├── .gitignore ├── .gitmodules ├── Dockerfile ├── LICENSE ├── README.md ├── config ├── config.ini ├── requirements.txt └── sensitive_words.txt ├── init.py ├── main.py ├── requirements.txt ├── resource └── subtitle.html ├── start.bat ├── start.sh ├── testing ├── blive.py ├── filter.py ├── gpt.py ├── my_old_thread_main.py ├── my_test_process.py ├── obsolete_danmu.py ├── process.py ├── pth2onnx.py ├── sensitive_words.txt ├── test1.py ├── test2.py ├── testPoolQueeu.py └── testQueue.py └── tts.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # User 7 | models/* 8 | output/* 9 | my_config.ini 10 | my_sensitive_words.txt 11 | temp.txt 12 | # C extensions 13 | *.so 14 | 15 | # Distribution / packaging 16 | .Python 17 | build/ 18 | develop-eggs/ 19 | dist/ 20 | downloads/ 21 | eggs/ 22 | .eggs/ 23 | lib/ 24 | lib64/ 25 | parts/ 26 | sdist/ 27 | var/ 28 | wheels/ 29 | pip-wheel-metadata/ 30 | share/python-wheels/ 31 | *.egg-info/ 32 | .installed.cfg 33 | *.egg 34 | MANIFEST 35 | 36 | # PyInstaller 37 | # Usually these files are written by a python script from a template 38 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 39 | *.manifest 40 | *.spec 41 | 42 | # Installer logs 43 | pip-log.txt 44 | pip-delete-this-directory.txt 45 | 46 | # Unit test / coverage reports 47 | htmlcov/ 48 | .tox/ 49 | .nox/ 50 | .coverage 51 | .coverage.* 52 | .cache 53 | nosetests.xml 54 | coverage.xml 55 | *.cover 56 | *.py,cover 57 | .hypothesis/ 58 | .pytest_cache/ 59 | 60 | # Translations 61 | *.mo 62 | *.pot 63 | 64 | # Django stuff: 65 | *.log 66 | local_settings.py 67 | db.sqlite3 68 | db.sqlite3-journal 69 | 70 | # Flask stuff: 71 | instance/ 72 | .webassets-cache 73 | 74 | # Scrapy stuff: 75 | .scrapy 76 | 77 | # Sphinx documentation 78 | docs/_build/ 79 | 80 | # PyBuilder 81 | target/ 82 | 83 | # Jupyter Notebook 84 | .ipynb_checkpoints 85 | 86 | # IPython 87 | profile_default/ 88 | ipython_config.py 89 | 90 | # pyenv 91 | .python-version 92 | 93 | # pipenv 94 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 95 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 96 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 97 | # install all needed dependencies. 98 | #Pipfile.lock 99 | 100 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 101 | __pypackages__/ 102 | 103 | # Celery stuff 104 | celerybeat-schedule 105 | celerybeat.pid 106 | 107 | # SageMath parsed files 108 | *.sage.py 109 | 110 | # Environments 111 | .env 112 | .venv 113 | env/ 114 | venv/ 115 | ENV/ 116 | env.bak/ 117 | venv.bak/ 118 | 119 | # Spyder project settings 120 | .spyderproject 121 | .spyproject 122 | 123 | # Rope project settings 124 | .ropeproject 125 | 126 | # mkdocs documentation 127 | /site 128 | 129 | # mypy 130 | .mypy_cache/ 131 | .dmypy.json 132 | dmypy.json 133 | 134 | # Pyre type checker 135 | .pyre/ 136 | -------------------------------------------------------------------------------- /.gitmodules: -------------------------------------------------------------------------------- 1 | [submodule "blivedm"] 2 | path = blivedm 3 | url = https://github.com/newreport/blivedm.git 4 | [submodule "MoeGoe"] 5 | path = MoeGoe 6 | url = https://github.com/newreport/MoeGoe.git -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/newreport/vtbai/d5fc86844d36f6dac6068150eb978466e762c23c/Dockerfile -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Function in coding .... 2 | - VTS API 关键字触发表情 3 | - 语句情感推断触发 VTS 表情 4 | - Azure API TTS 5 | - Link CharacterAI 角色扮演最好的 AI 6 | - Multi link 联动 7 | - ChatGLM-6B 本地1 8 | - ChatterBot 本地2 9 | - Twitch & Youtube 平台支持 10 | 11 | # 资源 12 | - [vits](https://github.com/jaywalnut310/vits) vits source 13 | - [MoeGoe](https://github.com/CjangCjengh/MoeGoe.git) vits chinese 14 | - [vits_with_chatgpt-gpt3](https://github.com/Paraworks/vits_with_chatgpt-gpt3) tts 推理参考 15 | - [blivedm](https://github.com/xfgryujk/blivedm/tree/master) 抓取 b 站直播间信息 16 | - [演示模型](https://huggingface.co/newreport/live_tts_default_model/tree/main) vits model (商用请自炼自然人同意的合法声源或用 Azure) 17 | 18 | - # 架构 19 | > 从哔哩哔哩直播间抓取弹幕和礼物，接收后发送给 openai 官方的 chatgpt，等待 gpt 回调消息后使用 vits 进行 tts 推理，然后根据关键字/VTS API 触发表情和 playsound 播放语音， 播放时 vts 根据声音匹配口型 20 | 21 | > 除非公司或大佬，非常不建议手搓 live2d，一是耗时，二是 vts 和 prprlive 配合关键字触发表情快捷键、VTS API 直播效果还可以 22 | 23 | > 本直播流程仅在 win 下测试并通过，理论 linux 和 mac 在合适的 py 环境中也能使用，py 版本为 conda 3.10.10 24 | 25 | > 注：有能者可以同理把老鼠和油管的扩展了，py 线程协程进程鲨我 26 | 27 | ## 工作流 28 | blivedm（抓直播间信息）——>openai（猫娘对话）——>vits（tts 文本转语音）——>vts（语音转口型，快捷键触发表情）——>obs(推流) 29 | 30 | ## 功能 31 | - 支持 api 请求，扩展用，比如联动，语音转文字后请求即可 httt://127.0.0.1:8080?text=你好 32 | - 支持优先级：api>舰长>礼物>SC>弹幕，礼物和弹幕队列容量默认为5/10，满了自动剔除时间线最后的，SC、舰长没有容量限制 33 | 34 | ## 我的开发环境 35 | - CPU：5700G 36 | - GPU：核显 37 | - 主板：华硕 B550m TUF 38 | - 硬盘：凯侠 RC20 39 | - 内存：16*4（3133hz 金百达） 40 | - 电源：台达 300W 41 | - 机箱：X40 5.5L 42 | 43 | > 主要速度慢在请求 openai 和 cpu 推理，用 gpu 会快很多，由于需要检测同音字敏感词以防爆房，故不能使用 SSE 44 | 45 | > obs、vts、雀魂 AI 全开的情况，推理时 cpu 负载约为 70%，理论讲 2k 内预算的丐中丐 5600G 也可以跑，功耗不超过 100W，ITX 都能跑，还要什么自行车，实际情况请用 n 卡 gpu 跑更好 46 | 47 | 48 | # 搭建流程 49 | 请确保您已安装好 [conda](https://newreport.top/2023-02-27/ubuntu-amd-centos-install-conda/)、[obs](https://obsproject.com/)、[vts](https://denchisoft.com/)、[vscode](https://code.visualstudio.com/) 50 | > 请用 conda 新建 python 3.10 环境，launch 了 vscode 51 | ```bash 52 | git clone -b 1.1-py https://github.com/newreport/vtbai.git 53 | cd vtbai 54 | start.bat 55 | # config\my_config.ini 填写房间号和 openai key 56 | python main.py 57 | # 弹幕，将 resource 中的 hmtl 拖到 obs 里 58 | ``` 59 | 60 | ![Star History Chart](https://api.star-history.com/svg?repos=newreport/live_tts_chatgpt&type=Date)] 61 | -------------------------------------------------------------------------------- /config/config.ini: -------------------------------------------------------------------------------- 1 | [main] 2 | # pro | dev 3 | env = pro 4 | # bili | twitch | ytb 5 | model = bili 6 | [queue] 7 | api_listen = http://0.0.0.0:3939 8 | # 是否联动，联动时只监听 top queue 9 | is_link = false 10 | [bili] 11 | # 房间id，可为短号 12 | roomid = 207640 13 | # 设置最优先id，可以设置自己 14 | topid = 1,2 15 | [twitch] 16 | [ytb] 17 | [openai] 18 | # openai key 19 | key = ***your key*** 20 | # 初始人设 21 | nya1 = 你是猫娘,you are in live,我你主人 22 | # openai api 代理，默认 https://api.openai.com/v1 23 | proxy_domain = https://api.openai.com/v1 24 | # 最大上下文 25 | max_context = 3 26 | # gpt-3.5-turbo | gpt-4 | gpt-4-32k 27 | model = gpt-3.5-turbo 28 | [tts] 29 | # 多少毫秒输出一个字 30 | interval_ms = 100 31 | # 最大缓存数量，超过时不再请求openai,即等播放完后再请求 32 | max_wav_queue = 5 33 | # 文本显示时最大断句 34 | max_text_length = 50 35 | # 语音最大断句 36 | # max_tts_length = 200 37 | # 推理模式 cpu | gpu 38 | # infernce_type = cpu 39 | 40 | model_onnx = ./models/model.onnx 41 | model_config = ./models/config.json 42 | model_pth = ./models/model.pth 43 | 44 | # 以下注释由 gpt 编写 45 | # 音频的长度缩放因子，通常用于控制语速。