alex
df8d1adf15
- Replace all AdventureLog references with Voyage across ~102 files (7 case variants: AdventureLog, adventurelog, Adventurelog, ADVENTURELOG, AdventUrelog, AdventureLOG, adventure-log, adventure_log) - Rename brand, static, and documentation assets to use voyage naming - Rename install_adventurelog.sh → install_voyage.sh - Update README.md and voyage_overview.md to credit AdventureLog as the upstream project and Sean Morley as its original creator
681 lines
29 KiB
Python
681 lines
29 KiB
Python
from rest_framework import viewsets
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from rest_framework.decorators import action
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from rest_framework.permissions import IsAuthenticated
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from rest_framework.response import Response
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from django.conf import settings
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import requests
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from geopy.distance import geodesic
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import logging
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from ..geocoding import search_google, search_osm
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logger = logging.getLogger(__name__)
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class RecommendationsViewSet(viewsets.ViewSet):
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permission_classes = [IsAuthenticated]
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OVERPASS_URL = "https://overpass-api.de/api/interpreter"
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NOMINATIM_URL = "https://nominatim.openstreetmap.org/search"
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HEADERS = {'User-Agent': 'Voyage Server'}
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# Quality thresholds
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MIN_GOOGLE_RATING = 3.0 # Minimum rating to include
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MIN_GOOGLE_REVIEWS = 5 # Minimum number of reviews
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MAX_RESULTS = 50 # Maximum results to return
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def calculate_quality_score(self, place_data):
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"""
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Calculate a quality score based on multiple factors.
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Higher score = better quality recommendation.
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"""
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import math
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score = 0.0
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# Rating contribution (0-50 points)
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rating = place_data.get('rating')
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if rating is not None and rating > 0:
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score += (rating / 5.0) * 50
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# Review count contribution (0-30 points, logarithmic scale)
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review_count = place_data.get('review_count')
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if review_count is not None and review_count > 0:
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# Logarithmic scale: 10 reviews = ~10 pts, 100 = ~20 pts, 1000 = ~30 pts
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score += min(30, math.log10(review_count) * 10)
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# Distance penalty (0-20 points, closer is better)
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distance_km = place_data.get('distance_km')
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if distance_km is not None:
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if distance_km < 1:
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score += 20
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elif distance_km < 5:
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score += 15
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elif distance_km < 10:
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score += 10
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elif distance_km < 20:
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score += 5
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# Verified/business status bonus (0-10 points)
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if place_data.get('is_verified') or place_data.get('business_status') == 'OPERATIONAL':
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score += 10
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# Has photos bonus (0-5 points)
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photos = place_data.get('photos')
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if photos and len(photos) > 0:
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score += 5
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# Has opening hours bonus (0-5 points)
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opening_hours = place_data.get('opening_hours')
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if opening_hours and len(opening_hours) > 0:
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score += 5
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return round(score, 2)
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def parse_google_places(self, places, origin):
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"""
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Parse Google Places API results into unified format.
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Enhanced with quality filtering and comprehensive data extraction.
