from __future__ import annotations

import re
from typing import Any

_STRATEGIC = (
    "paramount", "netflix", "disney", "hbo", "youtube premium", "aya ",
    "deezer", "globoplay", "truecaller", "food balance",
)


def _norm(value: Any) -> str:
    text = str(value or "").casefold()
    text = re.sub(r"[^a-z0-9áàâãéèêíìîóòôõúùûç+ ]+", " ", text)
    return " ".join(text.split())


def _iter_invoice_rows(invoice_detail: Any):
    if not isinstance(invoice_detail, dict):
        return
    for _, sections in invoice_detail.items():
        if not isinstance(sections, dict):
            continue
        for section, rows in sections.items():
            if not isinstance(rows, list):
                continue
            for row in rows:
                if isinstance(row, dict):
                    yield str(section or ""), row


def infer_informational_context(query: str, invoice_detail: Any = None) -> dict[str, list[str]]:
    """Infere a marca informacional usada pela finalização após uma consulta RAG.

    Não executa RAG e não guarda sessão. Apenas transforma a pergunta + evidência
    de fatura em metadata de domínio que o grafo/framework poderá persistir.
    """
    q = _norm(query)
    if not q:
        return {}
    names: list[str] = []
    types: list[str] = []
    for section, row in _iter_invoice_rows(invoice_detail):
        name = str(row.get("desc") or row.get("name") or row.get("description") or "").strip()
        if not name:
            continue
        n = _norm(name)
        if n and (n in q or q in n):
            names.append(name)
            sec = _norm(section)
            if "sva" in sec or "servico" in sec or "serviço" in sec:
                types.append("avulso")
    # Serviços estratégicos podem ser reconhecidos mesmo sem detalhe da fatura.
    if not names:
        for alias in _STRATEGIC:
            if _norm(alias) in q:
                names.append(alias.strip().title())
                types.append("estrategico")
                break
    if not names:
        return {}
    dedup_names = list(dict.fromkeys(names))
    dedup_types = list(dict.fromkeys(types))
    return {
        "informational_service_names": dedup_names,
        "informational_vas_types": dedup_types,
        "informational_rag_vas_types": dedup_types,
    }