Model: snake7gun/Z-Image-Turbo-int4-ov (ModelScope INT4)
SKILL_VERSION: v1.0.0
Network usage: Setup downloads pip dependencies (some pinned to git+https commits) from
github.com, and the model (~10 GB, resume supported) frommodelscope.cn. Inference is fully offline — no network calls once setup is complete.
First time? Before using this skill, run these two scripts once in a terminal:
python setup.py # creates venv, installs dependencies (~5 min) python download_model.py # downloads the model (~10 GB, resumable)Both scripts are in the skill directory alongside this SKILL.md.
Directory layout (all auto-created)
{USERNAME}_openvino\
├── venv\ ← shared venv (created by setup.py)
└── appstore_screenshots\
├── state.json ← written by setup.py
├── generate_appstore.py ← written in Step 2
├── Z-Image-Turbo-int4-ov\ ← downloaded by download_model.py (~10 GB)
└── outputs\YYYYMMDD_HHMMSS_{app_name}_{device_type}.png
⚠️ Agent instructions
- Windows / PowerShell only. Never use Linux commands (
ls,rm,cat). Never use&&orcall. - Every step reads
state.jsonitself — do not pass paths between steps manually. - Use
VENV_PYfrom state.json for all python calls — never use system python for inference. - CRITICAL — Never skip Step 2. Always run the version-check python script to write
generate_appstore.py. Never use the Write tool to create or modify it manually. - CRITICAL — If
generate_appstore.pyfails, do NOT rewrite it manually. Delete it and re-run Step 2's python script to regenerate. - Goal: generate Apple App Store-compliant listing screenshots and send previews.
Auto-recovery policy — try before asking user:
- If
STATE=MISSINGorVENV_PY=BROKEN: automatically runsetup.py(up to 3 attempts). Only ask user if all 3 fail. - If
MODEL_STATUS=MISSING: automatically rundownload_model.py(up to 3 attempts). Stop if a single attempt exceeds 20 minutes — download supports resume, partial progress is not lost. - Always announce before each attempt:
⚙️ Auto-installing environment (attempt N/3)…
Pipeline — follow exactly in order, no skipping:
Step 0: extract app info → APP_NAME, CATEGORY, TONE, DEVICE_TYPE, STYLE, EXPANDED_PROMPT
Step 1: verify environment → VENV_PY, APPSTORE_DIR confirmed ready
↳ if STATE=MISSING or VENV_BROKEN: auto-run setup.py (3 attempts)
↳ if MODEL_STATUS=MISSING: auto-run download_model.py (3 attempts)
Step 2: verify deps + write generate_appstore.py → SCRIPT_UPDATE=DONE/SKIPPED ← NEVER skip
Step 3: generate + send → [SUCCESS] + image previews
Step 0: extract app info and build generation prompt (LLM only — no tools)
Analyze the user's input (app screenshot image + text description) and extract:
- APP_NAME: App name (English or Chinese)
- CATEGORY: App category — choose from: productivity, utility, finance, health, education, entertainment, social, shopping
- TONE: Visual tone — choose from: minimalist, professional, tech, playful, casual, vibrant
- DEVICE_TYPE: Target device — choose from: iphone_67 (1290x2796), iphone_61 (1179x2556), ipad_129 (2048x2732). Default: iphone_67
- STYLE: Visual style for generation — choose from: minimalist, tech, playful, professional
- EXPANDED_PROMPT: Detailed image generation prompt in the following structure:
Prompt structure: [app category] [key features] [visual style] [color scheme] [layout] [quality tags]
Quality tags: App Store screenshot, clean UI, modern design, high quality, professional
| Input | Style | Expanded prompt | |-------|-------|-----------------| | 任务管理App | minimalist | A minimalist productivity app screenshot showing task list interface, clean white background with subtle shadows, modern iOS design, App Store screenshot, clean UI, high quality | | 健身追踪App | tech | A sleek fitness tracking app screenshot with dark gradient background, neon accent colors, data visualization charts, App Store screenshot, modern design, professional |
Show the result before proceeding:
📝 App: {app_name}
Category: {category}
Tone: {tone}
Device: {device_type} ({width}x{height})
Style: {style}
Prompt: {expanded_prompt}
Step 1: verify environment and model
🔍 Step 1/3: checking environment and model…
python -c "
import json, os, string, subprocess
from pathlib import Path
state = None
for d in string.ascii_uppercase:
sf = Path(f'{d}:\\\\') / f'{os.environ.get(\"USERNAME\",\"user\").lower()}_openvino' / 'appstore_screenshots' / 'state.json'
if sf.exists():
state = json.loads(sf.read_text(encoding='utf-8'))
break
if not state:
print('STATE=MISSING')
exit(1)
venv_py = Path(state['VENV_PY'])
appstore_dir = Path(state['APPSTORE_DIR'])
model_dir = appstore_dir / 'Z-Image-Turbo-int4-ov'
r = subprocess.run([str(venv_py), '--version'], capture_output=True, timeout=10)
if r.returncode != 0:
print('VENV_PY=BROKEN')
exit(1)
print(f'VENV_PY={venv_py}')
print(f'APPSTORE_DIR={appstore_dir}')
required = ['transformer', 'vae_decoder', 'text_encoder']
missing = [r for r in required if not (model_dir / r).exists()]
if not missing:
total = sum(f.stat().st_size for f in model_dir.rglob('*') if f.is_file()) / 1024**3
print(f'MODEL_STATUS=READY ({total:.2f} GB)')
else:
print(f'MODEL_STATUS=MISSING missing={missing}')
exit(1)
"
On success: record VENV_PY and APPSTORE_DIR from output, proceed to Step 2.