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"""
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locations = []
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api_key = getattr(settings, 'GOOGLE_MAPS_API_KEY', None)
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for place in places:
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location = place.get('location', {})
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types = place.get('types', [])
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# Extract display name
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display_name = place.get("displayName", {})
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name = display_name.get("text") if isinstance(display_name, dict) else display_name
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# Extract coordinates
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lat = location.get('latitude')
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lon = location.get('longitude')
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if not name or not lat or not lon:
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continue
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# Extract rating information
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rating = place.get('rating')
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review_count = place.get('userRatingCount', 0)
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# Quality filter: Skip low-rated or unreviewed places
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if rating and rating < self.MIN_GOOGLE_RATING:
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continue
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if review_count < self.MIN_GOOGLE_REVIEWS:
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continue
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# Calculate distance
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distance_km = geodesic(origin, (lat, lon)).km
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# Extract address information
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formatted_address = place.get("formattedAddress") or place.get("shortFormattedAddress")
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# Extract business status
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business_status = place.get('businessStatus')
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is_operational = business_status == 'OPERATIONAL'
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# Extract opening hours
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opening_hours = place.get('regularOpeningHours', {})
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current_opening_hours = place.get('currentOpeningHours', {})
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is_open_now = current_opening_hours.get('openNow')
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# Extract photos and construct URLs
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photos = place.get('photos', [])
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photo_urls = []
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if photos and api_key:
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# Get first 5 photos and construct full URLs
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for photo in photos[:5]:
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photo_name = photo.get('name', '')
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if photo_name:
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# Construct Google Places Photo API URL
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# Format: https://places.googleapis.com/v1/{name}/media?key={key}&maxHeightPx=800&maxWidthPx=800
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photo_url = f"https://places.googleapis.com/v1/{photo_name}/media?key={api_key}&maxHeightPx=800&maxWidthPx=800"
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photo_urls.append(photo_url)
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# Extract contact information
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phone_number = place.get('nationalPhoneNumber') or place.get('internationalPhoneNumber')
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website = place.get('websiteUri')
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google_maps_uri = place.get('googleMapsUri')
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# Extract price level
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price_level = place.get('priceLevel')
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# Extract editorial summary/description
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editorial_summary = place.get('editorialSummary', {})
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description = editorial_summary.get('text') if isinstance(editorial_summary, dict) else None
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# Filter out unwanted types (generic categories)
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filtered_types = [t for t in types if t not in ['point_of_interest', 'establishment']]
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# Build unified response
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place_data = {
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"id": f"google:{place.get('id')}",
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"external_id": place.get('id'),
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"source": "google",
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"name": name,
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"description": description,
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"latitude": lat,
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"longitude": lon,
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"address": formatted_address,
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"distance_km": round(distance_km, 2),
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"rating": rating,
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"review_count": review_count,
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"price_level": price_level,
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"types": filtered_types,
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"primary_type": filtered_types[0] if filtered_types else None,
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"business_status": business_status,
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"is_open_now": is_open_now,
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"opening_hours": opening_hours.get('weekdayDescriptions', []) if opening_hours else None,
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"phone_number": phone_number,
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"website": website,
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"google_maps_url": google_maps_uri,
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"photos": photo_urls,
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"is_verified": is_operational,
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}
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# Calculate quality score
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place_data['quality_score'] = self.calculate_quality_score(place_data)
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locations.append(place_data)
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return locations
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def parse_overpass_response(self, data, request, origin):
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"""
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Parse Overpass API (OSM) results into unified format.
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Enhanced with quality filtering and comprehensive data extraction.
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"""
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nodes = data.get('elements', [])
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locations = []
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for node in nodes:
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if node.get('type') not in ['node', 'way', 'relation']:
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continue
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tags = node.get('tags', {})
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# Get coordinates (for ways/relations, use center)
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lat = node.get('lat') or node.get('center', {}).get('lat')
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lon = node.get('lon') or node.get('center', {}).get('lon')
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# Extract name (with fallbacks)
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name = tags.get('name') or tags.get('official_name') or tags.get('alt_name')
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if not name or lat is None or lon is None:
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continue
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# Calculate distance
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distance_km = round(geodesic(origin, (lat, lon)).km, 2) if origin else None
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# Extract address information
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address_parts = [
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tags.get('addr:housenumber'),
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tags.get('addr:street'),
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tags.get('addr:suburb') or tags.get('addr:neighbourhood'),
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tags.get('addr:city'),
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tags.get('addr:state'),
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tags.get('addr:postcode'),
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tags.get('addr:country')
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]
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formatted_address = ", ".join(filter(None, address_parts)) or None
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# Extract contact information
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phone = tags.get('phone') or tags.get('contact:phone')
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website = tags.get('website') or tags.get('contact:website') or tags.get('url')
