Пример использования ML Space CLI в makefile

include .env_demo
export
PROFILE = DEMO
FILE_JOB = hello_world.yaml

.PHONY: configure
configure:
    @printf "$(MLS_APIKEY_ID)\n$(MLS_APIKEY_SECRET)\n$(WORKSPACE_ID)\n$(X_API_KEY)\n$(REGION)\n$(OUTPUT)\n" | mls configure --profile $(PROFILE)


.PHONY: create_file
create_file:
    @echo "job:" > $(FILE_JOB)
    @echo "  instance_type: a100.1gpu" >> $(FILE_JOB)
    @echo "  image: cr.ai.cloud.ru/aicloud-base-images/py3.10-torch2.1.2:0.0.40" >>$(FILE_JOB)
    @echo "  job_description: Все хорошо закончилось" >> $(FILE_JOB)
    @echo "  script: /home/jovyan/jobs_tests/test_pytorch2_torch2.py" >> $(FILE_JOB)
    @echo "  type: pytorch2" >> $(FILE_JOB)
    @echo "  number_of_workers: 1" >> $(FILE_JOB)
    @cat $(FILE_JOB)


.PHONY: run
run:
    mls job run --config $(FILE_JOB) --profile $(PROFILE) | jq -r ".job_name" > job_name.txt


read_log:
    sleep 10
    $(eval JOB_NAME=$(shell cat job_name.txt))
    @echo $(JOB_NAME)
    mls job logs $(JOB_NAME) --profile $(PROFILE) --output json


kill:
    @(eval JOB_NAME=$(shell cat job_name.txt))
    mls job kill $(JOB_NAME) --profile $(PROFILE) --output json
    @echo "Но задачу пришлось пристрелить"