例如，将 length_scale 设置为 1.5 可以使语音变慢，而将其设置为 0.5 可以使语音加速。 46 | length_scale = 1 47 | # 噪声比例，以控制情感，噪声的标准差缩放因子。默认值为 0.667。 48 | noise_scale = 0.667 49 | # 噪声偏差，以控制音速长短，噪声的标准差缩放因子的偏差值。默认值为 0.8。 50 | noise_scale_w = 0.8 51 | speaker_id = 0 52 | # 是否在播放完后自动删除生成的 wav 文件 1 | 0 53 | auto_del_wav = 0 -------------------------------------------------------------------------------- /config/requirements.txt: -------------------------------------------------------------------------------- 1 | opencc 2 | openai 3 | audonnx 4 | playsound 5 | xlrd 6 | xlwt 7 | xlutils 8 | torchvision 9 | asyncio -------------------------------------------------------------------------------- /config/sensitive_words.txt: -------------------------------------------------------------------------------- 1 | 敏感词1 2 | 敏感词2 -------------------------------------------------------------------------------- /init.py: -------------------------------------------------------------------------------- 1 | import os 2 | import urllib.request as urllib2 3 | from shutil import copyfile 4 | 5 | dirs = ['models','output','output/wav'] 6 | 7 | for dir in dirs: 8 | if not os.path.exists(dir): 9 | os.makedirs(dir) 10 | 11 | filenames = ['model.onnx','model.pth','config.json'] 12 | 13 | # https://huggingface.co/newreport/live_tts_default_model/resolve/main/model.onnx 14 | # https://huggingface.co/newreport/live_tts_default_model/resolve/main/model.pth 15 | # https://huggingface.co/newreport/live_tts_default_model/resolve/main/config.json 16 | url='https://huggingface.co/newreport/live_tts_default_model/resolve/main/' 17 | 18 | for filename in filenames: 19 | if not os.path.exists('models/'+filename): 20 | print("downloading..."+url+filename) 21 | f = urllib2.urlopen(url+filename) 22 | with open("models/"+filename, "wb") as code: 23 | code.write(f.read()) 24 | 25 | configs =['config/my_config.ini','config/my_sensitive_words.txt'] 26 | for config in configs: 27 | if not os.path.exists(config): 28 | filename=config.replace("my_","") 29 | copyfile(filename,config) -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import os 2 | import openai 3 | import asyncio 4 | import _thread 5 | import random 6 | import logging 7 | import blivedm.blivedm as blivedm 8 | import configparser 9 | import uuid 10 | from queue import Queue, PriorityQueue 11 | import json 12 | import time 13 | import requests 14 | import os 15 | import multiprocessing 16 | import datetime 17 | import xlrd 18 | import xlwt 19 | from flask_cors import CORS 20 | import sys 21 | from xlutils.copy import copy 22 | from pypinyin import lazy_pinyin 23 | from flask import Flask, request,jsonify 24 | import tts 25 | 26 | # 配置文件、当前文本、excel（对话列表数据库）、敏感词文本 27 | config_ini = 'config/config.ini' 28 | xlsl_path = 'output/record.xlsx' 29 | sensitive_txt = 'config/sensitive_words.txt' 30 | if os.path.exists('config/my_config.ini'): 31 | config_ini = 'config/my_config.ini' 32 | if os.path.exists('config/my_sensitive_words.txt'): 33 | sensitive_txt = 'config/my_sensitive_words.txt' 34 | con = configparser.ConfigParser() 35 | con.read(config_ini, encoding='utf-8') 36 | main_config = dict(con.items('main')) 37 | queue_config = dict(con.items('queue')) 38 | bili_config = dict(con.items('bili')) 39 | openai_config = dict(con.items('openai')) 40 | tts_config = dict(con.items('tts')) 41 | 42 | 43 | # excel数据库 44 | if os.path.exists(xlsl_path) == False: 45 | workbook = xlwt.Workbook() 46 | sheet = workbook.add_sheet("test") # 在工作簿中新建一个表格 47 | workbook.save(xlsl_path) 48 | print("xls格式表格初始化成功！") 49 | print('当前进程id::' + str(os.getpid())) 50 | def write_excel_xls_append(value): 51 | workbook = xlrd.open_workbook(xlsl_path) # 打开工作簿 52 | sheets = workbook.sheet_names() # 获取工作簿中的所有表格 53 | rows_old = 0 54 | sheetName = str(datetime.date.today()) 55 | if sheetName in sheets: 56 | worksheet = workbook.sheet_by_name(sheetName) 57 | rows_old = worksheet.nrows # 获取表格中已存在的数据的行数 58 | new_workbook = copy(workbook) # 将xlrd对象拷贝转化为xlwt对象 59 | if sheetName not in sheets: 60 | new_workbook.add_sheet(sheetName) 61 | new_worksheet = new_workbook.get_sheet(sheetName) # 获取转化后工作簿中的第一个表格 62 | new_worksheet.write(rows_old, 0, value['datetime']) 63 | new_worksheet.write(rows_old, 1, value['user']) 64 | new_worksheet.write(rows_old, 2, value['type']) 65 | new_worksheet.write(rows_old, 3, value['num']) 66 | new_worksheet.write(rows_old, 4, value['action']) 67 | new_worksheet.write(rows_old, 5, value['msg']) 68 | new_worksheet.write(rows_old, 6, value['price']) 69 | new_workbook.save(xlsl_path) # 保存工作簿 70 | if main_config['env'] == 'dev': 71 | print("xls格式表格【追加】写入数据成功！") 72 | 73 | 74 | # 配置openai 75 | openai.api_key = openai_config['key'] 76 | openai.api_base = openai_config['proxy_domain'] 77 | base_context = [{"role": "system", "content": openai_config['nya1']}] 78 | context_message = [] 79 | temp_message = [] 80 | async def chatgpt(is_run): 81 | print("运行gpt循环任务") 82 | while is_run: 83 | chatObj = {"name": '', "type": '', 'num': 0, 84 | 'action': '', 'msg': '', 'price': 0} 85 | # 从队列获取信息 86 | try: 87 | if topQue.empty() == False: 88 | chatObj = topQue.get(True, 1) 89 | elif guardQue.empty() == False: 90 | chatObj = guardQue.get(True, 1) 91 | chatObj = chatObj[1] 92 | elif giftQue.empty() == False: 93 | chatObj = giftQue.get(True, 1) 94 | chatObj = chatObj[1] 95 | elif scQue.empty() == False: 96 | chatObj = scQue.get(True, 1) 97 | chatObj = chatObj[1] 98 | elif danmuQue.empty() == False: 99 | chatObj = danmuQue.get(True, 1) 100 | chatObj = chatObj[1] 101 | except Exception as e: 102 | print("-----------ErrorStart--------------") 103 | print(e) 104 | print("gpt获取弹幕异常，当前线程：：") 105 | print(chatObj) 106 | print("-----------ErrorEnd--------------") 107 | await