基于单服务器

目录问题解决
摘要字数问题解决
参考文献带标题问题解决

chatgpt_post.py

@@ -1,7 +1,8 @@
 import requests
 import json
 
-OPENAI_API_KEY = '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'
+prompt = "请帮我根据题目为“{}”生成一个论文目录只含有一级目录和二级目录".format("煤业集团水文监测系统建设项目设计与实现")
+OPENAI_API_KEY = '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'
 
 url = "https://api.openai.com/v1/chat/completions"
 headers = {
@@ -11,9 +12,7 @@ headers = {
 data = {
     "model": "gpt-3.5-turbo",
     "messages": [
-            {"role": "user", "content": "请帮我改写这句话:在城市发展进程当中，逐渐呈现出一些综合性的大型建筑群。"},
+            {"role": "user", "content": prompt},
-            {"role": "assistant", "content": "随着城市的发展，综合性大型建筑群正在逐渐出现。"},
-            {"role": "user", "content": "这句话我不满意，再改一下帮我"}
         ],
     "temperature": 0.7
 }

flask_serve_1.py

@@ -31,9 +31,6 @@ lock = threading.RLock()
 pool = redis.ConnectionPool(host=config.reids_ip, port=config.reids_port, max_connections=50, db=config.reids_db, password=config.reids_password)
 redis_ = redis.Redis(connection_pool=pool, decode_responses=True)
 
-thanks = "致谢"
-references = "参考文献"
-
 flask_serves_env = "http://{}:{}".format(localhostip,config.flask_port)
 
 paper_download_url = flask_serves_env + "/download?filename_path={}/paper.docx"
@@ -406,7 +403,23 @@ def threading_mulu(api_key, title, uuid):
         mulu_list = str(mulu).split("\n")
         mulu_list = [i.strip() for i in mulu_list if i != ""]
 
-        print(mulu_list)
+        mulu_list_bool = []
+        for i in mulu_list:
+            result_biaoti_list = re.findall(config.pantten_biaoti, i)
+            if result_biaoti_list != []:
+                mulu_list_bool.append((i, "一级标题"))
+            else:
+                mulu_list_bool.append((i, "二级标题"))
+
+        mulu_list_bool_part = mulu_list_bool[:3]
+
+        if mulu_list_bool_part[0][1] != "一级标题":
+            redis_.lpush(redis_title, json.dumps({"id": uuid, "title": title}, ensure_ascii=False))  # 加入redis
+            redis_.persist(redis_key_name_openaikey_list)
+        if mulu_list_bool_part[0][1] == mulu_list_bool_part[1][1] == "一级标题":
+            redis_.lpush(redis_title, json.dumps({"id": uuid, "title": title}, ensure_ascii=False))  # 加入redis
+            redis_.persist(redis_key_name_openaikey_list)
+
 
         cun_bool = False
         table_of_contents = [mulu_list[0]]
@@ -430,15 +443,17 @@ def threading_mulu(api_key, title, uuid):
         # table_of_contents = table_of_contents[:3] + table_of_contents[-1:]
         # print(table_of_contents)
 
-        thanks_references_bool_table = table_of_contents[-3:]
+        thanks_references_bool_table = table_of_contents[-4:]
 
         # thanks = "致谢"
         # references = "参考文献"
-        if references in thanks_references_bool_table:
+        for i in thanks_references_bool_table:
-            table_of_contents.remove(references)
+            if config.references in i:
-
+                table_of_contents.remove(i)
-        if thanks in thanks_references_bool_table:
+            if config.thanks in i:
-            table_of_contents.remove(thanks)
+                table_of_contents.remove(i)
+            if config.excursus in i:
+                table_of_contents.remove(i)
 
         # table_of_contents.append(thanks)
         # table_of_contents.append(references)

serve_config_1.py

@@ -3,15 +3,16 @@ class Config:
         # 目录提取拼接相关参数
         self.pantten_second_biaoti = '[2二ⅡⅠ][、.]\s{0,}?[\u4e00-\u9fa5]+'
         self.pantten_other_biaoti = '[2-9二三四五六七八九ⅡⅢⅣⅤⅥⅦⅧⅨ][、.]\s{0,}?[\u4e00-\u9fa5]+'
+        self.pantten_biaoti = '[1-9一二三四五六七八九ⅠⅡⅢⅣⅤⅥⅦⅧⅨ][、.]\s{0,}?[\u4e00-\u9fa5a-zA-Z]+'
 
         # chatgpt 接口相关参数
-        self.mulu_prompt = "请帮我根据题目为“{}”生成一个论文目录"
+        self.mulu_prompt = "请帮我根据题目为“{}”生成一个论文目录其中只含有一级目录和二级标题目录"
         self.first_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的大标题“{}”的内容补充完整，补充内容字数在800字左右"
         self.small_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的小标题“{}”的内容补充完整，补充内容字数在800字左右"
         self.references_prompt = "论文题目是“{}”，目录是“{}”，请为这篇论文生成15篇左右的参考文献，要求其中有有中文参考文献不低于12篇，英文参考文献不低于2篇"
         self.thank_prompt = "请以“{}”为题写一篇论文的致谢"
         self.kaitibaogao_prompt = "请以《{}》为题目生成研究的主要的内容、背景、目的、意义，要求不少于1500字"
-        self.chinese_abstract_prompt = "请以《{}》为题目生成论文摘要，要求生成的字数在800字左右"
+        self.chinese_abstract_prompt = "请以《{}》为题目生成论文摘要，要求生成的字数在600字左右"
         self.english_abstract_prompt = "请把“{}”这段文字翻译成英文"
         self.chinese_keyword_prompt = "请为“{}”这段论文摘要生成3-5个关键字"
         self.english_keyword_prompt = "请把“{}”这几个关键字翻译成英文"
@@ -29,6 +30,7 @@ class Config:
         # 流程相关参数
         self.thanks = "致谢"
         self.references = "参考文献"
+        self.excursus = "附录"
 
         # flask port
         self.flask_port = "14002"

循环生成目录测试时间.py

@@ -0,0 +1,39 @@
+import requests
+import json
+import time
+
+prompt = "请帮我根据题目为“{}”生成一个论文目录"
+def requests_chatgpt(api_key,title):
+
+    OPENAI_API_KEY = api_key
+    url = "https://api.openai.com/v1/chat/completions"
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {OPENAI_API_KEY}"
+    }
+    data = {
+        "model": "gpt-3.5-turbo",
+        "messages": [
+                {"role": "user", "content": prompt.format(title)},
+            ],
+        "temperature": 0.7
+    }
+
+    response = requests.post(url,
+                             headers=headers,
+                             data=json.dumps(data),
+                             timeout=1000)
+
+    res = response.json()
+    print(res)
+    print(res["choices"][0]["message"]["content"])
+
+
+start = time.time()
+
+for i in range(10):
+    requests_chatgpt("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","大型商业建筑人员疏散设计研究")
+
+end = time.time()
+
+print(end-start)