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# Extract opening hours
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opening_hours = tags.get('opening_hours')
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# Extract rating/stars (if available)
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stars = tags.get('stars')
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# Determine category/type hierarchy
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category_keys = ['tourism', 'leisure', 'amenity', 'natural', 'historic', 'attraction', 'shop', 'sport']
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types = [tags.get(key) for key in category_keys if key in tags]
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primary_type = types[0] if types else None
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# Extract description and additional info
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description = tags.get('description') or tags.get('note')
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wikipedia = tags.get('wikipedia') or tags.get('wikidata')
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# Extract image if available
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image = tags.get('image') or tags.get('wikimedia_commons')
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# Quality filters for OSM data
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# Skip if it's just a generic POI without specific category
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if not primary_type:
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continue
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# Skip construction or disused places
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if tags.get('disused') or tags.get('construction'):
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continue
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# Build unified response
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place_data = {
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"id": f"osm:{node.get('type')}:{node.get('id')}",
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"external_id": str(node.get('id')),
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"source": "osm",
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"name": name,
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"description": description,
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"latitude": lat,
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"longitude": lon,
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"address": formatted_address,
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"distance_km": distance_km,
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"rating": None, # OSM doesn't have ratings
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"review_count": None,
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"price_level": None,
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"types": types,
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"primary_type": primary_type,
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"business_status": None,
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"is_open_now": None,
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"opening_hours": [opening_hours] if opening_hours else None,
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"phone_number": phone,
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"website": website,
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"google_maps_url": None,
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"photos": [image] if image else [],
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"is_verified": bool(wikipedia), # Has Wikipedia = more verified
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"osm_type": node.get('type'),
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"wikipedia": wikipedia,
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"stars": stars,
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}
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# Calculate quality score (will be lower without ratings)
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place_data['quality_score'] = self.calculate_quality_score(place_data)
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locations.append(place_data)
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return locations
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def query_overpass(self, lat, lon, radius, category, request):
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"""
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Query Overpass API (OpenStreetMap) for nearby places.
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Enhanced with better queries and error handling.
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"""
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# Limit radius for OSM to prevent timeouts (max 5km for OSM due to server limits)
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osm_radius = min(radius, 5000)
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# Build optimized query - use simpler queries and limit results
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# Reduced timeout and simplified queries to prevent 504 errors
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if category == 'tourism':
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query = f"""
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[out:json][timeout:25];
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(
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nwr["tourism"~"attraction|viewpoint|museum|gallery|zoo|aquarium"](around:{osm_radius},{lat},{lon});
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nwr["historic"~"monument|castle|memorial"](around:{osm_radius},{lat},{lon});
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nwr["leisure"~"park|garden|nature_reserve"](around:{osm_radius},{lat},{lon});
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);
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out center tags 50;
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"""
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elif category == 'lodging':
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query = f"""
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[out:json][timeout:25];
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nwr["tourism"~"hotel|motel|guest_house|hostel"](around:{osm_radius},{lat},{lon});
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out center tags 50;
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"""
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elif category == 'food':
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query = f"""
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[out:json][timeout:25];
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nwr["amenity"~"restaurant|cafe|bar|pub"](around:{osm_radius},{lat},{lon});
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out center tags 50;
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"""
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else:
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logger.error(f"Invalid category requested: {category}")
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return {"error": "Invalid category.", "results": []}
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try:
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response = requests.post(
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self.OVERPASS_URL,
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data=query,
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headers=self.HEADERS,
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timeout=30
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)
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response.raise_for_status()
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data = response.json()
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except requests.exceptions.Timeout:
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logger.warning(f"Overpass API timeout for {category} at ({lat}, {lon}) with radius {osm_radius}m")
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return {"error": f"OpenStreetMap query timed out. The service is overloaded. Radius limited to {int(osm_radius)}m.", "results": []}
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except requests.exceptions.HTTPError as e:
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if e.response.status_code == 504:
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logger.warning(f"Overpass API 504 Gateway Timeout for {category}")
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return {"error": "OpenStreetMap server is overloaded. Try again later or use Google source.", "results": []}
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logger.warning(f"Overpass API HTTP error: {e}")
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return {"error": f"OpenStreetMap error: please try again later.", "results": []}
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except requests.exceptions.RequestException as e:
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logger.warning(f"Overpass API error: {e}")
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return {"error": f"OpenStreetMap temporarily unavailable: please try again later.", "results": []}
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except ValueError as e:
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logger.error(f"Invalid JSON response from Overpass: {e}")
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return {"error": "Invalid response from OpenStreetMap.", "results": []}
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origin = (float(lat), float(lon))
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locations = self.parse_overpass_response(data, request, origin)
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logger.info(f"Overpass returned {len(locations)} results")
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return {"error": None, "results": locations}
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def query_google_nearby(self, lat, lon, radius, category, request):
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"""
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Query Google Places API (New) for nearby places.
