awesome-chatgpt-code-interpreter-experiments

Why we included this project

This is a hands-on collection of experiments and workarounds for OpenAI's ChatGPT Code Interpreter, assembled by a computer-vision practitioner who clearly enjoys pushing the sandbox to its limits. Rather than just listing prompts, it documents concrete, reproducible recipes: installing external Python packages from uploaded .whl files, running a YOLOv8 object detector, executing JavaScript via a bundled Deno binary, and doing face detection on video with classic Haar cascades. Each entry records the exact steps and the wording that gets the model to cooperate, which makes it useful for anyone who wants to understand the tool's real boundaries rather than the marketing version. The pro-tips section on context-window management and state loss is the kind of practical detail you only learn by actually using the environment. It is a curated reference for tinkering, not a deployable library, but for teams evaluating what Code Interpreter can and cannot do, it is a compact and honest field guide.