| # 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_path = "captcha.onnx" | |
| img_size = (32, 128) | |
| charset = r"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~" | |
| model = DocumentParserModel( | |
| model_path=model_path, | |
| img_size=img_size, | |
| charset=charset, | |
| ) | |
| 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, "vc": model.predict_text(image_path=event["image_path"])} | |