"""Central configuration: endpoints, paths, crawl politeness, model choice."""

from __future__ import annotations

import os
from pathlib import Path

# --- Wiki endpoints ---------------------------------------------------------
# Override WIKI_KB_HOST to re-point this KB at a different MediaWiki (scaffolding
# rewrites the literal default below for a new wiki).
WIKI_HOST = os.environ.get("WIKI_KB_HOST", "https://ck3.paradoxwikis.com").rstrip("/")
# The API path varies by install: paradoxwikis / wiki.gg use /api.php, Wikipedia
# uses /w/api.php. The article URL pattern varies too: /{Title} vs /wiki/{Title}.
# Override both when re-pointing at a wiki that doesn't match the paradoxwikis layout.
API_URL = os.environ.get("WIKI_KB_API_URL", f"{WIKI_HOST}/api.php")
PAGE_URL_TEMPLATE = os.environ.get("WIKI_KB_PAGE_URL", f"{WIKI_HOST}/{{title}}")

# Namespace 0 is the main (content) namespace.
CONTENT_NAMESPACE = 0

# Which page source to use: "mediawiki" (an open api.php — always preferred) or
# "html" (sitemap.xml + content-container extraction, for wikis with no API at all).
# scripts/detect_wiki.py probes a host and reports which applies.
SOURCE_KIND = os.environ.get("WIKI_KB_SOURCE", "mediawiki")
SITEMAP_URL = os.environ.get("WIKI_KB_SITEMAP", f"{WIKI_HOST}/sitemap.xml")

# --- Subpage policy -----------------------------------------------------------
# Whether "A/B" titles are noise or content. This is PER WIKI and must be measured,
# never assumed: on the CK3 wiki subpages are total-conversion mods (reject), while on
# the KCD wiki they are the sequel's pages -- "Alchemy/KCD2" -- so rejecting them
# deletes 441 pages of exactly the content you want (keep).
#   Counter(t.rsplit("/", 1)[-1] for t in titles if "/" in t)
# answers it in one API pass.
SUBPAGE_POLICY = os.environ.get("WIKI_KB_SUBPAGES", "reject")
# Subpage tails dropped even when the policy is "keep" (e.g. "loc" localisation dumps).
NOISE_SUBPAGE_TAILS = tuple(
    t.strip().lower() for t in os.environ.get("WIKI_KB_NOISE_TAILS", "").split(",") if t.strip()
)

# --- Editions / variants ------------------------------------------------------
# Some wikis cover two editions of one subject in a single namespace (a game and its
# sequel, two versions of a product). Declare them as "name:PREFIX" pairs, MOST
# SPECIFIC FIRST -- ordering is what lets "KCD" mean edition 1 without also matching
# "KCD2". A page matches a variant if its title ends "/PREFIX" or a category starts
# with PREFIX. Empty (the default) disables variant tagging entirely.
VARIANTS = tuple(
    (part.split(":", 1)[0].strip(), part.split(":", 1)[1].strip())
    for part in os.environ.get("WIKI_KB_VARIANTS", "").split(",")
    if ":" in part
)
# Default search scope. "any" returns everything; a variant name excludes the OTHER
# variants while always keeping pages tagged "both" or "unknown".
DEFAULT_VARIANT = os.environ.get("WIKI_KB_DEFAULT_VARIANT", "any")

# Total-conversion mod pages live in ns0 as subpages ("CK3AGOT/Dragon") or under
# these top-level prefixes. They are not base-game mechanics and pollute retrieval,
# so the scraper skips them (any title containing "/" is also treated as a mod/subpage).
_DEFAULT_MOD_PREFIXES = (
    "ck3agot",
    "lotr",
    "elder kings",
    "after the end",
    "the fallen eagle",
    "fallen eagle",
    "godherja",
    "princes of darkness",
    "rice",
    "realms in exile",
    "a game of thrones",
    "when the world stopped making sense",
    "more bookmarks",
)
# Override per-wiki with WIKI_KB_MOD_PREFIXES (comma-separated). Branchless so the
# import line is always exercised regardless of whether the env var is set.
MOD_TITLE_PREFIXES = tuple(
    p.strip().lower()
    for p in os.environ.get("WIKI_KB_MOD_PREFIXES", ",".join(_DEFAULT_MOD_PREFIXES)).split(",")
    if p.strip()
)

# --- Politeness / crawl -----------------------------------------------------
# Identify the bot honestly with a contact, per wiki etiquette.
# MediaWiki API:Etiquette requires a descriptive User-Agent with a real contact.
# Set WIKI_KB_CONTACT — the placeholder is deliberately obvious so an unconfigured
# run is embarrassing rather than silently anonymous.
CONTACT = os.environ.get("WIKI_KB_CONTACT", "UNCONFIGURED-set-WIKI_KB_CONTACT")
USER_AGENT = f"wiki-kb/0.1 (personal offline RAG mirror; contact: {CONTACT})"

