"""
NextActionPredictor inference helper.

Exposes recommend_action() used by the CMA tool recommend_action.
Falls back to DOMAIN_ACTION_PRIORS rule-based routing when no checkpoint exists.

The module-level NextActionPredictor instance is cached after the first call.
Call init_predictor() at server startup for a predictable load moment.
"""

from __future__ import annotations

import logging
from typing import Optional

from src.next_action.model import (
    EscalationAction,
    NextActionPredictor,
    build_feature_vector,
    entities_dict_to_flags,
)

logger = logging.getLogger(__name__)

_DEFAULT_MODEL_PATH = "models/next_action/model.pt"
_predictor: Optional[NextActionPredictor] = None


# ---------------------------------------------------------------------------
# Lifecycle helpers
# ---------------------------------------------------------------------------

def init_predictor(model_path: str = _DEFAULT_MODEL_PATH) -> NextActionPredictor:
    """
    Explicitly initialise (or reload) the module-level NextActionPredictor.

    Always succeeds: if the checkpoint is missing, the rule-based fallback is
    used and a warning is logged.  Call this at server startup so the load
    happens at a known moment rather than on the first request.
    """
    global _predictor
    _predictor = NextActionPredictor(model_path)
    if _predictor.uses_fallback:
        logger.warning(
            "NextActionPredictor is using rule-based fallback (no checkpoint at '%s'). "
            "Train with: python -m src.next_action.train --output_path %s",
            model_path, model_path,
        )
    return _predictor


# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------

def recommend_action(
    domain: str,
    entities: dict,
    prior_contact: bool = False,
    model_path: str = _DEFAULT_MODEL_PATH,
) -> list[EscalationAction]:
    """
    Return a ranked list of EscalationAction for *domain* and *entities*.

    Args:
        domain:        The classified complaint domain (one of the 6 G.U.I.D.E. domains).
        entities:      Dict of entity_type → value from EvidenceNER, e.g.
                       {"ORG": "Flipkart", "AMOUNT": "₹4,299", "REF_ID": "OD-123"}.
                       PERSON is ignored (role reference, not a routing signal).
        prior_contact: True if the user has already contacted the company without
                       resolution.  Causes company_support to be deprioritised.
        model_path:    Path to the .pt checkpoint; falls back to rule-based if absent.

    Returns:
        All 6 EscalationActions sorted by confidence descending.
        The caller (CMA) typically surfaces the top 2–3 to the user.
    """
    global _predictor
    if _predictor is None:
        init_predictor(model_path)

    entity_flags = entities_dict_to_flags(entities)
    fv = build_feature_vector(domain, entity_flags, float(prior_contact))

    return _predictor.predict(fv)