优化

app/api/chat/ai/chat_router.py

@@ -1,3 +1,6 @@
+import random
+
+from anyio import sleep
 from fastapi import APIRouter, HTTPException, Depends,FastAPI
 
 from starlette.requests import Request
@@ -23,7 +26,8 @@ from app.api.chat.ai.chat_service import (
     get_scenic_parking_data,
     extract_multi_scenic,
     query_multi_scenic_flow,
-    get_all_toilet_data
+    get_all_toilet_data,
+    generate_recommended_questions
 )
 # 导入用于异步执行同步函数的模块
 from concurrent.futures import ThreadPoolExecutor
@@ -54,7 +58,7 @@ async def universal_exception_handler(request: Request, exc: Exception):
         chunk_size = 8
         for i in range(0, len(error_msg), chunk_size):
             chunk = error_msg[i:i + chunk_size]
-            yield f"data: {json.dumps({'content': chunk})}\n\n"
+            yield f"data: {chunk}\n\n"
             await asyncio.sleep(0.03)  # 模拟自然打字速度
 
         # 发送结束标记
@@ -113,7 +117,7 @@ async def h5_chat_stream(request: Request, inp: ChatIn, redis_client = Depends(g
             chunk_size = 8
             for i in range(0, len(error_msg), chunk_size):
                 chunk = error_msg[i:i + chunk_size]
-                yield f"data: {json.dumps({'content': chunk})}\n\n"
+                yield f"data: {chunk}\n\n"
                 await asyncio.sleep(0.03)
 
             yield "data: [DONE]\n\n"
@@ -159,30 +163,44 @@ async def _handle_chat_request(
     user_messages_content = [msg.get('content', '') for msg in user_messages]
     all_messages = user_messages_content + [inp.message]
 
-    # 消息分类
-    cat = await classify(inp.message)
-    print(f"Message category: {cat}")
-
-    spot = None
-    scenics = None
-    if cat == "游玩判断" or cat == "保定文旅":
-        spot = await extract_spot(all_messages)
-    elif cat == "多景区比较":
-        scenics = await extract_multi_scenic(all_messages)
-
-    # 知识库查询准备
-    knowledge_task = None
-    if spot:
-        loop = asyncio.get_event_loop()
-        with ThreadPoolExecutor() as executor:
-            knowledge_task = loop.run_in_executor(executor, fetch_and_parse_markdown, user_id, inp.message)
-
-    # 获取快捷问题
-    questions = await QuickQuestion.filter(status="0", ischat="0").order_by("order_num").limit(4).values("title",
-                                                                                                         "subtitle",
-                                                                                                         "content")
-    question_titles = [f"{q['subtitle']}{q['title']}" for q in questions]
-    is_quick_question = inp.message in question_titles
+    try:
+        cached = await redis_client.get(inp.message)
+        if cached:
+            is_quick_question = True
+            # 缓存命中，直接返回缓存数据
+            questions = cached
+        else:
+            is_quick_question = False
+    except Exception as e:
+        print(f"[Redis] 查询缓存失败: {e}")
+        is_quick_question = False
+
+    if not is_quick_question:
+        # 消息分类
+        cat = await classify(inp.message)
+        print(f"Message category: {cat}")
+
+        spot = None
+        scenics = None
+        if cat == "游玩判断" or cat == "保定文旅":
+            spot = await extract_spot(all_messages)
+        elif cat == "多景区比较":
+            scenics = await extract_multi_scenic(all_messages)
+
+        # 知识库查询准备
+        knowledge_task = None
+        if spot:
+            loop = asyncio.get_event_loop()
+            with ThreadPoolExecutor() as executor:
+                knowledge_task = loop.run_in_executor(executor, fetch_and_parse_markdown, user_id, inp.message)
+
+    # # 获取快捷问题
+    # questions = await QuickQuestion.filter(status="0", ischat="0").order_by("order_num").limit(4).values("title",
+    #                                                                                                      "subtitle",
+    #                                                                                                      "content")
+    # question_titles = [f"{q['subtitle']}{q['title']}" for q in questions]
+    # is_quick_question = inp.message in question_titles
+
 
     # 添加用户消息到历史
     if not is_quick_question:
@@ -193,16 +211,36 @@ async def _handle_chat_request(
         nonlocal conversation_history
 
         try:
-            # 记录热门问题
-            await record_hot_question(inp.message)
+            try:
+                # 记录热门问题
+                await record_hot_question(inp.message)
+            except Exception as e:
+                print(f"记录热门问题失败: {e}，问题内容为：{inp.message}")
 
