Inference utilities for keynet - Triton Inference Server integration
Project description
keynet-inference
Triton Inference Server 통합과 보안 함수 실행을 위한 추론 유틸리티
설치
pip install keynet-inference
주요 기능
🔌 MLflow-Triton 통합
- MLflow 모델을 Triton Inference Server로 자동 배포
- Python 함수를 Triton 모델로 변환
- S3/MinIO 기반 모델 저장소 지원
🛡️ 보안 함수 실행
- 격리된 가상환경에서 안전한 실행
- 메모리 및 CPU 사용량 제한
- 타임아웃 기반 실행 제어
🛠️ Keynet CLI
- 함수 검증 및 테스트
- 배포 자동화
- 인증 관리
- Python 3.9~3.12 지원
사용 예제
Python 함수 작성
from keynet_inference.function import keynet_function
@keynet_function(
python_version="3.11",
requirements=["numpy", "pandas"],
timeout=30
)
def process_data(args):
"""데이터 처리 함수"""
data = args.get("data", [])
result = sum(data) / len(data) if data else 0
return {
"result": result,
"count": len(data)
}
CLI 사용
# 함수 검증
keynet validate my_function.py
# 테스트 실행
keynet test my_function.py --params '{"data": [1, 2, 3, 4, 5]}'
# 배포
keynet deploy my_function.py --name my_model
# 인증 관리
keynet login https://api.example.com
keynet logout --all
MLflow 플러그인 사용
import mlflow
from keynet_inference import TritonPlugin
# Triton으로 모델 배포
mlflow.deployments.create_deployment(
name="my-deployment",
model_uri="models:/my_model/1",
flavor="triton",
config={
"triton_url": "localhost:8001",
"model_repository": "s3://models"
}
)
API 문서
자세한 API 문서는 GitHub Wiki 참조
라이선스
MIT License
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