feat(offroute): Phase O3b — trail entry index, Valhalla stitching, /api/offroute endpoint

Phase A: Trail Entry Point Index
- Extract highway endpoints from idaho-latest.osm.pbf using osmium + ogr2ogr
- Store 740,430 entry points in /mnt/nav/navi.db (SQLite with spatial index)
- Entry points by class: service (271k), footway (152k), residential (146k),
  track (111k), path (26k), unclassified (16k), tertiary (9k), secondary (4k),
  primary (4k), bridleway (15)

Phase B: Pathfinder → Valhalla Stitching (router.py)
- OffrouteRouter orchestrates wilderness pathfinding + Valhalla on-network routing
- Queries entry points within 50km (expanding to 100km if needed)
- MCP pathfinder routes to nearest reachable entry point
- Calls Valhalla pedestrian/bicycle/auto costing for on-network segment
- Returns GeoJSON FeatureCollection with wilderness + network + combined segments

Phase C: Flask Endpoint
- POST /api/offroute with start/end coordinates, mode, boundary_mode
- Returns GeoJSON route with per-segment metadata and turn-by-turn maneuvers

Validated: 42.35,-114.30 → Twin Falls downtown
- Wilderness: 0.5km, 9min | Network: 36km, 413min | Total: ~421min
- 21 turn-by-turn instructions, segments connect at entry point

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

lib/offroute/router.py

@@ -0,0 +1,752 @@
+"""
+OFFROUTE Router — Wilderness to network path orchestration.
+
+Connects the raster pathfinder (wilderness segment) to Valhalla (on-network segment).
+
+Entry points are extracted from OSM highways and stored in /mnt/nav/navi.db.
+The pathfinder routes from a wilderness start to the nearest entry point,
+then Valhalla completes the route to the destination.
+"""
+import json
+import math
+import sqlite3
+import subprocess
+import tempfile
+import time
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple, Literal
+
+import numpy as np
+import requests
+from skimage.graph import MCP_Geometric
+
+from .dem import DEMReader
+from .cost import compute_cost_grid
+from .friction import FrictionReader, friction_to_multiplier
+from .barriers import BarrierReader
+from .trails import TrailReader
+
+# Paths
+NAVI_DB_PATH = Path("/mnt/nav/navi.db")
+OSM_PBF_PATH = Path("/mnt/nav/sources/idaho-latest.osm.pbf")
+
+# Valhalla endpoint
+VALHALLA_URL = "http://localhost:8002"
+
+# Search radius for entry points (km)
+DEFAULT_SEARCH_RADIUS_KM = 50
+EXPANDED_SEARCH_RADIUS_KM = 100
+
+# Memory limit
+MEMORY_LIMIT_GB = 12
+
+# Mode to Valhalla costing mapping
+MODE_TO_COSTING = {
+    "foot": "pedestrian",
+    "mtb": "bicycle",
+    "atv": "auto",
+}
+
+
+def haversine_distance(lat1: float, lon1: float, lat2: float, lon2: float) -> float:
+    """Calculate distance between two points in meters."""
+    R = 6371000
+    dlat = math.radians(lat2 - lat1)
+    dlon = math.radians(lon2 - lon1)
+    a = math.sin(dlat/2)**2 + math.cos(math.radians(lat1)) * math.cos(math.radians(lat2)) * math.sin(dlon/2)**2
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
+    return R * c
+
+
+def check_memory_usage() -> float:
+    """Check current memory usage in GB."""
+    try:
+        import psutil
+        process = psutil.Process()
+        return process.memory_info().rss / (1024**3)
+    except ImportError:
+        return 0
+
+
+class EntryPointIndex:
+    """
+    Trail entry point index for wilderness-to-network handoff.
+
+    Entry points are endpoints and intersections of OSM highways
+    that connect wilderness areas to the routable network.
+    """
+
+    def __init__(self, db_path: Path = NAVI_DB_PATH):
+        self.db_path = db_path
+        self._conn = None
+
+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(str(self.db_path))
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
+    def table_exists(self) -> bool:
+        """Check if trail_entry_points table exists."""
+        if not self.db_path.exists():
+            return False
+        conn = self._get_conn()
+        cur = conn.execute(
+            "SELECT name FROM sqlite_master WHERE type='table' AND name='trail_entry_points'"
+        )
+        return cur.fetchone() is not None
+
+    def get_entry_point_count(self) -> int:
+        """Get count of entry points."""
