add-image-vision

Image vision for multimodal agents works by downloading WhatsApp image attachments, resizing them with sharp, and encoding them into base64. These base64 images are then passed as content blocks to the agent for visual reasoning.

Processing WhatsApp image attachments for AI agents involves fetching the files, resizing them with sharp, and base64 encoding the results. This workflow delivers optimized visual content blocks to the agent for interpretation.

Base64 encoding is needed for multimodal agents because it converts binary image attachments into a text format that agents can process. This allows visual content blocks to be passed directly into the agent's reasoning pipeline.

Yes, sharp is used for image resizing in a WhatsApp agent workflow. It fetches, resizes, and stores image attachments in the group workspace before passing them to the agent for visual interpretation.

NanoClaw supports multimodal content blocks from WhatsApp images by downloading and processing the attachments. It encodes the images as base64, allowing agents to reason about shared photos to inform group decisions.