tradein-mvp/backend/app/api/v1/trade_in.py

@@ -26,6 +26,8 @@ from app.schemas.trade_in import (
     HouseAnalyticsResponse,
     HouseInfoForEstimate,
     IMVBenchmarkResponse,
+    LocationCoefFactorOut,
+    LocationCoefResponse,
     PhotoMeta,
     PlacementHistoryEntry,
     PriceHistoryYearPoint,
@@ -1519,6 +1521,79 @@ def get_estimate_imv_benchmark(
     )
 
 
+# ── Location-coef POI scoring (#2045 BE-3, LocationDrawer) ────────────────────
+
+
+@router.get("/location-coef", response_model=LocationCoefResponse)
+def get_location_coef(
+    estimate_id: UUID,
+    db: Annotated[Session, Depends(get_db)],
+    x_authenticated_user: Annotated[str | None, Header(alias="X-Authenticated-User")] = None,
+    radius_m: int | None = None,
+) -> LocationCoefResponse:
+    """Location-coefficient POI-скоринг для оценки (#2045 BE-3, LocationDrawer).
+
+    Резолвит lat/lon/median_price оценки, считает coef через
+    app.services.location_coef.compute_location_coef — straight-line POI weighted score
+    (портировано из Site Finder poi_score.py) поверх локального зеркала osm_poi_ekb_local,
+    обновляемого scheduler'ом (source=osm_poi_ekb_refresh). result_price_rub = round(
+    base_price_rub * coef).
+
+    404 — оценки нет / IDOR (тот же _assert_estimate_access_by_id, что и у соседних
+    derived-роутов). radius_m опционален (None → DEFAULT_RADIUS_M=1200м, подобран для
+    МКД, НЕ Ptica-дефолт 2000м для участков); явное значение клэмпится в [500, 3000].
+
+    Graceful fallback (НЕ 500, НЕ сфабрикованные факторы):
+      - osm_poi_ekb_local пуста/не отрефрешена на этом окружении → coef=1.0, factors=[],
+        geo_source="unavailable" (см. compute_location_coef).
+      - у оценки нет lat/lon (легаси/geo-fallback не сработал на POST) → тот же fallback.
+    """
+    _assert_estimate_access_by_id(db, estimate_id, x_authenticated_user)
+
+    row = db.execute(
+        text(
+            """
+            SELECT lat, lon, median_price
+            FROM trade_in_estimates
+            WHERE id = CAST(:id AS uuid)
+            """
+        ),
+        {"id": str(estimate_id)},
+    ).fetchone()
+    if row is None:
+        raise HTTPException(status_code=404, detail="estimate not found")
+
+    base_price_rub = int(row.median_price or 0)
+
+    if row.lat is None or row.lon is None:
+        logger.info("location_coef: estimate=%s has no lat/lon — unavailable fallback", estimate_id)
+        return LocationCoefResponse(
+            coef=1.0,
+            factors=[],
+            geo_source="unavailable",
+            base_price_rub=base_price_rub,
+            result_price_rub=base_price_rub,
+        )
+
+    from app.services.location_coef import DEFAULT_RADIUS_M, compute_location_coef
+
+    resolved_radius = DEFAULT_RADIUS_M if radius_m is None else max(500, min(radius_m, 3000))
+    result = compute_location_coef(db, float(row.lat), float(row.lon), radius_m=resolved_radius)
+
+    return LocationCoefResponse(
+        coef=result.coef,
+        factors=[
+            LocationCoefFactorOut(
+                poi_type=f.poi_type, name=f.name, distance_m=f.distance_m, weight=f.weight
+            )
+            for f in result.factors
+        ],
+        geo_source=result.geo_source,
+        base_price_rub=base_price_rub,
+        result_price_rub=round(base_price_rub * result.coef),
+    )
+
+
 # ── Street-level deals (rosreestr open dataset) ───────────────────────────────
 
 

tradein-mvp/backend/app/schemas/trade_in.py

@@ -549,3 +549,31 @@ class QuotaStatus(BaseModel):
     used: int  # использовано в текущем месяце
     remaining: int  # max(0, limit - used)
     unlimited: bool  # True для admin / kopylov / без заголовка
+
+
+class LocationCoefFactorOut(BaseModel):
+    """Один POI-фактор в ответе GET /api/v1/trade-in/location-coef (#2045 BE-3)."""
+
+    poi_type: str  # категория POI (school/kindergarten/metro_stop/... — те же значения,
+    # что в osm_poi_ekb на стороне gendesign)
+    name: str | None
+    distance_m: float
+    weight: float
+
+
+class LocationCoefResponse(BaseModel):
+    """Ответ GET /api/v1/trade-in/location-coef (#2045 BE-3, LocationDrawer).
+
+    coef — MVP-эвристика (НЕ откалибрована на реальных ценовых дельтах, см.
+    app/services/location_coef.py::_score_to_coef), диапазон [0.95, 1.05].
+    result_price_rub = round(base_price_rub * coef).
+
+    geo_source="unavailable" — osm_poi_ekb_local пуста/не отрефрешена на этом окружении
+    (graceful fallback: coef=1.0, factors=[], НЕ 500 и НЕ сфабрикованные факторы).
+    """
+
+    coef: float
+    factors: list[LocationCoefFactorOut]
+    geo_source: str
+    base_price_rub: int
+    result_price_rub: int