+        if not self.table_exists():
+            return 0
+        conn = self._get_conn()
+        cur = conn.execute("SELECT COUNT(*) FROM trail_entry_points")
+        return cur.fetchone()[0]
+
+    def query_bbox(self, south: float, north: float, west: float, east: float) -> List[Dict]:
+        """Query entry points within a bounding box."""
+        if not self.table_exists():
+            return []
+
+        conn = self._get_conn()
+        cur = conn.execute("""
+            SELECT id, lat, lon, highway_class, name
+            FROM trail_entry_points
+            WHERE lat >= ? AND lat <= ? AND lon >= ? AND lon <= ?
+        """, (south, north, west, east))
+
+        return [dict(row) for row in cur.fetchall()]
+
+    def query_radius(self, lat: float, lon: float, radius_km: float) -> List[Dict]:
+        """Query entry points within radius of a point."""
+        # Approximate bbox for the radius
+        lat_delta = radius_km / 111.0
+        lon_delta = radius_km / (111.0 * math.cos(math.radians(lat)))
+
+        points = self.query_bbox(
+            lat - lat_delta, lat + lat_delta,
+            lon - lon_delta, lon + lon_delta
+        )
+
+        # Filter by actual distance and add distance field
+        result = []
+        for p in points:
+            dist = haversine_distance(lat, lon, p['lat'], p['lon'])
+            if dist <= radius_km * 1000:
+                p['distance_m'] = dist
+                result.append(p)
+
+        return sorted(result, key=lambda x: x['distance_m'])
+
+    def build_index(self, osm_pbf_path: Path = OSM_PBF_PATH) -> Dict:
+        """
+        Build the entry point index from OSM PBF.
+
+        Extracts endpoints of highway features that connect to the network.
+        """
+        if not osm_pbf_path.exists():
+            raise FileNotFoundError(f"OSM PBF not found: {osm_pbf_path}")
+
+        print(f"Building trail entry point index from {osm_pbf_path}...")
+
+        # Highway types to extract (routable network entry points)
+        highway_types = [
+            "primary", "secondary", "tertiary", "unclassified",
+            "residential", "service", "track", "path", "footway", "bridleway"
+        ]
+
+        stats = {"total": 0, "by_class": {}}
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            # Extract highways to GeoJSON
+            geojson_path = Path(tmpdir) / "highways.geojson"
+
+            # Build osmium tags-filter expressions (one per highway type)
+            print(f"  Extracting highways with osmium...")
+            cmd = [
+                "osmium", "tags-filter",
+                str(osm_pbf_path),
+            ]
+            # Add each highway type as a separate filter expression
+            for ht in highway_types:
+                cmd.append(f"w/highway={ht}")
+            cmd.extend(["-o", str(Path(tmpdir) / "filtered.osm.pbf"), "--overwrite"])
+
+            subprocess.run(cmd, check=True, capture_output=True)
+
+            # Convert to GeoJSON
+            print(f"  Converting to GeoJSON with ogr2ogr...")
+            cmd = [
+                "ogr2ogr", "-f", "GeoJSON",
+                str(geojson_path),
+                str(Path(tmpdir) / "filtered.osm.pbf"),
+                "lines",
+                "-t_srs", "EPSG:4326"
+            ]
+            subprocess.run(cmd, check=True, capture_output=True)
+
+            # Parse GeoJSON and extract endpoints
+            print(f"  Extracting entry points...")
+            with open(geojson_path) as f:
+                data = json.load(f)
+
+            # Collect unique points (endpoints)
+            # Key: (lat, lon) rounded to 5 decimal places (~1m precision)
+            points = {}
+
+            for feature in data.get("features", []):
+                props = feature.get("properties", {})
+                geom = feature.get("geometry", {})
+
+                if geom.get("type") != "LineString":
+                    continue
+
+                coords = geom.get("coordinates", [])
+                if len(coords) < 2:
+                    continue
+
+                highway_class = props.get("highway", "unknown")
+                name = props.get("name", "")
+
+                # Extract endpoints
+                for coord in [coords[0], coords[-1]]:
+                    lon, lat = coord[0], coord[1]
+                    key = (round(lat, 5), round(lon, 5))
+
+                    if key not in points:
+                        points[key] = {
+                            "lat": lat,
+                            "lon": lon,
+                            "highway_class": highway_class,
+                            "name": name
+                        }
+                    else:
+                        # Keep the "best" highway class (roads > tracks > paths)
+                        existing = points[key]
+                        if self._highway_priority(highway_class) < self._highway_priority(existing["highway_class"]):
+                            points[key]["highway_class"] = highway_class
+                        if name and not existing["name"]:
+                            points[key]["name"] = name
+
+        # Create/update database
+        print(f"  Writing {len(points)} entry points to {self.db_path}...")
