import requests import urllib3 import json from utils import geoutil import regex_spatial from shapely.geometry import Polygon, MultiPoint, LineString, Point, mapping import re import geopandas as gpd from geocoder import geo_level1 from openai import OpenAI from utils.config import api_key import numpy as np client = OpenAI( api_key=api_key ) model = "gpt-4o" north = ["north", "N'", "North", "NORTH"] south = ["south", "S'", "South", "SOUTH"] east = ["east", "E'", "East", "EAST"] west = ["west", "W'", "West", "WEST"] northeast = ["north-east", "NE'", "north east", "NORTH-EAST", "North East", "NORTH EAST"] southeast = ["south-east", "SE'", "south east", "SOUTH-EAST", "South East", "SOUTH EAST"] northwest = ["north-west", "NW'", "north west", "NORTH-WEST", "North West", "NORTH WEST"] southwest = ["south-west", "SW'", "south west", "SOUTH-WEST", "South West", "SOUTH WEST"] center = ["center","central", "downtown","midtown"] def to_standard_2d_list(data): arr = np.array(data) flat = arr.flatten() if flat.size % 2 != 0: raise ValueError("元素个数不是2的倍数,不能 reshape 成 [N, 2] 格式") return flat.reshape(-1, 2).tolist() def get_geojson(ent, arr, centroid): poly_json = {} poly_json['type'] = 'FeatureCollection' poly_json['features'] = [] coordinates= [] coordinates.append(arr) poly_json['features'].append({ 'type':'Feature', 'id': ent, 'properties': { 'centroid': centroid }, 'geometry': { 'type':'Polygon', 'coordinates': coordinates } }) return poly_json def get_coordinates(ent): request_url = 'https://nominatim.openstreetmap.org/search.php?q= ' +ent +'&polygon_geojson=1&accept-language=en&format=jsonv2' headers = { "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.3 Safari/605.1.15" } page = requests.get(request_url, headers=headers, verify=False) json_content = json.loads(page.content) all_coordinates = json_content[0]['geojson']['coordinates'][0] centroid = (float(json_content[0]['lon']), float(json_content[0]['lat'])) for p in all_coordinates: p2 = (p[0], p[1]) angle = geoutil.calculate_bearing(centroid, p2) p.append(angle) geojson = get_geojson(ent, all_coordinates, centroid) return geojson['features'][0]['geometry']['coordinates'][0], geojson['features'][0]['properties']['centroid'] def get_coordinates(location): request_url = f'https://nominatim.openstreetmap.org/search.php?q={location}&polygon_geojson=1&accept-language=en&format=jsonv2' print(request_url) headers = {"User-Agent": "Mozilla/5.0"} response = requests.get(request_url, headers=headers, verify=False) json_content = json.loads(response.content) if json_content[0]['geojson']['type'] == 'Polygon': coordinates = json_content[0]['geojson']['coordinates'][0] elif json_content[0]['geojson']['type'] == 'Point': coordinates = json_content[0]['geojson']['coordinates'] else: print(json_content[0]['geojson']['type']) centroid = (float(json_content[0]['lon']), float(json_content[0]['lat'])) return (coordinates, centroid) # level3 def get_directional_coordinates_by_angle(coordinates, centroid, direction, minimum, maximum): direction_coordinates = [] for p in coordinates: angle = geoutil.calculate_bearing(centroid, p) p2 = (p[0], p[1], angle) if direction in geo_level1.east: if angle >= minimum or angle <= maximum: direction_coordinates.append(p2) else: if angle >= minimum and angle <= maximum: direction_coordinates.append(p2) return direction_coordinates def get_level3(level3): digits = re.findall('[0-9]+', level3)[0] unit = re.findall('[A-Za-z]+', level3)[0] return digits, unit def get_direction_coordinates(coordinates, centroid, level1): min_max = geo_level1.get_min_max(level1) if min_max is not None: coord = get_directional_coordinates_by_angle(coordinates, centroid, level1, min_max[0], min_max[1]) return coord return coordinates def sort_west(poly1, poly2, centroid): coords1 = mapping(poly1)["features"][0]["geometry"]["coordinates"] coords2 = mapping(poly2)["features"][0]["geometry"]["coordinates"] coord1 = [] coord2 = [] coord = [] for c in coords1: pol = list(c[::-1]) coord1.extend(pol) for c in coords2: pol = list(c[::-1]) coord2.extend(pol) coo1 = [] coo2 = [] for p in coord1: angle = geoutil.calculate_bearing(centroid, p) if angle >= 157 and angle <= 202: coo1.append((p[0], p[1], angle)) for p in coord2: angle = geoutil.calculate_bearing(centroid, p) if angle >= 157 and angle <= 202: coo2.append((p[0], p[1], angle)) coo1.extend(coo2) return coo1 def get_level3_coordinates(coordinates, level_3, level1): distance, unit = get_level3(level_3) kms = geoutil.get_kilometers(distance, unit) coord = [] coords0, center = coordinates if not isinstance(coords0, list) or len(coords0) < 3: lat_km = 111.32 lon_km = 111.32 * np.cos(np.radians(center[1])) dx = dy = 0 if level1 is not None: if level1 in geo_level1.east: dx = kms / lon_km elif level1 in geo_level1.west: dx = -kms / lon_km elif level1 in geo_level1.north: dy = kms / lat_km elif level1 in geo_level1.south: dy = -kms / lat_km new_center = (center[0] + dx, center[1] + dy) r_km = 1 circle_points = [] for theta in np.linspace(0, 360, num=100): theta_rad = np.radians(theta) d_lat = (np.sin(theta_rad) * r_km) / lat_km d_lon = (np.cos(theta_rad) * r_km) / lon_km circle_points.append((new_center[0] + d_lon, new_center[1] + d_lat)) if circle_points: