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# Import necessary libraries
import pennylane as qml
import sqlite3
import gpsd
import time
import openai
import json
from google.cloud import vision_v1
from google.cloud.vision_v1 import types
from pennylane import numpy as np

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[whisper]: Whispering voice.
[shout]: Shouting voice.
[italics]: Emphasize text as if it's italicized.
[bold]: Emphasize text as if it's bold.
[fast]: Increase speech speed.
[slow]: Decrease speech speed.
[robotic]: Robotic voice effect.
[echo]: Echo effect.
[reverb]: Reverb effect.
[footsteps]: Footsteps sound effect.

graylan0

import pennylane as qml
import sqlite3
import time
import openai
import json
from google.cloud import vision_v1
from google.cloud.vision_v1 import types
from pennylane import numpy as np
import cv2

graylan0

import numpy as np
import uuid
from scipy.io.wavfile import write as write_wav
from concurrent.futures import ThreadPoolExecutor
from bark import generate_audio, SAMPLE_RATE
import os
from quart import Quart, request, send_file
import nest_asyncio
import re

graylan0

import json
import re
import uuid
import openai
from concurrent.futures import ThreadPoolExecutor
from quart import Quart, request, send_file
from bark import generate_audio, SAMPLE_RATE
from scipy.io.wavfile import write as write_wav

# Read the configuration from config.json

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import requests
import subprocess
import webbrowser
from time import sleep

# Define the Client ID and Client Secret (You should replace these with your actual credentials)
clientID = "YOUR_CLIENT_ID"
clientSecret = "YOUR_CLIENT_SECRET"

# List of streamers

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import requests
import subprocess
import webbrowser
from time import sleep

# Define the Client ID and Client Secret (You should replace these with your actual credentials)
clientID = "puthere"
clientSecret = "puthere"

# List of streamers

graylan0

import requests
import json
import openai
import sqlite3
from flask import Flask, render_template, request
from datetime import datetime, timedelta
from flask_apscheduler import APScheduler

# Load OpenAI API key from config.json
with open('config.json') as f:

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import openai

class BarkaiMotivationalSpeech:
    def __init__(self):
        pass

    def construct_initial_prompt(self, user_age, user_location):
        rules = f"""Generate a daily morning motivational speech to be read by Barkai. Adhere to the following rules:
                    1. The speech should be tailored to an audience of age {user_age} and located in {user_location}.
                    2. Include a greeting, main body, and conclusion.

graylan0

import numpy as np
import re
import sounddevice as sd
import uuid
from scipy.io.wavfile import write as write_wav
from bark import generate_audio, SAMPLE_RATE
import os
from concurrent.futures import ThreadPoolExecutor

os.environ["SUNO_OFFLOAD_CPU"] = "True"