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DLazy Tongyi Wanxiang 2.7 Video Generation icon

DLazy Tongyi Wanxiang 2.7 Video Generation

Design & Media Updated 2026.08.30

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About this skill

Problem

When agents call video models, the friction is often operational rather than model-related: authentication, uploading local media, polling async jobs, and handling balance or permission errors. wan2.7 wraps Tongyi Wanxiang 2.7 video generation as a dlazy wan2.7 call, covering text-to-video, first/last-frame-to-video, and reference-to-video tasks.

How It Works And Boundaries

The skill is a thin client over dLazy's hosted API. On execution, prompts and parameters are sent to api.dlazy.com; local image, video, or audio paths are uploaded to files.dlazy.com so the model can read them; generated output is usually a URL hosted on files.dlazy.com. Authentication uses a dLazy API key, configured through the CLI or supplied via DLAZY_API_KEY, and the key can be rotated or revoked in the dashboard.

  • Synchronous calls wait for the result;
  • Async calls with --no-wait return task.generateId and status, requiring status polling;
  • Error handling must distinguish unauthorized, insufficient_balance, missing parameters, missing local files, and safety-policy rejections.

It fits engineers who already manage dLazy organization keys and credits, not fully local inference, private deployment, or scenarios that must avoid uploading media.

Use Cases

  • Generate short product clips from copy inside an agent workflow using Tongyi Wanxiang 2.7.
  • Upload local first and last frame images to the dLazy API to produce a fixed-start preview video.
  • Create showcase shots for an ecommerce product page by driving video generation from a reference image.
  • Poll an async generateId returned by --no-wait and check balance or permission errors.

Best For

  • Backend engineers calling video APIs in CI or agents, who want unified auth, media upload, and async status handling.
  • Creative product engineers turning reference images into showcase videos, who want to validate the generation flow via CLI.
  • Platform engineers managing dLazy organization keys and credits, who need to distinguish balance, permission, and safety-policy errors.
  • Application engineers building multimodal agents, who want to upload local first/last frames and poll generation results.