from __future__ import annotations

from dataclasses import dataclass, field
from enum import StrEnum


class EvidenceDecision(StrEnum):
    ANSWERABLE = "answerable"
    VERIFY_PDF = "verify_pdf"
    ABSTAIN = "abstain"


class SubjectScope(StrEnum):
    HUMAN = "human"
    NON_HUMAN = "non_human"
    UNKNOWN = "unknown"


class QueryIntent(StrEnum):
    FACT_LOOKUP = "fact_lookup"
    RECOMMENDATION = "recommendation"
    UNKNOWN = "unknown"


@dataclass(frozen=True)
class SourceRef:
    physical_page: int
    precision: str
    block_id: str | None = None
    bbox: tuple[float, float, float, float] | None = None
    source_crop: str | None = None
    page_range: tuple[int, int] | None = None
    printed_page: int | None = None
    printed_page_range: tuple[int, int] | None = None


@dataclass(frozen=True)
class RetrievalDocument:
    doc_id: str
    drug_id: str
    kind: str
    text: str
    section_key: str
    source_refs: tuple[SourceRef, ...]
    parent_id: str | None = None
    requires_visual_check: bool = False
    drug_name: str | None = None


@dataclass(frozen=True)
class ParentDocument:
    parent_id: str
    kind: str
    text: str
    source_refs: tuple[SourceRef, ...]
    requires_visual_check: bool = False


@dataclass(frozen=True)
class SearchHit:
    document: RetrievalDocument
    score: float


@dataclass(frozen=True)
class Evidence:
    evidence_id: str
    matched_doc_id: str
    kind: str
    text: str
    score: float
    source_refs: tuple[SourceRef, ...]
    hydrated_from_parent: bool
    requires_visual_check: bool


@dataclass(frozen=True)
class RetrievalResult:
    decision: EvidenceDecision
    reason: str
    evidence: tuple[Evidence, ...] = field(default_factory=tuple)
    resolved_drug_id: str | None = None
    drug_resolution_status: str = "not_attempted"
    # True when the user typed only a drug name (no attribute): the answer layer
    # should introduce the drug (what it is + what it treats), not restate a
    # section verbatim.
    is_drug_overview: bool = False