import json import time from http import HTTPStatus from typing import Dict from aws_lambda_powertools.event_handler import content_types from aws_lambda_powertools.utilities.typing import LambdaContext from src import app_logger from src.io.coordinates_pixel_conversion import get_point_latlng_to_pixel_coordinates, get_latlng_to_pixel_coordinates from src.prediction_api.predictors import samexporter_predict from src.utilities.constants import CUSTOM_RESPONSE_MESSAGES from src.utilities.utilities import base64_decode def get_response(status: int, start_time: float, request_id: str, response_body: Dict = None) -> str: """ Return a response for frontend clients. Args: status: status response start_time: request start time (float) request_id: str response_body: dict we embed into our response Returns: str: json response """ app_logger.debug(f"response_body:{response_body}.") response_body["duration_run"] = time.time() - start_time response_body["message"] = CUSTOM_RESPONSE_MESSAGES[status] response_body["request_id"] = request_id response = { "statusCode": status, "header": {"Content-Type": content_types.APPLICATION_JSON}, "body": json.dumps(response_body), "isBase64Encoded": False } app_logger.info(f"response type:{type(response)} => {response}.") return json.dumps(response) def get_parsed_bbox_points(request_input: Dict) -> Dict: app_logger.info(f"try to parsing input request {request_input}...") ne = request_input["ne"] sw = request_input["sw"] ne_latlng = [float(ne["lat"]), float(ne["lng"])] sw_latlng = [float(sw["lat"]), float(sw["lng"])] bbox = [ne_latlng, sw_latlng] zoom = int(request_input["zoom"]) for prompt in request_input["prompt"]: app_logger.info(f"current prompt: {type(prompt)}, value:{prompt}.") data = prompt["data"] app_logger.info(f"current data point: {type(data)}, value:{data}.") diff_pixel_coordinates_ne = get_latlng_to_pixel_coordinates(ne, data, zoom) app_logger.info(f'current data by current prompt["data"]: {type(data)}, {data} => {diff_pixel_coordinates_ne}.') prompt["data"] = [diff_pixel_coordinates_ne["x"], diff_pixel_coordinates_ne["y"]] app_logger.debug(f"bbox {bbox}.") app_logger.debug(f'request_input["prompt"]:{request_input["prompt"]}.') app_logger.info(f"unpacking elaborated {request_input}...") return { "bbox": bbox, "prompt": request_input["prompt"], "zoom": zoom } def lambda_handler(event: dict, context: LambdaContext): app_logger.info(f"start with aws_request_id:{context.aws_request_id}.") start_time = time.time() if "version" in event: app_logger.info(f"event version: {event['version']}.") try: app_logger.debug(f"event:{json.dumps(event)}...") app_logger.debug(f"context:{context}...") try: body = event["body"] except Exception as e_constants1: app_logger.error(f"e_constants1:{e_constants1}.") body = event app_logger.debug(f"body, #1: {type(body)}, {body}...") if isinstance(body, str): body_decoded_str = base64_decode(body) app_logger.debug(f"body_decoded_str: {type(body_decoded_str)}, {body_decoded_str}...") body = json.loads(body_decoded_str) app_logger.info(f"body, #2: {type(body)}, {body}...") try: body_request = get_parsed_bbox_points(body) body_response = samexporter_predict(body_request["bbox"], body_request["prompt"], body_request["zoom"]) app_logger.info(f"output body_response:{body_response}.") response = get_response(HTTPStatus.OK.value, start_time, context.aws_request_id, body_response) except Exception as ex2: app_logger.error(f"exception2:{ex2}.") response = get_response(HTTPStatus.UNPROCESSABLE_ENTITY.value, start_time, context.aws_request_id, {}) except Exception as ex1: app_logger.error(f"exception1:{ex1}.") response = get_response(HTTPStatus.INTERNAL_SERVER_ERROR.value, start_time, context.aws_request_id, {}) app_logger.info(f"response_dumped:{response}...") return response