tradein-mvp/backend/app/services/location_coef.py

@@ -0,0 +1,200 @@
+"""Location-coefficient POI scoring for trade-in estimates (#2045 BE-3, LocationDrawer).
+
+Ported straight-line formula from Site Finder (ПТИЦА)
+`backend/app/services/site_finder/poi_score.py::compute_poi_weighted_top7`:
+
+    weight = (1 / (distance_m + 100)) * CATEGORY_WEIGHTS[category]
+
+Reads from the LOCAL mirror table `osm_poi_ekb_local` (populated by
+`app/tasks/osm_poi_ekb_refresh.py` from the `gendesign_osm_poi_ekb` FDW — see migrations
+168-170). We deliberately do NOT query the FDW directly per-request: the same per-row cost
+measured for the analogous cadastral-buildings FDW (~1.16s/row without a geom index on the
+remote) would make a synchronous endpoint unusable.
+
+Scope (MVP, #2045 BE-3):
+  - Straight-line distance only. The ORS routing-decay mode from Site Finder
+    (`compute_poi_routing_decay`) is NOT ported — no ORS infrastructure in trade-in, out of
+    MVP scope.
+  - Radius tuned for apartments (1000-1500m), NOT Site Finder's 2000m default for land parcels.
+  - The score→coef mapping (`_score_to_coef`) is a NEW MVP heuristic, not present in Site
+    Finder (there POI score is a ranking metric, not a price multiplier) — see its docstring.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+from pydantic import BaseModel
+from sqlalchemy import text
+
+logger = logging.getLogger(__name__)
+
+# Веса по категории — скопированы as-is из Site Finder CATEGORY_WEIGHTS
+# (backend/app/services/site_finder/poi_score.py), чтобы ranking POI был согласован
+# между продуктами.
+CATEGORY_WEIGHTS: dict[str, float] = {
+    "metro_stop": 6.0,
+    "school": 5.0,
+    "kindergarten": 4.5,
+    "hospital": 4.0,
+    "shop_mall": 4.0,
+    "shop_supermarket": 3.5,
+    "bus_stop": 4.5,
+    "park": 3.5,
+    "pharmacy": 2.5,
+    "tram_stop": 2.0,
+    "shop_small": 2.0,
+    "default": 1.0,
+}
+
+# Радиус подобран для КВАРТИР (МКД), а не для участков (Ptica default 2000м) —
+# пешая доступность в пределах квартала/микрорайона.
+DEFAULT_RADIUS_M = 1200
+DEFAULT_TOP_N = 7
+
+# Теоретический максимум суммы весов top-7 POI при идеальном расположении (d=0):
+# w_i = cat_weight_i / (0 + 100) → max_sum = Σ(top7 cat_weights) / 100.
+# Top-7 категорий по убыванию веса: 6.0+5.0+4.5+4.5+4.0+4.0+3.5 = 31.5 (тот же набор, что у Ptica).
+_TOP7_WEIGHT_SUM: float = sum(sorted(CATEGORY_WEIGHTS.values(), reverse=True)[:7])
+_MAX_STRAIGHT_SCORE: float = _TOP7_WEIGHT_SUM / 100.0  # ≈ 0.315
+
+# coef диапазон ±5% вокруг 1.0 — heuristic v1, НЕ откалибровано на реальных ценовых дельтах
+# (в отличие от Ptica, где poi_weighted_score — ранжирующая метрика, не ценовой множитель).
+_COEF_BASE = 0.95
+_COEF_SPREAD = 0.10
+
+
+def _category_weight(category: str | None) -> float:
+    """Вернуть вес категории. Если не знаем — default."""
+    return CATEGORY_WEIGHTS.get(category or "default", CATEGORY_WEIGHTS["default"])
+
+
+class LocationCoefFactor(BaseModel):
+    """Один POI-фактор в ответе location-coef."""
+
+    poi_type: str
+    name: str | None
+    distance_m: float
+    weight: float
+
+
+class LocationCoefResult(BaseModel):
+    """Результат compute_location_coef — потребляется эндпоинтом location-coef."""
+
+    coef: float
+    factors: list[LocationCoefFactor]
+    geo_source: str  # "osm_poi_ekb" (норма) | "unavailable" (mirror пуста/не отрефрешена)
+
+
+def _score_to_coef(poi_weighted_score: float) -> float:
+    """MVP-эвристика score(0..100) → ценовой коэффициент.
+
+    coef = 0.95 + (score/100) * 0.10  →  диапазон [0.95, 1.05].
+
+    ВНИМАНИЕ: это НЕ откалиброванная на реальных ценовых дельтах формула — первая рабочая
+    эвристика для MVP location-coef. Site Finder использует ту же POI-модель как ранжирующую
+    метрику (poi_weighted_score), а не как прямой ценовой множитель; здесь смысл другой,
+    поэтому маппинг введён отдельно и явно помечен как heuristic v1.
+    """
+    return round(_COEF_BASE + (poi_weighted_score / 100.0) * _COEF_SPREAD, 4)
+
+
+_NEAREST_POI_SQL = text(
+    """
+    SELECT
+        p.name,
+        p.category,
+        CAST(
+            ST_Distance(
+                p.geom::geography,
+                ST_SetSRID(ST_MakePoint(:lon, :lat), 4326)::geography
+            ) AS double precision
+        ) AS distance_m
+    FROM osm_poi_ekb_local p
+    WHERE p.geom IS NOT NULL
+      AND ST_DWithin(
+          p.geom::geography,
+          ST_SetSRID(ST_MakePoint(:lon, :lat), 4326)::geography,
+          CAST(:radius_m AS double precision)
+      )
+    ORDER BY distance_m ASC
+    LIMIT :limit
+    """
+)
+
+
+def compute_location_coef(
+    db: Any,
+    lat: float,
+    lon: float,
+    radius_m: int = DEFAULT_RADIUS_M,
+    top_n: int = DEFAULT_TOP_N,
+) -> LocationCoefResult:
+    """Посчитать location-coef для координат (lat, lon) по POI из osm_poi_ekb_local.
+
+    Graceful fallback: если osm_poi_ekb_local пуста (рефреш ещё не запускался на этом
+    окружении) — возвращает coef=1.0, factors=[], geo_source="unavailable" вместо 500 или
+    сфабрикованных факторов. Отсутствие POI В РАДИУСЕ у непустой таблицы — это легитимный
+    результат (coef=0.95, factors=[], geo_source="osm_poi_ekb"), не fallback.
+
+    Args:
+        db: SQLAlchemy Session.
+        lat: широта целевой квартиры.
+        lon: долгота целевой квартиры.
+        radius_m: радиус поиска в метрах (default 1200 — подобран для МКД, не для участков).
+        top_n: количество POI, учитываемых в score (default 7).
+    """
+    total = db.execute(text("SELECT count(*) FROM osm_poi_ekb_local")).scalar() or 0
+    if total == 0:
+        logger.warning(
+            "location_coef: osm_poi_ekb_local is empty (refresh job not yet run on this "
+            "environment) — returning unavailable fallback, no fabricated factors"
+        )
+        return LocationCoefResult(coef=1.0, factors=[], geo_source="unavailable")
+
+    rows = (
+        db.execute(
+            _NEAREST_POI_SQL,
+            {"lat": lat, "lon": lon, "radius_m": radius_m, "limit": top_n * 10},
+        )
+        .mappings()
+        .all()
+    )
+
+    scored: list[tuple[float, LocationCoefFactor]] = []
+    for row in rows:
+        distance_m = float(row["distance_m"])
+        category = row["category"] or "default"
+        weight = (1.0 / (distance_m + 100.0)) * _category_weight(category)
+        scored.append(
+            (
+                weight,
+                LocationCoefFactor(
+                    poi_type=category,
+                    name=row["name"],
+                    distance_m=round(distance_m, 1),
+                    weight=round(weight, 6),
+                ),
+            )
+        )
+
+    scored.sort(key=lambda pair: pair[0], reverse=True)
+    top_factors = [factor for _weight, factor in scored[:top_n]]
+
+    raw_sum = sum(factor.weight for factor in top_factors)
+    poi_weighted_score = min(100.0, (raw_sum / _MAX_STRAIGHT_SCORE) * 100.0)
+    coef = _score_to_coef(poi_weighted_score)
+
+    logger.debug(
+        "location_coef: lat=%.5f lon=%.5f radius=%dm poi_found=%d top=%d " "score=%.1f coef=%.4f",
+        lat,
+        lon,
+        radius_m,
+        len(rows),
+        len(top_factors),
+        poi_weighted_score,
+        coef,
+    )
+
+    return LocationCoefResult(coef=coef, factors=top_factors, geo_source="osm_poi_ekb")

