JARVIS

Why we included this project

JARVIS, also known as HuggingGPT, is the reference implementation of an idea that has since been copied widely: a large language model acts as the controller, planning a user request, picking the right specialist model from the Hugging Face hub, running each subtask, and summarizing the results. If you are building multi-step AI workflows that cross modalities, say an image caption plus a text-to-speech readout in one pipeline, this repo shows a four-stage architecture worth studying or adapting. It includes a Gradio demo, a CLI, and a web API, and a lightweight config that calls Hugging Face inference endpoints, so you can try it without downloading large models locally. The companion papers on task automation and tool usage are useful background for anyone designing agent systems that delegate to external models.