diff --git a/request_llms/bridge_all.py b/request_llms/bridge_all.py index 2811295b..ead403c0 100644 --- a/request_llms/bridge_all.py +++ b/request_llms/bridge_all.py @@ -255,6 +255,8 @@ model_info = { "max_token": 128000, "tokenizer": tokenizer_gpt4, "token_cnt": get_token_num_gpt4, + "openai_disable_system_prompt": True, + "openai_disable_stream": True, }, "o1-mini": { "fn_with_ui": chatgpt_ui, @@ -263,6 +265,8 @@ model_info = { "max_token": 128000, "tokenizer": tokenizer_gpt4, "token_cnt": get_token_num_gpt4, + "openai_disable_system_prompt": True, + "openai_disable_stream": True, }, "gpt-4-turbo": { diff --git a/request_llms/bridge_chatgpt.py b/request_llms/bridge_chatgpt.py index a30b5c6c..cab5183a 100644 --- a/request_llms/bridge_chatgpt.py +++ b/request_llms/bridge_chatgpt.py @@ -133,22 +133,33 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], observe_window = None： 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 """ + from request_llms.bridge_all import model_info + watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可 - headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True) + + if model_info[llm_kwargs['llm_model']].get('openai_disable_stream', False): stream = False + else: stream = True + + headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=stream) retry = 0 while True: try: # make a POST request to the API endpoint, stream=False - from .bridge_all import model_info endpoint = verify_endpoint(model_info[llm_kwargs['llm_model']]['endpoint']) response = requests.post(endpoint, headers=headers, proxies=proxies, - json=payload, stream=True, timeout=TIMEOUT_SECONDS); break + json=payload, stream=stream, timeout=TIMEOUT_SECONDS); break except requests.exceptions.ReadTimeout as e: 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 not stream: + # 该分支仅适用于不支持stream的o1模型，其他情形一律不适用 + chunkjson = json.loads(response.content.decode()) + gpt_replying_buffer = chunkjson['choices'][0]["message"]["content"] + return gpt_replying_buffer + stream_response = response.iter_lines() result = '' json_data = None @@ -208,7 +219,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容 additional_fn代表点击的哪个按钮，按钮见functional.py """ - from .bridge_all import model_info + from request_llms.bridge_all import model_info if is_any_api_key(inputs): chatbot._cookies['api_key'] = inputs chatbot.append(("输入已识别为openai的api_key", what_keys(inputs))) @@ -237,6 +248,10 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith chatbot.append((_inputs, "")) yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面 + # 禁用stream的特殊模型处理 + if model_info[llm_kwargs['llm_model']].get('openai_disable_stream', False): stream = False + else: stream = True + # check mis-behavior if is_the_upload_folder(user_input): chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误！当您上传文档之后，需点击“**函数插件区**”按钮进行处理，请勿点击“提交”按钮或者“基础功能区”按钮。") @@ -270,7 +285,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith try: # make a POST request to the API endpoint, stream=True response = requests.post(endpoint, headers=headers, proxies=proxies, - json=payload, stream=True, timeout=TIMEOUT_SECONDS);break + json=payload, stream=stream, timeout=TIMEOUT_SECONDS);break except: retry += 1 chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg)) @@ -278,10 +293,15 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith 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 = "" - is_head_of_the_stream = True + if not stream: + # 该分支仅适用于不支持stream的o1模型，其他情形一律不适用 + yield from handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history) + return + if stream: + gpt_replying_buffer = "" + is_head_of_the_stream = True stream_response = response.iter_lines() while True: try: @@ -343,12 +363,24 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith chunk_decoded = chunk.decode() error_msg = chunk_decoded chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg) - yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面 + yield from update_ui(chatbot=chatbot, history=history, msg="Json解析异常" + error_msg) # 刷新界面 print(error_msg) return + return # return from stream-branch + +def handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history): + try: + chunkjson = json.loads(response.content.decode()) + gpt_replying_buffer = chunkjson['choices'][0]["message"]["content"] + log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer) + history[-1] = gpt_replying_buffer + chatbot[-1] = (history[-2], history[-1]) + yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 + except Exception as e: + yield from update_ui(chatbot=chatbot, history=history, msg="Json解析异常" + response.text) # 刷新界面 def handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg): - from .bridge_all import model_info + from request_llms.bridge_all import model_info openai_website = ' 请登录OpenAI查看详情 https://platform.openai.com/signup' if "reduce the length" in error_msg: if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出 @@ -381,6 +413,8 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st """ 整合所有信息，选择LLM模型，生成http请求，为发送请求做准备 """ + from request_llms.bridge_all import model_info + if not is_any_api_key(llm_kwargs['api_key']): raise AssertionError("你提供了错误的API_KEY。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。") @@ -409,10 +443,16 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st else: enable_multimodal_capacity = False + conversation_cnt = len(history) // 2 + openai_disable_system_prompt = model_info[llm_kwargs['llm_model']].get('openai_disable_system_prompt', False) + + if openai_disable_system_prompt: + messages = [] + else: + messages = [{"role": "system", "content": system_prompt}] + if not enable_multimodal_capacity: # 不使用多模态能力 - conversation_cnt = len(history) // 2 - messages = [{"role": "system", "content": system_prompt}] if conversation_cnt: for index in range(0, 2*conversation_cnt, 2): what_i_have_asked = {} @@ -434,8 +474,6 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st messages.append(what_i_ask_now) else: # 多模态能力 - conversation_cnt = len(history) // 2 - messages = [{"role": "system", "content": system_prompt}] if conversation_cnt: for index in range(0, 2*conversation_cnt, 2): what_i_have_asked = {}