rime_wanxiang_pro
Rime万象拼音输入方案增强版,词库基于AI筛选和语料辅助筛选精干高效,配合全新语言模型,输入不再纠结。支持全拼,7种双拼,8种辅助码,并且可以扩展更多,支持中英混输,内置超级注释lua,带调全拼输入码显示lua,快符与重复上屏lua等功能扩展,大大增强使用体验
Stars: 131
Rime Wanxiang Pro is an enhanced version of Wanxiang, supporting the 9, 14, and 18-key layouts. It features a pinyin library with optimized word and language models, supporting accurate sentence output with tones. The tool also allows for mixed Chinese and English input, offering various usage scenarios. Users can customize their input method by selecting different decoding and auxiliary code rules, enabling flexible combinations of pinyin and auxiliary codes. The tool simplifies the complex configuration of Rime and provides a unified word library for multiple input methods, enhancing input efficiency and user experience.
README:
万象系列方案: 本方案为万象增强版 万象基础版本支持同文9、14、18键
万象拼音 基于深度优化的词库和语言模型万象词库与万象语言模型 这是一种带声调的词库,经过AI和大基数语料筛选、加频,结合语言模型获得更准确的整句输出。还结合了中英文混输,一套词库,多种用法,具体可以跳转了解优势。
词库词语全部加音调,设计8种辅助码,头部使用全拼编码,可以转化为任何双拼编码,词库解码顺序为:全拼拼音;墨奇;鹤形;自然码;简单鹤;仓颉首末;虎码首末;五笔前2;汉心码,因此万象拼音支持拼音和辅助码任意两两组合。
#本方案匹配词库解码顺序为:全拼拼音;墨奇;鹤形;自然码;简单鹤;仓颉首末;虎码首末;五笔前2;汉心码
#############DIY你想要的方案组合,试试搭配一个自然码+墨奇辅助的方案吧!###########################
set_shuru_schema: #配置此项就是选择什么输入法,同时拆分反查和中英文混输也将匹配该输入方案
__include: algebra_zrm #可选解码规则有 algebra_pinyin, algebra_zrm, algebra_flypy, algebra_ziguang, algebra_sogou, algebra_mspy, algebra_abc 选择一个填入
set_algebra_fuzhu: #配置此项就是选择什么辅助码
__include: fuzhu_zrm #可选辅助码有:fuzhu_kong,fuzhu_moqi, fuzhu_zrm, fuzhu_flypy, fuzhu_tiger, fuzhu_cj, fuzhu_wubi, fuzhu_jdh fuzhu_hanxin 选择一个填入
pro_comment_format: # 超级注释模块,子项配置 true 开启,false 关闭
fuzhu_code: true # 启用辅助码提醒,用于辅助输入练习辅助码,成熟后可关闭
candidate_length: 1 # 候选词辅助码提醒的生效长度,0为关闭 但同时清空其它,应当使用上面开关来处理
fuzhu_type: zrm # 用于匹配对应的辅助码注释显示,基于默认词典的可选注释类型有:(tone, moqi, flypy, zrm, jdh, cj, tiger, wubi, hanxin)选择一个填入,之所以单独列出是因为这里有更多的可配置性,而真正的辅助码默认只有7种
corrector: true # 启用错音错词提醒,例如输入 geiyu 给予 获得 jǐ yǔ 提示
corrector_type: "{comment}" # 换一种显示类型,比如"({comment})"
########################以下是方案配置######################################################
再次打开radical_pinyin.schema.yaml
和 melt_eng.schema.yaml
表头进行选择,二者情况一致:
###############选择与之匹配的拼音方案#####################
set_shuru_schema:
__include: algebra_zrm #可选的选项有(algebra_pinyin, algebra_zrm, algebra_flypy, algebra_mspy, algebra_sogou, algebra_abc, algebra_ziguang)
######################################################
保存后部署方案即可!
- 配置复杂: rime的配置本就复杂(对于新手),常常会看到很多的方案和分支,这就又导致新手接触的时候要理清这些都是干什么的、有什么关联、我该选择什么?