asyncio.sleep(2) 108 | continue 109 | # print(chatObj) 110 | # 过滤队列 111 | if len(chatObj['name']) > 0: 112 | if filter_text(chatObj['name']) and filter_text(chatObj['msg']): 113 | send2gpt(chatObj) 114 | else: 115 | await asyncio.sleep(1) 116 | 117 | def send2gpt(msg): 118 | 119 | if main_config['env'] == 'dev': 120 | print('gpt当前进程id::' + str(os.getpid())) 121 | # 向 gpt 发送的消息 122 | send_gpt_msg = '' 123 | # 向 tts 写入的数据 124 | send_vits_msg = '' 125 | if msg['type'] == 'danmu': 126 | send_gpt_msg = msg['name'] + msg['action'] + msg['msg'] 127 | send_vits_msg = msg['msg'] 128 | elif msg['type'] == 'sc': 129 | send_gpt_msg = msg['name'] + msg['action'] + \ 130 | str(msg['price']) + '块钱sc说' + msg['msg'] 131 | send_vits_msg = send_gpt_msg 132 | elif msg['type'] == 'guard': 133 | guardType = '舰长' 134 | if msg['price'] > 200: 135 | guardType = '提督' 136 | elif msg['price'] > 2000: 137 | guardType = '总督' 138 | send_gpt_msg = msg['name'] + msg['action'] + \ 139 | guardType + '了,花了' + str(msg['price']) + '元' 140 | send_vits_msg = msg['name'] + msg['action'] + guardType + '了' 141 | elif msg['type'] == 'gift': 142 | send_gpt_msg = msg['name'] + msg['action'] + msg['msg'] 143 | send_vits_msg = send_gpt_msg 144 | else: 145 | send_gpt_msg = msg['msg'] 146 | send_vits_msg = send_gpt_msg 147 | 148 | # 生成上下文 149 | temp_message.append({"role": "user", "content": send_gpt_msg}) 150 | # 上下文最大值 151 | if len(temp_message) > 3: 152 | del (temp_message[0]) 153 | message = base_context + temp_message 154 | 155 | # 子进程4 156 | # 开启 openai 进程 157 | if tts_que.full() == False: 158 | p = multiprocessing.Process(target=rec2tts, args=( 159 | msg, send_gpt_msg, message, send_vits_msg,tts_que,tts_config)) 160 | p.start() 161 | # join 会阻塞当前 gpt 循环线程，但不会阻塞弹幕线程 162 | print("openai请求子进程开启完成") 163 | if tts_que.full(): 164 | p.join() 165 | 166 | def rec2tts(msg, send_gpt_msg, message, send_vits_msg,tts_que,tts_config): 167 | print("进入openai chatgpt进程，向gpt发送::" + send_gpt_msg) 168 | 169 | # 对话日志写入 excel 170 | with open('output/' + str(datetime.date.today()) + '.txt', 'a', encoding='utf-8') as a: 171 | a.write(str(datetime.datetime.now()) + "::发送::" + send_gpt_msg + '\n') 172 | a.flush() 173 | write_excel_xls_append({ 174 | 'datetime': str(datetime.datetime.now()), 175 | 'user': msg['name'], 176 | 'type': msg['type'], 177 | 'num': msg['num'], 178 | 'action': msg['action'], 179 | 'msg': msg['msg'], 180 | 'price': msg['price'] 181 | }) 182 | 183 | # 发送并收 184 | response = openai.ChatCompletion.create( 185 | model=openai_config['model'], messages=message) 186 | responseText = str(response['choices'][0]['message']['content']) 187 | 188 | # 敏感词词音过滤 189 | if filter_text(responseText) == False: 190 | print("检测到敏感词内容::" + responseText) 191 | return 192 | print("从gpt接收::" + responseText) 193 | tts_que.put(send_vits_msg) 194 | tts_que.put(responseText) 195 | 196 | # 对话日志 197 | with open('output/' + str(datetime.date.today()) + '.txt', 'a', encoding='utf-8') as a: 198 | a.write(str(datetime.datetime.now()) + "::接收::" + responseText + '\n') 199 | a.flush() 200 | write_excel_xls_append({ 201 | 'datetime': str(datetime.datetime.now()), 202 | 'user': 'gpt35', 203 | 'type': '', 204 | 'num': '', 205 | 'action': '说', 206 | 'msg': responseText, 207 | 'price': 0 208 | }) 209 | 210 | 211 | # 敏感词 212 | sensitiveF = open(sensitive_txt, 'r', encoding='utf-8') 213 | hanzi_sensitive_word = sensitiveF.readlines() 214 | pinyin_sensitive_word = [] 215 | for i in range(len(hanzi_sensitive_word)): 216 | hanzi_sensitive_word[i] = hanzi_sensitive_word[i].replace('\n', '') 217 | pinyin_sensitive_word.append(str.join('', lazy_pinyin(hanzi_sensitive_word[i]))) 218 | # 敏感词音检测 219 | def filter_text(text): 220 | # 为上舰时直接过 221 | if text == '-1': 222 | return True 223 | textPY = str.join('', lazy_pinyin(text)) 224 | for i in range(len(hanzi_sensitive_word)): 225 | if hanzi_sensitive_word[i] in text or pinyin_sensitive_word[i] in textPY: 226 | return False 227 | return True 228 | 229 | 230 | # tts 231 | tts_que = multiprocessing.Queue(maxsize=int(tts_config['max_wav_queue'])) 232 | wav_que = multiprocessing.Queue(maxsize=int(tts_config['max_wav_queue'])) 233 | 234 | # bilibili 235 | # 获取真实房间号 236 | roomID = json.loads(str(requests.get('https://api.live.bilibili.com/room/v1/Room/get_info?room_id=' + 237 | bili_config['roomid']).content, encoding="utf-8"))['data']['room_id'] 238 | # 最优先队列、sc、礼物、弹幕队列 239 | topQue = Queue(maxsize=0) 240 | # sc 队列 241 | scQue = PriorityQueue(maxsize=0) 242 | # 舰长队列 243 | guardQue = PriorityQueue(maxsize=0) 244 | # 礼物 245 | giftQue = PriorityQueue(maxsize=5) 246 | # 普通弹幕队列 247 | danmuQue = PriorityQueue(maxsize=10) 248 | topIDs = bili_config['topid'].split(',') 249 | async def run_single_client(): 250 | # 如果SSL验证失败就把ssl设为False，B站真的有过忘续证书的情况 251 | client = blivedm.BLiveClient(roomID, ssl=True) 252 | print(roomID) 253 | handler = MyHandler() 254 | client.add_handler(handler) 255 | client.start() 256 | try: 257 | await client.join() 258 | finally: 259 | await client.stop_and_close() 260 | 261 | class MyHandler(blivedm.BaseHandler): 262 | async def _on_heartbeat(self, client: blivedm.BLiveClient, message: blivedm.HeartbeatMessage): 263 | print(f'[{client.room_id}] 当前人气值：{message.popularity}') 264 | 265 | async def _on_danmaku(self, client: blivedm.BLiveClient, message: blivedm.DanmakuMessage): 266 | if message.dm_type == 0: 267 | print(f'弹幕：[{client.room_id}] {message.uname}：{message.msg}') 268 | # 权重计算 269 | guardLevel = message.privilege_type 270 | if guardLevel == 0: 271 | guardLevel = 0 272 | elif guardLevel == 3: 273 | guardLevel = 200 274 | elif guardLevel == 2: 275 | guardLevel = 2000 276 | elif guardLevel == 1: 277 | guardLevel = 20000 278 | # 舰长权重，勋章id权重*100，lv权重*100 279 | medalevel = 0 280 | if message.medal_room_id == roomID: 281 | medalevel = message.medal_level * 100 282 | rank = (999999 - message.user_level * 100 - 283 | guardLevel - medalevel - message.user_level * 10 + random.random()) 284 | if danmuQue.full(): 285 | try: 286 | danmuQue.get(True, 1) 287 | except BaseException: 288 | print("on_danmuku时，get异常") 289 | 290 | queData = {'name': message.uname, 'type': 'danmu', 'num': 1, 'action': '说', 291 | 'msg': message.msg.replace('[', '').replace(']', ''), 'price': 0} 292 | if main_config['env'] == 