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""" To use: install LLM studio (or Ollama), clone OpenVoice, run this script in the OpenVoice directory
    git clone https://github.com/myshell-ai/OpenVoice
    cd OpenVoice
    git clone https://huggingface.co/myshell-ai/OpenVoice
    cp -r OpenVoice/* .
    pip install whisper pynput pyaudio
"""

from openai import OpenAI
import time

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import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import (
    accuracy_score,
    precision_score,
    recall_score,
    confusion_matrix,
)
from sklearn.compose import ColumnTransformer, make_column_selector as selector

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#!/bin/bash

sudo apt update -y
sudo apt install  git gcc make openssl libssl-dev \
    libbz2-dev libreadline-dev libsqlite3-dev zlib1g-dev \
    libncursesw5-dev libgdbm-dev libc6-dev zlib1g-dev libsqlite3-dev \
    tk-dev libssl-dev openssl libffi-dev \
    -y

# install

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Data Science | miniconda

🐍 Installation

Windows and Mac users can use [GUI installer](https://docs.conda.io/en/latest/miniconda.html) . Remember to accept adding conda to PATH
Linux or Windows Subsystem Linux (wsl) can do:

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###################################################
# conda create -n opencnn python=3.7 tensorflow   #
# conda activate opencnn                          #
# pip install opencv-python mtcnn                 #
###################################################

import logging
import os

import cv2

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import json
import zlib
from typing import Any, Optional, Dict
import diskcache as dc


class DataCache:
	def __init__(
	self,
	cache_path: str,

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from datetime import datetime
from uuid import UUID, uuid4
from typing import Literal, Optional, Union
from pydantic import BaseModel, Field, ValidationError, validator, constr, confloat


class HouseDataValidation(BaseModel):

    id: Union[int, UUID] = Field(default_factory=uuid4)
    kind: Literal["villa", "apartment", "townhouse"]

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from pathlib import Path
from PIL import Image

# get all png images from folder `gotoslides`
SLIDES_IMAGES = Path("gotoslides").glob("*.png")

# maybe use a generator | convert RGB (since its png)
images = [Image.open(image).convert("RGB") for image in SLIDES_IMAGES]

with open("gotoslides.pdf", "wb") as pdf_file:

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# Using pyPDF2 and requests(or httpx) to extract PDF data

import io
import requests
import PyPDF2

# my favorite Kierkegard's PDF book
URI = "https://antilogicalism.com/wp-content/uploads/2017/07/thesicknessuntodeath.pdf"
headers = {"user-agent": "Prayson W. Daniel: prayson*at*.com"}