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# Ref. [Deploying a Machine Learning Model to AWS Lambda | TestDriven.io](https://testdriven.io/blog/ml-model-aws-lambda/)
import logging
from app import DocumentParserModel
# initialize logger and model during Lambda's cold start
LOGGER = logging.getLogger()
LOGGER.setLevel(logging.INFO)
model = DocumentParserModel()
def lambda_handle(event, context):
# Only used to keep the Lambda warm
if event.get("source") == "KEEP_LAMBDA_WARM":
LOGGER.info("No ML work to do. Just staying warm...")
return "Keeping Lambda warm"
return {"statusCode": 200, "result": model.predict_text(image_blob=event["image_blob"])}
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