import sys
import os
from pathlib import Path
import subprocess
import gradio as gr

# --------------------------
# 关键修复：添加项目根目录到 Python 路径
# --------------------------
# 获取当前文件（app.py）的父目录（Hugging Face Space 工作目录为 /app）
project_root = Path(__file__).parent.parent  # 若 app.py 在 /app 目录下，需向上两级
sys.path.insert(0, str(project_root))  # 确保优先搜索项目根目录

# --------------------------
# 导入 kling 模块（修复后）
# --------------------------
try:
    from kling.core import VideoWatermarkRemover
except ImportError as e:
    raise RuntimeError(
        f"导入 kling 模块失败：{str(e)}\n"
        "请检查：\n"
        "1. 子模块是否已通过 `git submodule update --init --recursive` 初始化？\n"
        "2. 项目根目录是否正确添加到 sys.path？（当前路径：{project_root}）"
    )

# --------------------------
# 视频处理函数
# --------------------------
def process_video(input_video, progress=gr.Progress()):
    try:
        # 保存输入视频到临时文件
        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as f:
            f.write(input_video.read())
            input_path = f.name
        progress(0.1, desc="输入视频已保存")

        # 检查 FFmpeg
        subprocess.run(["ffmpeg", "-version"], check=True, capture_output=True)
        progress(0.2, desc="FFmpeg 可用")

        # 初始化模型
        model_path = str(project_root / "kling" / "models" / "watermark_remover.pth")
        remover = VideoWatermarkRemover(device="cpu", model_path=model_path)
        progress(0.4, desc="模型加载完成")

        # 执行去水印
        output_filename = f"processed_{Path(input_path).stem}.mp4"
        output_path = os.path.join(tempfile.gettempdir(), output_filename)
        remover.remove_watermark(input_path=input_path, output_path=output_path)
        progress(0.9, desc="去水印完成")

        # 生成下载链接
        download_link = f"/files/{output_filename}"
        return output_path, download_link

    except Exception as e:
        return f"❌ 处理失败：{str(e)}", None

# --------------------------
# Gradio 界面配置
# --------------------------
with gr.Blocks(title="KLing 视频去水印工具") as demo:
    gr.Markdown("# 🚀 KLing 视频去水印工具")
    gr.Markdown("上传视频后自动处理并支持下载")

    with gr.Row():
        input_video = gr.Video(
            label="输入视频",
            type="filepath",
            max_file_size=200 * 1024 * 1024  # 200MB 限制
        )

    with gr.Row():
        output_video = gr.Video(label="输出视频", interactive=False)
        download_btn = gr.Button("⬇️ 下载结果", variant="secondary", interactive=False)

    submit_btn = gr.Button("开始处理")
    spinner = gr.Spinner(visible=False)

    # 绑定处理逻辑
    def handle_submit(input_video):
        spinner.visible = True
        output_path, download_path = process_video(input_video)
        spinner.visible = False
        if download_path:
            output_video.value = output_path
            download_btn.interactive = True
            return output_video, download_btn
        else:
            output_video.value = None
            download_btn.interactive = False
            return output_video, download_btn

    submit_btn.click(handle_submit, inputs=input_video, outputs=[output_video, download_btn])

if __name__ == "__main__":
    # 本地调试
    # demo.launch(debug=True, server_port=7860)
    pass