'dev': 293 | print("前弹幕队列容量：" + str(danmuQue.qsize())) 294 | print("rank:" + str(rank) + ";name:" + message.uname + ";msg:" + 295 | message.msg.replace('[', '').replace(']', '')) 296 | print(queData) 297 | try: 298 | danmuQue.put((rank, queData), True, 2) 299 | except Exception as e: 300 | print("ErrorStart-------------------------") 301 | print(e) 302 | print("put弹幕队列异常") 303 | print(queData) 304 | print("错误" + str(danmuQue.full())) 305 | print("错误" + str(danmuQue.empty())) 306 | print("后弹幕队列容量：" + str(danmuQue.qsize())) 307 | print("ErrorEnd-------------------------") 308 | 309 | async def _on_gift(self, client: blivedm.BLiveClient, message: blivedm.GiftMessage): 310 | if message.coin_type == 'gold': 311 | print(f'礼物：：[{client.room_id}] {message.uname} 赠送{message.gift_name}x{message.num}' 312 | f' （{message.coin_type}瓜子x{message.total_coin}）') 313 | price = message.total_coin / 1000 314 | if giftQue.full(): 315 | giftQue.get(False, 1) 316 | if price > 1: 317 | queData = {"name": message.uname, "type": 'gift', 'num': message.num, 318 | 'action': message.action, 'msg': message.gift_name, 'price': price} 319 | giftQue.put( 320 | (999999 - price + random.random(), queData), True, 1) 321 | 322 | async def _on_buy_guard(self, client: blivedm.BLiveClient, message: blivedm.GuardBuyMessage): 323 | print(f'上舰：：[{client.room_id}] {message.username} 购买{message.gift_name}') 324 | queData = {"name": message.username, "type": 'guard', 'num': 1, 325 | 'action': '上', 'msg': '-1', 'price': message.price / 1000} 326 | guardQue.put((message.guard_level + random.random(), queData)) 327 | 328 | async def _on_super_chat(self, client: blivedm.BLiveClient, message: blivedm.SuperChatMessage): 329 | print( 330 | f'SC：：[{client.room_id}] 醒目留言 ¥{message.price} {message.uname}：{message.message}') 331 | # 名称、类型、数量、动作、消息、价格 332 | queData = {"name": message.uname, "type": 'sc', 'num': 1, 333 | 'action': '发送', 'msg': message.message, 'price': message.price} 334 | scQue.put((999999 - message.price + random.random(), queData)) 335 | 336 | 337 | # api 338 | log = logging.getLogger('werkzeug') 339 | log.setLevel(logging.CRITICAL) 340 | app = Flask(__name__) 341 | CORS(app) 342 | 343 | @app.route('/', methods=['GET']) 344 | def putQueue(): 345 | message = request.args.get('text', '') 346 | queData = {"name": '-1', "type": 'top', 'num': 1, 347 | 'action': '', 'msg': message, 'price': 0} 348 | topQue.put(queData) 349 | return '1' 350 | @app.route('/subtitle', methods=['GET']) 351 | def subtitle(): 352 | # 读取共享内存变量的值 353 | return curr_txt.value 354 | 355 | 356 | 357 | if __name__ == '__main__': 358 | is_run = True 359 | # multiprocessing.set_start_method('spawn') 360 | manager = multiprocessing.Manager() 361 | curr_txt = manager.Value(str, "") 362 | 363 | # 主进程 364 | # chatgpt 365 | _thread.start_new_thread(asyncio.run,(chatgpt(is_run),)) 366 | # bilibili 367 | _thread.start_new_thread(asyncio.run,(run_single_client(),)) 368 | print('All thread start.') 369 | 370 | # 子进程1、2 371 | # playsound 播放进程 372 | p = multiprocessing.Process(target=tts.play, args=(is_run,tts_config,wav_que,curr_txt)) 373 | p.start() 374 | 375 | # 子进程3 376 | # tts 推理进程 377 | p = multiprocessing.Process(target=tts.inference, args=(is_run,tts_config,tts_que,wav_que)) 378 | p.start() 379 | 380 | print('All subprocesses start.') 381 | 382 | 383 | # api 384 | app.run("0.0.0.0", 3939) 385 | 386 | 387 | time.sleep(2) 388 | input('input to exit::\n') 389 | 390 | is_run = False 391 | print('All subprocesses done.') 392 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | openai 2 | torchvision 3 | pyaudio 4 | xlrd 5 | xlwt 6 | xlutils 7 | flask 8 | flask_cors -------------------------------------------------------------------------------- /resource/subtitle.html: -------------------------------------------------------------------------------- 1 |  90 | 91 | 92 | 93 | 94 | 102 | 103 | 104 | -------------------------------------------------------------------------------- /start.bat: -------------------------------------------------------------------------------- 1 | pip install -r requirements.txt 2 | git submodule update 3 | git submodule update --init --recursive 4 | git submodule update --remote 5 | pip install -r blivedm/requirements.txt 6 | pip install -r MoeGoe/requirements.txt 7 | python init.py -------------------------------------------------------------------------------- /start.sh: -------------------------------------------------------------------------------- 1 | pip install -r requirements.txt 2 | git submodule update 3 | git submodule update --init --recursive 4 | git submodule update --remote 5 | pip install -r blivedm/requirements.txt 6 | pip install -r MoeGoe/requirements.txt 7 | python init.py -------------------------------------------------------------------------------- /testing/blive.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import asyncio 3 | import random 4 | from queue import Queue, PriorityQueue 5 | import sys 6 | sys.path.append('../') 7 | import blivedm.blivedm as blivedm 8 | 9 | 10 | # 直播间ID的取值看直播间URL 11 | TEST_ROOM_IDS = [ 12 | 47867, 13 | ] 14 | 15 | 16 | async def main(): 17 | await run_single_client() 18 | 19 | 20 | async def run_single_client(): 21 | room_id = random.choice(TEST_ROOM_IDS) 22 | # 如果SSL验证失败就把ssl设为False，B站真的有过忘续证书的情况 23 | client = blivedm.BLiveClient(room_id, ssl=True) 24 | handler = MyHandler() 25 | client.add_handler(handler) 26 | 27 | client.start() 28 | try: 29 | await client.join() 30 | finally: 31 | await client.stop_and_close() 32 | 33 | # sc 队列 34 | scQue = PriorityQueue(maxsize=0) 35 | # 舰长队列 36 | guardQue = PriorityQueue(maxsize=0) 37 | # 礼物 38 | giftQue = PriorityQueue(maxsize=5) 39 | # 普通弹幕队列 40 | danmuQue = PriorityQueue(maxsize=5) 41 | 42 | 43 | class MyHandler(blivedm.BaseHandler): 44 | async def _on_danmaku(self, client: blivedm.BLiveClient, message: blivedm.DanmakuMessage): 45 | if message.dm_type == 0: 46 | print(f'弹幕：[{client.room_id}] {message.uname}：{message.msg}') 47 | # 权重计算 48 | privilege_type = message.privilege_type 49 | if privilege_type == 0: 50 | privilege_type = 9 51 | rank = (99999-message.user_level*10+(10-privilege_type) 52 | * 10+message.mobile_verify*10) 53 | if danmuQue.full(): 54 | danmuQue.get() 55 | danmuQue.put((rank, {"name": message.uname, "type": 'danmu', 56 | 'num': 1, 'action': '说', 'msg': message.msg, 'price': 0})) 57 | 58 | async def _on_gift(self, client: blivedm.BLiveClient, message: blivedm.GiftMessage): 59 | if message.coin_type == 'gold': 60 | print(f'礼物：[{client.room_id}] {message.uname} 赠送{message.gift_name}x{message.num}' 61 | f' （{message.coin_type}瓜子x{message.total_coin}）') 62 | price = message.total_coin/1000 63 | if giftQue.full(): 64 | giftQue.get() 65 | if price > 1: 66 | giftQue.put((999999-price, {"name": message.uname, "type": 'gift', 67 | 'num': message.num, 'action': message.action, 'msg': '-1', 'price': price})) 68 | 69 | async def _on_buy_guard(self, client: blivedm.BLiveClient, message: blivedm.GuardBuyMessage): 70 | print(f'上舰：[{client.room_id}] {message.username} 购买{message.gift_name}') 71 | guardQue([message.guard_level, { 72 | "name": message.username, "type": 'guard', 73 | 'num': 1, 'action': '上', 'msg': '-1', 'price': message.price/1000}]) 74 | 75 | async def _on_super_chat(self, client: blivedm.BLiveClient, message: blivedm.SuperChatMessage): 76 | print( 77 | f'SC:[{client.room_id}] 醒目留言 ¥{message.price} {message.uname}：{message.message}') 78 | # 名称、类型、数量、动作、消息、价格 79 | scQue.put((999999-message.price, {"name": message.uname, "type": 'sc', 80 | 'num': 1, 'action': '发送', 'msg': message.message, 'price': message.price})) 81 | 82 | 83 | 84 | 85 | 86 | if __name__ == '__main__': 87 | asyncio.run(main()) 88 | -------------------------------------------------------------------------------- /testing/filter.py: -------------------------------------------------------------------------------- 1 | from pypinyin import lazy_pinyin 2 | 3 | # 敏感词检测 同音字过滤 4 | f = open(r'sensitive_words.txt', 'r', encoding='utf-8') 5 | 6 | hz = f.readlines() 7 | py = [] 8 | for i in range(len(hz)): 9 | hz[i] = hz[i].replace('\n', '') 10 | py.append(str.join('', lazy_pinyin(hz[i]))) 11 | # print(hz) 12 | # print(py) 13 | 14 | 15 | readLine = True 16 | 17 | 18 | def filter_text(text): 19 | textPY=str.join('',lazy_pinyin(text)) 20 | print(textPY) 21 | for i in range(len(hz)): 22 | if hz[i] in text or py[i] in textPY: 23 | return False 24 | return True 25 | 26 | while readLine: 27 | inputStr = input('请输入：') 28 | if inputStr == 'q': 29 | readLine = False 30 | state = filter_text(inputStr) 31 | print(inputStr+':'+str(state)) 32 | -------------------------------------------------------------------------------- /testing/gpt.py: -------------------------------------------------------------------------------- 1 | import os 2 | import openai 3 | 4 | openai.api_key='' 5 | openai.api_base='' 6 | conversation=[{"role":"system","content":"你是一只会猫猫叫的猫娘，说话要带上喵"},{"role":"user","content":"我的上一句话是什么"}] 7 | response=openai.ChatCompletion.create(model="gpt-3.5-turbo",messages=conversation) 8 | context=response.id 9 | with open('temp.txt', 'a') as a: 10 | a.write('上下文id:'+context+'\n') 11 | a.flush() 12 | print(response.choices[0].message.content) 13 | print(response.usage) 14 | 15 | while True: 16 | str=input("Input Your Question: ") 17 | message=conversation 18 | message.append({"role":"user","content":str}) 19 | response=openai.ChatCompletion.create(model="gpt-3.5-turbo",messages=conversation) 20 | print("接收::"+response.choices[0].message.content) 21 | print(response.usage) 22 | print(response.id) -------------------------------------------------------------------------------- /testing/my_old_thread_main.py: -------------------------------------------------------------------------------- 1 | import openai 2 | import asyncio 3 | import random 4 | import blivedm.blivedm as blivedm 5 | import configparser 6 | from queue import Queue, PriorityQueue 7 | import json 8 | import time 9 | import requests 10 | import os 11 | import _thread 12 | from multiprocessing import Process 13 | import my_vits as vits 14 | import datetime 15 | from playsound import playsound 16 | import xlrd 17 | import xlwt 18 | from xlutils.copy import copy 19 | from pypinyin import lazy_pinyin 20 | 21 | 22 | def write_excel_xls_append(value): 23 | workbook = xlrd.open_workbook(xlslPATH) # 打开工作簿 24 | 25 | sheets = workbook.sheet_names() # 获取工作簿中的所有表格 26 | rows_old = 0 27 | sheetName = str(datetime.date.today()) 28 | if sheetName in sheets: 29 | worksheet = workbook.sheet_by_name(sheetName) 30 | rows_old = worksheet.nrows # 获取表格中已存在的数据的行数 31 | new_workbook = copy(workbook) # 将xlrd对象拷贝转化为xlwt对象 32 | if sheetName not in sheets: 33 | new_workbook.add_sheet(sheetName) 34 | new_worksheet = new_workbook.get_sheet(sheetName) # 获取转化后工作簿中的第一个表格 35 | new_worksheet.write(rows_old, 0, value['datetime']) 36 | new_worksheet.write(rows_old, 1, value['user']) 37 | new_worksheet.write(rows_old, 2, value['type']) 38 | new_worksheet.write(rows_old, 3, value['num']) 39 | new_worksheet.write(rows_old, 4, value['action']) 40 | new_worksheet.write(rows_old, 5, value['msg']) 41 | new_worksheet.write(rows_old, 6, value['price']) 42 | new_workbook.save(xlslPATH) # 保存工作簿 43 | if mainConfig['env'] == 'dev': 44 | print("xls格式表格【追加】写入数据成功！") 45 | 46 | 47 | def write_keyboard_text(text): 48 | if mainConfig['env'] == 'dev': 49 | print('vits当前进程id::'+str(os.getpid())) 50 | with open(currTXT, 'w') as w: 51 | w.write('') 52 | w.flush() 53 | with open(currTXT, 'a') as w: 54 | for txt in text: 55 | w.write(txt) 56 | w.flush() 57 | 58 | 59 | def send2gpt(msg): 60 | if mainConfig['env'] == 'dev': 61 | print('gpt当前进程id::'+str(os.getpid())) 62 | 63 | # 向gpt发送消息 64 | sendGptMsg = '' 65 | sendVitsMsg = '' 66 | if msg['type'] == 'danmu': 67 | sendGptMsg = msg['name']+msg['action']+msg['msg'] 68 | sendVitsMsg = msg['msg'] 69 | elif msg['type'] == 'sc': 70 | sendGptMsg = msg['name']+msg['action']+msg['price']+'块钱sc说'+msg['msg'] 71 | sendVitsMsg = sendGptMsg 72 | elif msg['type'] == 'guard': 73 | guardType = '舰长' 74 | if msg['price'] > 200: 75 | guardType = '提督' 76 | elif msg['price'] > 2000: 77 | guardType = '总督' 78 | sendGptMsg = msg['name']+msg['action'] + \ 79 | guardType+'了,花了'+msg['price']+'元' 80 | sendVitsMsg = msg['name']+msg['action'] + guardType+'了' 81 | elif msg['type'] == 'gift': 82 | sendGptMsg = msg['name']+msg['action'] + \ 83 | msg['msg']+',花了'+msg['price']+'元' 84 | sendVitsMsg = msg['name']+msg['action'] + msg['msg'] 85 | 86 | print("向gpt发送::"+sendGptMsg) 87 | # 对话日志 excel 88 | with open('output/'+str(datetime.date.today())+'.txt', 'a') as a: 89 | a.write(str(datetime.datetime.now())+"::发送::"+sendGptMsg+'\n') 90 | a.flush() 91 | write_excel_xls_append({ 92 | 'datetime': str(datetime.datetime.now()), 93 | 'user': msg['name'], 94 | 'type': msg['type'], 95 | 'num': msg['num'], 96 | 'action': msg['action'], 97 | 'msg': msg['msg'], 98 | 'price': msg['price'] 99 | }) 100 | 101 | # 发送给gpt 102 | tempMessage.append({"role": "user", "content": sendGptMsg}) 103 | if len(tempMessage) > 3: 104 | del (tempMessage[0]) 105 | message = baseContext+tempMessage 106 | 107 | # 接收 108 | response = openai.ChatCompletion.create( 109 | model="gpt-3.5-turbo", messages=message) 110 | responseText = str(response['choices'][0]['message']['content']) 111 | if filter_text(responseText) == False: 112 | return 113 | print("从gpt接收::"+responseText) 114 | 115 | # 生成发送语音 116 | vits.generated_speech(sendVitsMsg, 'sendVits.wav') 117 | # 生成接收语音 118 | vits.generated_speech(responseText, 'recVits.wav') 119 | 120 | playsound('output/sendVits.wav') 121 | time.sleep(0.5) 122 | # 模拟键盘输入 123 | write_keyboard_text(responseText) 124 | playsound('output/recVits.wav') 125 | 126 | # 对话日志 127 | with open('output/'+str(datetime.date.today())+'.txt', 'a') as a: 128 | a.write(str(datetime.datetime.now())+"::接收::"+responseText+'\n') 129 | a.flush() 130 | write_excel_xls_append({ 131 | 'datetime': str(datetime.datetime.now()), 132 | 'user': 'gpt35', 133 | 'type': '', 134 | 'num': '', 135 | 'action': '说', 136 | 'msg': responseText, 137 | 'price': 0 138 | }) 139 | 140 | 141 | def chatgpt35(): 142 | print("运行gpt循环任务") 143 | while True: 144 | chatObj = [0, {"name": '', "type": '', 'num': 0, 145 | 'action': '', 'msg': '', 'price': 0}] 146 | # 从队列获取信息 147 | try: 148 | if topQue.qsize() > 0: 149 | chatObj = topQue.get(True, 1) 150 | elif guardQue.qsize() > 0: 151 | chatObj = guardQue.get(True, 1) 152 | elif giftQue.qsize() > 0: 153 | chatObj = giftQue.get(True, 1) 154 | elif scQue.qsize() > 0: 155 | chatObj = scQue.get(True, 1) 156 | elif danmuQue.qsize() > 0: 157 | chatObj = danmuQue.get(True, 1) 158 | chatObj = chatObj[1] 159 | except: 160 | time.sleep(0) 161 | continue 162 | # 过滤队列 163 | if len(chatObj['name']) > 0: 164 | if filter_text(chatObj['name']) and filter_text(chatObj['msg']): 165 | send2gpt(chatObj) 166 | else: 167 | time.sleep(1) 168 | 169 | 170 | def filter_text(text): 171 | if text == '-1': 172 | return True 173 | textPY = str.join('', lazy_pinyin(text)) 174 | for i in range(len(hzSensitiveWord)): 175 | if hzSensitiveWord[i] in text or pySensitiveWord[i] in textPY: 176 | return False 177 | return True 178 | 179 | 180 | async def run_single_client(): 181 | # 如果SSL验证失败就把ssl设为False，B站真的有过忘续证书的情况 182 | client = blivedm.BLiveClient(roomID, ssl=True) 183 | handler = MyHandler() 184 | client.add_handler(handler) 185 | 186 | client.start() 187 | try: 188 | await client.join() 189 | finally: 190 | await client.stop_and_close() 191 | 192 | 193 | class MyHandler(blivedm.BaseHandler): 194 | async def _on_danmaku(self, client: blivedm.BLiveClient, message: blivedm.DanmakuMessage): 195 | if message.dm_type == 0: 196 | # print(f'弹幕：[{client.room_id}] {message.uname}：{message.msg}') 197 | # 权重计算 198 | privilege_type = message.privilege_type 199 | if privilege_type == 0: 200 | privilege_type = 9 201 | rank = (99999-message.user_level*10+(10-privilege_type) 202 | * 10+message.mobile_verify*10) 203 | print("rank:"+str(rank)+";name:"+message.uname+";msg:"+message.msg.replace('[', '').replace(']', '')) 204 | danmuQue.put((rank, {'name': message.uname, 'type': 'danmu','num': 1, 'action': '说', 'msg': message.msg.replace('[', '').replace(']', ''), 'price': 0})) 205 | 206 | async def _on_gift(self, client: blivedm.BLiveClient, message: blivedm.GiftMessage): 207 | if message.coin_type == 'gold': 208 | print(f'礼物：[{client.room_id}] {message.uname} 赠送{message.gift_name}x{message.num}' 209 | f' （{message.coin_type}瓜子x{message.total_coin}）') 210 | price = message.total_coin/1000 211 | if price > 1: 212 | giftQue.put((999999-price, {"name": message.uname, "type": 'gift', 213 | 'num': message.num, 'action': message.action, 'msg': '-1', 'price': price})) 214 | 215 | async def _on_buy_guard(self, client: blivedm.BLiveClient, message: blivedm.GuardBuyMessage): 216 | print(f'上舰：[{client.room_id}] {message.username} 购买{message.gift_name}') 217 | guardQue((message.guard_level, { 218 | "name": message.username, "type": 'guard', 219 | 'num': 1, 'action': '上', 'msg': '-1', 'price': message.price/1000})) 220 | 221 | async def _on_super_chat(self, client: blivedm.BLiveClient, message: blivedm.SuperChatMessage): 222 | print( 223 | f'SC:[{client.room_id}] 醒目留言 ¥{message.price} {message.uname}：{message.message}') 224 | # 名称、类型、数量、动作、消息、价格 225 | scQue.put((999999-message.price, {"name": message.uname, "type": 'sc', 226 | 'num': 1, 'action': '发送', 'msg': message.message, 'price': message.price})) 227 | 228 | def cleanQue(): 229 | while True: 230 | try: 231 | if giftQue.full(): 232 | giftQue.get(True, 1) 233 | elif danmuQue.full(): 234 | danmuQue.get(True, 1) 235 | except: 236 | print("满了") 237 | 238 | # 配置文件、日志、当前文本、记录excel、敏感词文本 239 | configINI = 'config.ini' 240 | tempTXT = 'output/temp.txt' 241 | currTXT = 'output/currText.txt' 242 | xlslPATH = 'output/record.xlsx' 243 | sensitiveTXT = 'sensitive_words.txt' 244 | 245 | # openai 246 | if os.path.exists('my_config.ini'): 247 | configINI = 'my_config.ini' 248 | con = configparser.ConfigParser() 249 | con.read(configINI, encoding='utf-8') 250 | sections = con.sections() 251 | mainConfig = dict(con.items('main')) 252 | roomID = json.loads(str(requests.get('https://api.live.bilibili.com/room/v1/Room/get_info?room_id=' + 253 | mainConfig['roomid']).content, encoding="utf-8"))['data']['room_id'] 254 | openai.api_key = mainConfig['key'] 255 | baseContext = [{"role": "system", "content": mainConfig['nya1']}] 256 | response = openai.ChatCompletion.create( 257 | model="gpt-3.5-turbo", messages=baseContext) 258 | time.sleep(1) 259 | print("主线程发送::"+mainConfig['nya1']+"\n主线程接收::" + 260 | str(response['choices'][0]['message']['content']).replace('\r', '').replace('\n', '')) 261 | # 带基础设定最大3条上下文 262 | contextMessage = [] 263 | tempMessage = [] 264 | 265 | # 敏感词 266 | if os.path.exists('my_sensitive_words.txt'): 267 | sensitiveTXT = 'my_sensitive_words.txt' 268 | sensitiveF = open(sensitiveTXT, 'r', encoding='utf-8') 269 | hzSensitiveWord = sensitiveF.readlines() 270 | pySensitiveWord = [] 271 | for i in range(len(hzSensitiveWord)): 272 | hzSensitiveWord[i] = hzSensitiveWord[i].replace('\n', '') 273 | pySensitiveWord.append(str.join('', lazy_pinyin(hzSensitiveWord[i]))) 274 | 275 | # 最优先队列、sc、礼物、弹幕队列 276 | topQue = Queue(maxsize=0) 277 | # sc 队列 278 | scQue = PriorityQueue(maxsize=0) 279 | # 舰长队列 280 | guardQue = PriorityQueue(maxsize=0) 281 | # 礼物 282 | giftQue = PriorityQueue(maxsize=5) 283 | # 普通弹幕队列 284 | danmuQue = PriorityQueue(maxsize=10) 285 | topIDs = mainConfig['topid'].split(',') 286 | 287 | # excel数据库 288 | if os.path.exists(xlslPATH) == False: 289 | workbook = xlwt.Workbook() 290 | sheet = workbook.add_sheet("test") # 在工作簿中新建一个表格 291 | workbook.save(xlslPATH) 292 | print("xls格式表格初始化成功！") 293 | print('当前进程id::'+str(os.getpid())) 294 | 295 | 296 | if __name__ == '__main__': 297 | isRun = True 298 | _thread.start_new_thread(cleanQue, ()) 299 | _thread.start_new_thread(chatgpt35, ()) 300 | _thread.start_new_thread(asyncio.get_event_loop( 301 | ).run_until_complete, (run_single_client(),)) 302 | print('All subprocesses start.') 303 | time.sleep(2) 304 | input('input to exit::') 305 | isRun = False 306 | print('All subprocesses done.') 307 | -------------------------------------------------------------------------------- /testing/my_test_process.py: -------------------------------------------------------------------------------- 1 | import asyncio 2 | import _thread 3 | import multiprocessing 4 | import time 5 | 6 | def fun1(): 7 | while True: 8 | print("fun1") 9 | time.sleep(1) 10 | 11 | 12 | def fun2(): 13 | print("fun2") 14 | time.sleep(10) 15 | 16 | def fun3(): 17 | while True: 18 | print("fun3") 19 | 20 | p=multiprocessing.Process(target=fun2, args=()) 21 | p.start() 22 | _thread.start_new_thread(fun1,()) 23 | _thread.start_new_thread(fun3,()) 24 | print("end1") 25 | input("input to here .....") 26 | print('end2') -------------------------------------------------------------------------------- /testing/obsolete_danmu.py: -------------------------------------------------------------------------------- 1 | from bilibili_api import live, sync 2 | import json 3 | import requests 4 | 5 | 6 | env = 'pro' # dev|pro 7 | 8 | roomID = '' 9 | # 获取房间真实 id 10 | room = live.LiveDanmaku(json.loads(str(requests.get('https://api.live.bilibili.com/room/v1/Room/get_info?room_id=' + 11 | roomID).content, encoding="utf-8"))['data']['room_id']) 12 | 13 | @room.on('DANMU_MSG') 14 | async def on_danmaku(event): 15 | print(event) 16 | # 收到弹幕 17 | name = event['data']['info'][2][1] 18 | msg = event['data']['info'][1] 19 | msgs = name+"说："+msg 20 | msgType = event['data']['info'][0][12] 21 | if env == 'dev': 22 | with open('danmu.txt', 'a') as a: 23 | a.write(str(event)+'\n') 24 | a.flush() 25 | if msgType == 0: 26 | m = 1 27 | print("弹幕::"+msgs) 28 | elif msgType == 1: 29 | print('表情::'+msgs) 30 | else: 31 | print('其他::'+msgs) 32 | 33 | @room.on('SEND_GIFT') 34 | async def on_gift(event): 35 | print(event) 36 | # 收到礼物 37 | if event['data']['data']['batch_combo_send'] is not None: 38 | name = event['data']['data']['batch_combo_send']['uname'] 39 | action = event['data']['data']['batch_combo_send']['action'] 40 | num = event['data']['data']['batch_combo_send']['gift_num'] 41 | gift = event['data']['data']['batch_combo_send']['gift_name'] 42 | msgs = name+action+str(num)+'个'+gift 43 | print("礼物::"+msgs) 44 | if env == 'dev': 45 | with open('gift.txt', 'a') as a: 46 | a.write(str(event)+'\n') 47 | a.flush() 48 | if __name__ == '__main__': 49 | sync(room.connect()) 50 | -------------------------------------------------------------------------------- /testing/process.py: -------------------------------------------------------------------------------- 1 | import multiprocessing 2 | from flask import Flask, request 3 | import time 4 | 5 | def func(num): 6 | # 共享数值型变量 7 | # num.value = 2 8 | 9 | # 共享数组型变量 10 | num[2] = 9999 11 | 12 | def rot(num): 13 | app = Flask(__name__) 14 | print("run le") 15 | app.run, ("0.0.0.0", 8081) 16 | 17 | @app.route('/', methods=['GET']) 18 | def put(): 19 | return '1' 20 | 21 | if __name__ == '__main__': 22 | # 共享数值型变量 23 | # num = multiprocessing.Value('d', 1) 24 | # print(num.value) 25 | 26 | # 共享数组型变量 27 | num = multiprocessing.Array('i', [1, 2, 3, 4, 5]) 28 | print(num[:]) 29 | 30 | 31 | p = multiprocessing.Process(target=func, args=(num,)) 32 | p.start() 33 | p.join() 34 | p1 = multiprocessing.Process(target=rot, args=(num,)) 35 | p1.start() 36 | p1.join 37 | 38 | # 共享数值型变量 39 | # print(num.value) 40 | time.sleep(100) 41 | # 共享数组型变量 42 | print(num[:]) -------------------------------------------------------------------------------- /testing/pth2onnx.py: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | import torch 5 | from light_cnns import mbv1 6 | 7 | sourcePath='/app/live_vits_chatgpt/models/G_latest.pth' 8 | outPath='/app/live_vits_chatgpt/models/G_latest.onnx' 9 | 10 | def main(): 11 | model = mbv1() 12 | imput = torch.randn(1,3,224,224) 13 | torch.onnx.export(model, input, "mobilenetV2.onnx", verbose=True, opset_version=11, export_params=True) 14 | 15 | if __name__ == '__main__': 16 | main() 17 | 18 | -------------------------------------------------------------------------------- /testing/sensitive_words.txt: -------------------------------------------------------------------------------- 1 | 台湾 2 | 新疆 3 | 北京 4 | 中国 -------------------------------------------------------------------------------- /testing/test1.py: -------------------------------------------------------------------------------- 1 | import test2 2 | import multiprocessing 3 | import time 4 | 5 | 6 | print("主进程") 7 | if __name__ == '__main__': 8 | multiprocessing.freeze_support() 9 | 10 | while True: 11 | p = multiprocessing.Process(target=test2.play) 12 | p.start() 13 | time.sleep(2) -------------------------------------------------------------------------------- /testing/test2.py: -------------------------------------------------------------------------------- 1 | 2 | print("子进程main外1") 3 | 4 | def play(): 5 | print("子进程 函数 3") 6 | 7 | if __name__ == '__main__': 8 | print("子进程main内2") -------------------------------------------------------------------------------- /testing/testPoolQueeu.