Chenyu Aigc

Data & APIs

Generate AI videos and images via Chenyu Studio AIGC API. Supports text-to-video, image-to-video, video extension, style transfer, and AI image generation. Trigger when: generate video, create AI video, text to video, image to video, AI image generation, video generation, 生成视频, AI视频, 文生视频, 图生视频, 生成图片.

Install

openclaw skills install chenyu-aigc

Chenyu AIGC - AI Video & Image Generation

Generate videos and images using AI models through the Chenyu Studio AIGC orchestration API.

When to Use

  • User wants to generate a video from text prompt
  • User wants to generate a video from an image (first/last frame)
  • User wants to extend or remix a video
  • User wants to generate AI images
  • User wants to check status of a generation task
  • User wants to list available AI models

When NOT to Use

  • User wants to analyze or understand existing videos (use video-analysis skill)
  • User wants to download videos from social platforms (use video-fetch skill)
  • User wants to manage digital humans or clone voices (use chenyu-core skill)

Authentication

Authorization: Bearer $CHENYU_API_KEY

Base URL: $CHENYU_BASE_URL (default: https://chenyu.pro)

Workflow

  1. Discover recipes — list available AI models (see below)
  2. Get recipe schema — check what inputs/parameters the recipe accepts
  3. Execute — submit a generation task → see execute-recipe.md
  4. Poll & manage — track status, get output, cancel → see manage-tasks.md

Step 1: List Available Recipes

curl -s "$CHENYU_BASE_URL/api/v1/aigc/recipes" \
  -H "Authorization: Bearer $CHENYU_API_KEY" | jq '.data[] | {recipe_id, name, slug, description, output_type}'

Each recipe represents an AI model capability. Key response fields:

  • recipe_id — use this ID when executing
  • slug — human-readable identifier (e.g. volcengine-seedance-v1-pro)
  • output_type — what it produces: video, image, audio

Step 2: Get Recipe Schema

curl -s "$CHENYU_BASE_URL/api/v1/aigc/recipes/{recipe_id}/schema" \
  -H "Authorization: Bearer $CHENYU_API_KEY" | jq '.data'

The schema tells you:

  • typed_inputs_schema.definitions — accepted input types and their fields
  • parameters_schema — available parameters with constraints (min/max/enum)
  • credit_cost / credit_cost_rules — how many credits it costs

After getting the schema, read execute-recipe.md for execution details.