"""Configuration loaded from environment / .env.

Secrets never reach the browser. The frontend talks only to this local
backend; the backend holds the GitHub PAT and Fireworks key.
"""

import os
from functools import lru_cache
from pathlib import Path

from dotenv import load_dotenv

load_dotenv()

_REPO_ROOT = Path(__file__).resolve().parent.parent
_CACHE_HOME = Path.home() / ".cache" / "pr-reviewer"


class Config:
    # --- GitHub ---
    # Either provide GITHUB_TOKEN (a PAT) here, or leave it blank to fall
    # back to `gh auth token` from your local gh CLI (see github_client.py).
    GITHUB_TOKEN: str = os.getenv("GITHUB_TOKEN", "").strip()
    GITHUB_ORG: str = os.getenv("GITHUB_ORG", "Sea-Haven-Industries").strip()
    # The search filter that defines the review queue.
    PR_SEARCH_FILTER: str = os.getenv(
        "PR_SEARCH_FILTER",
        "is:pr state:open archived:false sort:updated-desc org:Sea-Haven-Industries",
    ).strip()
    # Cap how many PRs we pull per refresh. GitHub search returns at most 100
    # per page; PRs beyond that are not paginated (fine at current org volume).
    MAX_PRS: int = int(os.getenv("MAX_PRS", "100"))
    # Skip diffs larger than this many bytes (keeps token cost sane).
    MAX_DIFF_BYTES: int = int(os.getenv("MAX_DIFF_BYTES", "120000"))

    # --- Fireworks (OpenAI-compatible endpoint) ---
    FIREWORKS_API_KEY: str = os.getenv("FIREWORKS_API_KEY", "").strip()
    FIREWORKS_BASE_URL: str = os.getenv(
        "FIREWORKS_BASE_URL", "https://api.fireworks.ai/inference/v1"
    ).strip()
    # Swap this to any Fireworks model id you like. Coding-strong defaults:
    #   accounts/fireworks/models/deepseek-v4-pro
    #   accounts/fireworks/models/kimi-k2p6
    FIREWORKS_MODEL: str = os.getenv(
        "FIREWORKS_MODEL", "accounts/fireworks/models/deepseek-v4-pro"
    ).strip()
    FIREWORKS_TEMPERATURE: float = float(os.getenv("FIREWORKS_TEMPERATURE", "0.2"))
    FIREWORKS_MAX_TOKENS: int = int(os.getenv("FIREWORKS_MAX_TOKENS", "4000"))

    # --- Review behavior ---
    # If a PR author's login is in this list (case-insensitive), the review
    # body will @-mention them. Handles the @openswe bot case.
    MENTION_AUTHORS: list[str] = [
        a.strip().lower()
        for a in os.getenv("MENTION_AUTHORS", "openswe").split(",")
        if a.strip()
    ]

    HOST: str = os.getenv("HOST", "127.0.0.1")
    PORT: int = int(os.getenv("PORT", "8765"))

    # --- Background auto-review worker ---
    # Seconds between poll cycles. The worker fetches the queue, then pre-reviews
    # any new or changed non-draft PR so results are ready before you open them.
    POLL_INTERVAL: int = int(os.getenv("POLL_INTERVAL", "300"))
    # How many PRs to review in parallel per cycle. Kept low for a single-user
    # tool to stay well under Fireworks rate limits.
    WORKER_CONCURRENCY: int = int(os.getenv("WORKER_CONCURRENCY", "2"))
    # Give up auto-retrying a PR that keeps failing until its diff changes.
    MAX_REVIEW_ATTEMPTS: int = int(os.getenv("MAX_REVIEW_ATTEMPTS", "3"))
    # SQLite cache of pre-computed reviews. Absolute path resolved from the repo
    # root so it lands in the same place regardless of the working directory.
    CACHE_DB: str = os.getenv("CACHE_DB", str(_REPO_ROOT / "pr_cache.db"))

    # --- Engineering-handbook grounding ---
    # When enabled, the reviewer is fed a distilled digest of the Sea Haven
    # engineering-handbook conventions, refreshed daily from an app-managed clone.
    HANDBOOK_ENABLED: bool = os.getenv("HANDBOOK_ENABLED", "true").lower() in (
        "1",
        "true",
        "yes",
        "on",
    )
    HANDBOOK_REPO_URL: str = os.getenv(
        "HANDBOOK_REPO_URL",
        "https://github.com/Sea-Haven-Industries/engineering-handbook.git",
    )
    # App-managed clone + digest cache, kept outside the repo (in ~/.cache).
    HANDBOOK_CACHE_DIR: str = os.getenv(
        "HANDBOOK_CACHE_DIR", str(_CACHE_HOME / "handbook")
    )
    HANDBOOK_DIGEST_PATH: str = os.getenv(
        "HANDBOOK_DIGEST_PATH", str(_CACHE_HOME / "handbook_digest.json")
    )
    # Re-pull and re-distill the handbook at most this often.
    HANDBOOK_REFRESH_HOURS: int = int(os.getenv("HANDBOOK_REFRESH_HOURS", "24"))


@lru_cache
def get_config() -> Config:
    return Config()