Developing an AI application locally using AWS Chalice

First, let's implement the private APIs and services that provide common capabilities. We will have two services; both of them should be created in the chalicelib directory:

1. StorageService: The StorageService class that's implemented in the storage_service.py file connects to AWS S3 via boto3 to perform tasks on files we need for the applications.

Let's implement StorageService, as follows:

import boto3

class StorageService:
    def __init__(self, storage_location):
        self.client = boto3.client('s3')
        self.bucket_name = storage_location

    def get_storage_location(self):
        return self.bucket_name

    def list_files(self):
        response = self.client.list_objects_v2(Bucket = self.bucket_name)

        files = []
        for content in response['Contents']:
            files.append...