If STATE=MISSING or VENV_PY=BROKEN → auto-run setup.py
python -c "
from pathlib import Path
p = Path(r'{baseDir}') / 'setup.py'
print(f'SETUP_PY={p}') if p.exists() else print('SETUP_PY=NOT_FOUND')
"
Announce and run (up to 3 attempts):
⚙️ Environment not initialized — auto-installing (attempt 1/3)…
python "<SETUP_PY path>"
Re-run Step 1's check after each attempt. If all 3 fail, show manual fallback below.
If MODEL_STATUS=MISSING → auto-run download_model.py
python -c "
from pathlib import Path
p = Path(r'{baseDir}') / 'download_model.py'
print(f'DOWNLOAD_PY={p}') if p.exists() else print('DOWNLOAD_PY=NOT_FOUND')
"
Announce to user and ask how to proceed:
📥 Model not found — download required (~10 GB)
Estimated time:
• 100 Mbps → ~15 min
• 50 Mbps → ~30 min
• 10 Mbps → ~2 hr
Download supports resume — safe to interrupt and retry.
✅ Start auto-download
📂 I'll download manually — show me the link
Auto-download (up to 3 attempts, stop if a single attempt exceeds 20 minutes):
python "<DOWNLOAD_PY path>"
Re-run Step 1's check after each attempt.
Manual download fallback:
ModelScope page: https://modelscope.cn/models/snake7gun/Z-Image-Turbo-int4-ov/files
Place all files under <APPSTORE_DIR>\Z-Image-Turbo-int4-ov\. Required subdirs:
Z-Image-Turbo-int4-ov\
├── transformer\
├── vae_decoder\
└── text_encoder\
Then re-run Step 1's check to verify.
Manual fallback (only if all 3 setup auto-attempts fail)
python -c "
from pathlib import Path
skill_dir = Path(r'{baseDir}')
for script in ['setup.py', 'download_model.py']:
p = skill_dir / script
if p.exists(): print(f'{script}={p}')
"
Show user:
⚠️ Auto-install failed. Please run manually in a terminal:
① Install environment:
python "<full path to setup.py>"
Takes ~5 min, fully automated.
② Download model (~10 GB):
python "<full path to download_model.py>"
Resumable — safe to interrupt and retry.
Come back here when done.
Step 2: verify deps and write generate_appstore.py
✍️ Step 2/3: checking dependencies and script version…
First verify dependencies (run via VENV_PY):
& "<VENV_PY>" -c "
import json, site
from pathlib import Path
EXPECTED_COMMITS = {
'optimum_intel': '2f62e5ae',
'diffusers': 'a1f36ee3',
}
def get_git_commit(pkg_name):
dirs = site.getsitepackages()
try: dirs += [site.getusersitepackages()]
except Exception: pass
for d in dirs:
for dist in Path(d).glob(f'{pkg_name}*.dist-info'):
url_file = dist / 'direct_url.json'
if url_file.exists():
data = json.loads(url_file.read_text(encoding='utf-8'))
return data.get('vcs_info', {}).get('commit_id', 'no_vcs_info')
return 'not_found'
results = {}
for pkg, imp in [('openvino','openvino'),('torch','torch'),('Pillow','PIL'),('modelscope','modelscope'),('cv2','cv2'),('yaml','yaml')]:
try:
ver = getattr(__import__(imp), '__version__', 'OK')
results[pkg] = ('OK', ver)
except ImportError as e:
results[pkg] = ('MISSING', str(e))
try:
from optimum.intel import OVZImagePipeline
results['OVZImagePipeline'] = ('OK', 'importable')
except ImportError as e:
results['OVZImagePipeline'] = ('MISSING', str(e))
for pkg_name, exp in EXPECTED_COMMITS.items():
actual = get_git_commit(pkg_name)
if actual == 'not_found':
results[f'{pkg_name}@commit'] = ('MISSING', 'not installed via git+https')
elif actual.startswith(exp):
results[f'{pkg_name}@commit'] = ('OK', actual[:16])
else:
results[f'{pkg_name}@commit'] = ('WRONG', f'got {actual[:16]} want {exp}...')