+
+        self.db_path.parent.mkdir(parents=True, exist_ok=True)
+        conn = self._get_conn()
+
+        # Create table
+        conn.execute("""
+            CREATE TABLE IF NOT EXISTS trail_entry_points (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                lat REAL NOT NULL,
+                lon REAL NOT NULL,
+                highway_class TEXT NOT NULL,
+                name TEXT
+            )
+        """)
+
+        # Clear existing data
+        conn.execute("DELETE FROM trail_entry_points")
+
+        # Insert new points
+        for point in points.values():
+            conn.execute("""
+                INSERT INTO trail_entry_points (lat, lon, highway_class, name)
+                VALUES (?, ?, ?, ?)
+            """, (point["lat"], point["lon"], point["highway_class"], point["name"]))
+
+            stats["total"] += 1
+            hc = point["highway_class"]
+            stats["by_class"][hc] = stats["by_class"].get(hc, 0) + 1
+
+        # Create spatial index
+        conn.execute("CREATE INDEX IF NOT EXISTS idx_entry_lat ON trail_entry_points(lat)")
+        conn.execute("CREATE INDEX IF NOT EXISTS idx_entry_lon ON trail_entry_points(lon)")
+        conn.execute("CREATE INDEX IF NOT EXISTS idx_entry_latlon ON trail_entry_points(lat, lon)")
+
+        conn.commit()
+
+        print(f"  Done. Total: {stats['total']} entry points")
+        for hc, count in sorted(stats["by_class"].items(), key=lambda x: -x[1]):
+            print(f"    {hc}: {count}")
+
+        return stats
+
+    def _highway_priority(self, highway_class: str) -> int:
+        """Lower number = better priority for entry points."""
+        priority = {
+            "primary": 1, "secondary": 2, "tertiary": 3,
+            "unclassified": 4, "residential": 5, "service": 6,
+            "track": 7, "path": 8, "footway": 9, "bridleway": 10
+        }
+        return priority.get(highway_class, 99)
+
+    def close(self):
+        if self._conn:
+            self._conn.close()
+            self._conn = None
+
+
+class OffrouteRouter:
+    """
+    OFFROUTE Router — orchestrates wilderness pathfinding and Valhalla stitching.
+    """
+
+    def __init__(self):
+        self.dem_reader = None
+        self.friction_reader = None
+        self.barrier_reader = None
+        self.trail_reader = None
+        self.entry_index = EntryPointIndex()
+
+    def _init_readers(self):
+        """Lazy init readers."""
+        if self.dem_reader is None:
+            self.dem_reader = DEMReader()
+        if self.friction_reader is None:
+            self.friction_reader = FrictionReader()
+        if self.barrier_reader is None:
+            self.barrier_reader = BarrierReader()
+        if self.trail_reader is None:
+            self.trail_reader = TrailReader()
+
+    def route(
+        self,
+        start_lat: float,
+        start_lon: float,
+        end_lat: float,
+        end_lon: float,
+        mode: Literal["foot", "mtb", "atv"] = "foot",
+        boundary_mode: Literal["strict", "pragmatic", "emergency"] = "pragmatic"
+    ) -> Dict:
+        """
+        Route from a wilderness start point to a destination.
+
+        Returns a GeoJSON FeatureCollection with wilderness and network segments.
+        """
+        t0 = time.time()
+
+        # Ensure entry point index exists
+        if not self.entry_index.table_exists() or self.entry_index.get_entry_point_count() == 0:
+            return {
+                "status": "error",
+                "message": "Trail entry point index not built. Run build_entry_index() first."
