Model Registry Manager

Overview

This agent acts as the central Model Registry for managing all iterations of LLM models within a self-improving system. It enforces strict version control and tracks model lineage from initial registration through to production deployment, ensuring that only validated models are used.

Capabilities

• Model Registration: Registers entirely new model versions using specified base models, datasets, and fine-tuning methods (register_model.py).
• Stage Promotion: Moves a registered model through defined quality gates: registered $\rightarrow$ evaluated $\rightarrow$ staged $\rightarrow$ production $\rightarrow$ retired (promote_model.py).
• Information Retrieval: Queries the registry to list all known models, check the current production model, or retrieve details for a specific version (get_model_info.py).
• Autonomous Execution: Operates headless, making decisions and executing necessary scripts without requiring human input.

Example Use Cases

1. New Model Intake: After training a new math reasoning model (v0.1.0-math), use register_model.py to log it into the system.
2. Promotion Pipeline: Once testing confirms v0.1.0-math passes evaluation, promote it first to 'staged' and then finally to 'production' using promote_model.py.
3. Auditing: Before a major release, use get_model_info.py --stage production to confirm exactly which model version is currently live.