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README.md

@@ -1,12 +1,12 @@
 ---
-title: Dockerb22
-emoji: 🐢
-colorFrom: red
-colorTo: purple
+title: dockerb2.1
+emoji: 🔧
+colorFrom: gray
+colorTo: indigo
 sdk: gradio
-sdk_version: 5.24.0
+sdk_version: 3.50.2
+private: true
 app_file: app.py
 pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+license: mit
+---

app.py

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+import gradio as gr
+import requests
+import json
+import geoutil
+from shapely.geometry import Polygon, MultiPoint, mapping
+import re
+import geopandas as gpd
+import geo_level1
+from openai import OpenAI
+import numpy as np
+import os
+
+api_key = os.getenv('api_key')
+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)
+
+    # 强制变成一维后 reshape，前提是元素总数是2的倍数
+    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)
+    # print(json_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):
+    # minimum = 157
+    # maximum = 202
+
+    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)
+    # print(type(direction_coordinates[0]))
+    # if(direction in geo_level1.west):
+    #    direction_coordinates.sort(key=lambda k: k[2], reverse=True)
+
+    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:
+
+        # 从原始点出发，根据方向移动距离 kms 得到新圆心
+        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
+            # 你也可以支持 northeast、southwest 等复合方向
+
+        new_center = (center[0] + dx, center[1] + dy)
+
+        # 用固定半径画个圆（例如半径2km）
+        r_km = 1  # 半径设为1km，你也可以设为其他值
+
+        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))
+
+        # 输出中心（使用新圆心）
+        if circle_points:
+            center_point = MultiPoint(circle_points).centroid
+            center = (center_point.x, center_point.y)
+        else:
+            center = new_center
+
+        return circle_points, center
+
+    # 正常 polygon 流程
+    poly1 = Polygon(coords0)
+    polygon1 = gpd.GeoSeries(poly1)
+
+    # 生成环形区域
+    poly2 = polygon1.buffer(0.0095 * kms, join_style=2)
+    poly3 = polygon1.buffer(0.013 * kms, join_style=2)
+    poly = poly3.difference(poly2)
+
+    # 获取坐标
+    coords = mapping(poly)["features"][0]["geometry"]["coordinates"]
+    for c in coords:
+        pol = list(c[::-1])
+        coord.extend(pol)
+
+    # 方向裁剪
+    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])
+
+    # 计算质心
+    if coord:
+        center_point = MultiPoint(coord).centroid
+        center = (center_point.x, center_point.y)
+    else:
+        center = coordinates[1]
+
+    return coord, center
+# level 3 end
+
+# between
+def get_between_coordinates(coordinates1, coordinates2):
+    """
+    计算两个区域之间的中间点，并生成一个等面积的圆形区域。
+    如果某个输入仅为点（坐标长度 < 3），则其面积设为 0；
+    如果两个输入都是点，则默认半径为 2km。
+    :param coordinates1: 第一个区域的边界坐标和中心点
+    :param coordinates2: 第二个区域的边界坐标和中心点
+    :return: 圆形区域的坐标集和圆心
+    """
+
+    def is_valid_polygon(coords):
+        return isinstance(coords, list) and len(coords) >= 3
+
+    coords1, center1 = coordinates1
+    coords2, center2 = coordinates2
+
+    # 判断输入是否为合法多边形（>=3个点）
+    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
+
+    # 计算中心点（两个中心的中点）
+    midpoint = (
+        (center1[0] + center2[0]) / 2,
+        (center1[1] + center2[1]) / 2
+    )
+
+    # 如果两个区域都是点，则使用默认半径 2km
+    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
+
+    # 经纬度距离换算因子
+    lat_km = 111.32
+    lon_km = 111.32 * np.cos(np.radians(midpoint[1]))
+
+    # 生成圆形区域坐标（100个点）
+    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
+# between end
+
+
+def llmapi(text):
+    system_prompt = (
+        "你是一个资深的地理学家，你的任务是通过给定的一段自然语言，来选择正确的定位函数顺序以及他们的输入。\n"
