#!/usr/bin/env python3
"""
视频拆分服务命令行接口
"""

from typing import Dict, Any
from dataclasses import asdict

from .types import DetectionConfig, DetectorType
from .service import VideoSplitterService
from python_core.utils.commander import JSONRPCCommander


class VideoSplitterCommander(JSONRPCCommander):
    """视频拆分服务命令行接口"""

    def __init__(self):
        self.service = None
        super().__init__("video_splitter")

    def _register_commands(self) -> None:
        """注册命令"""
        # 注册analyze命令
        self.register_command(
            name="analyze",
            description="分析视频场景",
            required_args=["video_path"],
            optional_args={
                "threshold": {"type": float, "default": 30.0, "description": "检测阈值"},
                "detector": {"type": str, "default": "content", "choices": ["content", "threshold"], "description": "检测器类型"},
                "min-scene-length": {"type": float, "default": 1.0, "description": "最小场景长度（秒）"},
                "output-base": {"type": str, "default": None, "description": "输出基础目录"}
            }
        )

        # 注册detect_scenes命令
        self.register_command(
            name="detect_scenes",
            description="检测视频场景（仅返回场景信息）",
            required_args=["video_path"],
            optional_args={
                "threshold": {"type": float, "default": 30.0, "description": "检测阈值"},
                "detector": {"type": str, "default": "content", "choices": ["content", "threshold"], "description": "检测器类型"},
                "min-scene-length": {"type": float, "default": 1.0, "description": "最小场景长度（秒）"},
                "output-base": {"type": str, "default": None, "description": "输出基础目录"}
            }
        )

    def _setup_service(self, output_base: str = None) -> None:
        """设置服务"""
        if self.service is None:
            self.service = VideoSplitterService(output_base_dir=output_base)

    def execute_command(self, command: str, args: Dict[str, Any]) -> Any:
        """执行命令"""
        # 设置服务
        self._setup_service(args.get("output_base"))

        # 创建配置
        config = DetectionConfig(
            threshold=args.get("threshold", 30.0),
            detector_type=DetectorType(args.get("detector", "content")),
            min_scene_length=args.get("min_scene_length", 1.0)
        )

        video_path = args["video_path"]

        if command == "analyze":
            # 完整的视频分析
            result = self.service.analyze_video(video_path, config)
            return result.to_dict()

        elif command == "detect_scenes":
            # 仅检测场景
            result = self.service.analyze_video(video_path, config)

            # 只返回场景信息
            scenes_result = {
                "success": result.success,
                "video_path": result.video_path,
                "total_scenes": result.total_scenes,
                "scenes": [asdict(scene) for scene in result.scenes],
                "detection_settings": asdict(config),
                "detection_time": result.analysis_time
            }

            if not result.success:
                scenes_result["error"] = result.error

            return scenes_result

        else:
            raise ValueError(f"Unknown command: {command}")

def main():
    """主函数"""
    commander = VideoSplitterCommander()
    commander.run()

if __name__ == "__main__":
    main()