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Enhanced with comprehensive field masks and better error handling.
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"""
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api_key = settings.GOOGLE_MAPS_API_KEY
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url = "https://places.googleapis.com/v1/places:searchNearby"
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# Comprehensive field mask to get all useful information
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headers = {
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'Content-Type': 'application/json',
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'X-Goog-Api-Key': api_key,
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'X-Goog-FieldMask': (
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'places.id,'
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'places.displayName,'
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'places.formattedAddress,'
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'places.shortFormattedAddress,'
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'places.location,'
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'places.types,'
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'places.rating,'
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'places.userRatingCount,'
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'places.businessStatus,'
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'places.priceLevel,'
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'places.websiteUri,'
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'places.googleMapsUri,'
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'places.nationalPhoneNumber,'
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'places.internationalPhoneNumber,'
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'places.editorialSummary,'
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'places.photos,'
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'places.currentOpeningHours,'
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'places.regularOpeningHours'
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)
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}
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# Map categories to place types - use multiple types for better coverage
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type_mapping = {
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'lodging': ['lodging', 'hotel', 'hostel', 'resort_hotel', 'extended_stay_hotel'],
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'food': ['restaurant', 'cafe', 'bar', 'bakery', 'meal_takeaway', 'meal_delivery'],
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'tourism': ['tourist_attraction', 'museum', 'art_gallery', 'aquarium', 'zoo', 'amusement_park', 'park', 'natural_feature'],
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}
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payload = {
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"includedTypes": type_mapping.get(category, ['tourist_attraction']),
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"maxResultCount": 20,
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"rankPreference": "DISTANCE", # Sort by distance first
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"locationRestriction": {
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"circle": {
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"center": {
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"latitude": float(lat),
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"longitude": float(lon)
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},
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"radius": float(radius)
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}
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}
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}
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try:
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response = requests.post(url, json=payload, headers=headers, timeout=15)
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response.raise_for_status()
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data = response.json()
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places = data.get('places', [])
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origin = (float(lat), float(lon))
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locations = self.parse_google_places(places, origin)
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logger.info(f"Google Places returned {len(locations)} quality results for category '{category}'")
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return Response(self._prepare_final_results(locations))
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except requests.exceptions.Timeout:
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logger.warning("Google Places API timeout, falling back to OSM")
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return self.query_overpass(lat, lon, radius, category, request)
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except requests.exceptions.RequestException as e:
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logger.warning(f"Google Places API error: {e}, falling back to OSM")
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return self.query_overpass(lat, lon, radius, category, request)
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except Exception as e:
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logger.error(f"Unexpected error with Google Places API: {e}")
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return self.query_overpass(lat, lon, radius, category, request)
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def _prepare_final_results(self, locations):
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"""
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Prepare final results: sort by quality score and limit results.
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"""
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# Sort by quality score (highest first)
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locations.sort(key=lambda x: x.get('quality_score', 0), reverse=True)
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# Limit to MAX_RESULTS
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locations = locations[:self.MAX_RESULTS]
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return locations
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def _deduplicate_results(self, google_results, osm_results):
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"""
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Deduplicate results from both sources based on name and proximity.
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Prioritize Google results when duplicates are found.
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"""
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from difflib import SequenceMatcher
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def is_similar(name1, name2, threshold=0.85):
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"""Check if two names are similar using fuzzy matching."""
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return SequenceMatcher(None, name1.lower(), name2.lower()).ratio() > threshold
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def is_nearby(loc1, loc2, max_distance_m=50):
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"""Check if two locations are within max_distance_m meters."""
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dist = geodesic(
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(loc1['latitude'], loc1['longitude']),
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(loc2['latitude'], loc2['longitude'])
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).meters
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return dist < max_distance_m
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# Start with all Google results (higher quality)
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deduplicated = list(google_results)
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# Add OSM results that don't match Google results
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for osm_loc in osm_results:
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is_duplicate = False
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for google_loc in google_results:
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if (is_similar(osm_loc['name'], google_loc['name']) and
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is_nearby(osm_loc, google_loc)):
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is_duplicate = True
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break
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if not is_duplicate:
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deduplicated.append(osm_loc)
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return deduplicated
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@action(detail=False, methods=['get'])
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def query(self, request):
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"""
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Query both Google Places and OSM for recommendations.
