"""Lepsza odpowiedź Matcher AI gdy baza naborów jest pusta."""
import logging

from fastapi import Depends, HTTPException

from endpoints.grants import router, MatchRequest, get_nabory, run_advanced_match_core, MATCH_FALLBACK_QUESTIONS, _rule_based_advanced_match_fallback
from endpoints.projects import get_db
from core.subscription.middleware import verify_token
from core.projects.models import Project

logger = logging.getLogger(__name__)

_orig_route = None


def apply_match_fix():
    global _orig_route
    for route in list(router.routes):
        if getattr(route, "path", "") == "/match" and "POST" in getattr(route, "methods", set()):
            router.routes.remove(route)
            _orig_route = route
            break

    @router.post("/match")
    async def match_grants_fixed(
        request: MatchRequest,
        token_data: dict = Depends(verify_token),
        db=Depends(get_db),
    ):
        clerk_id = token_data.get("sub")
        project = db.query(Project).filter(
            Project.id == request.project_id,
            Project.clerk_user_id == clerk_id,
        ).first()
        if not project:
            raise HTTPException(status_code=404, detail="Projekt nie istnieje lub brak dostępu")

        nabory_list: list = []
        try:
            nabory_resp = await get_nabory(force_refresh=False, db=db)
            nabory_list = nabory_resp.get("nabory", [])
            stats = nabory_resp.get("count", 0)

            if not nabory_list:
                return {
                    "status": "ok",
                    "project_id": request.project_id,
                    "needs_more_info": True,
                    "clarifying_questions": [
                        "Baza naborów jest pusta. Uruchom import: POST /api/admin/grants/import-wyszukiwarka "
                        "lub skrypt scripts/import_wyszukiwarka.py z plikiem WYSZUKIWARKA."
                    ],
                    "matches": [],
                    "catalog_empty": True,
                    "hint": "Ustaw WYSZUKIWARKA_JSON=/ścieżka/do/dotacje-2026-06-21.json i zaimportuj katalog.",
                }

            result = await run_advanced_match_core(
                title=project.title or "",
                description=project.description or "Brak opisu",
                estimated_value=project.estimated_value or 0.0,
                external_context=project.external_context or {},
                industry=project.industry if hasattr(project, "industry") else "",
                user_answers=request.user_answers or [],
                nabory_list=nabory_list,
            )

            if not result.needs_more_info:
                external_context = project.external_context or {}
                external_context["ai_matches"] = [m.model_dump() for m in result.matches]
                if request.user_answers:
                    external_context["ai_matches_qa_history"] = [
                        qa.model_dump() for qa in request.user_answers
                    ]
                project.external_context = external_context
                db.commit()

            return {
                "status": "ok",
                "project_id": request.project_id,
                "needs_more_info": result.needs_more_info,
                "clarifying_questions": result.clarifying_questions,
                "matches": [m.model_dump() for m in result.matches],
                "nabory_in_catalog": stats,
            }
        except Exception as e:
            logger.error("Error in match_grants for project %s: %s", request.project_id, e, exc_info=True)
            try:
                fallback = _rule_based_advanced_match_fallback(
                    project.title or "",
                    project.description or "",
                    project.external_context or {},
                    request.user_answers or [],
                    nabory_list,
                )
                return {
                    "status": "ok",
                    "project_id": request.project_id,
                    "needs_more_info": fallback.needs_more_info,
                    "clarifying_questions": fallback.clarifying_questions,
                    "matches": [m.model_dump() for m in fallback.matches],
                    "fallback_mode": "rule_based",
                    "detail": str(e)[:200],
                }
            except Exception:
                return {
                    "status": "error",
                    "detail": f"Błąd generowania dopasowań przez AI: {str(e)}",
                    "needs_more_info": True,
                    "clarifying_questions": MATCH_FALLBACK_QUESTIONS,
                    "matches": [],
                }

    logger.info("[grants_match_fix] POST /match patched with catalog-empty handling.")