VLM

To add image analysis to a chat application backend, use a multimodal SDK to process image inputs alongside conversational prompts. This Skill enables backend-driven workflows where the AI interprets and discusses visual content directly within user chat interactions.

Yes, you can use base64 image strings for multimodal vision chat. The Skill accepts both image URLs and base64-encoded image inputs, allowing flexible integration when passing visual data through backend prompts without requiring public image links.

Visual question answering in AI backend workflows is a multimodal capability where the model analyzes an image and responds to specific questions about its content. This enables descriptive, diagnostic, or comparative analysis of visual content directly within application chat interactions.

Yes, you need the z-ai-web-dev-sdk installed on your backend to process image inputs in chat. This dependency provides the underlying multimodal SDK capabilities required to handle image understanding and visual-question-answer interactions for your application.

Common use cases for multimodal image analysis include generating image descriptions, enabling visual question answering, enhancing accessibility features, and building image-enabled assistants for product or service applications that require conversational visual insights.

You can test image description and visual QA features using the optional testing scripts included with the Skill. These scripts allow developers to validate the multimodal backend processing of image URLs and base64 inputs before full application deployment.