app.py

from transformers import pipeline
import gradio as gr
import time
from video_downloader import download_video1
from moviepy.editor import AudioFileClip, VideoFileClip
from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip
import datetime
import os
from pydub import AudioSegment
from pydub.silence import split_on_silence

pipe = pipeline("automatic-speech-recognition", model="Artanis1551/whisper_swedish")


def process_video1(date):
    video_path = download_video1(date)

    # Get the duration of the video
    video = VideoFileClip(video_path)
    duration = video.duration

    # If the video is longer than 30 seconds, only take the first 30 seconds
    if duration > 30:
        video_path = f"short_{date}.mp4"
        ffmpeg_extract_subclip(video_path, 0, 30, targetname=video_path)

    # Extract audio from the video
    audio_path = f"audio_{date}.wav"
    AudioFileClip(video_path).write_audiofile(audio_path)

    # Split the audio into chunks
    audio = AudioSegment.from_wav(audio_path)
    chunks = split_on_silence(audio, min_silence_len=500, silence_thresh=-40)

    # Transcribe each chunk
    transcription = ""
    for i, chunk in enumerate(chunks):
        chunk.export(f"chunk{i}.wav", format="wav")
        with open(f"chunk{i}.wav", "rb") as audio_file:
            audio = audio_file.read()
        transcription += pipe(audio)["text"] + "\n "
        os.remove(f"chunk{i}.wav")

    # Remove the audio file
    os.remove(audio_path)

    return video_path, transcription


iface = gr.Interface(
    fn=process_video1,
    inputs=[
        gr.inputs.Textbox(label="Date with format YYYY-MM-DD"),
    ],
    outputs=[
        gr.outputs.Video(),
        gr.Textbox(lines=1000, max_lines=100, interactive=True),
    ],
    title="Transcribe Swedish Parliament Decisions",
    description="This app transcribes the top Swedish Parliament decision"
    + " video from the given date. Only the first 30 seconds of the "
    + "video will be used if it is longer than that.",
)

iface.launch()