智能选址agent修改

landsite_agent/examples.json

@@ -17,17 +17,17 @@
   {
     "query_type": "land_site_selection",
     "query": "请在萧山机场附近选出30-100亩之间的工业用地,数据表是公告地块",
-    "sql_code": "select t.id from (select id,dkmj,round(st_distance(st_geometryfromtext('POINT (120.42827489304307 30.23751646603668)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.ecgap_klyzy where tdyt like '%工业%' and sfsj=1 and shape is not null and dkmj BETWEEN 30 and 100) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
+    "sql_code": "select t.id from (select id,dkmj,dkcsd,ghfhd,dkgzd,jtblx,cyppd,round(st_distance(st_geometryfromtext('POINT (120.42827489304307 30.23751646603668)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.ecgap_klyzy where tdyt like '%工业%' and sfsj=1 and shape is not null and dkmj BETWEEN 30 and 100) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
   },
   {
     "query_type": "land_site_selection",
     "query": "帮我在萧山机场附近推荐几块50亩左右的工业用地,数据表是控制性详细规划",
-    "sql_code": "select t.id from (select id,ydmj,round(st_distance(st_geometryfromtext('POINT (120.42827489304307 30.23751646603668)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.kzxxxgh where ydxz like '%工业%' and shape is not null and abs(ydmj - 50*0.0667) <= 1) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
+    "sql_code": "select t.id from (select id,dkcsd,ghfhd,dkgzd,jtblx,cyppd,ydmj,round(st_distance(st_geometryfromtext('POINT (120.42827489304307 30.23751646603668)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.kzxxxgh where ydxz like '%工业%' and shape is not null and abs(ydmj - 50*0.0667) <= 1) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
   },
   {
     "query_type": "land_site_selection",
     "query": "帮我在温州南站附近推荐几块50亩左右的工业用地,温州南站的坐标为120.58,27.97,数据表是控制性详细规划",
-    "sql_code": "select t.id from (select id,ydmj,round(st_distance(st_geometryfromtext('POINT (120.58 27.97)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.kzxxxgh where ydxz like '%工业%' and shape is not null and abs(ydmj - 50*0.0667) <= 1) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
+    "sql_code": "select t.id from (select id,dkcsd,ghfhd,dkgzd,jtblx,cyppd,ydmj,round(st_distance(st_geometryfromtext('POINT (120.58 27.97)', 4490)::geography,shape::geography)::numeric,0) as distance from sde.kzxxxgh where ydxz like '%工业%' and shape is not null and abs(ydmj - 50*0.0667) <= 1) as t where t.distance <= 10000 order by (dkcsd + ghfhd + dkgzd + jtblx + cyppd) desc nulls last limit 5"
   },
   {
     "query_type": "land_site_selection",

