增扩框架的参数IO

request_llm/bridge_chatgpt.py

@@ -72,14 +72,14 @@ def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
         raise ConnectionAbortedError("Json解析不合常规，可能是文本过长" + response.text)
 
 
-def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], 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：
             是本次问询的输入
         sys_prompt:
             系统静默prompt
-        top_p, temperature：
+        llm_kwargs：
             chatGPT的内部调优参数
         history：
             是之前的对话列表
@@ -87,7 +87,7 @@ def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_pr
             用于负责跨越线程传递已经输出的部分，大部分时候仅仅为了fancy的视觉效果，留空即可。observe_window[0]：观测窗。observe_window[1]：看门狗
     """
     watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可
-    headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=True)
+    headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
     retry = 0
     while True:
         try:
@@ -135,8 +135,7 @@ def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_pr
     return result
 
 
-def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', 
-            stream = True, additional_fn=None):
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
     """
         发送至chatGPT，流式获取输出。
         用于基础的对话功能。
@@ -157,9 +156,9 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
         raw_input = inputs
         logging.info(f'[raw_input] {raw_input}')
         chatbot.append((inputs, ""))
-        yield from update_ui(chatbot=chatbot, history=history, msg="等待响应")
+        yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
 
-    headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
+    headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream)
     history.append(inputs); history.append(" ")
 
     retry = 0
@@ -172,7 +171,7 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
             retry += 1
             chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
             retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
-            yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg)
+            yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
             if retry > MAX_RETRY: raise TimeoutError
 
     gpt_replying_buffer = ""
@@ -200,11 +199,11 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
                     gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
                     history[-1] = gpt_replying_buffer
                     chatbot[-1] = (history[-2], history[-1])
-                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text)
+                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
 
                 except Exception as e:
                     traceback.print_exc()
-                    yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规")
+                    yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
                     chunk = get_full_error(chunk, stream_response)
                     error_msg = chunk.decode()
                     if "reduce the length" in error_msg:
@@ -218,10 +217,10 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
                         from toolbox import regular_txt_to_markdown
                         tb_str = '```\n' + traceback.format_exc() + '```'
                         chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk.decode()[4:])}")
-                    yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg)
+                    yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
                     return
 
-def generate_payload(inputs, top_p, temperature, history, system_prompt, stream):
+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
     """
@@ -257,8 +256,8 @@ def generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
     payload = {
         "model": LLM_MODEL,
         "messages": messages, 
-        "temperature": temperature,  # 1.0,
-        "top_p": top_p,  # 1.0,
+        "temperature": llm_kwargs['temperature'],  # 1.0,
+        "top_p": llm_kwargs['top_p'],  # 1.0,
         "n": 1,
         "stream": stream,
         "presence_penalty": 0,

request_llm/bridge_tgui.py

@@ -90,7 +90,7 @@ async def run(context, max_token=512):
 
 
 
-def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
+def predict_tgui(inputs, top_p, temperature, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
     """
         发送至chatGPT，流式获取输出。
         用于基础的对话功能。
@@ -111,7 +111,7 @@ def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prom
     logging.info(f'[raw_input] {raw_input}')
     history.extend([inputs, ""])
     chatbot.append([inputs, ""])
-    yield from update_ui(chatbot=chatbot, history=history, msg="等待响应")
+    yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
 
     prompt = inputs
     tgui_say = ""
@@ -138,7 +138,7 @@ def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prom
             tgui_say = mutable[0]
             history[-1] = tgui_say
             chatbot[-1] = (history[-2], history[-1])
-            yield from update_ui(chatbot=chatbot, history=history)
+            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
     logging.info(f'[response] {tgui_say}')