# AWS SageMaker Script

# Set up the environment
export PATH=/usr/local/bin:$PATH

# Set up the variables
export AWS_DEFAULT_REGION=us-east-1
export SAGEMAKER_ROLE_ARN=arn:aws:iam::${AWS_ACCOUNT_ID}:role/SageMakerRole
export SAGEMAKER_ENDPOINT_NAME=${AWS_ACCOUNT_ID}-endpoint
export SAGEMAKER_ENDPOINT_CONFIG_NAME=${AWS_ACCOUNT_ID}-endpoint-config
export SAGEMAKER_ENDPOINT_CONFIG_DESC="SageMaker Endpoint Config"
export SAGEMAKER_ENDPOINT_DESC="SageMaker Endpoint"
export SAGEMAKER_MODEL_NAME=${AWS_ACCOUNT_ID}-model
export SAGEMAKER_MODEL_DESC="SageMaker Model"
export SAGEMAKER_BUCKET_NAME=${AWS_ACCOUNT_ID}-sagemaker
export SAGEMAKER_DATA_DIR=${SAGEMAKER_BUCKET_NAME}/data
export SAGEMAKER_MODEL_DIR=${SAGEMAKER_BUCKET_NAME}/model
export SAGEMAKER_JOB_NAME=${AWS_ACCOUNT_ID}-job
export SAGEMAKER_JOB_DESC="SageMaker Job"
export SAGEMAKER_JOB_OUTPUT_DIR=${SAGEMAKER_BUCKET_NAME}/output
export SAGEMAKER_JOB_OUTPUT_FILE=${SAGEMAKER_JOB_OUTPUT_DIR}/${SAGEMAKER_JOB_NAME}.csv

# Create the S3 bucket
aws s3 mb s3://${SAGEMAKER_BUCKET_NAME}

# Create the SageMaker endpoint configuration
aws sagemaker create-endpoint-config \
    --endpoint-config-name ${SAGEMAKER_ENDPOINT_CONFIG_NAME} \
    --endpoint-config-description ${SAGEMAKER_ENDPOINT_CONFIG_DESC} \
    --production-variants ${SAGEMAKER_ENDPOINT_NAME}

# Create the SageMaker endpoint
aws sagemaker create-endpoint \
    --endpoint-name ${SAGEMAKER_ENDPOINT_NAME} \
    --endpoint-config-name ${SAGEMAKER_ENDPOINT_CONFIG_NAME} \
    --tags Key=${AWS_ACCOUNT_ID},Value=${AWS_ACCOUNT_ID} \
    --tags Key=${SAGEMAKER_ENDPOINT_NAME},Value=${SAGEMAKER_ENDPOINT_NAME} \
    --tags Key=${SAGEMAKER_ENDPOINT_CONFIG_NAME},Value=${SAGEMAKER_ENDPOINT_CONFIG_NAME} \
    --tags Key=${SAGEMAKER_ENDPOINT_CONFIG_DESC},Value=${SAGEMAKER_ENDPOINT_CONFIG_DESC} \
    --tags Key=${SAGEMAKER_ENDPOINT_DESC},Value=${SAGEMAKER_ENDPOINT_DESC}

# Create the SageMaker model
aws sagemaker create-model \
    --model-name ${SAGEMAKER_MODEL_NAME} \
    --primary-container-image ${SAGEMAKER_PRIMARY_CONTAINER_IMAGE} \
    --execution-role-arn ${SAGEMAKER_ROLE_ARN} \
    --tags Key=${AWS_ACCOUNT_ID},Value=${AWS_ACCOUNT_ID} \
    --tags Key=${SAGEMAKER_MODEL_NAME},Value=${SAGEMAKER_MODEL_NAME} \
    --tags Key=${SAGEMAKER_MODEL_DESC},Value=${SAGEMAKER_MODEL_DESC}

# Create the SageMaker model package
aws sagemaker create-model-package \
    --model-package-name ${SAGEMAKER_MODEL_NAME} \
    --model-package-description ${SAGEMAKER_MODEL_DESC} \
    --tags Key=${AWS_ACCOUNT_ID},Value=${AWS_ACCOUNT_ID} \
    --tags Key=${SAGEMAKER_MODEL_NAME},Value=${SAGEMAKER_MODEL_NAME} \
    --tags Key=${SAGEMAKER_MODEL_DESC},Value=${SAGEMAKER_MODEL_DESC}

# Create the SageMaker model artifact
aws s3 cp ${SAGEMAKER_MODEL_DIR} s3://${SAGEMAKER_BUCKET_NAME}/model

# Execute the SageMaker job
aws sagemaker create-transform-job \
    --model-name ${SAGEMAKER_MODEL_NAME} \
    --model-version-name ${SAGEMAKER_MODEL_VERSION} \
    --transform-job-name ${SAGEMAKER_JOB_NAME} \
    --transform-input-record-keys ${SAGEMAKER_INPUT_RECORD_KEYS} \
    --transform-output-path ${SAGEMAKER_JOB_OUTPUT_DIR} \
    --transform-resources ${SAGEMAKER_TRANSFORM_RESOURCES} \
    --tags Key=${AWS_ACCOUNT_ID},Value=${AWS_ACCOUNT_ID} \
    --tags Key=${SAGEMAKER_JOB_NAME},Value=${SAGEMAKER_JOB_NAME} \
    --tags Key=${SAGEMAKER_JOB_DESC},Value=${SAGEMAKER_JOB_DESC}

# Monitor the SageMaker job
aws sagemaker list-transform-jobs \
    --transform-job-name ${SAGEMAKER_JOB_NAME} \
    --max-results 1

# Wait for the SageMaker job to complete
aws sagemaker wait transform-job-completed \
    --transform-job-name ${SAGEMAKER_JOB_NAME}

# Download the SageMaker job output
aws s3 cp ${SAGEMAKER_JOB_OUTPUT_FILE} s3://${SAGEMAKER_BUCKET_NAME}/output/${SAGEMAKER_JOB_NAME}.csv