all_ok = all(v[0] == 'OK' for v in results.values())
for k, (status, detail) in results.items():
icon = '✅' if status == 'OK' else ('⚠️' if status == 'WRONG' else '❌')
print(f' {icon} {k}: {detail}')
print('DEP_CHECK=PASS' if all_ok else 'DEP_CHECK=FAIL')
"
| Output | Action |
|--------|--------|
| DEP_CHECK=PASS | ✅ Proceed to write script below |
| DEP_CHECK=FAIL (MISSING) | ⛔ Re-run setup.py and retry |
| DEP_CHECK=FAIL (@commit WRONG) | ⛔ Force reinstall: & "<VENV_PY>" -m pip uninstall optimum-intel diffusers -y then & "<VENV_PY>" -m pip install -r "{baseDir}\requirements_imagegen.txt" --no-cache-dir |
Then write generate_appstore.py:
python -c "
import json, os, string, re
from pathlib import Path
state = None
for d in string.ascii_uppercase:
sf = Path(f'{d}:\\\\') / f'{os.environ.get(\"USERNAME\",\"user\").lower()}_openvino' / 'appstore_screenshots' / 'state.json'
if sf.exists():
state = json.loads(sf.read_text(encoding='utf-8'))
break
if not state:
print('[ERROR] state.json not found — re-run Step 1')
exit(1)
appstore_dir = Path(state['APPSTORE_DIR'])
CURRENT_VERSION = 'v1.0.0'
script = appstore_dir / 'generate_appstore.py'
existing = None
if script.exists():
m = re.search(r\"SKILL_VERSION\s*=\s*[\\\"'](.*?)[\\\"']\", script.read_text(encoding='utf-8', errors='ignore'))
if m: existing = m.group(1)
if existing == CURRENT_VERSION:
print('SCRIPT_UPDATE=SKIPPED')
else:
code = r\'\'\'
SKILL_VERSION = \"v1.0.0\"
import sys, io, os, json, string, argparse, re, subprocess
from datetime import datetime
from pathlib import Path
# ── Apple App Store specs ──────────────────────────────
APPLE_SPECS = {
\"iphone_67\": {\"width\": 1290, \"height\": 2796, \"label\": \"iPhone 6.7 inch\"},
\"iphone_61\": {\"width\": 1179, \"height\": 2556, \"label\": \"iPhone 6.1 inch\"},
\"ipad_129\": {\"width\": 2048, \"height\": 2732, \"label\": \"iPad 12.9 inch\"},
}
# ── Z-Image supported resolutions (closest match) ─────
SUPPORTED_RES = [
\"720x1280 ( 9:16 )\",
\"1152x2048 ( 9:16 )\",
\"1024x1024 ( 1:1 )\",
\"896x1152 ( 7:9 )\",
]
def get_state():
for d in string.ascii_uppercase:
sf = Path(f\"{d}:\\\\\") / f\"{os.environ.get('USERNAME','user').lower()}_openvino\" / \"appstore_screenshots\" / \"state.json\"
if sf.exists():
return json.loads(sf.read_text(encoding='utf-8'))
return None
def get_device():
import openvino as ov
core = ov.Core()
devs = core.available_devices
print(f\"[INFO] Available devices: {devs}\")
for d in devs:
if \"GPU\" in d:
print(f\"[INFO] Using Intel GPU: {d}\")
return d
print(\"[INFO] Using CPU\")
return \"CPU\"
def find_closest_res(target_w, target_h):
target_ratio = target_w / target_h
best = SUPPORTED_RES[0]
best_diff = float('inf')
for res in SUPPORTED_RES:
m = re.search(r\"(\\d+)\\s*[xX]\\s*(\\d+)\", res)
if m:
w, h = int(m.group(1)), int(m.group(2))
diff = abs(w / h - target_ratio)
if diff < best_diff:
best_diff, best = diff, res
return best
def parse_res(res):
m = re.search(r\"(\\d+)\\s*[xX]\\s*(\\d+)\", res)
return (int(m.group(1)), int(m.group(2))) if m else (1024, 1024)
def add_text_overlay(image, title, position=\"top\", font_size=48, color=(255, 255, 255)):
\"\"\"Add text overlay using PIL.\"\"\"
from PIL import ImageDraw, ImageFont
draw = ImageDraw.Draw(image)
try:
font = ImageFont.truetype(\"arial.ttf\", font_size)
except (OSError, IOError):
font = ImageFont.load_default()
bbox = draw.textbbox((0, 0), title, font=font)
tw = bbox[2] - bbox[0]
if position == \"top\":
x, y = (image.width - tw) // 2, 40
elif position == \"center\":
x, y = (image.width - tw) // 2, (image.height - font_size) // 2
else:
x, y = (image.width - tw) // 2, image.height - 80 - font_size
draw.text((x, y), title, fill=color, font=font)
return image
def make_filename(app_name, device_type, style):
date_str = datetime.now().strftime('%Y%m%d_%H%M%S')
safe = re.sub(r'[^\\w]', '_', app_name.strip())[:20].strip('_')
return f\"{date_str}_{safe}_{device_type}_{style}.png\"