# Tool prefix for the MCP server: <namespace>_search / _get_page / _list_pages.
MCP_NAMESPACE = os.environ.get("WIKI_KB_NAMESPACE", "wiki")
# Minimum seconds between requests (single-flight, ~1 req/s).
REQUEST_INTERVAL_S = 1.0
# maxlag tells MediaWiki to reject our request if replication lag is high,
# so we back off instead of adding load. See MediaWiki API:Etiquette.
MAXLAG = 5
REQUEST_TIMEOUT_S = 30.0
MAX_RETRIES = 5
BACKOFF_BASE_S = 2.0  # exponential: BACKOFF_BASE ** attempt

# --- Paths ------------------------------------------------------------------
# WIKI_KB_ROOT isolates a KB's generated data (corpus/index/manifest) — lets one
# codebase serve multiple wikis by pointing at different roots. Branchless default.
_DEFAULT_ROOT = Path(__file__).resolve().parent.parent
ROOT = Path(os.environ.get("WIKI_KB_ROOT", str(_DEFAULT_ROOT)))
CORPUS_DIR = ROOT / "corpus"
INDEX_DIR = ROOT / "index"
DB_PATH = INDEX_DIR / "wiki.db"
EMBEDDINGS_PATH = INDEX_DIR / "embeddings.npy"
MANIFEST_PATH = ROOT / "manifest.json"

# --- Chunking ---------------------------------------------------------------
CHUNK_TARGET_CHARS = 2000  # ~500 tokens
CHUNK_OVERLAP_CHARS = 200
# Section headings excluded from the index (the page is still mirrored in full and
# still served by *_get_page). Wikis carry per-page boilerplate sections that are
# both expensive to embed and harmful to retrieval — on the KCD wiki, "Other
# languages" tables of localized UI names were 7% of all chunks and repeated every
# page's title in eight languages. Empty by default; set per wiki after inspecting
# the section histogram. Compared case-insensitively.
NOISE_SECTIONS = frozenset(
    s.strip().lower() for s in os.environ.get("WIKI_KB_NOISE_SECTIONS", "").split(",") if s.strip()
)

# --- Embeddings -------------------------------------------------------------
EMBED_MODEL = "BAAI/bge-small-en-v1.5"  # 384-dim, CPU-friendly via fastembed
EMBED_DIM = 384
EMBED_BATCH_SIZE = 32


def _parse_core_spec(spec: str, total: int) -> set[int]:
    """Parse "0-3,8" into a set of core ids clamped to [0, total)."""
    cores: set[int] = set()
    for part in spec.split(","):
        part = part.strip()
        if not part:
            continue
        if "-" in part:
            lo, hi = part.split("-", 1)
            cores.update(range(int(lo), int(hi) + 1))
        else:
            cores.add(int(part))
    return {c for c in cores if 0 <= c < total}


def _allowed_cores(total: int, reserved: set[int]) -> list[int]:
    """Cores usable by heavy jobs = all minus reserved (never empty)."""
    allowed = sorted(set(range(total)) - reserved)
    return allowed or list(range(total))


# --- CPU isolation ----------------------------------------------------------
# The bottleneck is core *contention* with the foreground game, not thread count.
# Keep RESERVED_CORES free for the game and let heavy jobs use every other core
# fully. Override WIKI_KB_RESERVED_CORES (e.g. "0-3" or "8,9"); set "" to use all cores.
TOTAL_CPUS = os.cpu_count() or 4
RESERVED_CORES = _parse_core_spec(os.environ.get("WIKI_KB_RESERVED_CORES", "0-3"), TOTAL_CPUS)
ALLOWED_CORES = _allowed_cores(TOTAL_CPUS, RESERVED_CORES)
# GENTLE BY DEFAULT: a running game floats across ALL cores, so heavy background
# work drops FPS no matter which cores it "owns" — nice only softens it. Default to
# a single-threaded, single-worker build (~1 core) pinned off RESERVED_CORES and
# niced. When the game is CLOSED, set WIKI_KB_EMBED_PARALLEL=<n> for a fast build.
EMBED_PARALLEL = int(os.environ.get("WIKI_KB_EMBED_PARALLEL", "1"))
EMBED_THREADS = int(os.environ.get("WIKI_KB_EMBED_THREADS", "1"))
# Lower scheduling priority so the game still wins on any shared core.
NICE_INCREMENT = int(os.environ.get("WIKI_KB_NICE", "10"))

# --- Retrieval --------------------------------------------------------------
RRF_K = 60  # Reciprocal Rank Fusion constant
DEFAULT_TOP_K = 8
CANDIDATE_POOL = 40  # per-retriever candidates before fusion


def page_url(title: str) -> str:
    """Public wiki URL for a page title."""
    return PAGE_URL_TEMPLATE.format(title=title.replace(" ", "_"))