+            }
+
+        # Find entry points near start
+        entry_points = self.entry_index.query_radius(
+            start_lat, start_lon, DEFAULT_SEARCH_RADIUS_KM
+        )
+
+        if not entry_points:
+            # Try expanded radius
+            entry_points = self.entry_index.query_radius(
+                start_lat, start_lon, EXPANDED_SEARCH_RADIUS_KM
+            )
+            if not entry_points:
+                return {
+                    "status": "error",
+                    "message": f"No trail entry points found within {EXPANDED_SEARCH_RADIUS_KM}km of start"
+                }
+
+        # Build bbox for pathfinding grid
+        # Include start, end, and all entry points
+        all_lats = [start_lat, end_lat] + [p["lat"] for p in entry_points]
+        all_lons = [start_lon, end_lon] + [p["lon"] for p in entry_points]
+
+        padding = 0.05  # ~5km padding
+        bbox = {
+            "south": min(all_lats) - padding,
+            "north": max(all_lats) + padding,
+            "west": min(all_lons) - padding,
+            "east": max(all_lons) + padding,
+        }
+
+        # Initialize readers
+        self._init_readers()
+
+        # Load elevation
+        try:
+            elevation, meta = self.dem_reader.get_elevation_grid(
+                south=bbox["south"],
+                north=bbox["north"],
+                west=bbox["west"],
+                east=bbox["east"],
+            )
+        except Exception as e:
+            return {"status": "error", "message": f"Failed to load elevation: {e}"}
+
+        # Check memory
+        mem = check_memory_usage()
+        if mem > MEMORY_LIMIT_GB:
+            return {"status": "error", "message": f"Memory limit exceeded: {mem:.1f}GB > {MEMORY_LIMIT_GB}GB"}
+
+        # Load friction
+        friction_raw = self.friction_reader.get_friction_grid(
+            south=bbox["south"],
+            north=bbox["north"],
+            west=bbox["west"],
+            east=bbox["east"],
+            target_shape=elevation.shape
+        )
+        friction_mult = friction_to_multiplier(friction_raw)
+
+        # Load barriers
+        barriers = self.barrier_reader.get_barrier_grid(
+            south=bbox["south"],
+            north=bbox["north"],
+            west=bbox["west"],
+            east=bbox["east"],
+            target_shape=elevation.shape
+        )
+
+        # Load trails
+        trails = self.trail_reader.get_trails_grid(
+            south=bbox["south"],
+            north=bbox["north"],
+            west=bbox["west"],
+            east=bbox["east"],
+            target_shape=elevation.shape
+        )
+
+        # Compute cost grid
+        cost = compute_cost_grid(
+            elevation,
+            cell_size_m=meta["cell_size_m"],
+            friction=friction_mult,
+            trails=trails,
+            barriers=barriers,
+            boundary_mode=boundary_mode,
+        )
+
+        # Convert start to pixel coordinates
+        start_row, start_col = self.dem_reader.latlon_to_pixel(start_lat, start_lon, meta)
+
+        # Validate start is in bounds
+        rows, cols = elevation.shape
+        if not (0 <= start_row < rows and 0 <= start_col < cols):
+            return {"status": "error", "message": "Start point outside grid bounds"}
+
+        # Mark entry points on the grid
+        entry_pixels = []
+        for ep in entry_points:
+            row, col = self.dem_reader.latlon_to_pixel(ep["lat"], ep["lon"], meta)
+            if 0 <= row < rows and 0 <= col < cols:
+                entry_pixels.append({
+                    "row": row,
+                    "col": col,
+                    "entry_point": ep
+                })
+
+        if not entry_pixels:
+            return {"status": "error", "message": "No entry points map to grid bounds"}
+
+        # Run MCP pathfinder
+        mcp = MCP_Geometric(cost, fully_connected=True)
+        cumulative_costs, traceback = mcp.find_costs([(start_row, start_col)])
+
+        # Find nearest reachable entry point
+        best_entry = None
+        best_cost = np.inf
+
+        for ep in entry_pixels:
+            ep_cost = cumulative_costs[ep["row"], ep["col"]]
+            if ep_cost < best_cost:
+                best_cost = ep_cost
+                best_entry = ep
+
+        if best_entry is None or np.isinf(best_cost):
+            return {
+                "status": "error",
+                "message": "No path found to any entry point (blocked by impassable terrain)"
+            }
+
+        # Traceback wilderness path
+        path_indices = mcp.traceback((best_entry["row"], best_entry["col"]))
+
+        # Convert to coordinates and collect stats
+        wilderness_coords = []
+        elevations = []
+        trail_values = []
+
+        for row, col in path_indices:
+            lat, lon = self.dem_reader.pixel_to_latlon(row, col, meta)
