VLM

To analyze images and generate textual descriptions, you can use multimodal interactions by providing an image URL or base64 encoding along with a text prompt to extract visual information. The system processes the input and returns a descriptive text response.

Yes, you can use base64 encoded images for vision chat interactions. The system supports both base64 encoding and image URLs as input formats, allowing you to integrate visual content directly into conversational AI prompts.

Yes, you need the z-ai-web-dev-sdk dependency installed in your environment to process image analysis requests. This backend SDK handles the core processing logic required to evaluate images and generate conversational AI responses.

The best way to compare two images and identify differences is to submit both images through multimodal interactions using their URLs or base64 data. The vision chat system will analyze the visual content and describe the distinctions based on your text prompt.

Multimodal interaction handles image URLs and text prompts by sending both data types to the backend processing system. The AI evaluates the visual content from the URL alongside the natural language query to generate a contextual text-based answer.