"""
POST /api/planning/exercise-suggest — planungsgebundene Übungssuche (Hybrid + Profil + optional LLM-Rerank).
"""
from fastapi import APIRouter, Depends

from db import get_db, get_cursor
from tenant_context import TenantContext, get_tenant_context
from planning_exercise_suggest import PlanningExerciseSuggestRequest, suggest_planning_exercises
from planning_exercise_path_builder import ProgressionPathSuggestRequest, suggest_progression_path
from club_features import probe_club_feature_access, resolve_club_id_for_probe

router = APIRouter(prefix="/api/planning", tags=["planning_exercise_suggest"])


@router.post("/exercise-suggest")
def post_planning_exercise_suggest(
    body: PlanningExerciseSuggestRequest,
    tenant: TenantContext = Depends(get_tenant_context),
):
    if body.include_llm_intent or body.include_llm_rank:
        probe_club_feature_access(
            feature_id="ai_calls",
            action="planning_suggest",
            club_id=resolve_club_id_for_probe(tenant),
            profile_id=tenant.profile_id,
            endpoint="POST /planning/exercise-suggest",
        )
    with get_db() as conn:
        cur = get_cursor(conn)
        return suggest_planning_exercises(cur, tenant=tenant, body=body)


@router.post("/progression-path-suggest")
def post_progression_path_suggest(
    body: ProgressionPathSuggestRequest,
    tenant: TenantContext = Depends(get_tenant_context),
):
    if (
        body.include_llm_intent
        or body.include_llm_path_qa
        or body.include_ai_gap_fill
    ):
        probe_club_feature_access(
            feature_id="ai_calls",
            action="progression_path_suggest",
            club_id=resolve_club_id_for_probe(tenant),
            profile_id=tenant.profile_id,
            endpoint="POST /planning/progression-path-suggest",
        )
    with get_db() as conn:
        cur = get_cursor(conn)
        return suggest_progression_path(cur, tenant=tenant, body=body)