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| from toolbox import CatchException, report_execption, select_api_key, update_ui, write_results_to_file, get_conf | |
| from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive | |
| def split_audio_file(filename, split_duration=1000): | |
| """ | |
| 根据给定的切割时长将音频文件切割成多个片段。 | |
| Args: | |
| filename (str): 需要被切割的音频文件名。 | |
| split_duration (int, optional): 每个切割音频片段的时长（以秒为单位）。默认值为1000。 | |
| Returns: | |
| filelist (list): 一个包含所有切割音频片段文件路径的列表。 | |
| """ | |
| from moviepy.editor import AudioFileClip | |
| import os | |
| os.makedirs('gpt_log/mp3/cut/', exist_ok=True) # 创建存储切割音频的文件夹 | |
| # 读取音频文件 | |
| audio = AudioFileClip(filename) | |
| # 计算文件总时长和切割点 | |
| total_duration = audio.duration | |
| split_points = list(range(0, int(total_duration), split_duration)) | |
| split_points.append(int(total_duration)) | |
| filelist = [] | |
| # 切割音频文件 | |
| for i in range(len(split_points) - 1): | |
| start_time = split_points[i] | |
| end_time = split_points[i + 1] | |
| split_audio = audio.subclip(start_time, end_time) | |
| split_audio.write_audiofile(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3") | |
| filelist.append(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3") | |
| audio.close() | |
| return filelist | |
| def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history): | |
| import os, requests | |
| from moviepy.editor import AudioFileClip | |
| from request_llm.bridge_all import model_info | |
| # 设置OpenAI密钥和模型 | |
| api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model']) | |
| chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint'] | |
| whisper_endpoint = chat_endpoint.replace('chat/completions', 'audio/transcriptions') | |
| url = whisper_endpoint | |
| headers = { | |
| 'Authorization': f"Bearer {api_key}" | |
| } | |
| os.makedirs('gpt_log/mp3/', exist_ok=True) | |
| for index, fp in enumerate(file_manifest): | |
| audio_history = [] | |
| # 提取文件扩展名 | |
| ext = os.path.splitext(fp)[1] | |
| # 提取视频中的音频 | |
| if ext not in [".mp3", ".wav", ".m4a", ".mpga"]: | |
| audio_clip = AudioFileClip(fp) | |
| audio_clip.write_audiofile(f'gpt_log/mp3/output{index}.mp3') | |
| fp = f'gpt_log/mp3/output{index}.mp3' | |
| # 调用whisper模型音频转文字 | |
| voice = split_audio_file(fp) | |
| for j, i in enumerate(voice): | |
| with open(i, 'rb') as f: | |
| file_content = f.read() # 读取文件内容到内存 | |
| files = { | |
| 'file': (os.path.basename(i), file_content), | |
| } | |
| data = { | |
| "model": "whisper-1", | |
| "prompt": parse_prompt, | |
| 'response_format': "text" | |
| } | |
| chatbot.append([f"将 {i} 发送到openai音频解析终端 (whisper)，当前参数：{parse_prompt}", "正在处理 ..."]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| proxies, = get_conf('proxies') | |
| response = requests.post(url, headers=headers, files=files, data=data, proxies=proxies).text | |
| chatbot.append(["音频解析结果", response]) | |
| history.extend(["音频解析结果", response]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| i_say = f'请对下面的音频片段做概述，音频内容是 ```{response}```' | |
| i_say_show_user = f'第{index + 1}段音频的第{j + 1} / {len(voice)}片段。' | |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| inputs=i_say, | |
| inputs_show_user=i_say_show_user, | |
| llm_kwargs=llm_kwargs, | |
| chatbot=chatbot, | |
| history=[], | |
| sys_prompt=f"总结音频。音频文件名{fp}" | |
| ) | |
| chatbot[-1] = (i_say_show_user, gpt_say) | |
| history.extend([i_say_show_user, gpt_say]) | |
| audio_history.extend([i_say_show_user, gpt_say]) | |
| # 已经对该文章的所有片段总结完毕，如果文章被切分了 | |
| result = "".join(audio_history) | |
| if len(audio_history) > 1: | |
| i_say = f"根据以上的对话，使用中文总结音频“{result}”的主要内容。" | |
| i_say_show_user = f'第{index + 1}段音频的主要内容：' | |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| inputs=i_say, | |
| inputs_show_user=i_say_show_user, | |
| llm_kwargs=llm_kwargs, | |
| chatbot=chatbot, | |
| history=audio_history, | |
| sys_prompt="总结文章。" | |
| ) | |
| history.extend([i_say, gpt_say]) | |
| audio_history.extend([i_say, gpt_say]) | |
| res = write_results_to_file(history) | |
| chatbot.append((f"第{index + 1}段音频完成了吗？", res)) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| # 删除中间文件夹 | |
| import shutil | |
| shutil.rmtree('gpt_log/mp3') | |
| res = write_results_to_file(history) | |
| chatbot.append(("所有音频都总结完成了吗？", res)) | |
| yield from update_ui(chatbot=chatbot, history=history) | |
| def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, WEB_PORT): | |
| import glob, os | |
| # 基本信息：功能、贡献者 | |
| chatbot.append([ | |
| "函数插件功能？", | |
| "总结音视频内容，函数插件贡献者: dalvqw & BinaryHusky"]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| try: | |
| from moviepy.editor import AudioFileClip | |
| except: | |
| report_execption(chatbot, history, | |
| a=f"解析项目: {txt}", | |
| b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade moviepy```。") | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # 清空历史，以免输入溢出 | |
| history = [] | |
| # 检测输入参数，如没有给定输入参数，直接退出 | |
| if os.path.exists(txt): | |
| project_folder = txt | |
| else: | |
| if txt == "": txt = '空空如也的输入栏' | |
| report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}") | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # 搜索需要处理的文件清单 | |
| extensions = ['.mp4', '.m4a', '.wav', '.mpga', '.mpeg', '.mp3', '.avi', '.mkv', '.flac', '.aac'] | |
| if txt.endswith(tuple(extensions)): | |
| file_manifest = [txt] | |
| else: | |
| file_manifest = [] | |
| for extension in extensions: | |
| file_manifest.extend(glob.glob(f'{project_folder}/**/*{extension}', recursive=True)) | |
| # 如果没找到任何文件 | |
| if len(file_manifest) == 0: | |
| report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何音频或视频文件: {txt}") | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # 开始正式执行任务 | |
| if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg") | |
| parse_prompt = plugin_kwargs.get("advanced_arg", '将音频解析为简体中文') | |
| yield from AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |