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Grok Imagine Image Pro

Generates and edits high-quality PNG images via xAI Grok/Flux API using prompts, styles, aspect ratios, and batch processing with base64 output.

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版本1.0.2
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技能说明


name: grok-imagine-image-pro description: Generiert hochwertige Bilder mit xAI Grok/Flux API. Use when user asks for image generation ("mach a Bild von...", "generier PNG...", "Bild erstellen") or image editing ("ändere das Bild", "mach daraus..."). Handles Prompts, styles, aspect ratios, edits, batch generation. Outputs PNG via base64 or file. metadata: openclaw: requires: env: - XAI_API_KEY bins: - curl - python3

Grok Imagine Image Pro

API Key: $XAI_API_KEY (already configured) Save dir: ~/.openclaw/media/ (resolves to /data/.openclaw/media/ — allowed for Telegram sending)

Available Models

  • grok-imagine-image — standard quality, faster
  • grok-imagine-image-pro — higher quality (default for generation)

1. Image Generation

curl -s https://api.x.ai/v1/images/generations \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -H "Content-Type: application/json" \
  --data '{
    "model": "grok-imagine-image-pro",
    "prompt": "<PROMPT>",
    "n": 1,
    "response_format": "b64_json"
  }' | python3 -c "
import json, sys, base64, os, time
os.makedirs(os.path.expanduser('~/.openclaw/media'), exist_ok=True)
r = json.load(sys.stdin)
ts = int(time.time())
for i, img in enumerate(r['data']):
    img_data = base64.b64decode(img['b64_json'])
    fpath = os.path.expanduser(f'~/.openclaw/media/generated_{ts}_{i}.png')
    with open(fpath, 'wb') as f:
        f.write(img_data)
    print(fpath)
"

Aspect Ratios

Add "aspect_ratio": "<ratio>" to the JSON body. Supported values:

RatioUse case
1:1Social media, thumbnails
16:9 / 9:16Widescreen, mobile stories
4:3 / 3:4Presentations, portraits
3:2 / 2:3Photography
2:1 / 1:2Banners, headers
autoModel picks best ratio (default)

Batch Generation

Set "n": <count> (1-10) to generate multiple images in one request.

2. Image Editing / Style Transfer

Edit an existing image by providing a source image plus an edit prompt. Uses the same /v1/images/generations endpoint with an added image_url field.

Do NOT use /v1/images/edits with multipart — xAI requires JSON.

IMPORTANT: For local files, use Python to build the payload JSON file, then curl with @file. Inline base64 in curl args causes "Argument list too long" for images >~100KB.

NOTE: This is NOT true image editing — the API generates a new image inspired by the source. It cannot make pixel-precise edits (e.g. changing only a car's color while keeping everything else identical).

Edit from local file (recommended approach):

python3 -c "
import json, base64
with open('<SOURCE_PATH>', 'rb') as f:
    b64 = base64.b64encode(f.read()).decode()
payload = {
    'model': 'grok-imagine-image',
    'prompt': '<EDIT_PROMPT>',
    'image_url': f'data:image/png;base64,{b64}',
    'n': 1,
    'response_format': 'b64_json'
}
with open('/tmp/img_edit_payload.json', 'w') as f:
    json.dump(payload, f)
print('Payload ready')
" && \
curl -s https://api.x.ai/v1/images/generations \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/img_edit_payload.json | python3 -c "
import json, sys, base64, os, time
os.makedirs(os.path.expanduser('~/.openclaw/media'), exist_ok=True)
r = json.load(sys.stdin)
img_data = base64.b64decode(r['data'][0]['b64_json'])
fpath = os.path.expanduser(f'~/.openclaw/media/edited_{int(time.time())}.png')
with open(fpath, 'wb') as f:
    f.write(img_data)
print(fpath)
"

Edit from URL:

curl -s https://api.x.ai/v1/images/generations \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -H "Content-Type: application/json" \
  --data '{
    "model": "grok-imagine-image",
    "prompt": "<EDIT_PROMPT>",
    "image_url": "<PUBLIC_IMAGE_URL>",
    "n": 1,
    "response_format": "b64_json"
  }' | python3 -c "
import json, sys, base64, os, time
os.makedirs(os.path.expanduser('~/.openclaw/media'), exist_ok=True)
r = json.load(sys.stdin)
img_data = base64.b64decode(r['data'][0]['b64_json'])
fpath = os.path.expanduser(f'~/.openclaw/media/edited_{int(time.time())}.png')
with open(fpath, 'wb') as f:
    f.write(img_data)
print(fpath)
"

Style Transfer Examples

Use editing with a style prompt, e.g.:

  • "Render this as an oil painting in impressionist style"
  • "Make this a pencil sketch with detailed shading"
  • "Convert to pop art with bold colors"
  • "Watercolor painting with soft edges"

3. Sending to Telegram

message tool: action=send, channel=telegram, target=<id>,
  message="<caption>", filePath=~/.openclaw/media/<file>.png
  • Always include message field (required even for media-only sends)
  • Allowed media paths: /tmp/, ~/.openclaw/media/, ~/.openclaw/agents/

Notes

  • Do NOT pass size parameter — returns 400
  • Aspect ratio: pass aspect_ratio in JSON body (not size)
  • Editing: use image_url field in the generations endpoint (NOT the edits endpoint with multipart)
  • Always use "response_format": "b64_json" — URL format returns temporary URLs that often 403
  • For large images: build payload with Python → save to /tmp/ → curl with @file syntax
  • Max 10 images per request
  • Images are subject to content moderation
  • Editing is style-transfer/reimagination, NOT pixel-precise inpainting

如何使用「Grok Imagine Image Pro」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Grok Imagine Image Pro」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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