Co-Produce AI: the build, in four parts.
A developer-facing walkthrough of the whole toolkit, drawn straight from the repo — setup and architecture, the full creative pipeline, and the reference layer that turns it into a product.
Build a Co-Producer That Sounds Like You: Setting Up Co-Produce AI
What the system is, how the scripts chain together, the quick start, the Python 3.11 environment, the cloud-GPU model, and the legal ground rules.
The Pipeline: From a Chaotic Sample Folder to a Finished, Trained Pack
The full creative chain — organize, analyze, caption, train, generate, remix, build beats, drive your VSTs, full songs, lyrics — plus the Creative Techniques Lab.
Reference & Scaling: Costs, Engines, and Turning the Toolkit into a Product
The operator's reference — GPU costs, lossless sourcing, the SA3 vs ACE-Step engine call, serverless, the pod workflow, and the full SaaS backend.
Train It, Then Talk to It: The Training & Prompting Playbook
The post-training playbook — the LoRA training command decoded flag by flag, every way to make beats once trained, and the full ready-to-paste prompt libraries.