landsite_agent/highway_distance.py

@@ -0,0 +1,200 @@
+import asyncio
+import json
+import aiohttp
+import urllib.parse
+import random
+from database import Database
+
+class HighwayDistanceCalculator:
+    def __init__(self):
+        self.db = Database()
+        self.tianditu_key = "3b2d9954565a494ffab9cfd26d7fc522"
+        self.base_url = "https://api.tianditu.gov.cn/v2/search"
+        self.keywords = ["高速", "互通"]
+        # 添加常见的User-Agent列表
+        self.user_agents = [
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.107 Safari/537.36",
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:90.0) Gecko/20100101 Firefox/90.0",
+            "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.1.1 Safari/605.1.15"
+        ]
+
+    def convert_distance_to_meters(self, distance_str):
+        """将距离字符串转换为米"""
+        try:
+            if 'km' in distance_str:
+                # 如果是千米，转换为米
+                return int(float(distance_str.replace('km', '')) * 1000)
+            else:
+                # 如果是米，直接转换
+                return int(distance_str.replace('m', ''))
+        except Exception as e:
+            print(f"距离转换错误: {distance_str}, {str(e)}")
+            return None
+
+    async def get_nearest_distance(self, point_lonlat):
+        """获取最近的距离"""
+        all_pois = []
+        
+        for keyword in self.keywords:
+            post_str = {
+                "keyWord": keyword,
+                "level": 12,
+                "queryRadius": 5000,
+                "pointLonlat": point_lonlat,
+                "queryType": 3
+            }
+            
+            # 120.38920002653107,30.221665152310052
+            print(f"查询关键词: {keyword}, 坐标: {point_lonlat}")
+            
+            # 将postStr参数进行URL编码
+            encoded_post_str = urllib.parse.quote(json.dumps(post_str))
+            
+            # 构建完整的URL
+            url = f"{self.base_url}?postStr={encoded_post_str}&type=query&tk={self.tianditu_key}"
+
+            # 随机选择一个User-Agent
+            headers = {
+                "User-Agent": random.choice(self.user_agents),
+                "Accept": "application/json, text/plain, */*",
+                "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+                "Accept-Encoding": "gzip, deflate, br",
+                "Connection": "keep-alive",
+                "Referer": "https://map.tianditu.gov.cn/",
+                "Origin": "https://map.tianditu.gov.cn"
+            }
+
+            async with aiohttp.ClientSession() as session:
+                try:
+                    async with session.get(url, headers=headers) as response:
+                        if response.status == 200:
+                            data = await response.json()
+                            if data.get("pois"):
+                                for poi in data["pois"]:
+                                    distance_meters = self.convert_distance_to_meters(poi["distance"])
+                                    if distance_meters is not None:
+                                        all_pois.append({
+                                            "distance": distance_meters,
+                                            "name": poi["name"],
+                                            "keyword": keyword
+                                        })
+                        else:
+                            print(f"请求失败，状态码: {response.status}")
+                            print(f"URL: {url}")
+                            print(f"响应内容: {await response.text()}")
+                except Exception as e:
+                    print(f"请求异常: {str(e)}")
+            
+            # 添加随机延迟，避免请求过于频繁
+            # await asyncio.sleep(random.uniform(1, 3))
+
+        # 按距离排序
+        if all_pois:
+            all_pois.sort(key=lambda x: x["distance"])
+            print(f"找到最近的点: {all_pois[0]['name']} ({all_pois[0]['keyword']}), 距离: {all_pois[0]['distance']}米")
+            return all_pois[0]["distance"]
+        return None
+
+    async def process_ecgap_klyzy(self):
+        """处理ecgap_klyzy表数据"""
+        sql = """
+        SELECT 
+            id,
+            ST_X(ST_Centroid(shape::geometry)) as center_x,
+            ST_Y(ST_Centroid(shape::geometry)) as center_y
+        FROM ecgap_klyzy 
+        WHERE shape IS NOT NULL
+        """
+        
+        try:
+            parcels = await self.db.execute_query(sql)
+            
+            for parcel in parcels:
+                id = parcel["id"]
+                center_x = parcel["center_x"]
+                center_y = parcel["center_y"]
+                
+                # 构建中心点坐标字符串
+                center_point = f"{center_x},{center_y}"
+                
+                # 获取最近距离
+                distance = await self.get_nearest_distance(center_point)
+                if distance is not None:
+                    # 更新数据库
+                    update_sql = f"""
+                    UPDATE ecgap_klyzy 
+                    SET gsjl = {distance} 
+                    WHERE id = '{id}'
+                    """
+                    await self.db.execute_transaction([update_sql])
+                    print(f"更新ecgap_klyzy表地块 ID: {id} 的最近距离为 {distance}米")
+                
+                # 添加随机延迟，避免请求过于频繁
+                await asyncio.sleep(random.uniform(1, 3))
+                
+        except Exception as e:
+            print(f"处理ecgap_klyzy表数据错误: {str(e)}")
+
+    async def process_kzxxxgh(self):
+        """处理kzxxxgh表数据"""
+        sql = """
+        SELECT 
+            id,
+            ST_X(ST_Centroid(shape::geometry)) as center_x,
+            ST_Y(ST_Centroid(shape::geometry)) as center_y
+        FROM kzxxxgh 
+        WHERE shape IS NOT NULL
+        """
+        
+        try:
+            parcels = await self.db.execute_query(sql)
+            
+            for parcel in parcels:
+                id = parcel["id"]
+                center_x = parcel["center_x"]
+                center_y = parcel["center_y"]
+                
+                # 构建中心点坐标字符串
+                center_point = f"{center_x},{center_y}"
+                
+                # 获取最近距离
+                distance = await self.get_nearest_distance(center_point)
+                if distance is not None:
+                    # 更新数据库
+                    update_sql = f"""
+                    UPDATE kzxxxgh 
+                    SET gsjl = {distance} 
+                    WHERE id = '{id}'
+                    """
+                    await self.db.execute_transaction([update_sql])
+                    print(f"更新kzxxxgh表地块 ID: {id} 的最近距离为 {distance}米")
+                
+                # 添加随机延迟，避免请求过于频繁
+                await asyncio.sleep(random.uniform(1, 3))
+                
+        except Exception as e:
+            print(f"处理kzxxxgh表数据错误: {str(e)}")
+
+    async def process_all_parcels(self):
+        """处理所有地块数据"""
+        try:
+            await self.db.connect()
+            
+            # print("开始处理ecgap_klyzy表...")
+            # await self.process_ecgap_klyzy()
+            
+            print("开始处理kzxxxgh表...")
+            await self.process_kzxxxgh()
+            
+        except Exception as e:
+            print(f"处理地块数据错误: {str(e)}")
+        finally:
+            await self.db.close()
+
+async def main():
+    calculator = HighwayDistanceCalculator()
+    await calculator.process_all_parcels()
+
+if __name__ == "__main__":
+    asyncio.run(main()) 