+        "你能选择的定位函数有：\n"
+        "1. 相对定位（Relative Positioning）：输入为地点坐标，方位，距���。输出为距离‘距离’输入的地点坐标的‘方位’的坐标。\n"
+        "2. 中间定位（Between Positioning）：输入为两个地点的坐标，输出为两个地点坐标的中点。\n"
+        "请先进行思维链（CoT）推理，并最终用 JSON 格式输出你的答案，用 `<<<JSON>>>` 和 `<<<END>>>` 包裹起来。\n"
+        "请确保所有输入仅包含：地点名称（字符串）、索引（整数）、方位（字符串，必须是英文）或距离（字符串，带单位），不允许返回诸如 'Chatswood 南4 km的坐标' 这样的内容。\n"
+        "每个步骤编号都有 id 记录，然后如果某个输入是之前步骤的输出，那么输入对应步骤的 id。\n"
+        "所有方向必须使用英文（如 south, west, northeast, etc.）。\n"
+        "示例输出：\n"
+        "<<<JSON>>>\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"
+        "<<<END>>>")
+
+    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'<<<JSON>>>\n(.*?)\n<<<END>>>', result, re.DOTALL)
+
+    if json_match:
+        # print(json.loads(json_match.group(1)))
+        return json.loads(json_match.group(1))
+    else:
+        raise ValueError("LLM 输出未包含预期的 JSON 格式数据。")
+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 `<<<JSON>>>` and `<<<END>>>`.\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"
+        "<<<JSON>>>\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"
+        "<<<END>>>")
+
+    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
+    print(result)
+    json_match = re.search(r'<<<JSON>>>\n(.*?)\n<<<END>>>', result, re.DOTALL)
+
+    if json_match:
+        return json.loads(json_match.group(1))
+    else:
+        raise ValueError("LLM 输出未包含预期的 JSON 格式数据。")
+
+
+
+
+
+def execute_steps(steps):
+    data = {}
+
+    for step in steps:
+        step_id = step['id']
+        function = step['function']
+        inputs = step['inputs']
+        # print('-' * 50)
+        # print(function)
+        # print(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)
+
+            location = [to_standard_2d_list(location[0])] + list(location[1:])
+            location = [[[151.214901,-33.859175]], (151.214901,-33.859175)]
+            result = get_level3_coordinates(location, distance, direction)
+            data[step_id] = result
+
+        elif function == "Between":
+
+
+            location1, location2 = resolved_inputs
+            # print(location1)
+            # print(111)
+            # print(location2)
+            if isinstance(location1, str):
+                location1 = get_coordinates(location1)
+
+                location1 = [to_standard_2d_list(location1[0])] + list(location1[1:])
+            if isinstance(location2, str):
+
+                location2 = get_coordinates(location2)
+                location2 = [to_standard_2d_list(location2[0])] + list(location2[1:])
+            result = get_between_coordinates(location1, location2)
+
+            data[step_id] = result
+
+    return data
+
+
+def process_api(input_text):
+    # 这里编写实际的后端处理逻辑
+
+    # return {
+    #     "status": "success",
+    #     # "result": f"Processed: {input_text.upper()}",
+    #     "result": f"Processed: {nlp(input_text).to_json()}",
+    #     "timestamp": time.time()
+    # }
+    parsed_steps = llmapi(input_text)
+    result = execute_steps(parsed_steps)
+    coords = result[(max(result.keys()))]
+
+    geojson = get_geojson(None, coords[0], coords[1])
+    return geojson
+
+request_url = 'https://nominatim.openstreetmap.org/search.php?q=Glebe&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"
+}
+page1 = requests.get(request_url, headers=headers, verify=False)
+cont = page1.content
+
+# 设置API格式为JSON
+gr.Interface(
+    fn=process_api,
+    # fn=cont,
+    inputs="text",
+    outputs="json",
+    title="Backend API",
+    allow_flagging="never"
+).launch(debug=True)
+
+
+

requirements.txt

@@ -0,0 +1,5 @@
+gradio
+geopandas
+openai
+quantities
+shapely