+            wilderness_coords.append([lon, lat])
+            elevations.append(elevation[row, col])
+            trail_values.append(trails[row, col])
+
+        # Calculate wilderness segment stats
+        wilderness_distance_m = 0
+        for i in range(1, len(wilderness_coords)):
+            lon1, lat1 = wilderness_coords[i-1]
+            lon2, lat2 = wilderness_coords[i]
+            wilderness_distance_m += haversine_distance(lat1, lon1, lat2, lon2)
+
+        elev_arr = np.array(elevations)
+        elev_diff = np.diff(elev_arr)
+        wilderness_gain = float(np.sum(elev_diff[elev_diff > 0]))
+        wilderness_loss = float(np.sum(np.abs(elev_diff[elev_diff < 0])))
+
+        trail_arr = np.array(trail_values)
+        on_trail_cells = np.sum(trail_arr > 0)
+        total_cells = len(trail_arr)
+        on_trail_pct = float(100 * on_trail_cells / total_cells) if total_cells > 0 else 0
+
+        # Entry point reached
+        entry_lat = best_entry["entry_point"]["lat"]
+        entry_lon = best_entry["entry_point"]["lon"]
+        entry_class = best_entry["entry_point"]["highway_class"]
+        entry_name = best_entry["entry_point"].get("name", "")
+
+        # Call Valhalla for on-network segment
+        valhalla_costing = MODE_TO_COSTING.get(mode, "pedestrian")
+
+        valhalla_request = {
+            "locations": [
+                {"lat": entry_lat, "lon": entry_lon},
+                {"lat": end_lat, "lon": end_lon}
+            ],
+            "costing": valhalla_costing,
+            "directions_options": {"units": "kilometers"}
+        }
+
+        network_segment = None
+        valhalla_error = None
+
+        try:
+            resp = requests.post(
+                f"{VALHALLA_URL}/route",
+                json=valhalla_request,
+                timeout=30
+            )
+
+            if resp.status_code == 200:
+                valhalla_data = resp.json()
+                trip = valhalla_data.get("trip", {})
+                legs = trip.get("legs", [])
+
+                if legs:
+                    leg = legs[0]
+                    shape = leg.get("shape", "")
+
+                    # Decode polyline6
+                    network_coords = self._decode_polyline(shape)
+
+                    # Extract maneuvers
+                    maneuvers = []
+                    for m in leg.get("maneuvers", []):
+                        maneuvers.append({
+                            "instruction": m.get("instruction", ""),
+                            "type": m.get("type", 0),
+                            "distance_km": m.get("length", 0),
+                            "time_seconds": m.get("time", 0),
+                            "street_names": m.get("street_names", []),
+                        })
+
+                    summary = trip.get("summary", {})
+                    network_segment = {
+                        "coordinates": network_coords,
+                        "distance_km": summary.get("length", 0),
+                        "duration_minutes": summary.get("time", 0) / 60,
+                        "maneuvers": maneuvers,
+                    }
+            else:
+                valhalla_error = f"Valhalla returned {resp.status_code}: {resp.text[:200]}"
+
+        except Exception as e:
+            valhalla_error = f"Valhalla request failed: {e}"
+
+        # Build response
+        features = []
+
+        # Feature 1: Wilderness segment
+        wilderness_feature = {
+            "type": "Feature",
+            "properties": {
+                "segment_type": "wilderness",
+                "effort_minutes": float(best_cost / 60),
+                "distance_km": float(wilderness_distance_m / 1000),
+                "elevation_gain_m": wilderness_gain,
+                "elevation_loss_m": wilderness_loss,
+                "boundary_mode": boundary_mode,
+                "on_trail_pct": on_trail_pct,
+                "cell_count": total_cells,
+            },
+            "geometry": {
+                "type": "LineString",
+                "coordinates": wilderness_coords,
+            }
+        }
+        features.append(wilderness_feature)
+
+        # Feature 2: Network segment (if available)
+        if network_segment:
+            network_feature = {
+                "type": "Feature",
+                "properties": {
+                    "segment_type": "network",
+                    "distance_km": network_segment["distance_km"],
+                    "duration_minutes": network_segment["duration_minutes"],
+                    "maneuvers": network_segment["maneuvers"],
+                },
+                "geometry": {
+                    "type": "LineString",
+                    "coordinates": network_segment["coordinates"],
+                }
+            }
+            features.append(network_feature)
+
+        # Build combined route coordinates
