- Store all tests under the
tests/
folder - Name test files based on the system component being tested (conceptual, not React component)
- Group related tests within a single file using
test.describe
blocks - Use descriptive test names that explain the functionality being tested
- use
test.use({storageState: ...})
for setting auth state across all test in the suite
#!/usr/bin/env python3 | |
""" | |
Google Drive MCP Server | |
This server provides Model Context Protocol (MCP) integration with Google Drive, | |
allowing clients to: | |
- List and search files in Google Drive | |
- Read file contents | |
- List, read, and write Google Sheet data | |
""" |
from dotenv import load_dotenv | |
from langchain_openai import ChatOpenAI | |
from pydantic import BaseModel | |
from browser_use import ActionResult, Agent, Controller | |
from browser_use.browser.context import BrowserContext | |
from browser_use.browser.browser import Browser, BrowserConfig | |
import asyncio | |
import os | |
import json | |
import re |
I wrapped Python traceback and Exception so whenever an Exception is raised, an automatic diagnosis is done by GPT-4. See results below:
This error message occurred because of 'test' at line 177 in file api.py, function main. The exception type is <class 'Exception'>. The function is:
import json | |
import pickle | |
import struct | |
import zipfile | |
import numpy as np | |
from sentencepiece import SentencePieceProcessor | |
def rms_norm(x): return (x / np.sqrt(np.square(x).mean(-1, keepdims=True) + 1e-6)) | |
def softmax(x): return (np.exp(x - np.max(x, axis=-1, keepdims=True))) / np.sum((np.exp(x - np.max(x, axis=-1, keepdims=True))), axis=-1, keepdims = True) |
Here is easy steps to try Windows 10 on ARM or Ubuntu for ARM64 on your Apple Silicon Mac. Enjoy!
NOTE: that this is current, 10/1/2021 state.
- Install Xcode from App Store or install Command Line Tools on your Mac
import os | |
import sys | |
from pathlib import Path | |
import joblib | |
import numpy as np | |
import pandas as pd | |
from IPython import get_ipython | |
from IPython.display import Markdown, display | |
from matplotlib import pyplot as plt |
from datetime import datetime, timedelta, timezone | |
from requests import get | |
import icalendar | |
from dateutil.rrule import * | |
import pytz | |
import locale | |
locale.setlocale(locale.LC_TIME, "it_IT") | |
import time |
<link href="https://rsms.me/inter/inter.css" rel="stylesheet" type="text/css"> | |
<style> | |
#zubovsky-pop-container{ | |
-webkit-font-smoothing: subpixel-antialiased; | |
background-attachment: scroll; | |
background-clip: border-box; | |
background-color: rgb(14, 27, 46); | |
background-image: none; | |
background-origin: padding-box; |
This document shows how to deploy an OpenShift instance on a server using CodeReady Containers (crc) that can be accessed remotely from one or more client machines (sometimes called a "headless" instance). This provides a low-cost test and development platform that can be shared by developers. Deploying this way also allows a user to create an instance that uses more cpu and memory resources than may be available on his or her laptop.
While there are benefits to this type of deployment, please note that the primary use case for crc is to deploy a local OpenShift instance on a workstation or laptop and access it directly from the same machine. The headless setup is configured completely outside of crc itself, and supporting a headless setup is beyond the mission of the crc development team. Please do not ask for changes to crc to support this type of deployment, it will only cost the team time as they politely decline :)
The instructions here were tested with F