This document outlines the architectural design for the Finite-State Machine (FSM) that will manage states and transitions within the KLLM kernel layer.
The FSM is a critical component for ensuring reliable and predictable behavior of the integrated AI models. It will be responsible for managing the state of each model and handling transitions between states in a structured manner.
The following states will be defined for each AI model:
- IDLE: The model is not currently active and is consuming minimal resources.
- LOADING: The model is being loaded into memory.
- RUNNING: The model is actively processing tasks.
- SUSPENDED: The model is temporarily paused, but its state is preserved in memory.
- ERROR: The model has encountered an error and is awaiting recovery or termination.
The FSM will define clear transitions between these states, triggered by specific events (e.g., an API call, a system event). Key transitions include:
IDLE->LOADINGLOADING->RUNNINGRUNNING->SUSPENDEDSUSPENDED->RUNNINGANY->ERROR
The FSM will provide a structured approach to error handling. When a model enters the ERROR state, the FSM will trigger a recovery mechanism or notify the system administrator.