Visual OpenLLM is an open-source interactive tool that connects multiple open vision and language models into one conversational interface, often described as an open-source counterpart to multimodal assistants like Baidu’s ERNIE Bot. The GitHub project has around 1,200 stars and was last updated in early 2024.
The project combines ChatGLM with ideas from Visual ChatGPT and Stable Diffusion: a language model acts as the controller, deciding when to call vision models so users can send images, ask questions about them, request edits and generate new pictures inside a single chat. Instead of a single monolithic multimodal model, Visual OpenLLM chains specialised open models together — image captioning, visual question answering, text-to-image generation and more — behind a simple interactive front end. It was built to demonstrate that capable multimodal assistants could be assembled entirely from open components, and it remains a readable reference implementation of that controller-style architecture, which later became the standard pattern for tool-using multimodal agents.
The project appeared early in the open multimodal wave, shortly after Visual ChatGPT, and helped popularise the idea of an LLM controller orchestrating specialist vision models. Its architecture is a useful teaching example for anyone designing modern tool-using agents.
Visual OpenLLM is free and open source; you download the code and models from GitHub and run everything on your own hardware, so the only cost is your own compute.
Developers and researchers interested in multimodal AI who want a hands-on example of chaining vision models behind a language-model controller, or a starting point for their own visual chat experiments.