tradein-mvp/backend/app/services/product_handlers.py

@@ -264,6 +264,19 @@ async def _job_cadastral_geo_match(
     )
 
 
+# ── osm_poi_ekb_refresh — sync FDW-refresh в executor ─────────────────────────
+async def _job_osm_poi_ekb_refresh(
+    db: Session, run_id: int, params: dict[str, Any], ctx: SchedulerContext
+) -> None:
+    from app.tasks.osm_poi_ekb_refresh import run_osm_poi_ekb_refresh
+
+    loop = asyncio.get_event_loop()
+    await loop.run_in_executor(
+        None,
+        lambda: run_osm_poi_ekb_refresh(db, run_id=run_id, params=params),
+    )
+
+
 # ── house_imv_backfill — async Avito-IMV с heartbeat, lifecycle в job ─────────
 async def _job_house_imv_backfill(
     db: Session, run_id: int, params: dict[str, Any], ctx: SchedulerContext
@@ -369,6 +382,7 @@ def build_product_handlers(ctx: SchedulerContext) -> dict[str, Handler]:
         "avito_detail_backfill": Handler(_job_avito_detail_backfill, "avito_detail_backfill"),
         "yandex_detail_backfill": Handler(_job_yandex_detail_backfill, "yandex_detail_backfill"),
         "cadastral_geo_match": Handler(_job_cadastral_geo_match, "cadastral_geo_match"),
+        "osm_poi_ekb_refresh": Handler(_job_osm_poi_ekb_refresh, "osm_poi_ekb_refresh"),
         "house_imv_backfill": Handler(_job_house_imv_backfill, "house_imv_backfill"),
         "house_dedup_merge": Handler(_job_house_dedup_merge, "house_dedup_merge"),
         "proxy_healthcheck": Handler(

tradein-mvp/backend/app/services/scheduler.py

@@ -125,6 +125,15 @@ Sources:
                               DISABLED (enabled=false) — deploy is neutral; enable deliberately
                               after a validated dry-run + manual run; weekly window 04:00-05:00
                               UTC — quiet hour, no scraper/proxy contention)
+  - osm_poi_ekb_refresh     → run_osm_poi_ekb_refresh
+                              (tasks/osm_poi_ekb_refresh.py, #2045 BE-3; single bulk FDW scan —
+                              TRUNCATE osm_poi_ekb_local; INSERT ... FROM gendesign_osm_poi_ekb
+                              (Site Finder OSM POI, EKB), building Point(4326) geom from lat/lon.
+                              Feeds app/services/location_coef.py (GET /trade-in/location-coef,
+                              LocationDrawer). OSM POI changes rarely → daily cadence is ample.
+                              Pure internal DB op — one FDW read + local TRUNCATE+INSERT, no
+                              HTTP/anti-bot; window 10:00-11:00 UTC — после cadastral_geo_match
+                              09:00-10:00 UTC)
 """
 
 from __future__ import annotations
@@ -1691,6 +1700,45 @@ async def trigger_cadastral_geo_match_run(db: Session, schedule_row: dict[str, A
     return run_id
 
 
+async def trigger_osm_poi_ekb_refresh_run(db: Session, schedule_row: dict[str, Any]) -> int | None:
+    """Создать scrape_runs + launch run_osm_poi_ekb_refresh в executor (#2045 BE-3).
+
+    Single bulk FDW scan (TRUNCATE osm_poi_ekb_local; INSERT ... FROM gendesign_osm_poi_ekb) —
+    feeds app/services/location_coef.py. No params consumed.
+
+    Sync task (one FDW read + local TRUNCATE+INSERT, no async HTTP) — run in run_in_executor
+    by the same pattern as trigger_cadastral_geo_match_run. run_osm_poi_ekb_refresh owns the
+    scrape_runs lifecycle (mark_done/mark_failed). SAFE to enable — seed 170 enabled=true,
+    pure internal DB op.
+
+    Returns run_id или None (skip — already running).
+    """
+    run_id = _claim_run(db, schedule_row)
+    if run_id is None:
+        return None
+
+    params = schedule_row.get("default_params") or {}
+
+    async def _run() -> None:
+        run_db = SessionLocal()
+        try:
+            from app.tasks.osm_poi_ekb_refresh import run_osm_poi_ekb_refresh
+
+            loop = asyncio.get_event_loop()
+            await loop.run_in_executor(
+                None,
+                lambda: run_osm_poi_ekb_refresh(run_db, run_id=run_id, params=params),
+            )
+        except Exception:
+            logger.exception("scheduler: run_osm_poi_ekb_refresh crashed run_id=%d", run_id)
+        finally:
+            run_db.close()
+
+    _spawn_tracked(_run())
+    logger.info("scheduler: triggered osm_poi_ekb_refresh run_id=%d", run_id)
+    return run_id
+
+
 async def trigger_house_imv_backfill_run(db: Session, schedule_row: dict[str, Any]) -> int | None:
     """Создать scrape_runs + launch backfill_house_imv в asyncio.create_task (#854).
 
