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Tencent SkillHub · AI

Jimeng AI

基于火山引擎即梦AI的文生图/文生视频能力，支持通过文本描述生成图片和视频。

skill openclawclawhub Free
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High Signal

基于火山引擎即梦AI的文生图/文生视频能力，支持通过文本描述生成图片和视频。

⬇ 0 downloads ★ 0 stars Unverified but indexed

Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
README.md, README_CN.md, SKILL.md, package-lock.json, package.json, scripts/common.ts

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

Open Send to Agent page Open JSON manifest Open Markdown brief

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.3.3

Documentation

ClawHub primary doc Primary doc: SKILL.md 26 sections Open source page

即梦AI 文生图/文生视频 Skill

基于火山引擎即梦AI的文生图和文生视频能力，支持通过文本描述生成图片和视频。

功能特性

执行过程存储：使用 MD5(提示词) 作为文件夹名保存任务状态 异步查询：支持断点续传，避免重复提交相同任务 Base64 图片处理：直接从 API 响应中解码并保存图片 支持即梦AI文生图（v3.0 / v3.1 / v4.0） 支持即梦AI文生视频（v3.0 1080P） 可配置宽高比、生成数量、自定义尺寸

所需环境变量

变量名是否必需说明VOLCENGINE_AK必需火山引擎 Access KeyVOLCENGINE_SK条件必需火山引擎 Secret Key（永久凭证必需）VOLCENGINE_TOKEN可选安全令牌（临时凭证 STS 必需） 注意：使用临时凭证（AKTP 开头）时，可以只使用 AK + Token，不需要 SK。

配置示例

export VOLCENGINE_AK="your-access-key" export VOLCENGINE_SK="your-secret-key" # 如果使用临时凭证(STS)，还需要设置 Token export VOLCENGINE_TOKEN="your-security-token" 获取方式： 登录 火山引擎控制台 进入"访问控制" -> "密钥管理" 创建或查看已有访问密钥

安装依赖

cd ~/.openclaw/workspace/skills/jimeng-ai npm install

首次执行（新任务）

使用新提示词运行时，脚本将： 向 API 提交任务 使用 md5(提示词) 作为文件夹名创建目录 保存 param.json、response.json 和 taskId.txt 输出："任务已提交，TaskId: xxx" $ npx ts-node scripts/text2image.ts "一只可爱的猫咪" 任务已提交，TaskId: 1234567890

后续执行（异步查询）

使用相同提示词运行将查询已有任务： 如果图片已存在 → 立即返回图片路径 如果任务未完成 → 输出："任务未完成，TaskId: xxx" 如果任务已完成 → 从 binary_data_base64 解码并保存图片 $ npx ts-node scripts/text2image.ts "一只可爱的猫咪" 任务未完成，TaskId: 1234567890 # 或者任务完成时： $ npx ts-node scripts/text2image.ts "一只可爱的猫咪" 任务已完成，图片保存路径： - ./output/<md5_hash>/1.jpg - ./output/<md5_hash>/2.jpg

基础用法

npx ts-node scripts/text2image.ts "一只可爱的猫咪"

完整参数

npx ts-node scripts/text2image.ts "提示词" \ --version v40 \ --ratio 16:9 \ --count 2

参数说明

参数说明默认值prompt图片生成提示词（必填）---versionAPI版本: v30, v31, v40v31--ratio宽高比: 1:1, 9:16, 16:9, 3:4, 4:3, 2:3, 3:2, 1:2, 2:116:9--count生成数量 1-41--width指定宽度（可选）---height指定高度（可选）---size指定面积（可选，如 4194304 表示 2048x2048）---seed随机种子（可选）---output图片输出目录./output--debug调试模式false--no-download不下载图片，只返回URLfalse

任务已提交（首次运行）

{ "success": true, "submitted": true, "prompt": "一只可爱的猫咪", "version": "v40", "ratio": "1:1", "count": 1, "taskId": "1234567890", "folder": "./output/<md5_hash>", "message": "任务已提交，请稍后使用相同提示词查询结果" }

任务已完成

{ "success": true, "prompt": "一只可爱的猫咪", "version": "v40", "ratio": "1:1", "count": 1, "taskId": "1234567890", "images": [ "./output/<md5_hash>/1.jpg", "./output/<md5_hash>/2.jpg" ], "outputDir": "./output/<md5_hash>" }

任务未完成

{ "success": true, "prompt": "一只可爱的猫咪", "version": "v40", "ratio": "1:1", "count": 1, "taskId": "1234567890", "folder": "./output/<md5_hash>", "message": "任务未完成，请稍后使用相同提示词查询结果" }

错误响应

{ "success": false, "error": { "code": "MISSING_CREDENTIALS", "message": "请设置环境变量 VOLCENGINE_AK 和 VOLCENGINE_SK" } }

文件夹结构

output/ └── <md5(prompt)>/ # md5哈希作为文件夹名 ├── param.json # 请求参数 ├── response.json # API提交响应 ├── taskId.txt # 任务ID └── 1.jpg, 2.jpg, ... # 生成的图片

生成风景画

npx ts-node scripts/text2image.ts "山水风景画，水墨风格" --version v40 --ratio 16:9

生成科幻城市

npx ts-node scripts/text2image.ts "未来科幻城市，霓虹灯光，赛博朋克风格" --version v40 --ratio 16:9 --count 2

指定尺寸生成

npx ts-node scripts/text2image.ts "抽象艺术" --width 2048 --height 1152

自定义输出目录

npx ts-node scripts/text2image.ts "一只可爱的猫咪" --output ~/Pictures/jimeng

版本说明

v30: 即梦3.0 基础版本 v31: 即梦3.1 改进版本 v40: 即梦4.0 最新版本（推荐）

基础用法

npx ts-node scripts/text2video.ts "一只可爱的猫咪在草地上奔跑"

完整参数

npx ts-node scripts/text2video.ts "提示词" \ --ratio 9:16 \ --duration 5 \ --fps 24

参数说明

参数说明默认值prompt视频生成提示词（必填）---ratio宽高比: 16:9, 4:3, 1:1, 3:4, 9:16, 21:99:16--duration视频时长: 5 或 10 秒5--fps帧率: 24 或 3024--output视频输出目录./output--wait等待任务完成false--debug调试模式false--no-download不下载视频，只返回URLfalse

视频输出格式

任务已提交 { "success": true, "submitted": true, "prompt": "元宵节灯笼", "ratio": "9:16", "duration": 5, "fps": 24, "taskId": "1234567890", "folder": "./output/video/<md5_hash>", "message": "任务已提交，请稍后使用相同提示词查询结果" } 任务已完成 { "success": true, "prompt": "元宵节灯笼", "ratio": "9:16", "duration": 5, "fps": 24, "taskId": "1234567890", "videoUrl": "https://...", "data": {} } 任务未完成 { "success": true, "pending": true, "prompt": "元宵节灯笼", "ratio": "9:16", "duration": 5, "fps": 24, "taskId": "1234567890", "status": "in_queue", "message": "任务处理中，请稍后使用相同提示词查询结果" }

视频文件夹结构

output/video/ └── <md5(prompt)>/ # md5哈希作为文件夹名 ├── param.json # 请求参数 ├── response.json # API提交响应 ├── taskId.txt # 任务ID └── video.mp4 # 生成的视频

参考文档

火山引擎即梦AI文生图文档 火山引擎即梦AI文生视频文档

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Docs2 Config1 Scripts
  • SKILL.md Primary doc
  • README_CN.md Docs
  • README.md Docs
  • scripts/common.ts Scripts
  • package-lock.json Config
  • package.json Config

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