# Personal AI Infrastructure — Model Ops Module

**Version**: v1.1.9 | **Status**: Active | **Last Updated**: March 2026

## Overview

The Model Ops (MLOps) module provides model lifecycle management — versioning, registering, deploying, and monitoring machine learning and AI models in production.

## PAI Capabilities

- Model versioning and registry
- Model deployment and serving
- A/B testing for model variants
- Performance monitoring and drift detection
- Model rollback and promotion

## Key Exports

| Export | Type | Purpose |
|--------|------|---------|
| Model registry | Various | Model versioning and storage |
| Deployment managers | Various | Model serving and scaling |
| Monitoring | Various | Drift detection and alerting |

## PAI Algorithm Phase Mapping

| Phase | Model Ops Contribution |
|-------|-------------------------|
| **PLAN** | Select model version for deployment |
| **EXECUTE** | Deploy and serve models |
| **VERIFY** | Monitor model performance and detect drift |
| **LEARN** | Register new model versions from training runs |

## Architecture Role

**Service Layer** — Consumes `llm/` (model management), `performance/` (benchmarking). Interface between model development and production serving.

## MCP Tools

This module does not expose MCP tools directly. Access its capabilities via:
- Direct Python import: `from codomyrmex.model_ops import ...`
- CLI: `codomyrmex model_ops <command>`

## Navigation

- **Self**: [PAI.md](PAI.md)
- **Parent**: [../PAI.md](../PAI.md) — Source-level PAI module map
- **Root Bridge**: [../../../PAI.md](../../../PAI.md) — Authoritative PAI system bridge doc
- **Siblings**: [README.md](README.md) | [AGENTS.md](AGENTS.md) | [SPEC.md](SPEC.md) | [API_SPECIFICATION.md](API_SPECIFICATION.md)
