Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Generate images from text prompts or transform existing images using AI with configurable count, watermark, and API key settings.
Generate images from text prompts or transform existing images using AI with configurable count, watermark, and API key settings.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
🔥 火山引擎 AI 生图 Skill。支持多种模型。
export HUOBAO_API_KEY="<your-api-key>" 或使用 --api-key 参数传入。
模型说明gemini-2.5-flash-imageGemini 2.5 Flash Imagegemini-2.5-flash-image-previewGemini 2.5 Flash Image Previewnano-bananaNano Banananano-banana-proNano Banana Pronano-banana-pro_4kNano Banana Pro 4Kdoubao-seedream-4-5-251128豆包 Seedream 4.5
尺寸说明1x1正方形16x9宽屏9x16竖屏3x4竖屏4x3宽屏
python3 scripts/t2i.py "提示词" --model nano-banana-pro --size 1x1
python3 scripts/i2i.py --image <图片URL> --prompt "描述" --model nano-banana-pro
参数说明prompt提示词(必填)--model模型名称(默认: nano-banana-pro)--size尺寸(默认: 1x1)--count生成数量 1-4 (默认: 1)--watermark是否添加水印 (默认: true)--api-keyAPI Key(必填)--debug调试模式
# 文生图 - Nano Banana Pro python3 scripts/t2i.py "一只可爱的猫咪" --model nano-banana-pro --size 1x1 --api-key "sk-xxx" # 文生图 - Gemini 2.5 Flash python3 scripts/t2i.py "风景画" --model gemini-2.5-flash-image --size 16x9 --api-key "sk-xxx" # 图生图 python3 scripts/i2i.py --image "https://example.com/img.jpg" --prompt "动漫风格" --model nano-banana-pro --api-key "sk-xxx"
成功返回 JSON: { "success": true, "prompt": "...", "model": "nano-banana-pro", "size": "1x1", "count": 1, "images": [{"url": "..."}], "usage": {...} }
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