Optimize the code to make it more readable, catch other exceptions, and avoid response contentless reading exceptions

request_llm/bridge_chatgpt.py

@@ -41,7 +41,9 @@ def get_full_error(chunk, stream_response):
     return chunk
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=None, sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(
+        inputs, llm_kwargs, history=None, sys_prompt="", observe_window=None, console_slience=False
+):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -63,25 +65,33 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=None, sys_prompt="
     while True:
         try:
             # make a POST request to the API endpoint, stream=False
-            from .bridge_all import model_info
+            from bridge_all import model_info
             endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
             response = requests.post(endpoint, headers=headers, proxies=proxies,
-                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
-        except requests.exceptions.ReadTimeout as e:
+                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS)
+            break
+        except requests.exceptions.ReadTimeout:
             retry += 1
             traceback.print_exc()
-            if retry > MAX_RETRY: raise TimeoutError
-            if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
+            if retry > MAX_RETRY:
+                raise TimeoutError
+            if MAX_RETRY != 0:
+                print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
+        except Exception as e:
+            print(f"出现异常：{e}")
+            raise e
 
     stream_response = response.iter_lines()
     result = ''
     while True:
-        try: chunk = next(stream_response).decode()
+        try:
+            chunk = next(stream_response).decode()
         except StopIteration: 
             break
         except requests.exceptions.ConnectionError:
             chunk = next(stream_response).decode()  # 失败了，重试一次？再失败就没办法了。
-        if len(chunk)==0: continue
+        if len(chunk) == 0:
+            continue
         if not chunk.startswith('data:'): 
             error_msg = get_full_error(chunk.encode('utf8'), stream_response).decode()
             if "reduce the length" in error_msg:
@@ -95,7 +105,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=None, sys_prompt="
         if "role" in delta: continue
         if "content" in delta: 
             result += delta["content"]
-            if not console_slience: print(delta["content"], end='')
+            if not console_slience:
+                print(delta["content"], end='')
             if observe_window is not None: 
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1: observe_window[0] += delta["content"]
@@ -232,6 +243,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
                     return
 
+
 def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     """
     整合所有信息，选择LLM模型，生成http请求，为发送请求做准备
@@ -251,23 +263,19 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     messages = [{"role": "system", "content": system_prompt}]
     if conversation_cnt:
         for index in range(0, 2*conversation_cnt, 2):
-            what_i_have_asked = {}
-            what_i_have_asked["role"] = "user"
-            what_i_have_asked["content"] = history[index]
-            what_gpt_answer = {}
-            what_gpt_answer["role"] = "assistant"
-            what_gpt_answer["content"] = history[index+1]
+            what_i_have_asked = {"role": "user", "content": history[index]}
+            what_gpt_answer = {"role": "assistant", "content": history[index + 1]}
             if what_i_have_asked["content"] != "":
-                if what_gpt_answer["content"] == "": continue
-                if what_gpt_answer["content"] == timeout_bot_msg: continue
+                if what_gpt_answer["content"] == "":
+                    continue
+                if what_gpt_answer["content"] == timeout_bot_msg:
+                    continue
                 messages.append(what_i_have_asked)
                 messages.append(what_gpt_answer)
             else:
                 messages[-1]['content'] = what_gpt_answer['content']
 
-    what_i_ask_now = {}
-    what_i_ask_now["role"] = "user"
-    what_i_ask_now["content"] = inputs
+    what_i_ask_now = {"role": "user", "content": inputs}
     messages.append(what_i_ask_now)
 
     payload = {
@@ -282,8 +290,8 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     }
     try:
         print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........")
-    except:
-        print('输入中可能存在乱码。')
+    except Exception as e:
+        print(f'输入中可能存在乱码。抛出异常: {e}')
     return headers, payload