johnowhitaker

import requests, json, glob

# Set up
api_key = ...
GPT_MODEL = "gpt-4-1106-preview"

# Read the wordlist and solution from a file
def get_words(idx=0):
    files = sorted(glob.glob("connections_data/*.json"))
    f = open(files[idx])

johnowhitaker

from fasthtml.all import *
import anthropic, base64
client = anthropic.Anthropic(
    api_key="your_key_here",
)


canvas_js = """
    const canvas = document.getElementById('drawingCanvas');
    const context = canvas.getContext('2d');

johnowhitaker

from fasthtml.all import *
import anthropic, base64, time


client = anthropic.Anthropic(
    api_key="your_key_here",
)

canvas_js = """
    const canvas = document.getElementById('drawingCanvas');

johnowhitaker

from starlette.responses import FileResponse, RedirectResponse
from fastcore.utils import *
from fastcore.xml import *
from fasthtml import *

from sqlite_utils import Database
from fastlite import *
from fastlite.kw import *

db = Database('todos.db')

johnowhitaker

import requests, json, uuid

from starlette.responses import FileResponse, RedirectResponse
from fastcore.utils import *
from fastcore.xml import *
from fasthtml import *
from oauthlib.oauth2 import WebApplicationClient


# Secrets + URLs

johnowhitaker

# Import the required modules
import sounddevice as sd # For accessing the microphone
import pynput # For sending keypresses
import numpy as np # For numerical calculations
import time as tm # For measuring time

# Define a function that checks the loudness of the sound input
def check_loudness(indata, outdata, frames, time, status):

    global prev_state, last_trigger

johnowhitaker

import trafilatura
import feedparser
import requests
from bs4 import BeautifulSoup
from feedgenerator import DefaultFeed, Enclosure


API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
headers = {"Authorization": "Bearer HF_TOKEN"}