"""QueryService — orchestrates plan → validate → compile → execute.

Top-level entry point for catalog-driven structured queries. Wired into
the chat endpoint when source_hint == "structured".

Flow per call:
  1. Plan (LLM): question + catalog → QueryIR
  2. Validate IR against catalog. On failure, re-prompt the planner with the
     error context and retry (up to `max_retries` total attempts).
  3. Dispatch IR to the right executor by `source.source_type`.
  4. Execute. Any exception (including NotImplementedError from the
     TabularExecutor placeholder) is caught and surfaced via
     `QueryResult.error` so the chatbot can branch on success / failure.

The service never raises — every code path returns a `QueryResult`.
"""

from __future__ import annotations

from collections.abc import Callable

from src.middlewares.logging import get_logger

from ..catalog.models import Catalog
from .executor.base import QueryResult
from .executor.dispatcher import ExecutorDispatcher
from .ir.validator import IRValidationError, IRValidator
from .planner.service import QueryPlannerService

logger = get_logger("query_service")


class QueryService:
    """End-to-end runner for a user question against a catalog.

    All heavy dependencies are injectable so unit tests don't need real
    LLMs or DB engines. Default constructors lazy-build the production
    deps so importing this module is side-effect-free.
    """

    def __init__(
        self,
        planner: QueryPlannerService | None = None,
        validator: IRValidator | None = None,
        dispatcher_factory: Callable[[Catalog], ExecutorDispatcher] | None = None,
        max_retries: int = 3,
    ) -> None:
        self._planner = planner or QueryPlannerService()
        self._validator = validator or IRValidator()
        self._dispatcher_factory = dispatcher_factory or ExecutorDispatcher
        self._max_retries = max(1, max_retries)

    async def run(self, user_id: str, question: str, catalog: Catalog) -> QueryResult:
        if not catalog.sources:
            return _error_result(
                source_id="",
                error="No structured data registered yet — connect a database "
                "or upload a CSV/XLSX before asking data questions.",
            )

        # ---------- planner + validator with retry ------------------
        previous_error: str | None = None
        ir = None
        for attempt in range(1, self._max_retries + 1):
            try:
                ir = await self._planner.plan(question, catalog, previous_error)
            except Exception as e:
                logger.error("planner crashed", attempt=attempt, error=str(e))
                return _error_result(source_id="", error=f"planner failed: {e}")

            try:
                self._validator.validate(ir, catalog)
                logger.info(
                    "ir planned and validated",
                    attempt=attempt,
                    source_id=ir.source_id,
                    table_id=ir.table_id,
                    select=[s.model_dump() for s in ir.select],
                    filters=[f.model_dump() for f in ir.filters],
                    group_by=ir.group_by,
                )
                break
            except IRValidationError as e:
                previous_error = str(e)
                logger.warning(
                    "ir validation failed",
                    attempt=attempt,
                    error=previous_error,
                )
                ir = None  # discard invalid IR
                continue
        else:
            return _error_result(
                source_id="",
                error=(
                    f"Planner could not produce a valid IR after "
                    f"{self._max_retries} attempts. Last error: {previous_error}"
                ),
            )

        # `ir` is non-None and valid here (guarded by the for/else above)
        assert ir is not None

        # ---------- dispatch + execute ------------------------------
        try:
            dispatcher = self._dispatcher_factory(catalog)
            executor = dispatcher.pick(ir)
        except Exception as e:
            logger.error("dispatch failed", source_id=ir.source_id, error=str(e))
            return _error_result(source_id=ir.source_id, error=f"dispatch failed: {e}")

        try:
            return await executor.run(ir)
        except NotImplementedError as e:
            # TabularExecutor placeholder — TAB owner ships PR3-TAB
            logger.warning(
                "executor not yet implemented",
                source_id=ir.source_id,
                error=str(e),
            )
            return _error_result(
                source_id=ir.source_id,
                error="Tabular execution is not yet available — pending PR3-TAB.",
            )
        except Exception as e:
            logger.error("executor crashed", source_id=ir.source_id, error=str(e))
            return _error_result(
                source_id=ir.source_id, error=f"executor failed: {e}"
            )


def _error_result(source_id: str, error: str) -> QueryResult:
    """Build a uniform error QueryResult.

    `backend` is intentionally empty when the failure happens before an
    executor is picked — the caller can still distinguish via `error`.
    """
    return QueryResult(source_id=source_id, backend="", error=error)