').strip('
')) return history def visualize_audio(chatbot, audio_shape): if len(chatbot) == 0: chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"]) chatbot[-1] = list(chatbot[-1]) p1 = '「' p2 = '」' chatbot[-1][-1] = re.sub(p1+r'(.*)'+p2, '', chatbot[-1][-1]) chatbot[-1][-1] += (p1+f"`{audio_shape}`"+p2) class AsyncGptTask(): def __init__(self) -> None: self.observe_future = [] self.observe_future_chatbot_index = [] def gpt_thread_worker(self, i_say, llm_kwargs, history, sys_prompt, observe_window, index): try: MAX_TOKEN_ALLO = 2560 i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO) gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt, observe_window=observe_window[index], console_slience=True) except ConnectionAbortedError as token_exceed_err: print('至少一个线程任务Token溢出而失败', e) except Exception as e: print('至少一个线程任务意外失败', e) def add_async_gpt_task(self, i_say, chatbot_index, llm_kwargs, history, system_prompt): self.observe_future.append([""]) self.observe_future_chatbot_index.append(chatbot_index) cur_index = len(self.observe_future)-1 th_new = threading.Thread(target=self.gpt_thread_worker, args=(i_say, llm_kwargs, history, system_prompt, self.observe_future, cur_index)) th_new.daemon = True th_new.start() def update_chatbot(self, chatbot): for of, ofci in zip(self.observe_future, self.observe_future_chatbot_index): try: chatbot[ofci] = list(chatbot[ofci]) chatbot[ofci][1] = markdown_convertion(of[0]) except: self.observe_future = [] self.observe_future_chatbot_index = [] return chatbot class InterviewAssistant(AliyunASR): def __init__(self): self.capture_interval = 0.5 # second self.stop = False self.parsed_text = "" # 下个句子中已经说完的部分, 由 test_on_result_chg() 写入 self.parsed_sentence = "" # 某段话的整个句子, 由 test_on_sentence_end() 写入 self.buffered_sentence = "" # self.audio_shape = "" # 音频的可视化表现, 由 audio_convertion_thread() 写入 self.event_on_result_chg = threading.Event() self.event_on_entence_end = threading.Event() self.event_on_commit_question = threading.Event() def __del__(self): self.stop = True self.stop_msg = "" self.commit_wd.kill_dog = True self.plugin_wd.kill_dog = True def init(self, chatbot): # 初始化音频采集线程 self.captured_audio = np.array([]) self.keep_latest_n_second = 10 self.commit_after_pause_n_second = 2.0 self.ready_audio_flagment = None self.stop = False self.plugin_wd = WatchDog(timeout=5, bark_fn=self.__del__, msg="程序终止") self.aut = threading.Thread(target=self.audio_convertion_thread, args=(chatbot._cookies['uuid'],)) self.aut.daemon = True self.aut.start() # th2 = threading.Thread(target=self.audio2txt_thread, args=(chatbot._cookies['uuid'],)) # th2.daemon = True # th2.start() def no_audio_for_a_while(self): if len(self.buffered_sentence) < 7: # 如果一句话小于7个字，暂不提交 self.commit_wd.begin_watch() else: self.event_on_commit_question.set() def begin(self, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt): # main plugin function self.init(chatbot) chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 self.plugin_wd.begin_watch() self.agt = AsyncGptTask() self.commit_wd = WatchDog(timeout=self.commit_after_pause_n_second, bark_fn=self.no_audio_for_a_while, interval=0.2) self.commit_wd.begin_watch() while not self.stop: self.event_on_result_chg.wait(timeout=0.25) # run once every 0.25 second chatbot = self.agt.update_chatbot(chatbot) # 将子线程的gpt结果写入chatbot history = chatbot2history(chatbot) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 self.plugin_wd.feed() if self.event_on_result_chg.is_set(): # called when some words have finished self.event_on_result_chg.clear() chatbot[-1] = list(chatbot[-1]) chatbot[-1][0] = self.buffered_sentence + self.parsed_text history = chatbot2history(chatbot) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 self.commit_wd.feed() if self.event_on_entence_end.is_set(): # called when a sentence has ended self.event_on_entence_end.clear() self.parsed_text = self.parsed_sentence self.buffered_sentence += self.parsed_text chatbot[-1] = list(chatbot[-1]) chatbot[-1][0] = self.buffered_sentence history = chatbot2history(chatbot) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 if self.event_on_commit_question.is_set(): # called when a question should be commited self.event_on_commit_question.clear() if len(self.buffered_sentence) == 0: raise RuntimeError self.commit_wd.begin_watch() chatbot[-1] = list(chatbot[-1]) chatbot[-1] = [self.buffered_sentence, "[ 等待GPT响应 ]"] yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # add gpt task 创建子线程请求gpt，避免线程阻塞 history = chatbot2history(chatbot) self.agt.add_async_gpt_task(self.buffered_sentence, len(chatbot)-1, llm_kwargs, history, system_prompt) self.buffered_sentence = "" chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 if not self.event_on_result_chg.is_set() and not self.event_on_entence_end.is_set() and not self.event_on_commit_question.is_set(): visualize_audio(chatbot, self.audio_shape) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 if len(self.stop_msg) != 0: raise RuntimeError(self.stop_msg) @CatchException def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): # pip install -U openai-whisper chatbot.append(["对话助手函数插件：使用时，双手离开鼠标键盘吧", "音频助手, 正在听您讲话（点击“停止”键可终止程序）..."]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 尝试导入依赖，如果缺少依赖，则给出安装建议 try: import nls from scipy import io except: chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return APPKEY = get_conf('ALIYUN_APPKEY') if APPKEY == "": chatbot.append(["导入依赖失败", "没有阿里云语音识别APPKEY和TOKEN, 详情见https://help.aliyun.com/document_detail/450255.html"]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 ia = InterviewAssistant() yield from ia.begin(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)