From f3caf4e663a00080ec09733bec1dd9bdfb2515f5 Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Mon, 24 Mar 2025 13:39:05 +0800
Subject: [PATCH] 'commit'

---
 AI/WxMini/X_Start.py | 21 +++++----------------
 1 file changed, 5 insertions(+), 16 deletions(-)

diff --git a/AI/WxMini/X_Start.py b/AI/WxMini/X_Start.py
index e866bd85..55df224c 100644
--- a/AI/WxMini/X_Start.py
+++ b/AI/WxMini/X_Start.py
@@ -59,7 +59,6 @@ milvus_pool = MilvusConnectionPool(host=MS_HOST, port=MS_PORT, max_connections=M
 collection_name = MS_COLLECTION_NAME
 collection_manager = MilvusCollectionManager(collection_name)
 
-
 # 将文本转换为嵌入向量
 def text_to_embedding(text):
     words = jieba.lcut(text)  # 使用 jieba 分词
@@ -74,7 +73,6 @@ def text_to_embedding(text):
         print("未找到有效词，返回零向量")
         return [0.0] * model.vector_size
 
-
 # 使用 Lifespan Events 处理应用启动和关闭逻辑
 @asynccontextmanager
 async def lifespan(app: FastAPI):
@@ -86,7 +84,6 @@ async def lifespan(app: FastAPI):
     milvus_pool.close()
     print("Milvus 连接池已关闭。")
 
-
 # 初始化 FastAPI 应用
 app = FastAPI(lifespan=lifespan)
 
@@ -99,10 +96,6 @@ client = OpenAI(
 # 设置相似度阈值
 SIMILARITY_THRESHOLD = 0.5  # 距离小于 0.5 的结果被认为是高相似度
 
-# 在 /reply 接口中优化查询逻辑和提示词构建方式
-# 在 /reply 接口中优化提示词传递和系统提示词
-# 在 /reply 接口中优化提示词传递和系统提示词
-# 在 /reply 接口中优化查询逻辑和提示词构建方式
 @app.post("/reply")
 async def reply(session_id: str = Form(...), prompt: str = Form(...)):
     """
@@ -123,7 +116,7 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
         print(f"提取的关键词: {keywords}")
 
         # 构建查询条件
-        expr = f"session_id == '{session_id}'"  # 只过滤 session_id
+        expr = build_query_expr(session_id, keywords)
         print(f"查询条件: {expr}")
 
         # 查询与当前对话最相关的五条历史交互
@@ -140,9 +133,6 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
         )
         end_time = time.time()
 
-        # 调试：输出查询结果
-        print(f"查询结果: {results}")
-
         # 构建历史交互提示词
         history_prompt = ""
         if results:
@@ -192,12 +182,12 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             collection_manager.insert_data(entities)
             print("用户输入和大模型反馈已记录到向量数据库。")
 
-            # 调用tts进行生成mp3
+            # 调用 TTS 生成 MP3
             uuid_str = str(uuid.uuid4())
             tts_file = "audio/" + uuid_str + ".mp3"
             t = TTS(tts_file)
             t.start(result)
-            # 文件上传到oss
+            # 文件上传到 OSS
             upload_mp3_to_oss(tts_file, tts_file)
             # 删除临时文件
             try:
@@ -205,7 +195,7 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
                 print(f"临时文件 {tts_file} 已删除")
             except Exception as e:
                 print(f"删除临时文件失败: {e}")
-            # 完整的url
+            # 完整的 URL
             url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/' + tts_file
             return {
                 "success": True,
@@ -221,9 +211,8 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
         # 释放连接
         milvus_pool.release_connection(connection)
 
-
 # 运行 FastAPI 应用
 if __name__ == "__main__":
     import uvicorn
 
-    uvicorn.run(app, host="0.0.0.0", port=5600)
+    uvicorn.run(app, host="0.0.0.0", port=5600)
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