center_point = MultiPoint(circle_points).centroid center = (center_point.x, center_point.y) else: center = new_center return circle_points, center poly1 = Polygon(coords0) polygon1 = gpd.GeoSeries(poly1) poly2 = polygon1.buffer(0.0095 * kms, join_style=2) poly3 = polygon1.buffer(0.013 * kms, join_style=2) poly = poly3.difference(poly2) coords = mapping(poly)["features"][0]["geometry"]["coordinates"] for c in coords: pol = list(c[::-1]) coord.extend(pol) if level1 is not None: coord = get_direction_coordinates(coord, coordinates[1], level1) if level1 in geo_level1.west: coord = sort_west(poly3, poly2, coordinates[1]) if coord: center_point = MultiPoint(coord).centroid center = (center_point.x, center_point.y) else: center = coordinates[1] return coord, center # between def get_between_coordinates(coordinates1, coordinates2): def is_valid_polygon(coords): return isinstance(coords, list) and len(coords) >= 3 coords1, center1 = coordinates1 coords2, center2 = coordinates2 if is_valid_polygon(coords1): poly1 = Polygon(coords1) area1 = poly1.area else: area1 = 0 if is_valid_polygon(coords2): poly2 = Polygon(coords2) area2 = poly2.area else: area2 = 0 midpoint = ( (center1[0] + center2[0]) / 2, (center1[1] + center2[1]) / 2 ) if area1 == 0 and area2 == 0: r_km = 2 else: avg_area = (area1 + area2) / 2 r_km = np.sqrt(avg_area / np.pi) * 111.32 # 近似 km 半径 lat_km = 111.32 lon_km = 111.32 * np.cos(np.radians(midpoint[1])) circle_points = [] for theta in np.linspace(0, 360, num=100): theta_rad = np.radians(theta) d_lat = (np.sin(theta_rad) * r_km) / lat_km d_lon = (np.cos(theta_rad) * r_km) / lon_km circle_points.append((midpoint[0] + d_lon, midpoint[1] + d_lat)) return circle_points, midpoint def llmapi(text): system_prompt = ( "You are an experienced geographer. Your task is to determine the correct sequence of positioning functions and their inputs based on a given piece of natural language.\n" "The positioning functions you can choose from are:\n" "1. Relative Positioning: Inputs is (location coordinate or location name, direction, and distance). Outputs the coordinates that are in the given 'direction' and 'distance' from the input location.\n" "2. Between Positioning: Inputs is (location 1 coordinates or location 1 name, location 2 coordinates or location 2 name). Outputs the midpoint coordinate between the two locations.\n" "You can only use the given functions, and the inputs to the functions must obey the above properties. The given functions can be combined to solve complex situations." "First, perform chain-of-thought (CoT) reasoning, and finally output your answer in JSON format, wrapped between `<<>>` and `<<>>`.\n" "Make sure all inputs only include: location names (strings), step indices (integers), directions (strings, must be in English), or distances (strings with units). Do not return expressions like 'the coordinate 4 km south of Chatswood'.\n" "Each step must have an 'id'. If the input of a step is the output of a previous step, use that step’s 'id' as the input.\n" "All directions must be in English (e.g., south, west, northeast, etc.).\n" "Example output:\n" "<<>>\n" "[{\"id\": 1, \"function\": \"Relative\", \"inputs\": [\"Chatswood\", \"south\", \"4 km\"]}," "{\"id\": 2, \"function\": \"Relative\", \"inputs\": [\"North Sydney\", \"west\", \"2 km\"]}," "{\"id\": 3, \"function\": \"Between\", \"inputs\": [1, 2]}," "{\"id\": 4, \"function\": \"Relative\", \"inputs\": [3, \"southwest\", \"5 km\"]}]\n" "<<>>") messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": text}, ] chat_completion = client.chat.completions.create( messages=messages, model=model, ) result = chat_completion.choices[0].message.content json_match = re.search(r'<<>>\n(.*?)\n<<>>', result, re.DOTALL) if json_match: return json.loads(json_match.group(1)) else: raise ValueError("The LLM output does not contain the expected JSON formatted data. Please try again.") def execute_steps(steps): data = {} locations_history = [] for step in steps: step_id = step['id'] function = step['function'] inputs = step['inputs'] resolved_inputs = [] for inp in inputs: if isinstance(inp, int): resolved_inputs.append(data[inp]) else: resolved_inputs.append(inp) if function == "Relative": location, direction, distance = resolved_inputs if isinstance(location, str): location = get_coordinates(location) locations_history.append(location) location = [to_standard_2d_list(location[0])] + list(location[1:]) result = get_level3_coordinates(location, distance, direction) locations_history.append(result) data[step_id] = result elif function == "Between": location1, location2 = resolved_inputs if isinstance(location1, str): location1 = get_coordinates(location1) locations_history.append(location1) location1 = [to_standard_2d_list(location1[0])] + list(location1[1:]) if isinstance(location2, str): location2 = get_coordinates(location2) locations_history.append(location2) location2 = [to_standard_2d_list(location2[0])] + list(location2[1:]) result = get_between_coordinates(location1, location2) locations_history.append(result) data[step_id] = result return [data, locations_history] if __name__ == '__main__': parsed_steps = [] step_loc = execute_steps(parsed_steps) result = step_loc[0]