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Cursor's Memory Bank

I am Cursor, an expert software engineer with a unique characteristic: my memory resets completely between sessions. This isn't a limitation - it's what drives me to maintain perfect documentation. After each reset, I rely ENTIRELY on my Memory Bank to understand the project and continue work effectively. I MUST read ALL memory bank files at the start of EVERY task - this is not optional.

Memory Bank Structure

The Memory Bank consists of required core files and optional context files, all in Markdown format. Files build upon each other in a clear hierarchy:

flowchart TD

How to use Amazon AWS Elasticsearch

The good news: you can get it running on the free tier (with a tiny instance).

The bad news: it's stuck on Elasticsearch 1.5.2 and dynamic scripting (Groovy) is disabled.

http://docs.aws.amazon.com/elasticsearch-service/latest/developerguide/aes-limits.html

Authentication: the safest option is to create a brand new IAM user (using the tool at https://console.aws.amazon.com/iam/home?region=us-east-1 ) with its own access key and secret key. Then when you create the Elasticsearch instance you can paste in the following IAM string:

	#!/usr/bin/env python3
	"""
	이미지 분할 도구
	위아래로 긴 이미지에서 중간 여백을 찾아 여러 개의 이미지로 분할합니다.
	"""

	import cv2
	import numpy as np
	import os
	import argparse

	-- ~/.config/nvim/lua/plugins/cmp.lua
	return {
	{
	"hrsh7th/nvim-cmp",
	opts = function(_, opts)
	local cmp = require("cmp")
	opts.mapping = vim.tbl_extend("force", opts.mapping, {
	["<Tab>"] = cmp.mapping(function(fallback)
	if cmp.visible() then
	cmp.confirm({ select = true })

	" (N)Vim Configuration File
	" vim : place in $HOME/.vimrc
	" nvim : place in $HOME/.config/nvim/init.vim
	" $ ln -s $HOME/.config/nvim/init.vim $HOME/.vimrc
	" General settings
	" https://learnvimscriptthehardway.stevelosh.com/
	" ---------------------------------------------------------------------------
	" drop vi support - kept for vim compatibility but not needed for nvim
	" Probably not needed with Vim 8+
	"set nocompatible

	#!/bin/bash

	# Specify the desired volume size in GiB as a command line argument. If not specified, default to 20 GiB.
	SIZE=64

	# Get the ID of the environment host Amazon EC2 instance.
	INSTANCEID=$(curl http://169.254.169.254/latest/meta-data/instance-id)
	REGION=$(curl -s http://169.254.169.254/latest/meta-data/placement/region)

	# Get the ID of the Amazon EBS volume associated with the instance.

	{
	"type": "record",
	"name": "Interactions",
	"namespace": "com.amazonaws.personalize.schema",
	"fields": [
	{
	"name": "USER_ID",
	"type": "string"
	},
	{

	import boto3
	import asyncio
	from concurrent.futures import ThreadPoolExecutor

	client = boto3.client('lambda')

	def call_lambda(args, *kwargs):
	return client.invoke(
	FunctionName='helloworld',
	)

	# run below code after install cudnn, cudatoolkit
	# !pip install tensorflow-gpu==2.1.0
	# !conda install cudnn cudatoolkit -y

	import tensorflow as tf
	import numpy as np
	from timeit import time

	tf.debugging.set_log_device_placement(True)
	tf.config.set_soft_device_placement(True)

	import os
	import json
	from base64 import b64encode, b64decode
	from matplotlib import pyplot as plt

	import mxnet as mx
	import sagemaker
	from gluoncv.utils import download, viz

	# 이미지를 로컬에 다운로드