"""Environment-driven configuration (handoff §10, §13).

All config flows through env vars so the SAME code runs as a plain process now and, later, as a
StartOS s9pk daemon (which injects these via the daemon's `exec.env` from a `store.json` FileModel).
A local `.env` (gitignored) is loaded for convenience during the pilot.

Live values confirmed against the operator's gateway 2026-06-07 (GET /api/status,/api/endpoints):
  gateway  = https://192.168.1.72:62419  (self-signed → SPARK_VERIFY_TLS=false)
  LLM      = RedHatAI/Qwen3.6-35B-A3B-NVFP4
  embed    = BAAI/bge-m3 (1024-d)         rerank = BAAI/bge-reranker-v2-m3
  ASR      = nvidia/parakeet-tdt-0.6b-v3  diarizer = nvidia/diar_sortformer_4spk-v1
"""
from __future__ import annotations

import os
from dataclasses import dataclass
from pathlib import Path


def _load_dotenv(path: str = ".env") -> None:
    """Minimal .env loader (no dependency): KEY=VALUE lines populate os.environ if not already set."""
    p = Path(path)
    if not p.exists():
        return
    for line in p.read_text().splitlines():
        line = line.strip()
        if not line or line.startswith("#") or "=" not in line:
            continue
        key, _, val = line.partition("=")
        os.environ.setdefault(key.strip(), val.strip().strip('"').strip("'"))


def _env(key: str, default: str | None = None) -> str | None:
    return os.environ.get(key, default)


@dataclass(frozen=True)
class Config:
    spark_control_url: str
    spark_verify_tls: bool
    spark_timeout_s: float
    audio_concurrency: int   # global in-flight cap across BOTH parakeet audio endpoints (sit at 2, ceiling 3)

    local_llm_model: str
    embed_model: str
    transcribe_model: str

    anthropic_api_key: str | None
    frontier_model: str

    # Extraction backend: 'local' (Qwen via Spark Control, default) | 'gemini' (batch overflow/fallback, §scaling)
    extraction_backend: str
    gemini_api_key: str | None
    gemini_model: str

    fmp_api_key: str | None
    edgar_user_agent: str

    data_dir: Path
    database_url: str
    audio_cache_dir: Path

    ui_port: int
    log_level: str

    @classmethod
    def from_env(cls) -> "Config":
        _load_dotenv()
        data_dir = Path(_env("DATA_DIR", "./data") or "./data")
        return cls(
            spark_control_url=_env("SPARK_CONTROL_URL", "https://192.168.1.72:62419") or "",
            spark_verify_tls=(_env("SPARK_VERIFY_TLS", "false") or "false").lower() == "true",
            spark_timeout_s=float(_env("SPARK_TIMEOUT_S", "180") or "180"),
            audio_concurrency=min(3, max(1, int(_env("AUDIO_CONCURRENCY", "2") or "2"))),
            local_llm_model=_env("LOCAL_LLM_MODEL", "RedHatAI/Qwen3.6-35B-A3B-NVFP4") or "",
            embed_model=_env("EMBED_MODEL", "BAAI/bge-m3") or "",
            transcribe_model=_env("TRANSCRIBE_MODEL", "nvidia/parakeet-tdt-0.6b-v3") or "",
            anthropic_api_key=_env("ANTHROPIC_API_KEY"),
            frontier_model=_env("FRONTIER_MODEL", "claude-opus-4-8") or "",
            extraction_backend=_env("EXTRACTION_BACKEND", "local") or "local",
            gemini_api_key=_env("GEMINI_API_KEY"),
            gemini_model=_env("GEMINI_MODEL", "gemini-2.5-flash") or "",
            fmp_api_key=_env("FMP_API_KEY"),
            edgar_user_agent=_env("EDGAR_USER_AGENT", "Ten31 Research grant@ten31.xyz") or "",
            data_dir=data_dir,
            database_url=_env("DATABASE_URL", "") or "",
            audio_cache_dir=Path(_env("AUDIO_CACHE_DIR", str(data_dir / "audio-cache")) or "audio-cache"),
            ui_port=int(_env("UI_PORT", "8000") or "8000"),
            log_level=_env("LOG_LEVEL", "INFO") or "INFO",
        )

    @property
    def db_path(self) -> Path:
        prefix = "sqlite:///"
        if self.database_url.startswith(prefix):
            return Path(self.database_url[len(prefix):])
        return self.data_dir / "signal.db"


def load_config() -> Config:
    return Config.from_env()