@@ -1955,6 +2003,8 @@ async def scheduler_loop() -> None:
                         await trigger_yandex_detail_backfill_run(db, sch)
                     elif source == "cadastral_geo_match":
                         await trigger_cadastral_geo_match_run(db, sch)
+                    elif source == "osm_poi_ekb_refresh":
+                        await trigger_osm_poi_ekb_refresh_run(db, sch)
                     elif source == "house_imv_backfill":
                         await trigger_house_imv_backfill_run(db, sch)
                     elif source == "house_dedup_merge":

tradein-mvp/backend/app/tasks/osm_poi_ekb_refresh.py

@@ -0,0 +1,109 @@
+"""OSM POI local-mirror refresh (#2045 BE-3, LocationDrawer location-coef).
+
+Populates `osm_poi_ekb_local` (empty at deploy, migration 169) via a single bulk scan of the
+`gendesign_osm_poi_ekb` FDW foreign table (migration 168 — live view of gendesign's
+`osm_poi_ekb` table, Site Finder's OSM POI registry, GRANTed to `tradein_fdw_reader` in PR-A
+of #2045, already merged + deployed on gendesign).
+
+WHY a local mirror (perf fact measured for the analogous gendesign_cad_buildings FDW — see
+`app/tasks/cadastral_geo_match.py`): a per-request FDW nearest-POI query pays a per-row FDW
+round-trip (~1.16s/row without a geom index on the remote table) — UNUSABLE for a synchronous
+endpoint (`GET /api/v1/trade-in/location-coef`). We materialize the FDW once (single bulk
+scan) into `osm_poi_ekb_local` with a real Point geom + GIST index, then
+`app/services/location_coef.py` runs fast LOCAL ST_DWithin/ST_Distance queries per estimate.
+
+Scheduler source='osm_poi_ekb_refresh' (daily — OSM POI data changes rarely). Pure internal
+DB op — one FDW read + local TRUNCATE+INSERT, no HTTP/anti-bot.
+
+psycopg v3: app SQL uses CAST(:x AS type), never :x::type.
+"""
+
+from __future__ import annotations
+
+import logging
+import time
+from dataclasses import dataclass, field
+
+from sqlalchemy import text
+from sqlalchemy.orm import Session
+
+from app.services import scrape_runs as runs_mod
+
+logger = logging.getLogger(__name__)
+
+
+def refresh_osm_poi_ekb_local(db: Session) -> int:
+    """TRUNCATE osm_poi_ekb_local; bulk INSERT from gendesign_osm_poi_ekb FDW.
+
+    Single FDW scan (no per-row round-trips). Builds a Point(4326) geom from lon/lat.
+    Idempotent: TRUNCATE+INSERT in one transaction — the table is fully replaced atomically.
+
+    Returns the number of rows loaded.
+    """
+    db.execute(text("TRUNCATE osm_poi_ekb_local"))
+    db.execute(
+        text(
+            """
+            INSERT INTO osm_poi_ekb_local (category, name, lat, lon, geom)
+            SELECT
+                category, name, lat, lon,
+                ST_SetSRID(ST_MakePoint(lon, lat), 4326)
+            FROM gendesign_osm_poi_ekb
+            WHERE lat IS NOT NULL
+              AND lon IS NOT NULL
+            """
+        )
+    )
+    count = db.execute(text("SELECT count(*) FROM osm_poi_ekb_local")).scalar() or 0
+    db.commit()
+    logger.info("refresh_osm_poi_ekb_local: loaded %d rows from FDW", count)
+    return int(count)
+
+
+@dataclass
+class OsmPoiRefreshResult:
+    poi_loaded: int = 0  # rows in osm_poi_ekb_local after refresh
+    duration_sec: float = field(default=0.0)
+
+    def to_counters(self) -> dict[str, int]:
+        return {
+            "poi_loaded": self.poi_loaded,
+            "duration_sec": int(self.duration_sec),
+        }
+
+
+def run_osm_poi_ekb_refresh(db: Session, *, run_id: int, params: dict) -> OsmPoiRefreshResult:
+    """Run-lifecycle wrapper for the OSM POI local-mirror refresh (scheduler entrypoint).
+
+    Launched by the in-app scheduler (source='osm_poi_ekb_refresh') via
+    trigger_osm_poi_ekb_refresh_run, or manually. No params consumed — single unconditional
+    bulk refresh (`params` accepted for scheduler-signature compatibility / future use).
+
+    Finalises scrape_runs (mark_done / mark_failed) with counters.
+    """
+    counters: dict[str, int] = {"poi_loaded": 0}
+    start = time.monotonic()
+
+    try:
+        runs_mod.update_heartbeat(db, run_id, counters)
+
+        loaded = refresh_osm_poi_ekb_local(db)
+        result = OsmPoiRefreshResult(poi_loaded=loaded, duration_sec=time.monotonic() - start)
+
+        counters = result.to_counters()
+        runs_mod.mark_done(db, run_id, counters)
+        logger.info(
+            "run_osm_poi_ekb_refresh: run_id=%d DONE poi_loaded=%d duration=%.1fs",
+            run_id,
+            result.poi_loaded,
+            result.duration_sec,
+        )
+        return result
+    except Exception as exc:
+        logger.exception("run_osm_poi_ekb_refresh: run_id=%d FAILED", run_id)
+        try:
+            db.rollback()
+        except Exception:
+            pass
+        runs_mod.mark_failed(db, run_id, str(exc)[:1000], counters)
+        raise

