import json
import uuid
from typing import List, Union, Optional, Dict

import pydantic
from pydantic import BaseModel, Field, ConfigDict, field_validator, ValidationError, model_validator, computed_field, \
    EmailStr

from ..cache_tasks.models import CacheTask, MediaSource, Base64File
from ..enums.models import MediaProtocol
from ..ffmpeg_tasks.models import WebhookNotify, FFMpegSliceSegment, FFMPEGSliceOptions
from ...utils.TimeUtils import TimeDelta


class ClusterCacheBatchRequest(BaseModel):
    tasks: List[CacheTask] = Field(description="批量操作任务,按列表顺序执行")

    model_config = ConfigDict()


class MediaSourcesRequest(BaseModel):
    inputs: List[MediaSource] = Field(examples=[
        [
            "vod://ap-shanghai/1500034234/1397757910405340824.mp4",
            "vod://ap-shanghai/1500034234/1397757910403699452.mp4",
            "s3://ap-northeast-2/modal-media-cache/concat/outputs/fc-01JTPV5FCNA74CKX3N3214XJPD/output.mp4"
        ]
    ], description="支持多种协议['vod://', 's3://'], 计划支持['cos://', http://]")

    @field_validator('inputs', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]) -> List[MediaSource]:
        if not v:
            raise ValidationError([
                {
                    'loc': ('inputs',),
                    'msg': "inputs为空",
                    'type': 'value_error',
                    'input': v
                }
            ], MediaSourcesRequest)
        result = []
        for item in v:
            if isinstance(item, str):
                result.append(MediaSource.from_str(item))
            elif isinstance(item, MediaSource):
                result.append(item)
            else:
                raise ValidationError([
                    {
                        'loc': ('inputs',),
                        'msg': "inputs元素类型错误: 必须是字符串",
                        'type': 'value_error',
                        'input': v
                    }
                ], MediaSourcesRequest)
        return result

    model_config = {
        "arbitrary_types_allowed": True
    }


class UploadBase64Request(BaseModel):
    file: Base64File = Field(description="上传的文件")
    prefix: Optional[str] = Field(description="文件存在的前缀目录", default=None)


class UploadPresignRequest(BaseModel):
    key: str = Field(description="上传文件的key", examples=['123/456/abc.mp4'])
    content_type: str = Field(description="上传对象的文件类型", examples=['video/mp4'])


class UploadMultipartPresignRequest(UploadPresignRequest):
    parts_count: int = Field(description="分片数量")


class MediaCopyRequest(BaseModel):
    class MediaCopyTask(BaseModel):
        source: MediaSource = Field(description="源媒体")
        destination: MediaSource = Field(description="")


class FFMPEGSliceTaskStatusRequest(BaseModel):
    taskId: str = Field(description="任务Id")


class BaseFFMPEGTaskRequest(BaseModel):
    webhook: Optional[WebhookNotify] = Field(description="Task webhook", default=None)


class FFMPEGSliceRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="待切割的媒体源")
    markers: List[FFMpegSliceSegment] = Field(description="按照时间顺序排序过的切割标记数组")
    options: FFMPEGSliceOptions = Field(default_factory=FFMPEGSliceOptions, description="输出质量选项")

    @field_validator('media', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGConcatRequest(BaseFFMPEGTaskRequest):
    medias: MediaSourcesRequest = Field(description="待合并的媒体源")


class FFMPEGExtractAudioRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="待提取音频的媒体源")

    @field_validator('media', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGCornerMirrorRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")

    @field_validator('media', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGBgmRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")
    bgm_media: MediaSource = Field(description="添加的BGM媒体源", alias="bgmMedia")

    @field_validator('media', mode='before')
    @classmethod
    def parse_media_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('bgm_media', mode='before')
    @classmethod
    def parse_bgm_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            media = MediaSource.from_str(v)
            if not media.file_extension in ['wav', 'mp3']:
                raise pydantic.ValidationError("必须使用符合规范的音频格式, 如wav或者mp3")
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGZoomLoopRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")
    duration: float = Field(description="放大缩小一个循环的持续时间秒数", default=6.0)
    zoom: float = Field(description="放大缩小系数", default=0.1)

    @field_validator('media', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGOverlayGifRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")
    gif: MediaSource = Field(description="叠加的特效gif")

    @field_validator('media', mode='before')
    @classmethod
    def parse_media_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(f"解析{type(v)}类型不支持")

    @field_validator('gif', mode='before')
    @classmethod
    def parse_fig_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            media = MediaSource.from_str(v)
            if not media.file_extension == 'gif':
                raise pydantic.ValidationError("必须使用.gif文件")
            return media
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGSubtitleOverlayRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")
    subtitle: Optional[MediaSource] = Field(default=None, description="需要叠加的字幕文件")
    embedded_subtitle: Optional[MediaSource] = Field(default=None, description="需要内嵌的字幕文件")
    fonts: Optional[List[MediaSource]] = Field(default=None, description="字幕文件内使用到的字体文件")

