Generic Pipeline for AIMLFW

Develop a Flexible, Modular Framework:
Create a dynamic and composable pipeline that enables seamless construction, configuration, and execution of ML workflows within AIMLFW.
Accelerate Model Lifecycle Management:
Facilitate streamlined processes for training, retraining, evaluation, and deployment, allowing users to adapt workflows dynamically to changing requirements.

Core Component Development:
Design and implement essential modules, including a Pipeline Orchestrator, component Registry.
Dynamic Pipeline Configuration:
Support JSON/YAML-based configuration for including or excluding component.
Extensibility & Integration:
Allow easy integration of custom component, and ensure compatibility with existing AIMLFW components (e.g., Training Manager, MME, deployment modules).
Testing & Documentation:
Establish comprehensive testing (unit, integration, and performance) and provide detailed documentation to support adoption and future enhancements.

Design Proposal

@startuml
actor "Component Builder" as CB
actor "Pipeline Designer" as PD
actor "Training Executor" as TE

rectangle "Dynamic Pipeline System" {
(Build Component) as BC
(Design Pipeline) as DP
(Execute Training Job) as ETJ
}

CB --> BC : Builds
PD --> DP : Design using Components
TE --> ETJ : Executes Training Job

BC --> DP : Used in
DP --> ETJ : Referenced in

' Many-to-One Relationship
note right of DP : Many components in one pipeline
note right of ETJ: Pipelines in one training job

@enduml

AI/ML Framework