- 用户词库: 词库涉及到丰富度、词频,一味地堆砌并不能提升体验,反而会提升内存占用,词频不恰当候选词可能排序不理想,影响输入效率。
- 探索适应期: 选择困难,每个都有各自的特点,无法一次性选择好方案,一个一个去尝试,耗费的是精力,损失的是用户词,找到与自己习惯匹配的方案似乎很难,这个过程越久越容易放弃。
- 简化合并词库:
-
简化选择,但又不能完全放弃选择,让用户有一个词库可选,却有多种方案可用。于是首先想到的是合并词库,每个方案都有自己的特定词库,他们编码方式不一样,词库内容和词频不一样,如果将其合并为一个词库,并解决这个词库的丰富度,解决词频问题,那将成为可扩展的元词库,我们将其称为——万象词库。
#词库解码顺序为:全拼拼音;墨奇;鹤形;自然码;简单鹤;仓颉首末;虎码首末;五笔前2 万 wan;av;ap;ag,ap;du;ms;fp;dn; 87991 象 xiang;du;dn;du,pd,ua;gh;no;wx;qj; 3107 拼 pin;fk;fk;fb;jp;qt,qj;ul;ru; 5904 音 yin;lo;lo;lo;cc;ya;xy;uj; 13619
这样的编码方式使用全拼作为基础意味着他能转换为任意一种双拼编码,有了共同的基底,后面通过分号隔开分别列举多种辅助码方式,我们可以通过运算规则来调用不同的辅助码。
- 拼写运算:
-
如何实现我们设想的两两组合呢,是否真的可以做到,经过分析使用自然码举例:
- 我们先去转换拼音为双拼编码,并命名为对应的输入方案,如:algebra_zrm;
- 当词库编码发生变化后我们通过运算实现双拼+辅助码的形式,从而真正可以打出这些字,我们把运算辅助码的部分命名为:fuzhu_zrm; 最后在 speller/algebra: 段落下按照顺序列出,从而形成一个完整连贯的运算规则。
-
下面来看自然码双运算规则,我们要把编码拼音部分做转换,但要保留第一个分号后及其后面所有内容:
algebra_zrm: __append: - derive/^([jqxy])u(;.*)$/$1v$2/ - derive/^([aoe])([ioun])(;.*)$/$1$1$2$3/ - xform/^([aoe])(ng)?(;.*)$/$1$1$2$3/ - xform/^(\w+?)iu(;.*)$/$1Ⓠ$2/ - xform/^(\w+?)[uv]an(;.*)$/$1Ⓡ$2/ - xform/^(\w+?)[uv]e(;.*)$/$1Ⓣ$2/ - xform/^(\w+?)ing(;.*)$/$1Ⓨ$2/ - xform/^(\w+?)uai(;.*)$/$1Ⓨ$2/ - xform/^(\w+?)uo(;.*)$/$1Ⓞ$2/ - xform/^(\w+?)[uv]n(;.*)$/$1Ⓟ$2/ - xform/^(\w+?)i?ong(;.*)$/$1Ⓢ$2/ - xform/^(\w+?)[iu]ang(;.*)$/$1Ⓓ$2/ - xform/^(\w+?)en(;.*)$/$1Ⓕ$2/ - xform/^(\w+?)eng(;.*)$/$1Ⓖ$2/ - xform/^(\w+?)ang(;.*)$/$1Ⓗ$2/ - xform/^(\w+?)ian(;.*)$/$1Ⓜ$2/ - xform/^(\w+?)an(;.*)$/$1Ⓙ$2/ - xform/^(\w+?)iao(;.*)$/$1Ⓒ$2/ - xform/^(\w+?)ao(;.*)$/$1Ⓚ$2/ - xform/^(\w+?)ai(;.*)$/$1Ⓛ$2/ - xform/^(\w+?)ei(;.*)$/$1Ⓩ$2/ - xform/^(\w+?)ie(;.*)$/$1Ⓧ$2/ - xform/^(\w+?)ui(;.*)$/$1Ⓥ$2/ - xform/^(\w+?)ou(;.*)$/$1Ⓑ$2/ - xform/^(\w+?)in(;.*)$/$1Ⓝ$2/ - xform/^(\w+?)[iu]a(;.*)$/$1Ⓦ$2/ - xform/^sh/Ⓤ/ - xform/^ch/Ⓘ/ - xform/^zh/Ⓥ/ - xlit/ⓆⓌⓇⓉⓎⓊⒾⓄⓅⓈⒹⒻⒼⒽⓂⒿⒸⓀⓁⓏⓍⓋⒷⓃ/qwrtyuiopsdfghmjcklzxvbn/
此时获得的输出是:
