from __future__ import annotations

from functools import lru_cache
from pathlib import Path
from typing import Optional

from pydantic import AliasChoices, Field, field_validator, model_validator
from pydantic_settings import BaseSettings, SettingsConfigDict


def _fish_api_env_file() -> Path:
    """fish_api/.env — 与启动 cwd 无关，避免从仓库根跑 uvicorn 时读不到 .env。"""
    return Path(__file__).resolve().parents[1] / ".env"


def fish_repo_root() -> Path:
    # fish_api/app/settings.py -> parent[2] = repo root (contains FishMeasure/, fish_api/)
    return Path(__file__).resolve().parents[2]


def models_dir() -> Path:
    """仓库内统一权重目录（YOLO / DGCNN / PointNet / X3D / SAM 等），与 FishMeasure 代码目录解耦。"""
    return fish_repo_root() / "models"


def _default_stream_tmp() -> Path:
    return fish_repo_root() / "fish_api" / ".data" / "ingest"


def _default_media_root() -> Path:
    return fish_repo_root() / "fish_api" / ".data" / "media"


def _default_sqlite_path() -> Path:
    return fish_repo_root() / "fish_api" / ".data" / "app.db"


def _default_action_output_root() -> Path:
    return fish_repo_root() / "fish_api" / ".data" / "action_output"


def _default_measure_debug_log_dir() -> Path:
    """DGCNN 体重推算过程等可调试文本（与终端一致的 calculation log）。"""
    return fish_repo_root() / "fish_api" / ".data" / "logs" / "measure"


class Settings(BaseSettings):
    model_config = SettingsConfigDict(
        env_file=_fish_api_env_file(),
        env_file_encoding="utf-8",
        extra="ignore",
    )

    #: 对外可访问的 API 基址（无末尾 `/`），用于 biomass 等 JSON 里 `video_left` / `video_right` 的绝对 URL。环境变量：**PUBLIC_BASE_URL**
    public_base_url: str = Field(
        default="http://127.0.0.1:8000",
        validation_alias=AliasChoices("PUBLIC_BASE_URL", "public_base_url"),
    )

    ingest_api_key: str = ""

    stream_tmp_dir: Path = Field(default_factory=_default_stream_tmp)
    media_root: Path = Field(default_factory=_default_media_root)
    sqlite_path: Path = Field(default_factory=_default_sqlite_path)

    fish_measure_root: Path = fish_repo_root() / "FishMeasure"
    fish_action_root: Path = fish_repo_root() / "FishAction"

    #: FishMeasure 推理输出（与 SQLite、媒体缓存同属 fish_api/.data；启动脚本默认保留，设置 CLEAR_MEASURE_OUTPUT=1 可清空）
    measure_output_root: Path = fish_repo_root() / "fish_api" / ".data" / "measure_output"
    #: 体重推算过程等调试文本写入目录（默认 fish_api/.data/logs/measure）。**MEASURE_DEBUG_LOG_DIR**
    measure_debug_log_dir: Path = Field(
        default_factory=_default_measure_debug_log_dir,
        validation_alias=AliasChoices("MEASURE_DEBUG_LOG_DIR", "measure_debug_log_dir"),
    )
    #: 为 False 时不写入上述目录（仍打 logger）。**MEASURE_DEBUG_LOG_WRITE**
    measure_debug_log_write: bool = Field(
        default=True,
        validation_alias=AliasChoices("MEASURE_DEBUG_LOG_WRITE", "measure_debug_log_write"),
    )
    #: FishAction 侧预留目录（与 measure 对称；启动脚本默认保留，设置 CLEAR_ACTION_OUTPUT=1 可清空）
    action_output_root: Path = Field(default_factory=_default_action_output_root)

    python_fish_measure: str = ""
    python_fish_action: str = ""

    #: SAM/CUDA 设备（cuda 或 cpu）
    sam_device: str = "cuda"

    #: 为 True 时在视频右上角显示大型 weight/length 标签（10倍字体）
    predict_show_large_labels_at_top_right: bool = False

    #: FishMeasure 中 YOLO 置信度见 ``measure_yolo_conf`` / ``MEASURE_YOLO_CONF``；其余脚本内参数仍可在 FishMeasure 目录修改。
    #: FishAction 核心参数见 ``action_checkpoint`` 等。

    #: FishAction X3D 模型路径（不设则用 models/action_x3d/checkpoint_best.pt）
    action_checkpoint: Optional[str] = None

    #: 为 True 时复用已有 cloud/*.ply（传 --reuse-existing-clouds）
    #: 为 False 时强制重新生成点云（传 --no-reuse-existing-clouds）
    measure_reuse_existing_clouds: bool = True