def generate(prompt, app_name='', device_type='iphone_67', style='professional',
steps=9, seed=42, title=None, output_path=None):
state = get_state()
if not state:
print(\"[ERROR] state.json not found — run setup.py\")
sys.exit(1)
appstore_dir = Path(state['APPSTORE_DIR'])
model_dir = appstore_dir / 'Z-Image-Turbo-int4-ov'
out_dir = appstore_dir / 'outputs'
out_dir.mkdir(parents=True, exist_ok=True)
required = ['transformer', 'vae_decoder', 'text_encoder']
missing = [r for r in required if not (model_dir / r).exists()]
if missing:
print(f\"[ERROR] Model incomplete: {missing} — run download_model.py\")
sys.exit(1)
# Apple spec resolution
spec = APPLE_SPECS.get(device_type, APPLE_SPECS[\"iphone_67\"])
width, height = spec[\"width\"], spec[\"height\"]
# Find closest supported resolution
res_str = find_closest_res(width, height)
gen_w, gen_h = parse_res(res_str)
device = get_device()
print(f\"[INFO] Loading model: {model_dir}\")
import torch
from optimum.intel import OVZImagePipeline
from diffusers import FlowMatchEulerDiscreteScheduler
pipe = OVZImagePipeline.from_pretrained(str(model_dir), device=device)
pipe.scheduler = FlowMatchEulerDiscreteScheduler(
num_train_timesteps=1000, shift=3.0)
print(\"[INFO] Model loaded\")
gen = torch.Generator('cpu').manual_seed(seed) if seed >= 0 else None
print(f\"[INFO] Inference: {gen_w}x{gen_h} -> {width}x{height}, steps={steps}, seed={seed}\")
print(f\"[INFO] Device: {device_type} ({spec['label']})\")
image = pipe(
prompt=prompt, height=gen_h, width=gen_w,
num_inference_steps=steps, guidance_scale=0.0, generator=gen
).images[0]
# Resize to exact Apple spec
if gen_w != width or gen_h != height:
image = image.resize((width, height))
# Add title overlay if provided
if title:
image = add_text_overlay(image, title, position=\"top\")
if output_path is None:
output_path = str(out_dir / make_filename(app_name, device_type, style))
image.save(output_path)
print(f\"[SUCCESS] {output_path}\")
print(f\"[META] device={device_type}, resolution={width}x{height}, style={style}, seed={seed}, steps={steps}\")
try:
subprocess.Popen(['explorer', output_path])
print(\"[INFO] Opened in default viewer\")
except Exception as e:
print(f\"[WARN] Could not open image: {e}\")
return output_path
if __name__ == \"__main__\":
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='replace', line_buffering=True)
sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8', errors='replace', line_buffering=True)
try:
p = argparse.ArgumentParser()
p.add_argument(\"--prompt\", required=True)
p.add_argument(\"--app_name\", default='app')
p.add_argument(\"--device\", default='iphone_67')
p.add_argument(\"--style\", default='professional')
p.add_argument(\"--title\", default=None)
p.add_argument(\"--steps\", type=int, default=9)
p.add_argument(\"--seed\", type=int, default=42)
p.add_argument(\"--output\", default=None)
args = p.parse_args()
print(generate(args.prompt, args.app_name, args.device, args.style,
args.steps, args.seed, args.title, args.output))
sys.stdout.flush()
except Exception as e:
import traceback
print(f\"[FATAL] {type(e).__name__}: {e}\", flush=True)
traceback.print_exc()
sys.exit(1)
\'\'\'
script.write_text(code.strip(), encoding='utf-8')
print('SCRIPT_UPDATE=DONE')
print(f'EXISTS={script.exists()}')
"
| Output | Action |
|--------|--------|
| SCRIPT_UPDATE=SKIPPED | ✅ Already up to date, proceed to Step 3 |
| SCRIPT_UPDATE=DONE | ✅ Script written, proceed to Step 3 |
| EXISTS=False | ⛔ Write failed — check directory permissions on APPSTORE_DIR |
Step 3: generate App Store screenshot and send preview
🎨 Step 3/3: running inference…
Run these two commands separately:
$env:PYTHONUTF8 = "1"
& "<VENV_PY>" "<APPSTORE_DIR>\generate_appstore.py" --prompt "EXPANDED_PROMPT" --app_name "APP_NAME" --device "DEVICE_TYPE" --style "STYLE" --title "APP_NAME" --steps 9 --seed 42
Pass: stdout contains [SUCCESS]. Record OUTPUT_PATH from the [SUCCESS] line.