#词库解码顺序为:全拼拼音;墨奇;鹤形;自然码;简单鹤;仓颉首末;虎码首末;五笔前2 万 wj;av;ap;ag,ap;du;ms;fp;dn; 87991 象 xd;du;dn;du,pd,ua;gh;no;wx;qj; 3107 拼 pn;fk;fk;fb;jp;qt,qj;ul;ru; 5904 音 yn;lo;lo;lo;cc;ya;xy;uj; 13619
在此基础之上对于辅助码进行运算,这里针对不同位置的辅助码分别写了提取规则,但是提取之后则采用了统一格式的运算,这就大大减小了运算难度:
fuzhu_zrm: ########################################位于词库第三个分号后 __append: - xform|^(.{2});.*?;.*?;(.*?);.*$|$1;$2| - xform|^(\w+?);.*?;.*?;(.*?);.*$|$1;$2| #匹配当前方案,转换为 双拼;辅助码(当前方案)的形式 - derive/^(.{2}|\w+?);.*$/$1/ # 纯双拼的情况 - derive/^(.{2}|\w+?);(\w)(\w).*$/$1$2/ # 双拼+一位辅助码的情况 - derive/^(.{2}|\w+?);(\w)(\w).*$/$1[$2/ # 双拼+[一位辅助码的情况 - derive/^(.{2}|\w+?);.*?,(\w)(\w).*$/$1$2/ # 双拼+一位辅助码的情况 - derive/^(.{2}|\w+?);.*?,(\w)(\w).*$/$1[$2/ # 双拼+[一位辅助码的情况 - abbrev/^(.{2}|\w+?);(\w)(\w).*$/$1$2$3/ # 双拼+2位辅助码的情况,abbrev类型不可以整句内输入2位辅助码,必须加o或/ - abbrev/^(.{2}|\w+?);.*?,(\w)(\w).*$/$1$2$3/ # 双拼+2位辅助码的情况,abbrev类型不可以整句内输入2位辅助码,必须加o或/ - derive/^(.{2}|\w+?);(\w)(\w).*$/$1$2$3o/ # 整句模式下,输入syffo 出单字 增强单字性能 - derive|^(.{2});(\w)(\w).*$|$1$2$3/| # 整句模式下,输入syff/ 出单字 增强单字性能 - derive|^(\w+?);(\w)(\w).*$|$1$2$3/| # 整句模式下,输入syff/ 出单字 增强单字性能 - derive/^(.{2}|\w+?);.*,(\w)(\w).*$/$1$2$3o/ # 整句模式下,输入syffo 出单字 增强单字性能 - derive|^(.{2});.*,(\w)(\w).*$|$1$2$3/| # 整句模式下,输入syff/ 出单字 增强单字性能 - derive|^(\w+?);.*,(\w)(\w).*$|$1$2$3/| # 整句模式下,输入syff/ 出单字 增强单字性能 - derive|^(.{2});.*,(\w)(\w).*$|$1$2$3/| # 整句模式下,输入syff/ 出单字 增强单字性能
第一二条就是把很长的编码缩短到双拼+辅助码的形态,本来一条即可,为了照顾微软和搜狗方案中使用了分号作为一个韵母多写了一条,毕竟我们说了要自由搭配的,所以兼容性必须做。
输出:
万 wj;ag,ap 87991 象 xd;du,pd,ua 3107 拼 pn;fb 5904 音 yn;lo 13619
没错用逗号隔开的是辅助容错码,不管输入哪两个都可以打出这个字,这样大部分时候靠猜测也能利用起来辅助码,这个场景也做了兼容。
最后通过运算规则这个“万”字就有了以下几种组合可以输出:
万 wj 万 wja 万 wjag 万 wjap 为了增强整句中单字性能,通过增加o或者/的方式还可以获得以下输出 万 wjago 万 wjapo 万 wjag/ 万 wjap/
-
缝合:
在rime中
speller/algebra:
