               "with a flat beige #e8e4d8 background. The motif is plakatativ-simple — recognizable from a thumbnail. "
               "FORBIDDEN: text, letters, numbers, watermarks, logos, borders, frames, photo-realistic lighting, "
               "lens-flare, people faces, hands, brand names, shadows.")

STEPS = {
    'woher': (
        "SCENE: a centered round Earth globe in dark forest green and sage green, "
        "with simple geographic shapes (one continent shape with white tiny dots for cities). "
        "Around the globe, 5 small flat food icons evenly spaced like a clockface: "
        "a yellow-mustard banana shape (top), a red-orange tomato (right), a forest-green coffee bean (bottom-right), "
        "a sage-green pepper grain cluster (bottom-left), a beige bread slice (left). "
        "Soft dotted curved lines connect each food to the globe (like trade routes)."
    ),
    'forschung': (
        "SCENE: a centered flat-style world map (silhouette of continents in sage green on beige ocean) "
        "with a large dark forest green magnifying glass overlapping the right side. "
        "The map has 3-4 red-orange pin-drop markers at different locations. "
        "The magnifying glass handle points to the bottom-right."
    ),
    'punkte': (
        "SCENE: a centered tall trophy cup in yellow-mustard with dark forest green handles and base. "
        "Inside the cup, a 5-pointed sage-green star. "
        "Three small flat circular medals float around the cup — one with a star, one with a leaf, one with a globe symbol — "
        "all in white outlines on dark forest green circles."
    ),
    'klima': (
        "SCENE: a centered round Earth globe in sage green and dark forest green, with a young green sapling/seedling "
        "growing out of the top of the globe (two small leaves in sage green). "
        "Below the globe, a flat container ship silhouette in dark forest green on a beige horizontal sea line. "
        "A small white CO₂ cloud shape on the upper-right (made from 2-3 overlapping circles)."
    ),
    'glossar': (
        "SCENE: a centered open hardcover book viewed from above. The cover and edges are dark forest green, "
        "the pages are warm beige. On the left page: 3-4 horizontal sage-green text lines (abstract, no real letters). "
        "On the right page: a small dark forest green globe icon centered. "
        "A yellow-mustard bookmark ribbon hangs from the top center."
    ),
}

def generate(key, scene):
    out_png  = ORIG_DIR / f'{key}.png'
    out_webp = OUT_DIR / f'{key}.webp'
    if out_webp.exists():
        print(f'   SKIP (existiert): {out_webp.name}')
        return True
    prompt = PROMPT_BASE + ' ' + scene
    body = json.dumps({'model': 'gpt-image-2', 'prompt': prompt, 'n': 1, 'size': '1024x1024'}, ensure_ascii=False)
    with tempfile.NamedTemporaryFile(mode='w', encoding='utf-8', suffix='.json', delete=False) as f:
        f.write(body); bpath = f.name
    r = subprocess.run(['curl', '-sS',
        '-X', 'POST', 'https://api.openai.com/v1/images/generations',
        '-H', 'Authorization: Bearer ' + KEY,
        '-H', 'Content-Type: application/json',
        '--data-binary', '@' + bpath], capture_output=True, text=True, timeout=300)
    os.unlink(bpath)
    try:
        data = json.loads(r.stdout)
        item = data['data'][0]
        if 'b64_json' in item:
            with open(out_png, 'wb') as f:
                f.write(base64.b64decode(item['b64_json']))
        elif 'url' in item:
            subprocess.run(['curl', '-sS', '-o', str(out_png), item['url']],
                           capture_output=True, text=True, timeout=60)
        else:
            return False
    except Exception as e:
        print(f'   FAIL: {r.stdout[:200] if r.stdout else e}')
        return False
    if not out_png.exists() or out_png.stat().st_size < 10000:
        return False
    try:
        from PIL import Image
        img = Image.open(out_png)
        img = img.resize((320, 320), Image.LANCZOS)
        img.save(out_webp, 'webp', quality=85, method=6)
    except Exception as e:
        print(f'   WebP-Fail: {e}')
        return False
    return True

ids = sys.argv[1:] if len(sys.argv) > 1 else list(STEPS.keys())
for k in ids:
    if k not in STEPS:
        print(f'-> {k}: UNBEKANNT')
        continue
    print(f'-> {k} ...', flush=True)
    ok = generate(k, STEPS[k])
    print(f'   {"OK" if ok else "FAIL"}: {k}.webp')