google-veo by inferen-sh/skills
npx skills add https://github.com/inferen-sh/skills --skill google-veo通过 inference.sh CLI 使用 Google Veo 模型生成视频。
需要 inference.sh CLI (
infsh)。安装说明
infsh login
infsh app run google/veo-3-1-fast --input '{"prompt": "drone shot over a mountain lake"}'
| 模型 | 应用 ID | 速度 | 质量 |
|---|---|---|---|
| Veo 3.1 | google/veo-3-1 | 较慢 |
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| 最佳 |
| Veo 3.1 Fast | google/veo-3-1-fast | 快速 | 优秀 |
| Veo 3 | google/veo-3 | 中等 | 优秀 |
| Veo 3 Fast | google/veo-3-fast | 快速 | 非常好 |
| Veo 2 | google/veo-2 | 中等 | 良好 |
infsh app list --search "veo"
infsh app run google/veo-3-1-fast --input '{
"prompt": "Cinematic drone shot flying through a misty forest at sunrise, volumetric lighting"
}'
infsh app run google/veo-3 --input '{
"prompt": "Sleek smartphone rotating on a dark reflective surface, studio lighting"
}'
infsh app run google/veo-3-1-fast --input '{
"prompt": "Timelapse of clouds moving over a mountain range, golden hour"
}'
infsh app run google/veo-3 --input '{
"prompt": "Slow motion water droplet splashing into a pool, macro shot"
}'
infsh app run google/veo-3-1-fast --input '{
"prompt": "Busy city street at night with neon signs and rain reflections, Tokyo style"
}'
摄像机运动 : drone shot, tracking shot, pan, zoom, dolly, steadicam
灯光 : golden hour, blue hour, studio lighting, volumetric, neon, natural
风格 : cinematic, documentary, commercial, artistic, realistic
时间 : slow motion, timelapse, real-time
# 1. 生成示例输入以查看所有选项
infsh app sample google/veo-3-1-fast --save input.json
# 2. 编辑提示词
# 3. 运行
infsh app run google/veo-3-1-fast --input input.json
# 完整平台技能（所有 150+ 应用）
npx skills add inference-sh/skills@infsh-cli
# 所有视频生成模型
npx skills add inference-sh/skills@ai-video-generation
# AI 虚拟形象与唇形同步
npx skills add inference-sh/skills@ai-avatar-video
# 图像生成（用于图像转视频）
npx skills add inference-sh/skills@ai-image-generation
浏览所有视频应用：infsh app list --category video
每周安装量
7.0K
代码仓库
GitHub 星标数
184
首次出现
13 天前
安全审计
安装于
claude-code5.6K
gemini-cli5.0K
codex5.0K
opencode5.0K
amp5.0K
github-copilot5.0K
Generate videos with Google Veo models via inference.sh CLI.
Requires inference.sh CLI (
infsh). Install instructions
infsh login
infsh app run google/veo-3-1-fast --input '{"prompt": "drone shot over a mountain lake"}'
| Model | App ID | Speed | Quality |
|---|---|---|---|
| Veo 3.1 | google/veo-3-1 | Slower | Best |
| Veo 3.1 Fast | google/veo-3-1-fast | Fast | Excellent |
| Veo 3 | google/veo-3 | Medium | Excellent |
| Veo 3 Fast | google/veo-3-fast | Fast | Very Good |
| Veo 2 | google/veo-2 | Medium | Good |
infsh app list --search "veo"
infsh app run google/veo-3-1-fast --input '{
"prompt": "Cinematic drone shot flying through a misty forest at sunrise, volumetric lighting"
}'
infsh app run google/veo-3 --input '{
"prompt": "Sleek smartphone rotating on a dark reflective surface, studio lighting"
}'
infsh app run google/veo-3-1-fast --input '{
"prompt": "Timelapse of clouds moving over a mountain range, golden hour"
}'
infsh app run google/veo-3 --input '{
"prompt": "Slow motion water droplet splashing into a pool, macro shot"
}'
infsh app run google/veo-3-1-fast --input '{
"prompt": "Busy city street at night with neon signs and rain reflections, Tokyo style"
}'
Camera movements : drone shot, tracking shot, pan, zoom, dolly, steadicam
Lighting : golden hour, blue hour, studio lighting, volumetric, neon, natural
Style : cinematic, documentary, commercial, artistic, realistic
Timing : slow motion, timelapse, real-time
# 1. Generate sample input to see all options
infsh app sample google/veo-3-1-fast --save input.json
# 2. Edit the prompt
# 3. Run
infsh app run google/veo-3-1-fast --input input.json
# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@infsh-cli
# All video generation models
npx skills add inference-sh/skills@ai-video-generation
# AI avatars & lipsync
npx skills add inference-sh/skills@ai-avatar-video
# Image generation (for image-to-video)
npx skills add inference-sh/skills@ai-image-generation
Browse all video apps: infsh app list --category video
Weekly Installs
7.0K
Repository
GitHub Stars
184
First Seen
13 days ago
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Installed on
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amp5.0K
github-copilot5.0K
99,500 周安装