musegpt successfully validated the core hypothesis that local LLM inference within music production tools is technically feasible and can provide value to creators. The project demonstrated that on-device inference in creative tools works.
I archived it because my focus shifted to other research areas, including MCP server evaluation with mcpbr. The broader ecosystem of AI music tools has also grown significantly since I created musegpt, and keeping up with rapid changes in model formats and inference engines requires sustained effort.
The project remains valuable as a reference implementation showing how to integrate llama.cpp with JUCE, and as an early exploration of local AI in creative workflows. The code is open source and available for anyone interested in building upon these ideas.