From f4daa9d5872bc6b2bc5ea2a777fadca1ab74a87b Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Mon, 24 Mar 2025 15:07:46 +0800
Subject: [PATCH] 'commit'

---
 AI/WxMini/Start.py | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/AI/WxMini/Start.py b/AI/WxMini/Start.py
index 2246e935..2f5e2075 100644
--- a/AI/WxMini/Start.py
+++ b/AI/WxMini/Start.py
@@ -21,6 +21,7 @@ import jieba.analyse
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 logger = logging.getLogger(__name__)
 
+
 # 提取用户输入的关键词
 def extract_keywords(text, topK=3):
     """
@@ -32,6 +33,7 @@ def extract_keywords(text, topK=3):
     keywords = jieba.analyse.extract_tags(text, topK=topK)
     return keywords
 
+
 # 初始化 Word2Vec 模型
 model_path = MS_MODEL_PATH
 model = KeyedVectors.load_word2vec_format(model_path, binary=False, limit=MS_MODEL_LIMIT)
@@ -44,6 +46,7 @@ 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
@@ -58,6 +61,7 @@ def text_to_embedding(text):
         logger.warning("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):
@@ -69,6 +73,7 @@ async def lifespan(app: FastAPI):
     milvus_pool.close()
     logger.info("Milvus 连接池已关闭。")
 
+
 # 初始化 FastAPI 应用
 app = FastAPI(lifespan=lifespan)
 
@@ -78,6 +83,7 @@ client = AsyncOpenAI(
     base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
 )
 
+
 @app.post("/reply")
 async def reply(session_id: str = Form(...), prompt: str = Form(...)):
     """
@@ -130,7 +136,8 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
         response = await client.chat.completions.create(  # 使用异步调用
             model=MODEL_NAME,
             messages=[
-                {"role": "system", "content": "你是一个私人助理，负责回答用户的问题。请根据用户的历史对话和当前问题，提供准确且简洁的回答。不要提及你是通义千问或其他无关信息,也不可以回复与本次用户问题不相关的历史对话记录内容。"},
+                {"role": "system",
+                 "content": "你是一个私人助理，负责回答用户的问题。请根据用户的历史对话和当前问题，提供准确且简洁的回答。不要提及你是通义千问或其他无关信息,也不可以回复与本次用户问题不相关的历史对话记录内容。"},
                 {"role": "user", "content": f"历史对话记录：{history_prompt},本次用户问题: {prompt}"}  # 将历史交互和当前输入一起发送
             ],
             max_tokens=500
@@ -183,8 +190,9 @@ 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)
\ No newline at end of file
+    uvicorn.run(app, host="0.0.0.0", port=5600, workers=4)