    #: YOLO 检测置信度，传给 ``predict_weigth_from_svo2.py --conf``（与 FishMeasure ``run_predict_from_svo2_fish9.sh`` 等使用的 0.8 对齐）。**MEASURE_YOLO_CONF**
    measure_yolo_conf: float = Field(
        default=0.8,
        ge=0.0,
        le=1.0,
        validation_alias=AliasChoices("MEASURE_YOLO_CONF", "measure_yolo_conf"),
    )
    #: 传给 FishMeasure ``--filter-pointcloud``（默认开启，与 fish9 脚本对齐）。
    measure_filter_pointcloud: bool = Field(
        default=True,
        validation_alias=AliasChoices(
            "MEASURE_FILTER_POINTCLOUD", "measure_filter_pointcloud"
        ),
    )
    #: 传给 FishMeasure ``--use-density-filter``（默认开启，与 fish9 脚本对齐）。
    measure_use_density_filter: bool = Field(
        default=True,
        validation_alias=AliasChoices(
            "MEASURE_USE_DENSITY_FILTER", "measure_use_density_filter"
        ),
    )
    #: 传给 FishMeasure ``--use-pointcloud-classifier``（默认开启，与 fish9 脚本对齐）。
    measure_use_pointcloud_classifier: bool = Field(
        default=True,
        validation_alias=AliasChoices(
            "MEASURE_USE_POINTCLOUD_CLASSIFIER", "measure_use_pointcloud_classifier"
        ),
    )
    #: PointNet2 点云分类器阈值，传给 ``--pointcloud-classifier-threshold``。
    measure_pointcloud_classifier_threshold: float = Field(
        default=0.7,
        ge=0.0,
        le=1.0,
        validation_alias=AliasChoices(
            "MEASURE_POINTCLOUD_CLASSIFIER_THRESHOLD",
            "measure_pointcloud_classifier_threshold",
        ),
    )
    #: 点云分类器模型路径，传给 ``--pointcloud-classifier``。
    measure_pointcloud_classifier: Optional[Path] = Field(
        default=None,
        validation_alias=AliasChoices(
            "MEASURE_POINTCLOUD_CLASSIFIER", "measure_pointcloud_classifier"
        ),
    )
    #: 传给 FishMeasure ``--use-flatness-filter``（默认开启，与 fish9 脚本对齐）。
    measure_use_flatness_filter: bool = Field(
        default=True,
        validation_alias=AliasChoices(
            "MEASURE_USE_FLATNESS_FILTER", "measure_use_flatness_filter"
        ),
    )
    #: 平整度阈值，传给 ``--flatness-threshold``。
    measure_flatness_threshold: float = Field(
        default=55.0,
        validation_alias=AliasChoices(
            "MEASURE_FLATNESS_THRESHOLD", "measure_flatness_threshold"
        ),
    )

    # ── 体重聚合规则（传给 predict_weigth_from_svo2.py → test_dgcnn_weight_estimator.py） ──

    #: DGCNN top-K 帧数，传给 ``--weight-top-k``。**MEASURE_WEIGHT_TOP_K**
    measure_weight_top_k: int = Field(
        default=5,
        ge=1,
        validation_alias=AliasChoices("MEASURE_WEIGHT_TOP_K", "measure_weight_top_k"),
    )
    #: 按长度选 top-K，传给 ``--weight-top-by-length``。**MEASURE_WEIGHT_TOP_BY_LENGTH**
    measure_weight_top_by_length: bool = Field(
        default=True,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_TOP_BY_LENGTH", "measure_weight_top_by_length"
        ),
    )
    #: top-K 按长度选时，若 K 个平均长度 > 此值则切为按重量选，传给 ``--weight-length-switch-mm``。**MEASURE_WEIGHT_LENGTH_SWITCH_MM**
    measure_weight_length_switch_mm: float = Field(
        default=319.0,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_LENGTH_SWITCH_MM", "measure_weight_length_switch_mm"
        ),
    )
    #: 几何过滤：length > 此值的帧排除，传给 ``--weight-max-length-mm``（0 关闭）。**MEASURE_WEIGHT_MAX_LENGTH_MM**
    measure_weight_max_length_mm: float = Field(
        default=400.0,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_MAX_LENGTH_MM", "measure_weight_max_length_mm"
        ),
    )
    #: 几何过滤：PCA 长/宽 < 此值的帧排除，传给 ``--weight-min-length-width-ratio``（0 关闭）。**MEASURE_WEIGHT_MIN_LENGTH_WIDTH_RATIO**
    measure_weight_min_length_width_ratio: float = Field(
        default=1.5,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_MIN_LENGTH_WIDTH_RATIO", "measure_weight_min_length_width_ratio"
        ),
    )
    #: 全池均值模式，传给 ``--weight-average-all-after-filter``。**MEASURE_WEIGHT_AVERAGE_ALL_AFTER_FILTER**
    measure_weight_average_all_after_filter: bool = Field(
        default=False,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_AVERAGE_ALL_AFTER_FILTER", "measure_weight_average_all_after_filter"
        ),
    )
    #: 全池均值 > 此值时改用 max（规则 A），传给 ``--weight-average-all-fallback-max-if-mean-over-g``（0 关闭）。**MEASURE_WEIGHT_AVG_ALL_FALLBACK_MAX_G**
    measure_weight_avg_all_fallback_max_g: float = Field(
        default=400.0,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_AVG_ALL_FALLBACK_MAX_G", "measure_weight_avg_all_fallback_max_g"
        ),
    )
    #: 全池 candidates 均值 > 此值时改用 max（规则 B, 440g 保护），传给 ``--weight-mean-pool-fallback-max-if-over-g``（0 关闭）。**MEASURE_WEIGHT_MEAN_POOL_FALLBACK_MAX_G**
    measure_weight_mean_pool_fallback_max_g: float = Field(
        default=440.0,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_MEAN_POOL_FALLBACK_MAX_G", "measure_weight_mean_pool_fallback_max_g"
        ),
    )
    #: 异常值剔除开关，传给 ``--weight-remove-outliers``。**MEASURE_WEIGHT_REMOVE_OUTLIERS**
    measure_weight_remove_outliers: bool = Field(
        default=False,
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_REMOVE_OUTLIERS", "measure_weight_remove_outliers"
        ),
    )
    #: 异常值剔除方法（iqr / zscore），传给 ``--weight-outlier-method``。**MEASURE_WEIGHT_OUTLIER_METHOD**
    measure_weight_outlier_method: str = Field(
        default="iqr",
        validation_alias=AliasChoices(
            "MEASURE_WEIGHT_OUTLIER_METHOD", "measure_weight_outlier_method"
        ),
    )

