"""설정 로딩 — config.yaml + credentials.env"""

import os
from pathlib import Path

import yaml
from pydantic import BaseModel


class UploadConfig(BaseModel):
    max_bytes: int = 100_000_000
    content_length_slack_ratio: float = 1.05
    stream_chunk_bytes: int = 1_048_576
    # orphan cleanup (`*.uploading` — 크래시/abort 후 잔존물)
    orphan_max_age_sec: int = 3600
    cleanup_warn_threshold: int = 10


class AIModelConfig(BaseModel):
    endpoint: str
    model: str
    max_tokens: int = 4096
    timeout: int = 60
    daily_budget_usd: float | None = None
    require_explicit_trigger: bool = False
    # B-0: 4B/26B 에 부여한 실사용 컨텍스트 상한 (char). triage=120k, primary=260k.
    # classify_worker 가 에스컬레이션 판정 시 참고. 0/None 이면 상한 무시.
    context_char_limit: int | None = None


class DeepSummaryBacklogConfig(BaseModel):
    """B-1 R2 — deep_summary enqueue 폭발 억제 임계치."""
    ratio_threshold: float = 0.3     # 지난 window 의 deep_n/classify_n
    pending_threshold: int = 5       # deep_summary pending+processing
    window_minutes: int = 30


class AIConfig(BaseModel):
    gateway_endpoint: str
    # B-0: 3-tier routing. triage(4B) 상시, primary(26B) escalation-only, fallback(4B) 최후.
    triage: AIModelConfig
    primary: AIModelConfig
    fallback: AIModelConfig
    premium: AIModelConfig
    embedding: AIModelConfig
    rerank: AIModelConfig
    # Phase 3.5a: exaone classifier (optional — 없으면 score-only gate)
    classifier: AIModelConfig | None = None
    # Phase 3.5b: exaone verifier (optional — 없으면 grounding-only)
    verifier: AIModelConfig | None = None
    # Legacy: vision 슬롯 (현재 사용처 0 — Document Server 는 OCR/STT 별도 서비스).
    # 제거 진행 중이므로 optional 로 관대한 로딩 유지.
    vision: AIModelConfig | None = None
    # B-1 R2: backlog guard 임계치
    deep_summary_backlog: DeepSummaryBacklogConfig = DeepSummaryBacklogConfig()


class Settings(BaseModel):
    # DB
    database_url: str = ""

    # AI
    ai: AIConfig | None = None

    # NAS
    nas_mount_path: str = "/documents"
    nas_pkm_root: str = "/documents/PKM"

    # 인증
    jwt_secret: str = ""
    totp_secret: str = ""

    # Phase 3.5: eval runner shared secret — X-Source=eval / X-Eval-Case-Id 헤더 신뢰 검증.
    # 비어있으면 모든 eval 헤더 거부 (부재 = 비활성).
    eval_runner_token: str = ""

    # kordoc
    kordoc_endpoint: str = "http://kordoc-service:3100"

    # OCR (Surya)
    ocr_endpoint: str = "http://ocr-service:3200"

    # STT (faster-whisper, §3)
    stt_endpoint: str = "http://stt-service:3300"

    # §3 file_watcher: Roon 음원 경로 (prefix match 로 skip).
    # 빈 문자열이면 skip 없음. 예: "/documents/PKM/../Music/roon-library" 또는
    # NFS 경유 별도 마운트된 Roon 라이브러리.
    roon_library_path: str = ""

    # 분류 체계
    taxonomy: dict = {}
    document_types: list[str] = []

    # 업로드 한도 (authoritative policy)
    upload: UploadConfig = UploadConfig()


def load_settings() -> Settings:
    """config.yaml + 환경변수에서 설정 로딩"""
    # 환경변수 (docker-compose에서 주입)
    database_url = os.getenv("DATABASE_URL", "")
    jwt_secret = os.getenv("JWT_SECRET", "")
    totp_secret = os.getenv("TOTP_SECRET", "")
    eval_runner_token = os.getenv("EVAL_RUNNER_TOKEN", "")
    kordoc_endpoint = os.getenv("KORDOC_ENDPOINT", "http://kordoc-service:3100")
    ocr_endpoint = os.getenv("OCR_ENDPOINT", "http://ocr-service:3200")
    stt_endpoint = os.getenv("STT_ENDPOINT", "http://stt-service:3300")
    roon_library_path = os.getenv("ROON_LIBRARY_PATH", "")

    # config.yaml — Docker 컨테이너 내부(/app/config.yaml) 또는 프로젝트 루트
    config_path = Path("/app/config.yaml")
    if not config_path.exists():
        config_path = Path(__file__).parent.parent.parent / "config.yaml"
    ai_config = None
    nas_mount = "/documents"
    nas_pkm = "/documents/PKM"

    if config_path.exists():
        with open(config_path) as f:
            raw = yaml.safe_load(f)

        if "ai" in raw:
            ai_raw = raw["ai"]
            models = ai_raw.get("models", {})
            # B-0: triage 는 config.yaml 에 없을 수도 있는 신규 슬롯. 구버전 호환을 위해
            # 없으면 fallback 를 triage 로 대체 (동일 모델 재사용).
            triage_raw = models.get("triage") or models.get("fallback")
            if triage_raw is None:
                raise ValueError("config.yaml: ai.models.triage (or fallback) required")
            ai_config = AIConfig(
                gateway_endpoint=ai_raw.get("gateway", {}).get("endpoint", ""),
                triage=AIModelConfig(**triage_raw),
                primary=AIModelConfig(**models["primary"]),
                fallback=AIModelConfig(**models["fallback"]),
                premium=AIModelConfig(**models["premium"]),
                embedding=AIModelConfig(**models["embedding"]),
                rerank=AIModelConfig(**models["rerank"]),
                vision=(AIModelConfig(**models["vision"]) if "vision" in models else None),
                classifier=(
                    AIModelConfig(**models["classifier"]) if "classifier" in models else None
                ),
                verifier=(
                    AIModelConfig(**models["verifier"]) if "verifier" in models else None
                ),
                deep_summary_backlog=DeepSummaryBacklogConfig(
                    **ai_raw.get("deep_summary_backlog", {})
                ),
            )

        if "nas" in raw:
            nas_mount = raw["nas"].get("mount_path", nas_mount)
            nas_pkm = raw["nas"].get("pkm_root", nas_pkm)

    taxonomy = raw.get("taxonomy", {}) if config_path.exists() and raw else {}
    document_types = raw.get("document_types", []) if config_path.exists() and raw else []
    upload_cfg = (
        UploadConfig(**raw["upload"])
        if config_path.exists() and raw and "upload" in raw
        else UploadConfig()
    )

    return Settings(
        database_url=database_url,
        ai=ai_config,
        nas_mount_path=nas_mount,
        nas_pkm_root=nas_pkm,
        jwt_secret=jwt_secret,
        totp_secret=totp_secret,
        eval_runner_token=eval_runner_token,
        kordoc_endpoint=kordoc_endpoint,
        ocr_endpoint=ocr_endpoint,
        stt_endpoint=stt_endpoint,
        roon_library_path=roon_library_path,
        taxonomy=taxonomy,
        document_types=document_types,
        upload=upload_cfg,
    )


settings = load_settings()