ochilab

  form.setIsQuiz(true);
  form.setCollectEmail(true); // メールアドレス収集
  //form.setRequireLogin(true);   // 非推奨メソッド （これは使わない）
  //確認済みメールアドレスで収集  （これが正解）
  form.setEmailCollectionType(FormApp.EmailCollectionType.VERIFIED);

ochilab

REGION = os.getenv("AWS_REGION", "us-east-1")
brt = boto3.client("bedrock-runtime", region_name=REGION)

def call_claude(model_id: str, user_text: str, max_tokens=600, temperature=0):
    body = {
        "anthropic_version": "bedrock-2023-05-31",
        "max_tokens": max_tokens,
        "temperature": temperature,
        "messages": [{"role": "user", "content": [{"type":"text","text": user_text}]}]
    }

ochilab

function createQuizForm() {
  var form = FormApp.create('復習テスト'); // フォームのタイトル
  form.setIsQuiz(true);
  form.setCollectEmail(true);              // メールアドレス収集
  form.setLimitOneResponsePerUser(true);   // 1人1回答

  var sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();

  // シート全体のデータ
  var data = sheet.getDataRange().getValues();

ochilab

import requests, json, urllib.parse as ul

# === 事前設定 ===
ENDPOINT = "https://<your-ll-host>/data/xAPI/"   # 末尾は /data/xAPI/
KEY = "<LL_CLIENT_KEY>"
SECRET = "<LL_CLIENT_SECRET>"

#ここのパラメータを変えることで検索条件を指定できる
params = {  
    "limit": 10,

ochilab

docker pull redis:5.0.4

docker run --rm \
  -v learning-locker-docker-image-main_learninglocker-redis:/data \
  -v $(pwd):/backup \
  alpine sh -c 'cd /data && tar czf /backup/redis-data-backup-$(date +%F-%H%M%S).tar.gz .'
  
docker run --rm -it \
  -v learning-locker-docker-image-main_learninglocker-redis:/data \
  --entrypoint redis-check-aof \

ochilab

$EMAIL_ADDRESS = "[email protected]"
$ORGANIZATION  = "personal"
$PASSWORD      = "************"
$CONTAINER     = "learninglocker"
Write-Host "Creating site admin for Learning Locker..."
Write-Host "Email: $EMAIL_ADDRESS"
Write-Host "Organization: $ORGANIZATION"
docker exec $CONTAINER bash -lc "cd /usr/local/src/learninglocker && node cli/dist/server createSiteAdmin '$EMAIL_ADDRESS' '$ORGANIZATION' '$PASSWORD'"
Write-Host "Done."

ochilab

import flet as ft
import threading
from PIL import Image, ImageDraw
import pystray
import asyncio
import time

def main(page: ft.Page):
    page.title = "Flet MenuBar App"
    page.add(ft.Text("メニューバー常駐のサンプル"))

ochilab

import cv2
import base64
import threading
import flet as ft
from io import BytesIO
from PIL import Image

# カメラ映像を定期的にキャプチャして画像を更新
def camera_thread(page: ft.Page, image_control: ft.Image):
    cap = cv2.VideoCapture(1)

ochilab

import cv2
import torch
from segment_anything import sam_model_registry, SamPredictor
import numpy as np
from google.colab.patches import cv2_imshow


# SAMモデルの読み込み（パスは適宜変更）
# sam_checkpoint = "sam_vit_h.pth"
sam_checkpoint = "sam_vit_h_4b8939.pth"

ochilab

import pandas as pd
import torch
from py_irt.models.two_param_logistic import TwoParamLog

class SafeTwoParamLog(TwoParamLog):
    def fit_MCMC(self, models, items, responses, num_epochs=1000):
        from pyro.infer import MCMC, NUTS

        nuts_kernel = NUTS(self.model_vague, adapt_step_size=True)
        hmc_posterior = MCMC(