"""
视频处理模块
"""

import gradio as gr
from typing import List, Tuple, Optional

from .veo3_client import Veo3Client
from ..utils.file_utils import cleanup_temp_file


class VideoProcessor:
    """视频处理器类"""
    
    def __init__(self):
        self.client = None
    
    def set_api_key(self, api_key: str):
        """设置API密钥"""
        self.client = Veo3Client(api_key)
    
    def process_veo3_video(
        self, 
        prompt: str, 
        uploaded_files: List[str], 
        api_key: str, 
        aspect_ratio: str = "16:9", 
        watermark: str = "", 
        seeds: Optional[int] = None, 
        enable_fallback: bool = False, 
        progress: gr.Progress = None
    ) -> Tuple[Optional[str], str]:
        """
        处理Veo3视频生成的主函数
        """
        # 验证输入
        if not api_key or not api_key.strip():
            return None, "❌ Please enter API Key"

        if not prompt or not prompt.strip():
            return None, "❌ Please enter a prompt"

        # 设置客户端
        self.set_api_key(api_key.strip())

        # 图片是可选的，用于image-to-video
        image_urls = []
        file_paths = []
        
        print(f"DEBUG: uploaded_files = {uploaded_files}, type = {type(uploaded_files)}")
        
        if uploaded_files:
            # 确保是列表格式
            file_paths = uploaded_files if isinstance(uploaded_files, list) else [uploaded_files]
            # 验证图片数量
            if len(file_paths) > 1:
                return None, "❌ Maximum 1 image allowed for video generation"

        try:
            if progress:
                progress(0.1, desc="📤 Processing input...")

            # 如果有图片，上传到 KIE AI 并获取公开URL
            if file_paths:
                for i, file_path in enumerate(file_paths):
                    if progress:
                        progress(0.1 + (0.2 * i / len(file_paths)), desc=f"📤 Uploading image {i + 1}/{len(file_paths)}...")

                    success, result = self.client.upload_file(file_path)
                    if success:
                        image_urls.append(result)
                        # 上传成功后删除本地临时文件
                        cleanup_temp_file(file_path)
                    else:
                        return None, f"❌ Failed to upload image {i + 1}: {result}"

            if progress:
                progress(0.3, desc="🚀 Creating video generation task...")

            # 创建Veo3任务
            status_code, result = self.client.create_task(
                prompt.strip(), 
                image_urls, 
                aspect_ratio=aspect_ratio,
                watermark=watermark,
                seeds=seeds,
                enable_fallback=enable_fallback
            )

            if status_code != 200:
                return None, f"❌ Failed to create task: {result}"

            task_id = result
            if progress:
                progress(0.4, desc=f"📋 Task ID: {task_id}")

            if progress:
                progress(0.5, desc="⏳ Generating video, please wait...")

            # 轮询获取结果
            status_code, result = self.client.get_task_result(task_id)

            if status_code != 200:
                return None, f"❌ Video generation failed: {result}"

            if progress:
                progress(0.9, desc="📥 Processing video...")

            # 处理返回的视频URL
            if result:
                if progress:
                    progress(1.0, desc="✅ Complete!")
                return result, f"✅ Successfully generated video! Task ID: {task_id}"
            else:
                return None, "❌ No video URL received"

        except Exception as e:
            return None, f"❌ Error occurred during processing: {str(e)}"
        finally:
            # 最终清理：删除任何剩余的临时文件
            try:
                for file_path in file_paths:
                    cleanup_temp_file(file_path)
            except:
                pass