jaeyow

table_node_mapping = SQLTableNodeMapping(sql_database)

table_schema_objs = []
for table_name, table_description in all_tables:
    table_schema_objs.append(
        SQLTableSchema(table_name=table_name, context_str=table_description))
    
print(table_node_mapping)
print(table_schema_objs)

jaeyow

table_node_mapping = SQLTableNodeMapping(sql_database)

table_schema_objs = []
for table_name, table_description in all_tables:
    table_schema_objs.append(
        SQLTableSchema(table_name=table_name, context_str=table_description))
    
print(table_node_mapping)
print(table_schema_objs)

jaeyow

    @step
    def deploy_best_model(self):
        """
        Deploy the best model to AWS Lambda using SAM CLI
        """
        try:
            AWS_REGION = "ap-southeast-2"
            BASE_PATH = "sam"
            PROFILE_NAME = "Cevo-Dev.AWSFullAccountAdmin"
            BEST_MODEL = self.MODEL_PKL_FILENAME

jaeyow

[alias]
# one-line log
    l = log --pretty=format:"%C(yellow)%h\\ %ad%Cred%d\\ %Creset%s%Cblue\\ [%cn]" --decorate --date=short
    a = add
    ap = add -p
    c = commit --verbose
    ca = commit -a --verbose
    cm = commit -m
    cam = commit -a -m
    m = commit --amend --verbose

jaeyow

def get_popular_items(user_id="x"):
    ssm = boto3.client("ssm")
    recommenderArn = ssm.get_parameter(
        Name="/cevo-shopping-demo/recommender/arn-retaildemostore-popular-items",
        WithDecryption=False,
    )
    response = personalizeRuntime.get_recommendations(
        recommenderArn=recommenderArn["Parameter"]["Value"],
        userId=user_id,
        numResults=100,

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def get_recommended_items(user_id):
    ssm = boto3.client("ssm")
    recommenderArn = ssm.get_parameter(
        Name="/cevo-shopping-demo/recommender/arn-retaildemostore-recommended-for-you",
        WithDecryption=False,
    )
    response = personalizeRuntime.get_recommendations(
        recommenderArn=recommenderArn["Parameter"]["Value"],
        userId=user_id,
        numResults=30,

jaeyow

import boto3
from generators.generate_items_and_interactions_personalize import generate_user_items

bucket = "cevo-shopping-demo"
products_filename = "./generators/items.csv"

generate_user_items()

boto3.Session(profile_name=<aws-profile-replace-me>, region_name="ap-southeast-2").resource(
    "s3"

jaeyow

import boto3
from generators.generate_items_and_interactions_personalize import generate_interactions

bucket = "cevo-shopping-demo"
interactions_filename = "./generators/interactions.csv"

generate_interactions()

boto3.Session(profile_name=<aws-profile-replace-me>, region_name="ap-southeast-2").resource(
    "s3"

jaeyow

import pandas as pd
import boto3
from generators.generate_users_json import generate_users_json

bucket = "cevo-shopping-demo"
users_filename = "./generators/users.csv"

generate_users_json()

boto3.Session(profile_name=<aws-profile-replace-me>, region_name="ap-southeast-2").resource(

jaeyow

def getCustomLabelsOfImage(model_arn, bucket_name, image):
    # Use boto3 call detect_custom_labels API call to get Rekognition Custom Labels
    client = boto3.client("rekognition")
    response = client.detect_custom_labels(
        ProjectVersionArn=model_arn,
        Image={"S3Object": {"Bucket": bucket_name, "Name": image}},
        MinConfidence=98,
    )
    return response["CustomLabels"]