tradein-mvp/backend/data/sql/168_fdw_osm_poi_ekb.sql

@@ -0,0 +1,36 @@
+-- 168_fdw_osm_poi_ekb.sql
+-- FDW foreign table bridging to gendesign's v_tradein_osm_poi_ekb view for
+-- location-coef / POI scoring in LocationDrawer (#2045, BE-3 final PR).
+--
+-- Mirrors 060_postgres_fdw_extension.sql conventions: uses the SAME SERVER
+-- gendesign_remote (already created there) — this migration does NOT create a new
+-- SERVER / USER MAPPING.
+--
+-- DEPENDENCIES:
+--   - 060_postgres_fdw_extension.sql (SERVER gendesign_remote + USER MAPPING, managed by
+--     backend startup with env password).
+--   - gendesign: view public.v_tradein_osm_poi_ekb + GRANT SELECT to tradein_fdw_reader
+--     (PR-A of #2045, already merged + deployed on gendesign).
+--
+-- Idempotent: DROP FOREIGN TABLE IF EXISTS + re-CREATE.
+
+BEGIN;
+
+DROP FOREIGN TABLE IF EXISTS gendesign_osm_poi_ekb;
+
+CREATE FOREIGN TABLE gendesign_osm_poi_ekb (
+    category text,
+    name     text,
+    lat      double precision,
+    lon      double precision
+)
+SERVER gendesign_remote
+OPTIONS (schema_name 'public', table_name 'v_tradein_osm_poi_ekb');
+
+COMMENT ON FOREIGN TABLE gendesign_osm_poi_ekb IS
+    'Live view of gendesign.osm_poi_ekb (Site Finder OSM POI, EKB). USER MAPPING managed by '
+    'backend startup (see 060). Materialized locally by the osm_poi_ekb_refresh scheduler job '
+    'into osm_poi_ekb_local (migration 169) — see app/tasks/osm_poi_ekb_refresh.py. '
+    'Feeds app/services/location_coef.py (GET /api/v1/trade-in/location-coef).';
+
+COMMIT;

tradein-mvp/backend/data/sql/169_osm_poi_ekb_local.sql

@@ -0,0 +1,42 @@
+-- 169_osm_poi_ekb_local.sql
+-- Local materialized mirror of gendesign_osm_poi_ekb (postgres_fdw foreign table, migration
+-- 168) for fast location-coef / POI scoring (#2045 BE-3, LocationDrawer).
+--
+-- WHY (mirrors 124_cad_buildings_local.sql — same perf fact measured for the analogous
+--   gendesign_cad_buildings FDW): a per-request FDW nearest-POI query would pay a per-row FDW
+--   round-trip (~1.16s/row without a geom index on the remote table) — UNUSABLE for a
+--   synchronous endpoint (GET /api/v1/trade-in/location-coef). Solution: materialize the FDW
+--   once (single bulk scan) into a LOCAL table with a real Point geom + GIST index, then run
+--   fast local ST_DWithin/ST_Distance queries per estimate.
+--
+-- This migration creates the EMPTY table + index only. It does NOT read the FDW — deploy
+--   never depends on the gendesign DB / FDW server being reachable. The table is populated by
+--   the refresh job (app/tasks/osm_poi_ekb_refresh.py), driven by the in-app scheduler
+--   (source='osm_poi_ekb_refresh', seed in 170_scrape_schedules_seed_osm_poi_ekb_refresh.sql).
+--
+-- DEPENDENCIES: PostGIS (postgis extension, present since geom on listings/houses).
+-- Idempotent: CREATE TABLE/INDEX IF NOT EXISTS. Safe to re-run.
+
+BEGIN;
+
+CREATE TABLE IF NOT EXISTS osm_poi_ekb_local (
+    id       bigserial PRIMARY KEY,
+    category text,
+    name     text,
+    lat      double precision,
+    lon      double precision,
+    geom     geometry(Point, 4326)
+);
+
+COMMENT ON TABLE osm_poi_ekb_local IS
+    'Local mirror of gendesign_osm_poi_ekb FDW (Site Finder OSM POI registry, EKB). '
+    'Populated by app/tasks/osm_poi_ekb_refresh.py (single bulk FDW scan, TRUNCATE+INSERT). '
+    'Point geom + GIST enables fast local nearest-POI scoring for '
+    'app/services/location_coef.py (GET /api/v1/trade-in/location-coef, LocationDrawer). '
+    'Migration 168/169. Refresh driven by scheduler source=osm_poi_ekb_refresh.';
+
+-- GIST on geom — required for ST_DWithin / ST_Distance nearest-POI scoring.
+CREATE INDEX IF NOT EXISTS osm_poi_ekb_local_geom_idx
+    ON osm_poi_ekb_local USING GIST (geom);
+
+COMMIT;

tradein-mvp/backend/data/sql/170_scrape_schedules_seed_osm_poi_ekb_refresh.sql

@@ -0,0 +1,46 @@
+-- 170_scrape_schedules_seed_osm_poi_ekb_refresh.sql
+-- Scheduler seed for the OSM POI local-mirror refresh job (#2045 BE-3, LocationDrawer).
+--
+-- WHAT (source='osm_poi_ekb_refresh'):
+--   trigger_osm_poi_ekb_refresh_run (scheduler.py) → run_osm_poi_ekb_refresh
+--   (tasks/osm_poi_ekb_refresh.py). Single bulk FDW scan: TRUNCATE osm_poi_ekb_local;
+--   INSERT ... SELECT FROM gendesign_osm_poi_ekb, building a Point(4326) geom from lat/lon.
+--
+--   OSM POI data changes rarely (Site Finder refreshes its own osm_poi_ekb table
+--   infrequently) — a daily cadence is more than sufficient freshness margin at near-zero
+--   cost (pure internal DB op, no external HTTP/anti-bot).
+--
+-- SAFE to enable by default (enabled=true), like cadastral_geo_match (seed 125).
+--
+-- Window 10:00-11:00 UTC (13:00-14:00 MSK): after cadastral_geo_match (09:00-10:00 UTC);
+--   pure-DB so no contention with scraper/proxy work either way.
+--
+-- next_run_at = tomorrow 10:00 UTC (NOT NULL — avoid deploy-time fire, same convention as
+--   the cadastral_geo_match seed 125; NULL would make get_due_schedules pick it up on the
+--   very next tick).
+--
+-- DEPENDENCIES: 052_scrape_schedules.sql (table + UNIQUE(source)), 169_osm_poi_ekb_local.sql.
+-- Idempotent: ON CONFLICT (source) DO NOTHING.
+
+BEGIN;
+
+INSERT INTO scrape_schedules (
+    source,
+    enabled,
+    window_start_hour,
+    window_end_hour,
+    next_run_at,
+    default_params
+)
+VALUES
+(
+    'osm_poi_ekb_refresh',
+    true,
+    10,
+    11,
+    ((CURRENT_DATE + INTERVAL '1 day') + make_interval(hours => 10)) AT TIME ZONE 'UTC',
+    '{}'::jsonb
+)
+ON CONFLICT (source) DO NOTHING;
+
+COMMIT;