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/newreport/vtbai/d5fc86844d36f6dac6068150eb978466e762c23c/testing/testPoolQueeu.py -------------------------------------------------------------------------------- /testing/testQueue.py: -------------------------------------------------------------------------------- 1 | from queue import Queue, PriorityQueue 2 | import _thread 3 | import datetime 4 | import time 5 | 6 | q=PriorityQueue(maxsize=20) 7 | 8 | 9 | def Put(vau): 10 | while True: 11 | if q.qsize()>10: 12 | print("is full") 13 | try: 14 | q.get(True,1) 15 | except: 16 | q.put(vau,vau) 17 | q.put(vau,vau) 18 | # time.sleep(1) 19 | 20 | def Get(): 21 | while True: 22 | str1=q.get() 23 | print(str(datetime.datetime.now())+':'+str(str1)) 24 | # time.sleep(1) 25 | 26 | _thread.start_new_thread(Get, ()) 27 | _thread.start_new_thread(Put, (2,)) 28 | _thread.start_new_thread(Put, (1,)) 29 | input() -------------------------------------------------------------------------------- /tts.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import multiprocessing 3 | import onnxruntime as ort 4 | import torchvision.models as models 5 | from scipy.io import wavfile 6 | import time 7 | import wave 8 | import pyaudio 9 | import os 10 | import sys 11 | import numpy as np 12 | import asyncio 13 | import torch 14 | import uuid 15 | import configparser 16 | sys.path.append('MoeGoe') 17 | import commons as commons 18 | import utils as ttsUtils 19 | from text import text_to_sequence 20 | 21 | 22 | def is_japanese(string): 23 | for ch in string: 24 | if ord(ch) > 0x3040 and ord(ch) < 0x30FF: 25 | return True 26 | return False 27 | 28 | 29 | def is_english(string): 30 | import re 31 | pattern = re.compile('^[A-Za-z0-9.,:;!?()_*"\' ]+$') 32 | if pattern.fullmatch(string): 33 | return True 34 | else: 35 | return False 36 | 37 | 38 | # 生成/推理语音 39 | def generated_speech(hps, ort_sess, tts_config, text, fileName): 40 | text = f"[ZH]{text}[ZH]" 41 | if is_japanese(text): 42 | text = f"[JA]{text}[JA]" 43 | 44 | # 将文本字符串转换为id 45 | seq = text_to_sequence(text, symbols=hps.symbols, 46 | cleaner_names=hps.data.text_cleaners) 47 | if hps.data.add_blank: 48 | seq = commons.intersperse(seq, 0) 49 | with torch.no_grad(): 50 | x = np.array([seq], dtype=np.int64) 51 | x_len = np.array([x.shape[1]], dtype=np.int64) 52 | sid = tts_config['speaker_id'] 53 | sid = np.array([sid], dtype=np.int64) 54 | scales = np.array([tts_config['noise_scale'], tts_config['noise_scale_w'], 55 | tts_config['length_scale']], dtype=np.float32) 56 | scales.resize(1, 3) 57 | ort_inputs = { 58 | 'input': x, 59 | 'input_lengths': x_len, 60 | 'scales': scales, 61 | 'sid': sid 62 | } 63 | t1 = time.time() 64 | audio = np.squeeze(ort_sess.run(None, ort_inputs)) 65 | audio *= 32767.0 / max(0.01, np.max(np.abs(audio))) * 0.6 66 | audio = np.clip(audio, -32767.0, 32767.0) 67 | t2 = time.time() 68 | spending_time = "推理时间："+str(t2-t1)+"s" 69 | print(spending_time+" 推理内容:"+text) 70 | wavfile.write('output/wav/'+fileName+'.wav', hps.data.sampling_rate, 71 | audio.astype(np.int16)) 72 | 73 | # 播放语音和更改文字 74 | 75 | 76 | def play(is_run, tts_config, wav_que, curr_txt): 77 | print("运行play子进程") 78 | is_auto_del = bool(int(tts_config['auto_del_wav'])) 79 | while is_run: 80 | # 阻塞 81 | text = wav_que.get() 82 | print("开始播放内容::"+text) 83 | name = text.split("::")[0] 84 | txt = text.split("::")[1] 85 | p = multiprocessing.Process( 86 | target=change_txt, args=(tts_config, txt, curr_txt)) 87 | p.start() 88 | play_audio('output/wav/'+name+'.wav') 89 | if is_auto_del: 90 | os.remove('output/wav/'+name+'.wav') 91 | time.sleep(0.5) 92 | p.join() 93 | 94 | def change_txt(tts_config, text, curr_txt): 95 | # print("改变文字"+text) 96 | curr_txt.value = '' 97 | for txt in text: 98 | curr_txt.value = curr_txt.value + txt 99 | # print(curr_txt.value) 100 | time.sleep(float(tts_config['interval_ms'])/1000) 101 | 102 | def play_audio(file_path): 103 | CHUNK = 1024 104 | wf = wave.open(file_path, 'rb') 105 | p = pyaudio.PyAudio() 106 | stream = p.open(format=p.get_format_from_width(wf.getsampwidth()), 107 | channels=wf.getnchannels(), 108 | rate=wf.getframerate(), 109 | output=True) 110 | 111 | data = wf.readframes(CHUNK) 112 | 113 | while data: 114 | stream.write(data) 115 | data = wf.readframes(CHUNK) 116 | 117 | stream.stop_stream() 118 | stream.close() 119 | 120 | p.terminate() 121 | 122 | 123 | 124 | def inference(is_run, tts_config, ttsQue, wav_que): 125 | print("运行tts子进程") 126 | config_ini = 'config/config.ini' 127 | if os.path.exists('config/my_config.ini'): 128 | config_ini = 'config/my_config.ini' 129 | con = configparser.ConfigParser() 130 | con.read(config_ini, encoding='utf-8') 131 | tts_config = dict(con.items('tts')) 132 | 133 | hps = ttsUtils.get_hparams_from_file(tts_config['model_config']) 134 | ort_sess = ort.InferenceSession(tts_config['model_onnx']) 135 | 136 | while is_run: 137 | # 阻塞 138 | text = ttsQue.get() 139 | name = str(uuid.uuid1()) 140 | print("生成语音：："+name+"::"+text) 141 | generated_speech(hps, ort_sess, tts_config, text,name) 142 | wav_que.put(name+"::"+text) 143 | 144 | if __name__ == '__main__': 145 | config_ini = 'config/config.ini' 146 | if os.path.exists('config/my_config.ini'): 147 | config_ini = 'config/my_config.ini' 148 | con = configparser.ConfigParser() 149 | con.read(config_ini, encoding='utf-8') 150 | tts_config = dict(con.items('tts')) 151 | 152 | hps = ttsUtils.get_hparams_from_file(tts_config['model_config']) 153 | ort_sess = ort.InferenceSession(tts_config['model_onnx']) 154 | 155 | str1 = "最喜欢的季节是春天。我觉得春天是一个充满生机和活力的季节。随着百花的盛开，春天带来了新的生命和希望。在春天，气温逐渐升高，天气也变得温暖和宜人。大自然开始苏醒，鸟儿唧唧喳喳地叫着，树木渐渐发芽，花儿绽放出五彩斑斓的色彩。春天也是一个让人感到愉快的季节。人们开始换上轻便的衣服，走出户外，感受大自然的美妙。我喜欢在春天里去公园散步，享受春风拂面的感觉。在公园里，可以看到满眼的绿意和各种各样的鲜花，让人心情舒畅。此外，春天也是一个让人充满期待和希望的季节。在新的一年里，一切都是全新的开始。人们开始规划新的计划和目标，并努力实现它们。总之，对我来说，春天是一个非常特别的季节。它带给我无尽的欢乐和动力，让我感到充满希望和激情。我相信，在这个美好的季节里，我们可以收获更多的爱与快乐。" 156 | generated_speech(hps, ort_sess, tts_config, str1, 'temp1') 157 | --------------------------------------------------------------------------------