增加测试scokt请求，并更改流程

main.py

@@ -211,6 +211,55 @@ def ulit_request_file(new_id, sentence, title):
                 "content": f"{row['正文']}\n以上这条中可能包含了一些病情或者症状，请帮我归纳这条中所对应的病情或者症状是哪些，总结出来，不需要很长，简单归纳即可，直接输出症状或者病情，可以包含一些形容词来辅助描述，不需要有辅助词汇"
             }],
             "top_p": 0.9,
+            "temperature": 0.3
+        })
+
+    # 并发处理请求
+    with concurrent.futures.ThreadPoolExecutor(200) as executor:
+        results = list(executor.map(dialog_line_parse, data_list))
+
+    # 更新总结字段
+    for idx, result in zip(to_process.index, results):
+        summary = result['choices'][0]['message']['content']
+        df.at[idx, "总结"] = summary
+
+    # 保存更新后的CSV
+    df.to_csv(file_name_res_save, sep="\t", index=False)
+    return df
+
+
+def ulit_request_file_zongjie(new_id, sentence, zongjie, title):
+    file_name_res_save = f"data_file_res/{title}.csv"
+
+    # 初始化或读取CSV文件
+    if os.path.exists(file_name_res_save):
+        df = pd.read_csv(file_name_res_save, sep="\t")
+    else:
+        df = pd.DataFrame(columns=["ID", "正文", "总结", "有效", "已向量化"])
+
+    # # 添加新数据（生成唯一ID）
+    # new_row = {
+    #     "ID": str(new_id),
+    #     "正文": sentence,
+    #     "总结": zongjie,
+    #     "有效": True,
+    #     "已向量化": False
+    # }
+    # df = pd.concat([df, pd.DataFrame([new_row])], ignore_index=True)
+
+    # 筛选需要处理的记录
+    to_process = df[df["有效"] == True]
+
+    # 调用API生成总结（示例保留原有逻辑）
+    data_list = []
+    for _, row in to_process.iterrows():
+        data_list.append({
+            "model": "gpt-4-turbo",
+            "messages": [{
+                "role": "user",
+                "content": f"{row['正文']}\n以上这条中可能包含了一些病情或者症状，请帮我归纳这条中所对应的病情或者症状是哪些，总结出来，不需要很长，简单归纳即可，直接输出症状或者病情，可以包含一些形容词来辅助描述，不需要有辅助词汇"
+            }],
+            "top_p": 0.9,
             "temperature": 0.6
         })
 
@@ -227,6 +276,7 @@ def ulit_request_file(new_id, sentence, title):
     df.to_csv(file_name_res_save, sep="\t", index=False)
     return df
 
+
 def main(question, title, top):
     db_dict = {
         "1": "yetianshi"
@@ -264,7 +314,7 @@ def main(question, title, top):
         vector_path = f"data_np/{title_dan}.npy"
         vectors = np.load(vector_path)
 
-        data_str = pd.read_csv(f"data_file/{title_dan}.csv", sep="\t", encoding="utf-8").values.tolist()
+        data_str = pd.read_csv(f"data_file_res/{title_dan}.csv", sep="\t", encoding="utf-8").values.tolist()
         index.add(vectors)
         D, I = index.search(embs, int(top))
         print(I)
@@ -274,7 +324,7 @@ def main(question, title, top):
             reference_list.append([data_str[i], j])
 
         for i,j in enumerate(reference_list):
-            paper_list_str += "第{}篇\n{}，此篇文章跟问题的相关度为{}%\n".format(str(i+1), j[0][0], j[1])
+            paper_list_str += "第{}篇\n{}，此篇文章跟问题的相关度为{}%\n".format(str(i+1), j[0][1], j[1])
 
 
     '''
@@ -334,6 +384,7 @@ def upload_file_check():
     sentence = request.form.get('sentence')
     title = request.form.get("title")
     new_id = request.form.get("id")
+    zongjie = request.form.get("zongjie")
     state = request.form.get("state")
     '''
         {
@@ -343,14 +394,29 @@ def upload_file_check():
             "4": "pdf"
         }
     '''
+    # 增
     state_res = ""
     if state == "1":
         df = ulit_request_file(new_id, sentence, title)
         Building_vector_database(title, df)
         state_res = "上传完成"
+
+    # 删
     elif state == "2":
         delete_data(title, new_id)
         state_res = "删除完成"
+
+    # 改
+    elif state == "3":
+        df = ulit_request_file(new_id, sentence, title)
+        Building_vector_database(title, df)
+        state_res = "修改完成"
+
+    # 查
+    elif state == "4":
+        df = ulit_request_file(new_id, sentence, title)
+        state_res = ""
+
     return_json = {
         "code": 200,
         "info": state_res