+        combined_coords = wilderness_coords.copy()
+        if network_segment:
+            # Skip first point of network segment (it's the same as last wilderness point)
+            combined_coords.extend(network_segment["coordinates"][1:])
+
+        # Feature 3: Combined route
+        combined_feature = {
+            "type": "Feature",
+            "properties": {
+                "segment_type": "combined",
+                "mode": mode,
+                "boundary_mode": boundary_mode,
+            },
+            "geometry": {
+                "type": "LineString",
+                "coordinates": combined_coords,
+            }
+        }
+        features.append(combined_feature)
+
+        geojson = {
+            "type": "FeatureCollection",
+            "features": features,
+        }
+
+        # Build summary
+        total_distance_km = wilderness_distance_m / 1000
+        total_effort_minutes = best_cost / 60
+
+        if network_segment:
+            total_distance_km += network_segment["distance_km"]
+            total_effort_minutes += network_segment["duration_minutes"]
+
+        summary = {
+            "total_distance_km": float(total_distance_km),
+            "total_effort_minutes": float(total_effort_minutes),
+            "wilderness_distance_km": float(wilderness_distance_m / 1000),
+            "wilderness_effort_minutes": float(best_cost / 60),
+            "network_distance_km": float(network_segment["distance_km"]) if network_segment else 0,
+            "network_duration_minutes": float(network_segment["duration_minutes"]) if network_segment else 0,
+            "on_trail_pct": on_trail_pct,
+            "boundary_mode": boundary_mode,
+            "mode": mode,
+            "entry_point": {
+                "lat": entry_lat,
+                "lon": entry_lon,
+                "highway_class": entry_class,
+                "name": entry_name,
+            },
+            "computation_time_s": time.time() - t0,
+        }
+
+        result = {
+            "status": "ok",
+            "route": geojson,
+            "summary": summary,
+        }
+
+        if valhalla_error:
+            result["warning"] = f"Network segment incomplete: {valhalla_error}"
+
+        return result
+
+    def _decode_polyline(self, encoded: str, precision: int = 6) -> List[List[float]]:
+        """Decode a polyline string into coordinates [lon, lat]."""
+        coords = []
+        index = 0
+        lat = 0
+        lon = 0
+
+        while index < len(encoded):
+            # Latitude
+            shift = 0
+            result = 0
+            while True:
+                b = ord(encoded[index]) - 63
+                index += 1
+                result |= (b & 0x1f) << shift
+                shift += 5
+                if b < 0x20:
+                    break
+            dlat = ~(result >> 1) if result & 1 else result >> 1
+            lat += dlat
+
+            # Longitude
+            shift = 0
+            result = 0
+            while True:
+                b = ord(encoded[index]) - 63
+                index += 1
+                result |= (b & 0x1f) << shift
+                shift += 5
+                if b < 0x20:
+                    break
+            dlon = ~(result >> 1) if result & 1 else result >> 1
+            lon += dlon
+
+            coords.append([lon / (10 ** precision), lat / (10 ** precision)])
+
+        return coords
+
+    def close(self):
+        """Close all readers."""
+        if self.dem_reader:
+            self.dem_reader.close()
+        if self.friction_reader:
+            self.friction_reader.close()
+        if self.barrier_reader:
+            self.barrier_reader.close()
+        if self.trail_reader:
+            self.trail_reader.close()
+        self.entry_index.close()
+
+
+def build_entry_index():
+    """Build the trail entry point index."""
+    index = EntryPointIndex()
+    stats = index.build_index()
+    index.close()
+    return stats
+
+
+if __name__ == "__main__":
+    import sys
+
+    if len(sys.argv) > 1 and sys.argv[1] == "build":
+        print("Building trail entry point index...")
+        stats = build_entry_index()
+        print(f"\nDone. Total entry points: {stats['total']}")
+
+    elif len(sys.argv) > 1 and sys.argv[1] == "test":
+        print("Testing router...")
+
+        router = OffrouteRouter()
+
+        # Test route: wilderness to Twin Falls
+        result = router.route(
+            start_lat=42.35,
+            start_lon=-114.30,
+            end_lat=42.5629,
+            end_lon=-114.4609,
+            mode="foot",
+            boundary_mode="pragmatic"
+        )
+
+        print(json.dumps(result, indent=2, default=str))
+        router.close()
+
+    else:
+        print("Usage:")
+        print("  python router.py build   # Build entry point index")
+        print("  python router.py test    # Test route")