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Implement speech-to-text (ASR/automatic speech recognition) capabilities using the…
Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task
$ npx -y skills add jjyaoao/helloagents --skill video-generation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/video-generationContext preview
The summary Claude sees to decide when to auto-load this skill.
Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task
name: Video Generation description: Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task management with status polling and result retrieval. license: MIT
This skill guides the implementation of video generation functionality using the z-ai-web-dev-sdk package, enabling AI models to create videos from text descriptions or images through asynchronous task processing.
**Skill Location**: `{project_path}/skills/video-generation`
This skill is located at the above path in your project.
**Reference Scripts**: Example test scripts are available in the `{Skill Location}/scripts/` directory for quick testing and reference. See `{Skill Location}/scripts/video.ts` for a working example.
Video Generation allows you to build applications that can create video content from text prompts or images, with customizable parameters like resolution, frame rate, duration, and quality settings. The API uses an asynchronous task model where you create a task and poll for results.
**IMPORTANT**: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.
The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.
For simple video generation tasks, you can use the z-ai CLI instead of writing code. The CLI handles task creation and polling automatically, making it ideal for quick tests and simple automation.
# Generate video with automatic polling z-ai video --prompt "A cat playing with a ball" --poll # Using short options z-ai video -p "Beautiful landscape with mountains" --poll
# Quality mode (speed or quality) z-ai video -p "Ocean waves at sunset" --quality quality --poll # Custom resolution and FPS z-ai video \ -p "City timelapse" \ --size "1920x1080" \ --fps 60 \ --poll # Custom duration (5 or 10 seconds) z-ai video -p "Fireworks display" --duration 10 --poll
**IMPORTANT**: For `image_url` parameter, it is **strongly recommended to use base64-encoded image data** instead of URLs. This approach is more reliable and avoids potential network issues or access restrictions.
**Note**: Match the MIME type in the data URI to your actual image format (image/jpeg, image/png, image/webp, etc.) to avoid decoding issues.
# Generate video from single image using base64 (RECOMMENDED)
# Convert your image to base64 with correct MIME type
# For PNG images
IMAGE_BASE64=$(base64 -i image.png)
z-ai video \
--image-url "data:image/png;base64,${IMAGE_BASE64}" \
--prompt "Make the scene come alive" \
--poll
# For JPEG images
IMAGE_BASE64=$(base64 -i photo.jpg)
z-ai video \
--image-url "data:image/jpeg;base64,${IMAGE_BASE64}" \
--prompt "Make the scene come alive" \
--poll
# For WebP images
IMAGE_BASE64=$(base64 -i image.webp)
z-ai video \
--image-url "data:image/webp;base64,${IMAGE_BASE64}" \
--prompt "Make the scene come alive" \
--poll
# Using URL (less recommended, may have reliability issues)
z-ai video \
-i "https://example.com/photo.jpg" \
-p "Add motion to this scene" \
--poll**IMPORTANT**: For best reliability, use base64-encoded images instead of URLs. Ensure the MIME type matches your actual image format.
# Generate video between two frames using base64 (RECOMMENDED)
# Make sure to use the correct MIME type for each image
# Example with PNG images
START_BASE64=$(base64 -i start.png)
END_BASE64=$(base64 -i end.png)
z-ai video \
--image-url "data:image/png;base64,${START_BASE64},data:image/png;base64,${END_BASE64}" \
--prompt "Smooth transition between frames" \
--poll
# Example with JPEG images
START_BASE64=$(base64 -i start.jpg)
END_BASE64=$(base64 -i end.jpg)
z-ai video \
--image-url "data:image/jpeg;base64,${START_BASE64},data:image/jpeg;base64,${END_BASE64}" \
--prompt "Smooth transition between frames" \
--poll
# Using URLs (less recommended)
z-ai video \
--image-url "https://example.com/start.png,https://example.com/end.png" \
--prompt "Smooth transition between frames" \
--poll# Generate video with AI-generated audio effects z-ai video \ -p "Thunder storm approaching" \ --with-audio \ --poll
# Save task result to JSON file z-ai video \ -p "Sunrise over mountains" \ --poll \ -o video_result.json
# Customize polling behavior z-ai video \ -p "Dancing robot" \ --poll \ --poll-interval 10 \ --max-polls 30 # Create task without polling (get task ID) z-ai video -p "Abstract art animation" -o task.json
🤖 生产级多智能体框架 - 工具响应协议、上下文工程、会话持久化、子代理机制等16项核心能力 HelloAgents 是一个基于 OpenAI 原生 API 构建的生产级多智能体框架,集成了工具响应协议(ToolResponse)、上下文工程(HistoryManager/TokenCounter)、会话持久化(SessionStore)、子代理机制(TaskTool)、乐观锁(文件编辑)、熔断器(CircuitBreaker)、Skills 知识外化、TodoWrite 进度管理、DevLog
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