A single function Jev-like wrapper for LLMs, including vision models

The author was inspired by Jev, OpenJev, and SemIf to explore reading an LLM's token probabilities. The provided code snippet demonstrates a system that continuously previews webcam frames, processes them one at a time using a ThreadPoolExecutor, and sends them as base64-encoded JPEG images to a scoring function. This setup is designed for real-time evaluation, including image encoding, and handles webcam input and display, with error handling for frame reading and encoding.

This report details a single-function wrapper for LLMs, including vision models, unlike other projects that focus on self-hostable Jev-like systems.