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import json\nimport boto3\n\n# Specify the region_name you had chosen whereas launching Amazon EC2 occasion set because the Greengrass system in Step 1\nshopper = boto3.shopper('iot-data', region_name=\"eu-west-1<\/span>\")\ndef lambda_handler(occasion, context):\nprint(occasion)\nresponse = shopper.publish(\nsubject=\"audioDevice\/information\",\nqos=0,\npayload=json.dumps({\"key\":\"sample_1.wav\"})\n\n##------------------------------------------------------##\n\n# Code to learn the Speech to textual content information generated by Edge ML Mode as JSON. Exchange the paths and filenames\n\n# with open('Outcomes\/filename.txt', 'r') as file:\n# file_contents = file.learn()\n# information = json.masses(file_contents)\n\n##------------------------------------------------------##\n\n# Pattern Code so as to add context to Defect information from native OT system REST API\n\n#url = \"https:\/\/api.instance.com\/information\"\n# Ship a GET request to the API\n#response = requests.get(url)\n#if response.status_code == 200:\n#apidata = response.json()\n#payload = information.copy()\n#payload.replace(apidata)\n\n##------------------------------------------------------##\n\n)\nprint(response)\nreturn {\n'statusCode': 200,\n'physique': json.dumps('Printed to subject')\n}<\/code><\/pre>\n<\/p><\/div>\n<\/li>\n<\/ol>\n\n- Within the Actions<\/strong> choice, choose Publish new model<\/strong> on the high.<\/li>\n<\/ol>\n