VLM

Implement vision-based AI chat with image URLs and base64 images.

1|Updated Feb 14, 2026
One-click install
npx skills add https://github.com/digresik-tech/olt-monitoring-mini --skill vlm-digresik-tech
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: VLM
Source: https://github.com/digresik-tech/olt-monitoring-mini/tree/main/skills/VLM
Command: npx skills add https://github.com/digresik-tech/olt-monitoring-mini --skill vlm-digresik-tech

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z-ai-web-dev-sdk, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables AI models to understand and respond to images combined with text prompts, allowing for visual content analysis and conversational AI applications.

Core Features & Use Cases

  • Image Analysis: Describe, classify, and extract information from images.
  • Multimodal Chat: Engage in conversations that include visual context.
  • Use Case: Upload a photo of a product and ask the AI to describe its features, suggest similar items, or provide usage instructions.

Quick Start

Use the VLM skill to describe the image located at https://cdn.bigmodel.cn/static/logo/register.png.

Frequently Asked Questions about VLM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze images with AI chat to extract visual content?

To analyze images with AI chat, use multimodal vision models to process image URLs or base64 encoded images combined with text prompts, generating conversational descriptions and extracting visual information.

Does the z-ai-web-dev-sdk support multimodal image analysis and base64 inputs?

Yes, the z-ai-web-dev-sdk supports multimodal image analysis by accepting both image URLs and base64 encoded images for natural language processing and visual content understanding.

What is the best way to combine computer vision with natural language processing?

Combining computer vision with natural language processing involves using multimodal AI chat capabilities to pass image URLs alongside text prompts, allowing models to describe, classify, and extract information visually.

How do I implement vision-based AI chat for image understanding?

Implement vision-based AI chat by integrating the z-ai-web-dev-sdk to handle multimodal interactions, passing visual inputs like base64 images to enable conversational image analysis and feature extraction.

Are there limitations when using AI chat for image analysis with base64 encoded images?

Limitations of using AI chat for image analysis include dependency on the z-ai-web-dev-sdk for multimodal processing and potential constraints with base64 encoded image sizes or unsupported visual contexts.