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Returns unified, high-quality results sorted by quality score.
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Query Parameters:
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- lat (required): Latitude
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- lon (required): Longitude
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- radius (optional): Search radius in meters (default: 5000, max: 50000)
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- category (required): Category - 'tourism', 'food', or 'lodging'
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- sources (optional): Comma-separated sources - 'google', 'osm', or 'both' (default: 'both')
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|
"""
|
|
lat = request.query_params.get('lat')
|
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lon = request.query_params.get('lon')
|
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# Allow a free-text `location` parameter which will be geocoded
|
|
location_param = request.query_params.get('location')
|
|
radius = request.query_params.get('radius', '5000')
|
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category = request.query_params.get('category')
|
|
sources = request.query_params.get('sources', 'both').lower()
|
|
|
|
# If lat/lon not supplied, try geocoding the free-text location param
|
|
if (not lat or not lon) and location_param:
|
|
geocode_results = None
|
|
# Try Google first if API key configured
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|
if getattr(settings, 'GOOGLE_MAPS_API_KEY', None):
|
|
try:
|
|
geocode_results = search_google(location_param)
|
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except Exception:
|
|
logger.warning("Google geocoding failed; falling back to OSM")
|
|
geocode_results = None
|
|
|
|
# Fallback to OSM Nominatim
|
|
if not geocode_results:
|
|
try:
|
|
geocode_results = search_osm(location_param)
|
|
except Exception:
|
|
logger.warning("OSM geocoding failed")
|
|
geocode_results = None
|
|
|
|
# Validate geocode results
|
|
if isinstance(geocode_results, dict) and geocode_results.get('error'):
|
|
# Log internal geocoding error but avoid exposing sensitive details
|
|
logger.warning("Geocoding helper returned an internal error")
|
|
return Response({"error": "Geocoding failed. Please try a different location or contact support."}, status=400)
|
|
|
|
if not geocode_results:
|
|
return Response({"error": "Could not geocode provided location."}, status=400)
|
|
|
|
# geocode_results expected to be a list of results; pick the best (first)
|
|
best = None
|
|
if isinstance(geocode_results, list) and len(geocode_results) > 0:
|
|
best = geocode_results[0]
|
|
elif isinstance(geocode_results, dict):
|
|
# Some helpers might return a dict when only one result found
|
|
best = geocode_results
|
|
|
|
if not best:
|
|
return Response({"error": "No geocoding results found."}, status=400)
|
|
|
|
try:
|
|
lat = float(best.get('lat') or best.get('latitude'))
|
|
lon = float(best.get('lon') or best.get('longitude'))
|
|
except Exception:
|
|
return Response({"error": "Geocoding result missing coordinates."}, status=400)
|
|
|
|
# Replace location_param with display name when available for logging/debug
|
|
location_param = best.get('display_name') or best.get('name') or location_param
|
|
|
|
# Validation: require lat and lon at this point
|
|
if not lat or not lon:
|
|
return Response({
|
|
"error": "Latitude and longitude parameters are required (or provide a 'location' parameter to geocode)."
|
|
}, status=400)
|
|
|
|
try:
|
|
lat = float(lat)
|
|
lon = float(lon)
|
|
radius = min(float(radius), 50000) # Max 50km radius
|
|
except ValueError:
|
|
return Response({
|
|
"error": "Invalid latitude, longitude, or radius value."