    #: 非空时由 fish_api 在后台持续扫描该目录中的新 MP4 并跑 FishAction（与 ingest 共用 SQLite 最新结果）
    action_watch_dir: Optional[Path] = None
    action_watch_poll_interval: float = Field(default=2.0, ge=0.1)
    action_watch_stable_polls: int = Field(default=3, ge=1)
    action_watch_recursive: bool = False
    #: 状态管理：true=持久化到 SQLite（重启后记住），false=内存模式（重启后清空）
    action_watch_use_state_file: bool = True

    #: 优先作为「水上视频」源文件；未设置时在 ACTION_WATCH_DIR 取最新 .mp4（FishAction 输入）。**BIOMASS_WATER_VIDEO_SOURCE**
    biomass_water_video_source: Optional[Path] = None
    #: 发布到 MEDIA_ROOT 的 H.264 文件名。**BIOMASS_WATER_VIDEO_MEDIA_NAME**
    biomass_water_video_media_name: str = "biomass_water_surface.mp4"

    #: 优先作为「声呐视频」源文件；未设置时在 BIOMASS_SONAR_VIDEO_DIR 取最新 .mp4。**BIOMASS_SONAR_VIDEO_SOURCE**
    biomass_sonar_video_source: Optional[Path] = None
    #: 声呐 MP4 目录（与 ACTION_WATCH_DIR 独立，避免与水面视频混用）。**BIOMASS_SONAR_VIDEO_DIR**
    biomass_sonar_video_dir: Optional[Path] = None
    #: 是否在 SONAR_VIDEO_DIR 中递归查找 .mp4。**BIOMASS_SONAR_VIDEO_RECURSIVE**
    biomass_sonar_video_recursive: bool = False
    #: 发布到 MEDIA_ROOT 的 H.264 文件名。**BIOMASS_SONAR_VIDEO_MEDIA_NAME**
    biomass_sonar_video_media_name: str = "biomass_sonar.mp4"

    #: 非空时后台持续扫描该目录中的新 .svo2 并跑 FishMeasure（与 ingest 共用 SQLite 最新结果）
    measure_watch_dir: Optional[Path] = None
    measure_watch_poll_interval: float = Field(default=2.0, ge=0.1)
    measure_watch_stable_polls: int = Field(default=3, ge=1)
    measure_watch_recursive: bool = False
    #: 状态管理：true=持久化到 SQLite（重启后记住），false=内存模式（重启后清空）
    measure_watch_use_state_file: bool = True

    default_fish_species: str = "大黄鱼"

    @field_validator(
        "action_watch_dir",
        "biomass_water_video_source",
        "biomass_sonar_video_source",
        "biomass_sonar_video_dir",
        "measure_watch_dir",
        mode="before",
    )
    @classmethod
    def _empty_str_path_none(cls, v: object) -> object:
        if v is None:
            return None
        if isinstance(v, str) and not v.strip():
            return None
        return v

    @model_validator(mode="after")
    def _default_paths(self) -> "Settings":
        md = models_dir()
        if not self.action_checkpoint:
            object.__setattr__(
                self, "action_checkpoint", str(md / "action_x3d" / "checkpoint_best.pt")
            )
        if self.measure_pointcloud_classifier is None:
            object.__setattr__(
                self,
                "measure_pointcloud_classifier",
                self.fish_measure_root
                / "pointcloud_classifier"
                / "Pointnet_Pointnet2_pytorch"
                / "log"
                / "classification"
                / "fish_pointnet2_finetune"
                / "checkpoints"
                / "best_model.pth",
            )
        return self


@lru_cache
def get_settings() -> Settings:
    return Settings()