import copy
import subprocess

from pytube import YouTube
from scipy.signal import resample
import numpy as np
import pytsmod as tsm

from moviepy.audio.AudioClip import AudioArrayClip
from moviepy.editor import *
from moviepy.video.fx.speedx import speedx

from sentence_transformers import SentenceTransformer, util
from transformers import pipeline, BertTokenizer, BertForNextSentencePrediction
import torch 
import whisper

subprocess.run(['apt-get', '-y', 'install', 'imagemagick'])

transcriber = whisper.load_model("medium")
sentence_transformer = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
tokenizer = BertTokenizer.from_pretrained("bert-base-cased")
next_sentence_predict = BertForNextSentencePrediction.from_pretrained("bert-base-cased").eval()
summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")

def get_youtube(video_url):
    # YouTubeの動画をダウンロード
    print("Start download video")
    yt = YouTube(video_url)
    abs_video_path = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first().download(filename='download.mp4', output_path='movies/')
    print("Success download video")
    print(abs_video_path)
    return abs_video_path

def two_chnnel_to_one_channel(sample):
    # 音声を2チャンネルから1チャンネルに変換
    left_channel = sample[:, 0]
    right_channel = sample[:, 1]
    mono_sample = (left_channel + right_channel) / 2
    return mono_sample

def convert_sample_rate(data, original_sr, target_sr):
    # 音声データのサンプリング周波数を変更
    target_length = int(len(data) * target_sr / original_sr)
    return resample(data, target_length)