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# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch
import torch.nn as nn

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch

# reuse the models from the previous snippets or copy the class

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch
import torch.nn as nn

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///

import torch
import torch.nn.functional as F

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///

import torch

drbh

# /// script
# dependencies = [
#   "requests<3",
# ]
# ///

import requests
import concurrent.futures
import time
from datetime import datetime

drbh

// Roku device IP address
const rokuIp = "192.168.1.252";
// Base URL for ECP commands
const baseUrl = `http://${rokuIp}:8060/keypress`;
// Delay between commands in milliseconds
const delay = 3000;

async function sendKeypress(command) {
    try {
        const response = await fetch(`${baseUrl}/${command}`, { method: 'POST' });

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from collections import deque
import time
from dataclasses import dataclass
from typing import Deque, List, Dict
import requests
import os


class Colors:
    PURPLE = "\033[95m"

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from openai import OpenAI

ENDPOINT_URL = "ENDPOINT_URL"
HF_TOKEN = "YOUR_TOKEN"

# Initialize the client, pointing it to one of the available models
client = OpenAI(
    base_url=ENDPOINT_URL + "/v1/",
    api_key=HF_TOKEN,
)

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const SEND_IN_BLUE_KEY = "..."

const randomString = (length) => {
    const bytes = new Uint8Array(length);
    window.crypto.getRandomValues(bytes);
    let result = '';
    bytes.forEach((b) => {
        // Convert each byte to a digit (0-9)
        result += (b % 10).toString();
    });