"""
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 account_lifecycle import assert_min_account_state
from capabilities import probe_capability
from club_features import (
    consume_club_feature_with_usage,
    merge_feature_usage_into_response,
    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),
):
    uses_ai = body.include_llm_intent or body.include_llm_rank
    club_id = resolve_club_id_for_probe(tenant) if uses_ai else None
    if uses_ai:
        assert_min_account_state(tenant, "active_member", endpoint="POST /planning/exercise-suggest")
        probe_capability(
            tenant,
            "planning.ai.suggest",
            action="planning_suggest",
            club_id=club_id,
            endpoint="POST /planning/exercise-suggest",
        )
        probe_club_feature_access(
            feature_id="ai_calls",
            action="planning_suggest",
            club_id=club_id,
            profile_id=tenant.profile_id,
            portal_role=tenant.global_role,
            endpoint="POST /planning/exercise-suggest",
            tenant=tenant,
        )
    with get_db() as conn:
        cur = get_cursor(conn)
        result = suggest_planning_exercises(cur, tenant=tenant, body=body)
        if uses_ai:
            usage = consume_club_feature_with_usage(
                feature_id="ai_calls",
                club_id=club_id,
                profile_id=tenant.profile_id,
                portal_role=tenant.global_role,
                action="planning_suggest",
                cur=cur,
                tenant=tenant,
                conn=conn,
            )
            result = merge_feature_usage_into_response(result, usage)
        return result


@router.post("/progression-path-suggest")
def post_progression_path_suggest(
    body: ProgressionPathSuggestRequest,
    tenant: TenantContext = Depends(get_tenant_context),
):
    uses_ai = (
        body.include_llm_intent
        or body.include_llm_path_qa
        or body.include_ai_gap_fill
    )
    club_id = resolve_club_id_for_probe(tenant) if uses_ai else None
    if uses_ai:
        assert_min_account_state(
            tenant, "active_member", endpoint="POST /planning/progression-path-suggest"
        )
        probe_capability(
            tenant,
            "planning.ai.progression_path",
            action="progression_path_suggest",
            club_id=club_id,
            endpoint="POST /planning/progression-path-suggest",
        )
        probe_club_feature_access(
            feature_id="ai_calls",
            action="progression_path_suggest",
            club_id=club_id,
            profile_id=tenant.profile_id,
            portal_role=tenant.global_role,
            endpoint="POST /planning/progression-path-suggest",
            tenant=tenant,
        )
    with get_db() as conn:
        cur = get_cursor(conn)
        result = suggest_progression_path(cur, tenant=tenant, body=body)
        if uses_ai:
            usage = consume_club_feature_with_usage(
                feature_id="ai_calls",
                club_id=club_id,
                profile_id=tenant.profile_id,
                portal_role=tenant.global_role,
                action="progression_path_suggest",
                cur=cur,
                tenant=tenant,
                conn=conn,
            )
            result = merge_feature_usage_into_response(result, usage)
        return result