             if is_quick_question:
+                await asyncio.sleep(0.5)
+                full_response = ""
                 # 处理快捷问题
-                question_content = next(
-                    q["content"] for q in questions if f"{q['subtitle']}{q['title']}" == inp.message)
-                async for chunk in handle_quick_question(inp, question_content):
+                question_content = questions
+                #每次输出随机1-10个字符
+                chunk_size = random.randint(5, 15)
+                for i in range(0, len(question_content), chunk_size):
+                    chunk = question_content[i:i + chunk_size]
+                    full_response += chunk
                     yield f"data: {chunk}\n\n"
-                    await asyncio.sleep(0.01)
+                    await asyncio.sleep(0.09)
+                if full_response:
+                    recommended_questions = await generate_recommended_questions(inp.message, full_response)
+                    if recommended_questions:
+                        # 添加分隔符和标题
+                        yield "\n\n### 您可能还想了解："
+                        # 逐个返回推荐问题
+                        for i, question in enumerate(recommended_questions, 1):
+                            yield f"\n{i}. {question}"
+
+                # async for chunk in handle_quick_question(inp, question_content):
+                #     yield f"data: {chunk}\n\n"
+                #     await asyncio.sleep(0.01)
             else:
                 # 处理不同分类的消息
                 if cat == "游玩判断":
@@ -272,7 +310,7 @@ async def _handle_chat_request(
             chunk_size = 8
             for i in range(0, len(error_msg), chunk_size):
                 chunk = error_msg[i:i + chunk_size]
-                yield f"data: {json.dumps({'content': chunk})}\n\n"
+                yield f"data: {chunk})\n\n"
                 await asyncio.sleep(0.03)
 
             yield "data: [DONE]\n\n"
@@ -495,7 +533,7 @@ async def get_all_scenic_flow(request: Request, req: AllScenicFlowRequest, redis
 
 
 @router.post("/get_all_toilet_info")
-async def get_all_toilet_info(request: Request, req: AllScenicFlowRequest):
+async def get_all_toilet_info(request: Request, req: AllScenicFlowRequest, redis_client = Depends(get_redis_client)):
     """
     获取所有厕所信息
     """
@@ -512,7 +550,7 @@ async def get_all_toilet_info(request: Request, req: AllScenicFlowRequest):
         raise HTTPException(status_code=401, detail="无效的签名")
     
     try:
-        data = await get_all_toilet_data(request)
+        data = await get_all_toilet_data(request, redis_client)
         
         if not data:
             return {
@@ -524,7 +562,7 @@ async def get_all_toilet_info(request: Request, req: AllScenicFlowRequest):
         return {
             "code": 200,
             "message": "查询成功",
-            "data": data
+            "data": json.loads(data)
         }
     except Exception as e:
         print(f"查询所有厕所信息异常: {e}")

app/api/chat/ai/chat_service.py

@@ -36,7 +36,7 @@ EXTRACT_PROMPT = """你是一名景区名称精准匹配助手。用户的问题
 白石山景区
 阜平云花溪谷-玫瑰谷
 保定军校纪念馆
-保定直隶总督署博物馆
+直隶总督署博物馆
 冉庄地道战遗址
 刘伶醉景区
 曲阳北岳庙景区
@@ -51,7 +51,7 @@ EXTRACT_PROMPT = """你是一名景区名称精准匹配助手。用户的问题
 满城汉墓景区
 灵山聚龙洞旅游风景区
 易县狼牙山风景区
-留法勤工俭学纪念馆
+留法勤工俭学运动纪念馆
 白求恩柯棣华纪念馆
 唐县秀水峪
 腰山王氏庄园
@@ -548,6 +548,8 @@ async def get_all_scenic_flow_data(request: Request, redis_client = None) -> lis
                 for row in rows:
                     id,scenic_name, enter_num, leave_num, max_capacity = row
                     in_park_num = abs(enter_num - leave_num)  # 确保是正数
+                    if in_park_num > max_capacity:
+                        in_park_num = max_capacity
                     
                     # 避免除以零的情况
                     if max_capacity > 0:
@@ -625,7 +627,8 @@ async def get_scenic_detail_data(request: Request, id: int, redis_client = None)
                 
                 # 计算在园人数
                 in_park_num = abs(enter_num - leave_num)  # 确保是正数
-                
+                if in_park_num > max_capacity:
+                    in_park_num = max_capacity
                 # 计算承载率和舒适度
                 if max_capacity > 0:
                     capacity_rate = in_park_num / max_capacity
@@ -874,7 +877,7 @@ MULTI_SCENIC_EXTRACT_PROMPT = """你是一名景区名称提取助手。用户
 白石山景区
 阜平云花溪谷-玫瑰谷
 保定军校纪念馆
-保定直隶总督署博物馆
+直隶总督署博物馆
 冉庄地道战遗址
 刘伶醉景区
 曲阳北岳庙景区
@@ -889,7 +892,7 @@ MULTI_SCENIC_EXTRACT_PROMPT = """你是一名景区名称提取助手。用户
 满城汉墓景区
 灵山聚龙洞旅游风景区
 易县狼牙山风景区
-留法勤工俭学纪念馆
+留法勤工俭学运动纪念馆
 白求恩柯棣华纪念馆
 唐县秀水峪
 腰山王氏庄园
@@ -998,11 +1001,23 @@ async def query_multi_scenic_flow(request: Request, scenics: list, msg: str, red
 
 
 # 在文件末尾添加新函数用于获取所有厕所信息
-async def get_all_toilet_data(request: Request) -> list:
+async def get_all_toilet_data(request: Request, redis_client = None) -> list:
     """
     查询所有厕所信息
     """
     try:
+        cache_key = "all_toilet_list"
+        if redis_client is None:
+            redis_client = request.app.state.redis_client
+
+        try:
+            cached = await redis_client.get(cache_key)
+            if cached:
+                # 缓存命中，直接返回缓存数据
+                return json.loads(cached)
+        except Exception as e:
+            print(f"[Redis] 查询缓存失败: {e}")
+
         pool = request.app.state.mysql_pool
         async with pool.acquire() as conn:
             async with conn.cursor() as cur: