"""Bounded graph recall over current Memory cards; no model or approval side effects."""

from dataclasses import dataclass

from pydantic import BaseModel, ConfigDict, Field, model_validator

from .models import Card, Family, MemoryNotFound

PROJECTION_FORMAT = 2
MAX_SEEDS = 100
MAX_DEPTH = 2
MAX_LINKS_PER_CARD = 20
MAX_VISITED = 200
MAX_EDGES = 400
RRF_K = 60


class RecallScope(BaseModel):
    """Exact business scope/concepts and hierarchical physical context.

    Cards without dependencies are workspace-wide. A dependency applies to its
    database and every descendant of the schema/table/column it names.
    All physical fields must match the SAME dependency, never separate entries.
    """

    model_config = ConfigDict(extra="forbid", str_strip_whitespace=True)
    scope: str = Field(default="", max_length=10000)
    database: str = Field(default="", max_length=200)
    schema_name: str = Field(default="", max_length=200)
    table: str = Field(default="", max_length=200)
    column: str = Field(default="", max_length=200)
    concepts: list[str] = Field(default_factory=list, max_length=100)

    @model_validator(mode="after")
    def validate_context(self):
        if ((self.schema_name and not self.database) or (self.table and not self.schema_name)
                or (self.column and not self.table)):
            raise ValueError("Physical recall scope requires its database/schema/table ancestors")
        if any(not value.strip() or len(value) > 200 for value in self.concepts):
            raise ValueError("Recall concepts must contain between 1 and 200 characters")
        return self

    def matches(self, card: Card) -> bool:
        if self.scope and self.scope != card.scope:
            return False
        if not set(self.concepts) <= set(card.concepts):
            return False
        if not self.database or not card.dependencies:
            return True
        return any(all(not getattr(self, key) or getattr(dep, key) in ("", getattr(self, key))
                       for key in ("database", "schema_name", "table", "column"))
                   for dep in card.dependencies)

    def vector_filter(self, family: Family | None) -> dict:
        return {"memory": {**self.model_dump(), "family": family,
                           "format": PROJECTION_FORMAT}}


@dataclass(frozen=True)
class RecalledCard:
    card: Card
    score: float
    path: tuple[str, ...]


def expand_and_rank(repo, hits, *, scope: RecallScope, family: Family | None,
                    excluded: set[str], top: int) -> list[RecalledCard]:
    """RRF direct rank + strongest link path, decayed by 0.5 per outgoing hop.

    Roots, nodes, fan-out and depth are all bounded. Repeated paths do not add
    votes: cycles and highly connected cards cannot amplify their own relevance.
    The caller holds the workspace operation lock while resolving authority.
    """
    cache: dict[str, Card | None] = {}

    def current(identity):
        if identity not in cache:
            if len(cache) >= MAX_VISITED:
                return None
            try:
                card = repo.get(identity)
            except MemoryNotFound:
                card = None
            if card is not None and (not card.indexed or card.id in excluded
                    or (family and card.family != family) or not scope.matches(card)):
                card = None
            cache[identity] = card
        return cache[identity]

    direct: dict[str, float] = {}
    graph: dict[str, tuple[float, tuple[str, ...]]] = {}
    seeds = []
    for rank, hit in enumerate(hits[:MAX_SEEDS], 1):
        card = current(hit.ref)
        if (card is None or hit.metadata.get("memory_revision") != card.revision
                or hit.metadata.get("memory_format") != PROJECTION_FORMAT
                or card.id in direct):
            continue
        direct[card.id] = 1 / (RRF_K + rank)
        seeds.append(card)

    traversed = 0
    for seed in seeds:
        frontier = [(seed, (seed.id,))]
        visited = {seed.id}
        for depth in range(1, MAX_DEPTH + 1):
            next_frontier = []
            for source, path in frontier:
                for link in sorted(source.links, key=lambda link: link.target_id)[:MAX_LINKS_PER_CARD]:
                    if traversed >= MAX_EDGES:
                        break
                    traversed += 1
                    if link.target_id in visited:
                        continue
                    visited.add(link.target_id)
                    target = current(link.target_id)
                    if target is None:
                        continue
                    target_path = (*path, target.id)
                    score = direct[seed.id] * 0.5 ** depth
                    previous = graph.get(target.id)
                    if previous is None or (-score, target_path) < (-previous[0], previous[1]):
                        graph[target.id] = (score, target_path)
                    next_frontier.append((target, target_path))
            frontier = next_frontier

    ranked = []
    for identity in direct.keys() | graph.keys():
        graph_score, path = graph.get(identity, (0, (identity,)))
        ranked.append(RecalledCard(cache[identity], direct.get(identity, 0) + graph_score, path))
    return sorted(ranked, key=lambda result: (-result.score, result.card.id))[:top]