import os
import requests

from dotenv import load_dotenv
from moviepy import VideoFileClip
from openai import OpenAI
from pydub import AudioSegment

DEFAULT_PROMPT = "You will be provided a video transcription for which you are to generate a blog post in Markdown format summarizing the video contents."

def main(args):
    openai_client = OpenAI()
    return summarize_transcription(
            openai_client,
            transcribe_audio(
                openai_client,
                get_audio_from_video(
                    get_video_from_url()
                    )
                )
            )

def get_video_from_url():
    video_file_url = os.getenv('INPUT_VIDEO_URL')
    video_file_path = os.getenv('TMP_VIDEO_PATH' , '/tmp/video_summary_bot_tmp_video.mp4')
    request = requests.get(video_file_url)
    with open(video_file_path, 'wb') as f:
        for chunk in requests.get(video_file_url).iter_content(chunk_size=255):
            if chunk:
                f.write(chunk)

def get_audio_from_video():
    tmp_audio_path = os.getenv('TMP_AUDIO_PATH', '/tmp/video_summary_bot_tmp_audio.wav')
    video_file_path = os.getenv('TMP_VIDEO_PATH')
    VideoFileClip(video_file_path).audio.write_audiofile(tmp_audio_path)
    return AudioSegment.from_wav(tmp_audio_path)

def transcribe_audio(openai_client, audio):
    segment_duration = int(os.getenv('SEGMENT_DURATION', 30000)),
    transcription_model = os.getenv('OPENAI_TRANSCRIPTION_MODEL', 'whisper-1')
    return ' '.join([
        openai_client.audio.transcriptions.create(
            model=transcription_model,
            file=each
            ).text for each in [audio[i:i + segment_duration] for i in range(0, len(audio), segment_duration)]
        ])

def summarize_transcription(openai_client, transcription):
    prompt = os.getenv('OPENAI_RESPONSES_PROMPT', DEFAULT_PROMPT)
    responses_model = os.getenv('OPENAI_RESPONSES_MODEL', 'whisper-1')
    return client.responses.create(
            model=responses_model,
            instructions=prompt,
            input=transcription
            )

if __name__ == '__main__':
    load_dotenv()
    main(parser.parse_args())