Analyze images via the z-ai-web-dev-sdk for vision-assisted chat.
npx skills add https://github.com/Lucmac667/Be-Ballenced-Dashboard --skill vlm-lucmac667
Please help me install this Agent Skill. Skill: VLM Source: https://github.com/Lucmac667/Be-Ballenced-Dashboard/tree/main/Be-Ballenced-Dashboard/skills/VLM Command: npx skills add https://github.com/Lucmac667/Be-Ballenced-Dashboard --skill vlm-lucmac667
This Skill enables developers to build applications that understand and discuss visual content by combining image analysis with natural language conversation, streamlining workflows that require image-based reasoning.
Quick Start: Run the vlm.ts script in scripts/ to test vision chat with an example image URL and prompt.
High-intent search queries and answers about installing and using this skill.
To analyze images in a chat backend, you can use this Skill's vlm.ts script with the z-ai-web-dev-sdk to process image URLs or base64 strings. It enables vision-assisted chat by passing visual content directly in conversational prompts for backend image analysis.
Yes, the z-ai-web-dev-sdk supports multimodal workflows by accepting both image URLs and base64-encoded images. This allows you to integrate base64 visual content directly into your backend vision-assisted chat applications.
The best way to add vision-based chat is by integrating the SDK calls provided or running the included vlm.ts script. This connects your application to the z-ai-web-dev-sdk, enabling it to describe images and answer questions about visual content.
Yes, you can run image analysis from the CLI by executing the vlm.ts script in the scripts directory. It provides a quick-start path to test vision chat with an example image URL and prompt without needing a full frontend setup.
You can describe and identify objects using the z-ai-web-dev-sdk integrated through this Skill. It processes image URLs or base64 data to perform object and scene analysis, returning natural language descriptions of the visual content.
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