diff --git a/request_llm/bridge_all.py b/request_llm/bridge_all.py index 1f8a1dc..7f612bb 100644 --- a/request_llm/bridge_all.py +++ b/request_llm/bridge_all.py @@ -351,6 +351,22 @@ if "qwen" in AVAIL_LLM_MODELS: }) except: print(trimmed_format_exc()) +if "chatgpt_website" in AVAIL_LLM_MODELS: # 接入一些逆向工程https://github.com/acheong08/ChatGPT-to-API/ + try: + from .bridge_chatgpt_website import predict_no_ui_long_connection as chatgpt_website_noui + from .bridge_chatgpt_website import predict as chatgpt_website_ui + model_info.update({ + "chatgpt_website": { + "fn_with_ui": chatgpt_website_ui, + "fn_without_ui": chatgpt_website_noui, + "endpoint": None, + "max_token": 4096, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, + } + }) + except: + print(trimmed_format_exc()) def LLM_CATCH_EXCEPTION(f): """ diff --git a/request_llm/bridge_chatgpt.py b/request_llm/bridge_chatgpt.py index 96af833..ea48fba 100644 --- a/request_llm/bridge_chatgpt.py +++ b/request_llm/bridge_chatgpt.py @@ -186,16 +186,15 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp try: chunk_decoded = chunk.decode() # 前者是API2D的结束条件，后者是OPENAI的结束条件 - if 'data: [DONE]' in chunk_decoded: + if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0): # 判定为数据流的结束，gpt_replying_buffer也写完了 logging.info(f'[response] {gpt_replying_buffer}') break # 处理数据流的主体 chunkjson = json.loads(chunk_decoded[6:]) status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}" - delta = chunkjson['choices'][0]["delta"] - if "content" in delta: - gpt_replying_buffer = gpt_replying_buffer + delta["content"] + # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出 + gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk_decoded[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) # 刷新界面 diff --git a/request_llm/bridge_chatgpt_website.py b/request_llm/bridge_chatgpt_website.py new file mode 100644 index 0000000..96af833 --- /dev/null +++ b/request_llm/bridge_chatgpt_website.py @@ -0,0 +1,297 @@ +# 借鉴了 https://github.com/GaiZhenbiao/ChuanhuChatGPT 项目 + +""" + 该文件中主要包含三个函数 + + 不具备多线程能力的函数： + 1. predict: 正常对话时使用，具备完备的交互功能，不可多线程 + + 具备多线程调用能力的函数 + 2. predict_no_ui：高级实验性功能模块调用，不会实时显示在界面上，参数简单，可以多线程并行，方便实现复杂的功能逻辑 + 3. predict_no_ui_long_connection：在实验过程中发现调用predict_no_ui处理长文档时，和openai的连接容易断掉，这个函数用stream的方式解决这个问题，同样支持多线程 +""" + +import json +import time +import gradio as gr +import logging +import traceback +import requests +import importlib + +# config_private.py放自己的秘密如API和代理网址 +# 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件 +from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc +proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG = \ + get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG') + +timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \ + '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。' + +def get_full_error(chunk, stream_response): + """ + 获取完整的从Openai返回的报错 + """ + while True: + try: + chunk += next(stream_response) + except: + break + return chunk + + +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 + llm_kwargs： + chatGPT的内部调优参数 + history： + 是之前的对话列表 + 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 + """ + 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) + retry = 0 + while True: + try: + # make a POST request to the API endpoint, stream=False + 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: + 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}) ……') + + stream_response = response.iter_lines() + result = '' + while True: + 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 not chunk.startswith('data:'): + error_msg = get_full_error(chunk.encode('utf8'), stream_response).decode() + if "reduce the length" in error_msg: + raise ConnectionAbortedError("OpenAI拒绝了请求:" + error_msg) + else: + raise RuntimeError("OpenAI拒绝了请求：" + error_msg) + if ('data: [DONE]' in chunk): break # api2d 正常完成 + json_data = json.loads(chunk.lstrip('data:'))['choices'][0] + delta = json_data["delta"] + if len(delta) == 0: break + if "role" in delta: continue + if "content" in delta: + result += delta["content"] + 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"] + # 看门狗，如果超过期限没有喂狗，则终止 + if len(observe_window) >= 2: + if (time.time()-observe_window[1]) > watch_dog_patience: + raise RuntimeError("用户取消了程序。") + else: raise RuntimeError("意外Json结构："+delta) + if json_data['finish_reason'] == 'content_filter': + raise RuntimeError("由于提问含不合规内容被Azure过滤。") + if json_data['finish_reason'] == 'length': + raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。") + return result + + +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。 + inputs 是本次问询的输入 + top_p, temperature是chatGPT的内部调优参数 + history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误） + 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 + """ + 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))) + yield from update_ui(chatbot=chatbot, history=history, msg="api_key已导入") # 刷新界面 + return + elif not is_any_api_key(chatbot._cookies['api_key']): + chatbot.append((inputs, "缺少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。")) + yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面 + return + + if additional_fn is not None: + from core_functional import handle_core_functionality + inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) + + 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") # 刷新界面 + + try: + headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream) + except RuntimeError as e: + chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。您可能选择了错误的模型或请求源。") + yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面 + return + + history.append(inputs); history.append("") + + retry = 0 + while True: + try: + # make a POST request to the API endpoint, stream=True + 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: + 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) # 刷新界面 + if retry > MAX_RETRY: raise TimeoutError + + gpt_replying_buffer = "" + + is_head_of_the_stream = True + if stream: + stream_response = response.iter_lines() + while True: + try: + chunk = next(stream_response) + except StopIteration: + # 非OpenAI官方接口的出现这样的报错，OpenAI和API2D不会走这里 + 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="非Openai官方接口返回了错误:" + chunk.decode()) # 刷新界面 + return + + # print(chunk.decode()[6:]) + if is_head_of_the_stream and (r'"object":"error"' not in chunk.decode()): + # 数据流的第一帧不携带content + is_head_of_the_stream = False; continue + + if chunk: + try: + chunk_decoded = chunk.decode() + # 前者是API2D的结束条件，后者是OPENAI的结束条件 + if 'data: [DONE]' in chunk_decoded: + # 判定为数据流的结束，gpt_replying_buffer也写完了 + logging.info(f'[response] {gpt_replying_buffer}') + break + # 处理数据流的主体 + chunkjson = json.loads(chunk_decoded[6:]) + status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}" + delta = chunkjson['choices'][0]["delta"] + if "content" in delta: + gpt_replying_buffer = gpt_replying_buffer + delta["content"] + history[-1] = gpt_replying_buffer + chatbot[-1] = (history[-2], history[-1]) + yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面 + except Exception as e: + 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) + 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 + print(error_msg) + return + +def handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg): + from .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 + history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], + max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一 + chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)") + # history = [] # 清除历史 + elif "does not exist" in error_msg: + chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格.") + elif "Incorrect API key" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务. " + openai_website) + elif "exceeded your current quota" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website) + elif "account is not active" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website) + elif "associated with a deactivated account" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website) + elif "bad forward key" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] Bad forward key. API2D账户额度不足.") + elif "Not enough point" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] Not enough point. API2D账户点数不足.") + else: + from toolbox import regular_txt_to_markdown + tb_str = '```\n' + trimmed_format_exc() + '```' + chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}") + return chatbot, history + +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 + """ + 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。") + + api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model']) + + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {api_key}" + } + if API_ORG.startswith('org-'): headers.update({"OpenAI-Organization": API_ORG}) + if llm_kwargs['llm_model'].startswith('azure-'): headers.update({"api-key": api_key}) + + 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 = {} + 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] + if what_i_have_asked["content"] != "": + 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 + messages.append(what_i_ask_now) + + payload = { + "model": llm_kwargs['llm_model'].strip('api2d-'), + "messages": messages, + "temperature": llm_kwargs['temperature'], # 1.0, + "top_p": llm_kwargs['top_p'], # 1.0, + "n": 1, + "stream": stream, + "presence_penalty": 0, + "frequency_penalty": 0, + } + try: + print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........") + except: + print('输入中可能存在乱码。') + return headers,payload + +