tradein-mvp/backend/data/sql/_manifest_applied.txt

@@ -172,3 +172,6 @@
 165_remove_n1_source.sql
 166_purge_listings_phones.sql
 167_drop_client_pii.sql
+168_fdw_osm_poi_ekb.sql
+169_osm_poi_ekb_local.sql
+170_scrape_schedules_seed_osm_poi_ekb_refresh.sql

tradein-mvp/backend/tests/services/test_location_coef.py

@@ -0,0 +1,178 @@
+"""Unit tests for app.services.location_coef (#2045 BE-3, LocationDrawer).
+
+No live Postgres needed — DB is a minimal fake returning queued results (mirrors the
+convention in tests/tasks/test_cadastral_geo_match.py). Covers:
+  - pure functions: _category_weight, _score_to_coef, normalization constants
+  - compute_location_coef: weighted top-N scoring, empty-mirror graceful fallback,
+    no-POI-in-radius (legit zero-score, NOT "unavailable")
+"""
+
+from __future__ import annotations
+
+import os
+from typing import Any
+
+# psycopg v3 driver required; stub DATABASE_URL before any app import (settings needs a DSN).
+os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost:5432/test")
+
+from app.services import location_coef as lc
+
+# ── Pure functions ──────────────────────────────────────────────────────────
+
+
+def test_category_weight_known_categories() -> None:
+    assert lc._category_weight("metro_stop") == 6.0
+    assert lc._category_weight("school") == 5.0
+    assert lc._category_weight("kindergarten") == 4.5
+    assert lc._category_weight("hospital") == 4.0
+    assert lc._category_weight("shop_mall") == 4.0
+    assert lc._category_weight("shop_supermarket") == 3.5
+    assert lc._category_weight("bus_stop") == 4.5
+    assert lc._category_weight("park") == 3.5
+    assert lc._category_weight("pharmacy") == 2.5
+    assert lc._category_weight("tram_stop") == 2.0
+    assert lc._category_weight("shop_small") == 2.0
+
+
+def test_category_weight_unknown_and_none_fall_back_to_default() -> None:
+    assert lc._category_weight("unknown_category") == 1.0
+    assert lc._category_weight(None) == 1.0
+
+
+def test_top7_weight_sum_matches_ptica() -> None:
+    """Same category set as Site Finder → identical top-7 normalization constant (31.5)."""
+    assert lc._TOP7_WEIGHT_SUM == 31.5
+    assert abs(lc._MAX_STRAIGHT_SCORE - 0.315) < 1e-9
+
+
+def test_score_to_coef_bounds() -> None:
+    assert lc._score_to_coef(0.0) == 0.95
+    assert lc._score_to_coef(100.0) == 1.05
+
+
+def test_score_to_coef_midpoint() -> None:
+    assert lc._score_to_coef(50.0) == 1.0
+
+
+def test_score_to_coef_is_monotonic() -> None:
+    scores = [0.0, 10.0, 25.0, 50.0, 75.0, 90.0, 100.0]
+    coefs = [lc._score_to_coef(s) for s in scores]
+    assert coefs == sorted(coefs)
+
+
+# ── compute_location_coef with a fake DB ─────────────────────────────────────
+
+
+class _FakeResult:
+    def __init__(self, *, scalar_value: Any = None, mapping_rows: list[dict] | None = None):
+        self._scalar_value = scalar_value
+        self._mapping_rows = mapping_rows or []
+
+    def scalar(self) -> Any:
+        return self._scalar_value
+
+    def mappings(self) -> Any:
+        class _Mappings:
+            def __init__(self, rows: list[dict]) -> None:
+                self._rows = rows
+
+            def all(self) -> list[dict]:
+                return self._rows
+
+        return _Mappings(self._mapping_rows)
+
+
+class _FakeDB:
+    """Minimal Session stand-in: execute() returns queued results in order."""
+
+    def __init__(self, results: list[_FakeResult]) -> None:
+        self._results = list(results)
+        self.executed: list[Any] = []
+
+    def execute(self, clause: Any, params: dict | None = None) -> _FakeResult:
+        self.executed.append((clause, params))
+        return self._results.pop(0)
+
+
+def test_compute_location_coef_empty_mirror_returns_unavailable() -> None:
+    """osm_poi_ekb_local not yet refreshed (count=0) → unavailable, no fabricated factors."""
+    db = _FakeDB([_FakeResult(scalar_value=0)])
+    result = lc.compute_location_coef(db, lat=56.84, lon=60.6)
+    assert result.coef == 1.0
+    assert result.factors == []
+    assert result.geo_source == "unavailable"
+    # Only the count probe ran — no nearest-POI query issued against an empty mirror.
+    assert len(db.executed) == 1
+
+
+def test_compute_location_coef_no_poi_in_radius_is_legit_zero_score() -> None:
+    """Mirror populated (count>0) but nothing within radius → coef floor, NOT unavailable."""
+    db = _FakeDB(
+        [
+            _FakeResult(scalar_value=500),  # mirror has rows elsewhere
+            _FakeResult(mapping_rows=[]),  # nothing near this point
+        ]
+    )
+    result = lc.compute_location_coef(db, lat=56.84, lon=60.6)
+    assert result.factors == []
+    assert result.geo_source == "osm_poi_ekb"
+    assert result.coef == lc._score_to_coef(0.0) == 0.95
+
+
+def test_compute_location_coef_weights_and_ranks_top_n() -> None:
+    """Nearer + higher-weight-category POI ranks above farther/lower-weight ones."""
+    rows = [
+        {"name": "Школа №1", "category": "school", "distance_m": 300.0},
+        {"name": "ТЦ Мега", "category": "shop_mall", "distance_m": 900.0},
+        {"name": "Метро Ботаническая", "category": "metro_stop", "distance_m": 150.0},
+        {"name": "Аптека", "category": "pharmacy", "distance_m": 50.0},
+    ]
+    db = _FakeDB([_FakeResult(scalar_value=1000), _FakeResult(mapping_rows=rows)])
+    result = lc.compute_location_coef(db, lat=56.84, lon=60.6, top_n=7)
+
+    assert result.geo_source == "osm_poi_ekb"
+    assert len(result.factors) == 4
+    # metro_stop (weight 6.0) at 150m beats school (5.0) at 300m despite being closer only
+    # marginally — sanity check the ranking is weight-driven, not distance-only.
+    assert result.factors[0].poi_type == "metro_stop"
+    # Weights strictly descending (sorted DESC by weight before slicing to top_n).
+    weights = [f.weight for f in result.factors]
+    assert weights == sorted(weights, reverse=True)
+    # coef must land inside the documented [0.95, 1.05] MVP range.
+    assert 0.95 <= result.coef <= 1.05
+
+
+def test_compute_location_coef_limits_to_top_n() -> None:
+    """More than top_n candidates → only top_n factors surface in the response."""
+    rows = [
+        {"name": f"POI {i}", "category": "shop_small", "distance_m": float(100 + i * 10)}
+        for i in range(20)
+    ]
+    db = _FakeDB([_FakeResult(scalar_value=20), _FakeResult(mapping_rows=rows)])
+    result = lc.compute_location_coef(db, lat=56.84, lon=60.6, top_n=7)
+    assert len(result.factors) == 7
+
+
+def test_compute_location_coef_unknown_category_uses_default_weight() -> None:
+    rows = [{"name": "Неизвестный POI", "category": "some_new_osm_tag", "distance_m": 200.0}]
+    db = _FakeDB([_FakeResult(scalar_value=1), _FakeResult(mapping_rows=rows)])
+    result = lc.compute_location_coef(db, lat=56.84, lon=60.6)
+    assert len(result.factors) == 1
+    expected_weight = (1.0 / (200.0 + 100.0)) * lc.CATEGORY_WEIGHTS["default"]
+    assert abs(result.factors[0].weight - round(expected_weight, 6)) < 1e-9
+
+
+def test_compute_location_coef_passes_radius_param() -> None:
+    """radius_m is forwarded as a bound param (psycopg v3 CAST discipline, no :p::type)."""
+    db = _FakeDB([_FakeResult(scalar_value=1), _FakeResult(mapping_rows=[])])
+    lc.compute_location_coef(db, lat=56.84, lon=60.6, radius_m=1500)
+    _clause, params = db.executed[1]
+    assert params is not None
+    assert params["radius_m"] == 1500
+
+
+def test_no_psycopg_v3_colon_colon_cast() -> None:
+    """psycopg v3: never :param::type — must use CAST(:param AS type)."""
+    import re
+
+    assert not re.search(r":\w+::", str(lc._NEAREST_POI_SQL.text))

