Generates descriptive and analytical responses from image URLs or base64 inputs via createVision API.
npx skills add https://github.com/favouritehu/call_tracking --skill vlm-favouritehu
Please help me install this Agent Skill. Skill: VLM Source: https://github.com/favouritehu/call_tracking/tree/main/skills/VLM Command: npx skills add https://github.com/favouritehu/call_tracking --skill vlm-favouritehu
Vision-based analysis and conversational responses for images, enabling automatic description and insight generation in backend applications.
Install the z-ai-web-dev-sdk, create a Vision Chat backend using createVision, and test with an image URL and a prompt such as "Describe this image." Use the sample scripts in skills/VLM/scripts as reference.
High-intent search queries and answers about installing and using this skill.
To generate descriptive text from an image URL in a backend service, use the z-ai-web-dev-sdk createVision API to process the URL and send text prompts for conversational image analysis.
Yes, you can use base64-encoded images for vision chat analysis by passing the base64 string directly into the multimodal chat interface alongside your text prompt.
Multimodal image analysis supports multi-turn conversations, allowing you to combine text prompts with image inputs for rich, contextual follow-up questions about the visual content.
To set up a backend vision chat, install the z-ai-web-dev-sdk, implement the createVision API, and reference the sample scripts provided in the scripts directory for integration guidance.
Common use cases for AI image description include building applications that automatically describe product photos, summarize complex diagrams, or perform question answering on image content.
Multimodal vision chat requires backend deployment to securely run the z-ai-web-dev-sdk and process image URLs or base64 inputs without exposing API keys to the frontend.
ashishkushwaha-mpuAnalyze single or multiple images with conversational vision chat using the z-ai-web-dev-sdk.
synaptiaiParse API, webhook, file, and sensor data into validated structured payloads.
Tommy-ywCombine CLIP vision encoder with Vicuna/LLaMA language models for image-based conversations.
nidhalboumaiza-0Generate base64-encoded images from text prompts via z-ai-web-dev-sdk.