Send preview via message tool:
action: "send" filePath: "OUTPUT_PATH" message: "✅ APP_NAME - DEVICE_TYPE App Store Screenshot (STYLE style)"
Final announcement:
✅ Done! Path: <OUTPUT_PATH>
📝 App: {app_name} | Category: {category} | Style: {style}
⚙️ Device: {device_type} ({width}×{height}), steps=9, seed=42 | device: {CPU/GPU}
Apple App Store Specifications
| Device | Resolution | Aspect Ratio | Safe Area (top/bottom/left/right) | |--------|-----------|-------------|-----------------------------------| | iPhone 6.7" | 1290×2796 | 9:19.5 | 180 / 180 / 60 / 60 | | iPhone 6.1" | 1179×2556 | 9:19.5 | 160 / 160 / 50 / 50 | | iPad 12.9" | 2048×2732 | 3:4 | 200 / 200 / 100 / 100 |
Visual Styles
| Style | Colors | Best For | |-------|--------|----------| | minimalist | White, light gray, subtle accent | Productivity, utility, finance | | tech | Dark gradient, blue/purple accents | Technology, developer tools, SaaS | | playful | Vibrant colors, rounded shapes | Entertainment, social, gaming | | professional | Navy, white, gold accents | Business, finance, education |
Parameters
| Param | Default | Notes |
|-------|---------|-------|
| --prompt | required | English or Chinese |
| --app_name | app | App name for filename |
| --device | iphone_67 | iphone_67, iphone_61, ipad_129 |
| --style | professional | minimalist, tech, playful, professional |
| --title | None | Title text overlay on screenshot |
| --steps | 9 | Higher = more detail; no hard limit |
| --seed | 42 | -1 = random |
| --output | auto | Custom absolute output path |
guidance_scaleis fixed at0.0and not exposed as a parameter.
Multi-device batch generation
To generate screenshots for multiple device types at once, run Step 3 multiple times with different --device values:
& "<VENV_PY>" "<APPSTORE_DIR>\generate_appstore.py" --prompt "..." --device iphone_67 --style minimalist
& "<VENV_PY>" "<APPSTORE_DIR>\generate_appstore.py" --prompt "..." --device iphone_61 --style minimalist
& "<VENV_PY>" "<APPSTORE_DIR>\generate_appstore.py" --prompt "..." --device ipad_129 --style minimalist
Troubleshooting
| Error | Cause | Fix |
|-------|-------|-----|
| STATE=MISSING | setup.py never run | Run python setup.py from the skill directory |
| VENV_PY=BROKEN | venv corrupted | Re-run python setup.py — rebuilds venv automatically |
| MODEL_STATUS=MISSING | download never run or interrupted | Run python download_model.py — resumes automatically |
| DEP_CHECK=FAIL (MISSING) | packages not installed in venv | Re-run setup.py |
| DEP_CHECK=FAIL (@commit WRONG) | PyPI release installed instead of pinned commit | Uninstall optimum-intel + diffusers, reinstall with --no-cache-dir |
| @commit shows not installed via git+https | git was missing when pip ran | Confirm git is installed, re-run setup.py |
| [ERROR] Model incomplete | Download interrupted mid-file | Re-run download_model.py — resumes automatically |
| [ERROR] state.json not found | state.json missing | Re-run Step 1 |
| EXISTS=False | No write permission on APPSTORE_DIR | Check directory permissions |
| RuntimeError on GPU | Insufficient VRAM | Lower resolution or hardcode return "CPU" in get_device() |
| Black / noisy output | Too few steps | Use --steps ≥ 4; 9 recommended |
| Download timeout | Network issue or proxy needed | Configure proxy and retry — download supports resume |
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