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• Definition
  • Initial AI/ML workflow implementation for O-RAN environment. Need to interact with another project to accomplish a whole life cycle management of the AI model.
• Project Scope
  • AI 모델 라이프 사이클 관리 ( 모델 학습 파이프라인 관리 / 학습완료된 모델 버전 관리 및 배포시스템 연동 / AI 서비스 (Application) 관리 ) , Dashboard
  • AI 모델 학습 환경 ( 데이터 추출 / Feature 관리 및 연동 / AI 모델 저장 기능 / 모델 학습 플랫폼 지원 or 모델 학습/학습 파이프라인 구동 환경 )
  • AI 모델 추론 환경 ( 모델 서빙 플랫폼 지원 or 모델 추론 서비스 구동 환경 )
• g rel scope

AIML Framework (AIMLFW)

Mission: Stand-alone installation (separated from existing platform deployment) and initial AIML workflow modules

Original primary goals:

• Stand-alone installation with Kubeflow as a Training host backend and Kserve as a Inference host backend

• Manual Deployment of ML rApp and ML xApp

• Training Job Management: Create/Edit/Delete usecases and Training pipelines and monitoring current training jobs

• Data Extraction for model training from data lake

• Model feature database for Training pipeline

• Trained model storage

• Sample ML pipeline and ML xApp : QoE Prediction model using LSTM with data from ricapp/qp

G release source code, container images and deployment instructions

TODO

Repo. hierarchy

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