tradein-mvp/backend/tests/test_location_coef_endpoint.py

@@ -0,0 +1,251 @@
+"""Tests for GET /api/v1/trade-in/location-coef (#2045 BE-3, LocationDrawer).
+
+Mirrors the IDOR + mocked-DB conventions of test_estimate_idor.py / test_street_deals_endpoint.py
+(no live Postgres needed). Covers:
+  - IDOR guard (owner / other pilot 404 / admin / unauthenticated 401)
+  - graceful fallback: osm_poi_ekb_local empty/not-refreshed, estimate has no lat/lon
+  - happy path: base_price_rub * coef → result_price_rub, factors surfaced
+  - radius_m query-param clamping
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+from types import SimpleNamespace
+from unittest.mock import MagicMock
+
+# psycopg v3 driver required; stub DATABASE_URL before any app import.
+os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost:5432/test")
+
+# WeasyPrint requires GTK — not present in CI/Windows. Stub before any app import
+# (trade_in.py imports generate_trade_in_pdf at module load).
+_wp_mock = MagicMock()
+sys.modules.setdefault("weasyprint", _wp_mock)
+sys.modules.setdefault("weasyprint.CSS", _wp_mock)
+sys.modules.setdefault("weasyprint.HTML", _wp_mock)
+
+import pytest  # noqa: E402
+from fastapi import FastAPI  # noqa: E402
+from fastapi.testclient import TestClient  # noqa: E402
+
+_ESTIMATE_ID = "22222222-2222-2222-2222-222222222222"
+
+
+@pytest.fixture(autouse=True)
+def _restore_get_role():
+    """Restore app.core.auth.get_role after each test (mirror test_estimate_idor)."""
+    from app.core import auth as auth_mod
+
+    original = auth_mod.get_role
+    yield
+    auth_mod.get_role = original
+
+
+@pytest.fixture()
+def trade_in_app() -> FastAPI:
+    """Minimal FastAPI app mounting only the trade-in router."""
+    from app.api.v1 import trade_in as trade_in_module
+
+    application = FastAPI()
+    application.include_router(trade_in_module.router, prefix="/api/v1/trade-in")
+    return application
+
+
+def _client_with(app: FastAPI, db_mock: MagicMock, role: str | None) -> TestClient:
+    """Override get_db with *db_mock*; patch get_role to return *role* (or raise KeyError)."""
+    from app.core.db import get_db
+
+    def _override_db():
+        yield db_mock
+
+    app.dependency_overrides[get_db] = _override_db
+
+    auth_mod = sys.modules["app.core.auth"]
+    if role is None:
+
+        def _raise_keyerror(_u: str):
+            raise KeyError(_u)
+
+        auth_mod.get_role = _raise_keyerror  # type: ignore[assignment]
+    else:
+        auth_mod.get_role = lambda _u: role  # type: ignore[assignment]
+    return TestClient(app)
+
+
+def _fetchone_result(row: object) -> MagicMock:
+    r = MagicMock()
+    r.fetchone.return_value = row
+    return r
+
+
+def _scalar_result(value: object) -> MagicMock:
+    r = MagicMock()
+    r.scalar.return_value = value
+    return r
+
+
+def _mapping_result(rows: list[dict]) -> MagicMock:
+    r = MagicMock()
+    r.mappings.return_value.all.return_value = rows
+    return r
+
+
+def _db_with(*results: MagicMock) -> MagicMock:
+    db = MagicMock()
+    db.execute.side_effect = list(results)
+    return db
+
+
+# ── IDOR guard ────────────────────────────────────────────────────────────────
+
+
+def test_location_coef_other_pilot_gets_404(trade_in_app: FastAPI) -> None:
+    """Non-owner pilot must NOT read someone else's location-coef → 404."""
+    db = _db_with(_fetchone_result(SimpleNamespace(created_by="victim")))
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "attacker"},
+    )
+    assert resp.status_code == 404
+
+
+def test_location_coef_requires_authenticated_user(trade_in_app: FastAPI) -> None:
+    """No X-Authenticated-User header → 401 (guard query already ran, header check fails)."""
+    db = _db_with(_fetchone_result(SimpleNamespace(created_by="kopylov")))
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+    )
+    assert resp.status_code == 401
+
+
+def test_location_coef_unknown_estimate_returns_404(trade_in_app: FastAPI) -> None:
+    db = _db_with(_fetchone_result(None))
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "kopylov"},
+    )
+    assert resp.status_code == 404
+
+
+def test_location_coef_admin_can_read_any(trade_in_app: FastAPI) -> None:
+    """Admin reads any estimate's location-coef regardless of owner → 200."""
+    db = _db_with(