    @field_validator('media', mode='before')
    @classmethod
    def parse_media_input(cls, v: Union[str, MediaSource]) -> MediaSource:
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('subtitle', mode='before')
    @classmethod
    def parse_subtitle_input(cls, v: Union[str, MediaSource]) -> Optional[MediaSource]:
        if not v:
            return None
        if isinstance(v, str):
            media = MediaSource.from_str(v)
            if not media.file_extension in ['ass']:
                raise pydantic.ValidationError("必须使用标准字幕文件, 如.ass")
            return media
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('embedded_subtitle', mode='before')
    @classmethod
    def parse_embedded_subtitle_input(cls, v: Union[str, MediaSource]) -> Optional[MediaSource]:
        if not v:
            return None
        if isinstance(v, str):
            media = MediaSource.from_str(v)
            if not media.file_extension in ['vtt', 'srt', 'ass']:
                raise pydantic.ValidationError("必须使用标准字幕文件, 如.vtt/.srt/.ass")
            return media
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('fonts', mode='before')
    @classmethod
    def parse_font_input(cls, v: Union[str, MediaSource]) -> Optional[List[MediaSource]]:
        if not v:
            return None
        result = []
        for item in v:
            if isinstance(item, str):
                result.append(MediaSource.from_str(item))
            elif isinstance(item, MediaSource):
                result.append(item)
            else:
                raise pydantic.ValidationError("fonts元素类型错误: 必须是字符串")
        return result

    @model_validator(mode='after')
    def check_at_least_one(self):
        if self.subtitle is None and self.embedded_subtitle is None:
            raise pydantic.ValidationError("至少需要提供一个有效字幕")
        if self.subtitle is not None and self.fonts is None:
            raise pydantic.ValidationError("使用叠加字幕时需要指定使用的字体文件")
        return self


class FFMPEGMixBgmWithNoiseReduceRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="需要处理的媒体源")
    bgm: MediaSource = Field(description="需要添加的BGM媒体源")
    video_volume: float = Field(description="最终输出的视频音量系数", default=1.4)
    music_volume: float = Field(description="最终输出的BGM音量系数", default=0.1)
    noise_sample: Optional[MediaSource] = Field(description="常考噪音样本，如不指定将使用源视频的前2秒作为样本",
                                                default=None)

    @field_validator('media', mode='before')
    @classmethod
    def parse_media_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('bgm', mode='before')
    @classmethod
    def parse_bgm_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('noise_sample', mode='before')
    @classmethod
    def parse_sample_input(cls, v: Union[None, str, MediaSource]):
        if not v:
            return None
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGVideoLoopFillAudioRequest(BaseFFMPEGTaskRequest):
    video: MediaSource = Field(description="用来填充的视频素材")
    audio: MediaSource = Field(description="被填充的音频素材")

    @field_validator('video', mode='before')
    @classmethod
    def parse_video_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @field_validator('audio', mode='before')
    @classmethod
    def parse_audio_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGExtractFrameRequest(BaseFFMPEGTaskRequest):
    video: MediaSource = Field(description="提取帧画面的来源")
    seek_time: Optional[Union[str, int, float]] = Field(default=None, description="先跳转到视频对应时间再取首帧",
                                                        examples=["00:00:01.000", "5.4", "2"])
    frame_index: int = Field(description="提取的第几帧, 从1开始，默认为1", default=1)

    @field_validator('video', mode='before')
    @classmethod
    def parse_video_input(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)

    @computed_field(description="格式处理后的Seek Time")
    @property
    def prased_seek_time(self) -> 'TimeDelta':
        if self.seek_time is None:
            return None
        elif isinstance(self.seek_time, str):
            return TimeDelta.from_format_string(self.seek_time)
        elif isinstance(self.seek_time, int):
            return TimeDelta(seconds=self.seek_time)
        elif isinstance(self.seek_time, float):
            return TimeDelta(seconds=self.seek_time)
        else:
            raise TypeError("不支持的时间类型")

    model_config = {
        "arbitrary_types_allowed": True
    }


class ComfyTaskRequest(BaseFFMPEGTaskRequest):
    video_path: MediaSource = Field(
        default=None, description="视频源")
    start_time: str = Field(default="00:00:01.600", description="开始时间")
    filename_prefix: str = Field(default=str(uuid.uuid4()), description="生成文件名前缀")
    tts_text1: str = Field(default="好好看，这是我们家专门为女生定制的背心，", description="tts文本1")
    tts_text2: str = Field(default="", description="tts文本2")
    tts_text3: str = Field(default="", description="tts文本3")
    tts_text4: str = Field(default="", description="tts文本4")
    anchor_id: str = Field(default="dawan", description="讲话人ID")
    speed: float = Field(default=1, description="讲话语速")