|
|
}, status=400)
|
|
|
|
valid_categories = ['lodging', 'food', 'tourism']
|
|
if category not in valid_categories:
|
|
return Response({
|
|
"error": f"Invalid category. Valid categories: {', '.join(valid_categories)}"
|
|
}, status=400)
|
|
|
|
valid_sources = ['google', 'osm', 'both']
|
|
if sources not in valid_sources:
|
|
return Response({
|
|
"error": f"Invalid sources. Valid options: {', '.join(valid_sources)}"
|
|
}, status=400)
|
|
|
|
api_key = getattr(settings, 'GOOGLE_MAPS_API_KEY', None)
|
|
|
|
google_results = []
|
|
osm_results = []
|
|
|
|
# Query Google Places if available and requested
|
|
if api_key and sources in ['google', 'both']:
|
|
try:
|
|
url = "https://places.googleapis.com/v1/places:searchNearby"
|
|
headers = {
|
|
'Content-Type': 'application/json',
|
|
'X-Goog-Api-Key': api_key,
|
|
'X-Goog-FieldMask': (
|
|
'places.id,places.displayName,places.formattedAddress,'
|
|
'places.shortFormattedAddress,places.location,places.types,'
|
|
'places.rating,places.userRatingCount,places.businessStatus,'
|
|
'places.priceLevel,places.websiteUri,places.googleMapsUri,'
|
|
'places.nationalPhoneNumber,places.internationalPhoneNumber,'
|
|
'places.editorialSummary,places.photos,'
|
|
'places.currentOpeningHours,places.regularOpeningHours'
|
|
)
|
|
}
|
|
|
|
type_mapping = {
|
|
'lodging': ['lodging', 'hotel', 'hostel', 'resort_hotel'],
|
|
'food': ['restaurant', 'cafe', 'bar', 'bakery'],
|
|
'tourism': ['tourist_attraction', 'museum', 'art_gallery', 'aquarium', 'zoo', 'park'],
|
|
}
|
|
|
|
payload = {
|
|
"includedTypes": type_mapping.get(category, ['tourist_attraction']),
|
|
"maxResultCount": 20,
|
|
"rankPreference": "DISTANCE",
|
|
"locationRestriction": {
|
|
"circle": {
|
|
"center": {"latitude": lat, "longitude": lon},
|
|
"radius": radius
|
|
}
|
|
}
|
|
}
|
|
|
|
response = requests.post(url, json=payload, headers=headers, timeout=15)
|
|
response.raise_for_status()
|
|
data = response.json()
|
|
places = data.get('places', [])
|
|
origin = (lat, lon)
|
|
google_results = self.parse_google_places(places, origin)
|
|
logger.info(f"Google Places: {len(google_results)} quality results")
|
|
|
|
except Exception as e:
|
|
logger.warning(f"Google Places failed: {e}")
|
|
|
|
# Query OSM if requested or as fallback
|
|
osm_error = None
|
|
if sources in ['osm', 'both'] or (sources == 'google' and not google_results):
|
|
osm_response = self.query_overpass(lat, lon, radius, category, request)
|
|
osm_results = osm_response.get('results', [])
|
|
osm_error = osm_response.get('error')
|
|
|
|
if osm_error:
|
|
logger.warning(f"OSM query had issues: {osm_error}")
|
|
|
|
# Combine and deduplicate if using both sources
|
|
if sources == 'both' and google_results and osm_results:
|
|
all_results = self._deduplicate_results(google_results, osm_results)
|
|
else:
|
|
all_results = google_results + osm_results
|
|
|
|
# Prepare final results
|
|
final_results = self._prepare_final_results(all_results)
|
|
|
|
logger.info(f"Returning {len(final_results)} total recommendations")
|
|
|
|
# Build response with metadata
|
|
response_data = {
|
|
"count": len(final_results),
|
|
"results": final_results,
|
|
"sources_used": {
|
|
"google": len(google_results),
|
|
"osm": len(osm_results),
|
|
"total_before_dedup": len(google_results) + len(osm_results)
|
|
}
|
|
}
|
|
|
|
# Add warnings if there were errors but we still have some results
|
|
warnings = []
|
|
if osm_error and len(osm_results) == 0:
|
|
warnings.append(osm_error)
|
|
|
|
if warnings:
|
|
response_data["warnings"] = warnings
|
|
|
|
# If no results at all and user requested only OSM, return error status
|
|
if len(final_results) == 0 and sources == 'osm' and osm_error:
|
|
# Log internal error notice for investigation but do not expose details to clients
|
|
logger.debug("OSM query error (internal)")
|
|
return Response({
|
|
"error": "OpenStreetMap service temporarily unavailable. Please try again later.",
|
|
"count": 0,
|
|
"results": [],
|
|
"sources_used": response_data["sources_used"]
|
|
}, status=503)
|
|
|
|
return Response(response_data) |