+        _fetchone_result(SimpleNamespace(created_by="someone_else")),  # guard
+        _fetchone_result(SimpleNamespace(lat=None, lon=None, median_price=5_000_000)),  # target
+    )
+    client = _client_with(trade_in_app, db, role="admin")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "admin"},
+    )
+    assert resp.status_code == 200
+
+
+# ── Graceful fallback ───────────────────────────────────────────────────────
+
+
+def test_location_coef_no_lat_lon_returns_unavailable(trade_in_app: FastAPI) -> None:
+    """Estimate without lat/lon → unavailable fallback, no osm_poi_ekb_local query at all."""
+    db = _db_with(
+        _fetchone_result(SimpleNamespace(created_by="kopylov")),  # guard
+        _fetchone_result(SimpleNamespace(lat=None, lon=None, median_price=5_000_000)),  # target
+    )
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "kopylov"},
+    )
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["geo_source"] == "unavailable"
+    assert body["coef"] == 1.0
+    assert body["factors"] == []
+    assert body["base_price_rub"] == 5_000_000
+    assert body["result_price_rub"] == 5_000_000
+    # Short-circuits before compute_location_coef: only guard + target queries ran.
+    assert db.execute.call_count == 2
+
+
+def test_location_coef_empty_mirror_returns_unavailable(trade_in_app: FastAPI) -> None:
+    """osm_poi_ekb_local not yet refreshed (count=0) → unavailable, no fabricated factors."""
+    db = _db_with(
+        _fetchone_result(SimpleNamespace(created_by="kopylov")),  # guard
+        _fetchone_result(SimpleNamespace(lat=56.84, lon=60.6, median_price=5_000_000)),  # target
+        _scalar_result(0),  # osm_poi_ekb_local count
+    )
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "kopylov"},
+    )
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["geo_source"] == "unavailable"
+    assert body["coef"] == 1.0
+    assert body["factors"] == []
+    assert body["result_price_rub"] == body["base_price_rub"]
+
+
+# ── Happy path ────────────────────────────────────────────────────────────────
+
+
+def test_location_coef_happy_path_computes_result_price(trade_in_app: FastAPI) -> None:
+    """POI found within radius → coef applied to base_price_rub, factors surfaced."""
+    poi_rows = [
+        {"name": "Школа №1", "category": "school", "distance_m": 300.0},
+        {"name": "Метро Ботаническая", "category": "metro_stop", "distance_m": 150.0},
+    ]
+    db = _db_with(
+        _fetchone_result(SimpleNamespace(created_by="kopylov")),  # guard
+        _fetchone_result(SimpleNamespace(lat=56.84, lon=60.6, median_price=5_000_000)),  # target
+        _scalar_result(1000),  # osm_poi_ekb_local count
+        _mapping_result(poi_rows),  # nearest POI
+    )
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID},
+        headers={"X-Authenticated-User": "kopylov"},
+    )
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["geo_source"] == "osm_poi_ekb"
+    assert body["base_price_rub"] == 5_000_000
+    assert 0.95 <= body["coef"] <= 1.05
+    assert body["result_price_rub"] == round(5_000_000 * body["coef"])
+    assert len(body["factors"]) == 2
+    poi_types = {f["poi_type"] for f in body["factors"]}
+    assert poi_types == {"school", "metro_stop"}
+
+
+def test_location_coef_radius_m_clamped_to_bounds(trade_in_app: FastAPI) -> None:
+    """Explicit radius_m outside [500, 3000] is clamped before hitting the DB query."""
+    db = _db_with(
+        _fetchone_result(SimpleNamespace(created_by="kopylov")),  # guard
+        _fetchone_result(SimpleNamespace(lat=56.84, lon=60.6, median_price=5_000_000)),  # target
+        _scalar_result(10),  # osm_poi_ekb_local count
+        _mapping_result([]),  # nearest POI query
+    )
+    client = _client_with(trade_in_app, db, role="pilot")
+    resp = client.get(
+        "/api/v1/trade-in/location-coef",
+        params={"estimate_id": _ESTIMATE_ID, "radius_m": 50},
+        headers={"X-Authenticated-User": "kopylov"},
+    )
+    assert resp.status_code == 200
+    # 4th execute() call is the nearest-POI query — inspect its bound radius_m param.
+    nearest_call = db.execute.call_args_list[3]
+    params = (
+        nearest_call.args[1] if len(nearest_call.args) > 1 else nearest_call.kwargs.get("params")
+    )
+    assert params["radius_m"] == 500