import gradio as gr
import ffmpeg
import os
import requests
from huggingface_hub import HfApi, HfFolder

# Mengambil API Token dari Secrets Hugging Face
HF_TOKEN = os.getenv("HF_TOKEN")  # Mengambil token API dari Secrets
HF_REPO_ID = os.getenv("HF_REPO_ID")  # Mengambil ID repo dari Secrets

api = HfApi()
HfFolder.save_token(HF_TOKEN)

# Fungsi untuk mengompresi video
def compress_video(video_path, quality, mode):
    output_path = video_path.replace(".", "_compressed.")

    # Menentukan tingkat kompresi berdasarkan kualitas yang dipilih
    if quality == "High":
        crf = 28  # Ukuran lebih kecil, kualitas lebih rendah
    elif quality == "Medium":
        crf = 23  # Kualitas standar
    else:
        crf = 18  # Kualitas lebih baik, ukuran lebih besar

    # Mode High Resolution - Low Capacity
    if mode == "High Resolution - Low Capacity":
        preset = "slow"
        bitrate = "2M"
    else:
        preset = "medium"
        bitrate = "4M"

    # Kompresi video menggunakan FFmpeg
    try:
        (
            ffmpeg
            .input(video_path)
            .output(output_path, vcodec="libx264", crf=crf, preset=preset, video_bitrate=bitrate)
            .run(overwrite_output=True)
        )
        return output_path
    except Exception as e:
        return str(e)

# Fungsi untuk mengunggah hasil ke Hugging Face Hub
def upload_to_huggingface(file_path):
    filename = os.path.basename(file_path)
    api.upload_file(
        path_or_fileobj=file_path,
        path_in_repo=f"compressed_videos/{filename}",
        repo_id=HF_REPO_ID,
        repo_type="dataset",
    )
    return f"https://huggingface.co/datasets/{HF_REPO_ID}/resolve/main/compressed_videos/{filename}"

# Fungsi utama untuk menangani input video
def process_video(video, quality, mode):
    input_video_path = video  # Karena `type="filepath"`, video adalah path, bukan objek file

    # Periksa ukuran file (500MB - 12GB)
    file_size_gb = os.path.getsize(input_video_path) / (1024 ** 3)
    if file_size_gb < 1:
        return "❌ Video terlalu kecil! Harus minimal 500 MB."
    elif file_size_gb > 12:
        return "❌ Video terlalu besar! Maksimal 12 GB."

    # Kompresi video
    compressed_video_path = compress_video(input_video_path, quality, mode)

    if not os.path.exists(compressed_video_path):
        return "❌ Gagal mengompresi video!"

    # Unggah ke Hugging Face
    download_url = upload_to_huggingface(compressed_video_path)
    
    return f"✅ Video berhasil dikompresi!\n\n🔗 [Unduh Video Terkompresi]({download_url})"

# UI dengan Gradio
with gr.Blocks() as demo:
    gr.Markdown("# 🎥 Video Compressor - Hugging Face API")
    gr.Markdown("Unggah video (1GB-12GB) dan pilih kualitas kompresi.")

    video_input = gr.File(label="Unggah Video (MP4, AVI, MOV)", type="filepath")
    quality = gr.Radio(["High", "Medium", "Low"], label="Tingkat Kompresi", value="Medium")
    mode = gr.Radio(["Normal", "High Resolution - Low Capacity"], label="Mode Kompresi", value="Normal")
    compress_button = gr.Button("Kompres Video")
    output_link = gr.Markdown("")

    compress_button.click(process_video, inputs=[video_input, quality, mode], outputs=output_link)

# Menjalankan aplikasi
if __name__ == "__main__":
    demo.launch()