landsite_agent/requirements.txt

@@ -9,4 +9,5 @@ pydantic==2.11.5
 Shapely==2.1.1
 uvicorn==0.34.2
 faiss-cpu==1.11.0
-python-dotenv==1.0.1
+python-dotenv==1.0.1
+aiohttp==3.9.3

landsite_agent/xuanzhi_query.py

@@ -11,13 +11,17 @@ database = Database()
 @router.get("/kg-query")
 async def kg_query(id: str = Query(..., description="ID列表, 逗号分隔")) -> List[Any]:
     """
-    查询控制性详细规划信息
+    查询控制性详细规划信息，按照dkcsd,ghfhd,dkgzd,jtblx,cyppd总和倒序排序
     """
     sql = (
         "select id, xzqmc, xzqdm, dymc, yddm, ydxz, ydmj, rjlsx, rjlxx, jzmdsx, jzmdxx, "
-        "jzgdsx, jzgdxx, ldlsx, ldlxx, pfwh, pfsj,dkcsd,ghfhd,dkgzd,jtblx,cyppd, st_area(shape::geography) as pfmarea, "
-        "st_astext(shape) as geom, st_astext(st_centroid(shape)) as center_wkt "
-        "from sde.kzxxxgh where id in ({id})"
+        "jzgdsx, jzgdxx, ldlsx, ldlxx, pfwh, pfsj, dkcsd, ghfhd, dkgzd, jtblx, cyppd, "
+        "st_area(shape::geography) as pfmarea, st_astext(shape) as geom, "
+        "st_astext(st_centroid(shape)) as center_wkt, "
+        "(COALESCE(dkcsd, 0) + COALESCE(ghfhd, 0) + COALESCE(dkgzd, 0) + "
+        "COALESCE(jtblx, 0) + COALESCE(cyppd, 0)) as total_score "
+        "from sde.kzxxxgh where id in ({id}) "
+        "order by total_score desc"
     )
     result = await database.execute_query(sql.format(id=id))
     return result
@@ -25,11 +29,14 @@ async def kg_query(id: str = Query(..., description="ID列表, 逗号分隔")) -
 @router.get("/klyzy-query")
 async def klyzy_query(id: str = Query(..., description="ID列表, 逗号分隔")) -> List[Any]:
     """
-    查询可利用资源信息
+    查询可利用资源信息，按照dkcsd,ghfhd,dkgzd,jtblx,cyppd总和倒序排序
     """
     sql = (
-        "select *, st_astext(shape) as geom, st_astext(st_centroid(shape)) as center_wkt "
-        "from sde.ecgap_klyzy where id in ({id})"
+        "select *, st_astext(shape) as geom, st_astext(st_centroid(shape)) as center_wkt, "
+        "(COALESCE(dkcsd, 0) + COALESCE(ghfhd, 0) + COALESCE(dkgzd, 0) + "
+        "COALESCE(jtblx, 0) + COALESCE(cyppd, 0)) as total_score "
+        "from sde.ecgap_klyzy where id in ({id}) "
+        "order by total_score desc"
     )
     result = await database.execute_query(sql.format(id=id))
     return result