    @field_validator('video_path', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            return MediaSource.from_str(v)
        elif isinstance(v, MediaSource):
            return v
        else:
            raise TypeError(v)


class FFMPEGStreamRecordRequest(BaseFFMPEGTaskRequest):
    stream_source: str = Field(description="直播源地址")
    first_segment_duration: int = Field(default=2,
                                        description="hls首个片段时长(秒), 首片段长度越小hls流能越快速开始播放")
    segment_duration: int = Field(default=10, description="hls片段时长(秒)")
    recording_timeout: int = Field(default=300, description="hls流无内容后等待的时长(秒)")
    monitor_timeout: int = Field(default=36000, description="录制监控最大时长(秒), 默认为10小时, 不可大于12小时",
                                 le=43200)


class GeminiRequest(BaseFFMPEGTaskRequest):
    media_hls_url: MediaSource = Field(default="", description="视频流录制HLS地址 hls://格式 需录制超过20分钟")
    product_cover_grid_uri_list: List[str] = Field(description="商品封面网格拼图URI列表")
    product_list: List[str] = Field(description="商品名列表(时间倒序)"),
    start_time: str = Field(default="00:00:00.000", description="开始时间(hls)")
    end_time: str = Field(default="00:20:00.000", description="结束时间(hls)")
    options: FFMPEGSliceOptions = Field(default=FFMPEGSliceOptions(), description="输出质量选项")
    scale: float = Field(default=0.85, description="视频尺寸缩放倍率")
    last_product_text: str = Field(default="", description="上一段视频结尾介绍的商品以及标签")

    @field_validator('media_hls_url', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            media_source = MediaSource.from_str(v)
            if media_source.protocol == MediaProtocol.hls:
                return media_source
            else:
                raise pydantic.ValidationError('media只支持hls格式的urn')
        elif isinstance(v, MediaSource):
            return v
        else:
            raise pydantic.ValidationError("media格式读取失败")


class GeminiRequestFirstOnly(BaseFFMPEGTaskRequest):
    product_cover_grid_uri_list: List[str] = Field(description="商品封面网格拼图URI列表")
    product_list: List[str] = Field(description="商品名列表(时间倒序)"),
    prompt_label: str = Field(default="production", description="使用的Langfuse Prompt Label")


class GeminiRequestSecondOnly(BaseFFMPEGTaskRequest):
    media_hls_url: MediaSource = Field(default="", description="视频流录制HLS地址 hls://格式 需录制超过20分钟")
    identified_product_list: List[Dict] = Field(description="第一阶段返回的识别商品及特征列表")
    start_time: str = Field(default="00:00:00.000", description="开始时间(hls)")
    end_time: str = Field(default="00:20:00.000", description="结束时间(hls)")
    options: FFMPEGSliceOptions = Field(default=FFMPEGSliceOptions(), description="输出质量选项")
    scale: float = Field(default=0.85, description="视频尺寸缩放倍率")
    prompt_label: str = Field(default="production", description="使用的Langfuse Prompt Label"),
    last_product_text: str = Field(default="", description="上一段视频结尾介绍的商品以及标签")

    @field_validator('media_hls_url', mode='before')
    @classmethod
    def parse_inputs_media_hls_url(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            media_source = MediaSource.from_str(v)
            if media_source.protocol == MediaProtocol.hls:
                return media_source
            else:
                raise pydantic.ValidationError('media只支持hls格式的urn')
        elif isinstance(v, MediaSource):
            return v
        else:
            raise pydantic.ValidationError("media格式读取失败")

    @field_validator("identified_product_list", mode="before")
    @classmethod
    def parse_inputs_identified_product_list(cls, v: str):
        if isinstance(v, str):
            return json.loads(v)
        else:
            raise pydantic.ValidationError("identified_product_list")


class MonitorLiveRoomProductRequest(BaseModel):
    cookie: str = Field(default="YOUR_COOKIE", description="用户网页版抖音Cookie/Your web version of Douyin Cookie")
    room_id: str = Field(default="", description="直播间room_id/Room room_id")
    author_id: str = Field(default="", description="作者id/Author id")


class MakeGridGeminiRequest(BaseFFMPEGTaskRequest):
    pic_info_list: List[Dict[str, str]] = Field(default=[],
                                                description="包含图片信息的字典列表，每个字典包含 \"title\" 和 \"cover\" 键")
    image_size: int = Field(default=450, description="单个图片网格的尺寸/像素")
    text_height: int = Field(default=40, description="文本框的高度/像素")
    font_size: int = Field(default=18, description="文本尺寸/像素")
    padding: int = Field(default=5, description="文本距离文本框边缘距离/像素")
    separator: int = Field(default=12, description="分割线宽度/像素")


class FFMPEGConvertStreamRequest(BaseFFMPEGTaskRequest):
    media: MediaSource = Field(description="待转换的媒体源")
    options: FFMPEGSliceOptions = Field(default_factory=FFMPEGSliceOptions, description="输出质量选项")

    @field_validator('media', mode='before')
    @classmethod
    def parse_inputs(cls, v: Union[str, MediaSource]):
        if isinstance(v, str):
            media_source = MediaSource.from_str(v)
            if media_source.protocol == MediaProtocol.hls:
                return media_source
            else:
                raise pydantic.ValidationError('media只支持hls格式的urn')
        elif isinstance(v, MediaSource):
            return v
        else:
            raise pydantic.ValidationError("media格式读取失败")


class NakamaLogin(BaseModel):
    email: EmailStr = Field(description="Bowong Echo(Nakama)的登录账号")
    password: str = Field(description="Bowong Echo(Nakama)的登录密码")