就是拼写运算之处,我们为了用户自定义变得方便,我们基于三个维度制作了一个表头,用来前置参数配置:#本方案匹配词库解码顺序为:全拼拼音;墨奇;鹤形;自然码;简单鹤;仓颉首末;虎码首末;五笔前2 #############DIY你想要的方案组合,试试搭配一个自然码+墨奇辅助的方案吧!########################### set_shuru_schema: #配置此项就是选择什么输入法,同时拆分反查和中英文混输也将匹配该输入方案 __include: algebra_zrm #可选解码规则有 algebra_pinyin, algebra_zrm, algebra_flypy, algebra_ziguang, algebra_sogou, algebra_mspy, algebra_abc 选择一个填入 set_algebra_fuzhu: #配置此项就是选择什么辅助码 __include: fuzhu_zrm #可选辅助码有:fuzhu_kong,fuzhu_moqi, fuzhu_zrm, fuzhu_flypy, fuzhu_tiger, fuzhu_cj, fuzhu_wubi, fuzhu_jdh 选择一个填入 #Lua 配置: 超级注释模块 pro_comment_format: # 超级注释,子项配置 true 开启,false 关闭 fuzhu_code: true # 启用辅助码提醒,用于辅助输入练习辅助码,成熟后可关闭 candidate_length: 1 # 候选词辅助码提醒的生效长度,0为关闭 但同时清空其它,应当使用上面开关来处理 fuzhu_type: zrm # 用于匹配对应的辅助码注释显示,可选显示类型有:moqi, flypy, zrm, jdh, cj, tiger, wubi, hx选择一个填入,应与上面辅助码类型一致 corrector: true # 启用错音错词提醒,例如输入 geiyu 给予 获得 jiyu 提示 corrector_type: "{comment}" # 新增一个显示类型,比如"【{comment}】" ########################以下是方案配置######################################################
我们需要按照如下格式对
speller/algebra:
进行排序:speller: # table_translator翻译器,支持自动上屏。例如 “zmhu”可以自动上屏“怎么回事” auto_select: true # auto_select_pattern: ^[a-z]+/|^[a-df-zA-DF-Z]\w{3}|^e\w{4} # 如果不想让什么标点直接上屏,可以加在 alphabet,或者编辑标点符号为两个及以上的映射 alphabet: zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA`/ # initials 定义仅作为始码的按键,排除 ` 让单个的 ` 可以直接上屏 initials: zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA delimiter: " '" # 第一位<空格>是拼音之间的分隔符;第二位<'>表示可以手动输入单引号来分割拼音。 algebra: __patch: - set_shuru_schema #拼音转双拼码 - set_algebra_fuzhu #辅助码部分
至此只需要模块化分别列举出不同的双拼方案,不同的辅助码形态交叉调用即可实现自然码+鹤形,小鹤+自然码,搜狗+五笔,甚至全拼+辅助码的形态等各种奇怪的组合。
表头的第三个维度,为用户留出了初学需要看辅助码,可以用于记忆慢慢让字都能出现在第一位。
-
功能:
辅助码它可以在输入一个确定得拼音后面继续输入一个部首的读音,使得这个字出现在靠前甚至第一位。这种方式易于理解,无须记忆字根,一切基于拼音得基础上。例如:
功能1 如果想要
镇
字显示在前面 那么在本方案下提供两种方式,第一种就是辅助码声母,vf
继续输入j
也就是金字旁得声母即可出现结果,如果还是出现不了你要的结果,可以输入另外主体字的声母来继续缩小范围。功能2 第二种方式是通过反查字库来定位,只是通过不同的方案实现,在输入主要拼音后,通过符号``` 来引导进入反查状态,引导后继续输入
jn
金 则包含金的字就会被选出来;引导后继续输入
mu 木
则带木
的字就会被选出来功能3 通过 拼音状态下
az
字母来引导拆字模式 举例震
假设你不认识,你可以通过雨和辰
来合并输入,拼音状态输入后,继续输入其它字符字母az会消失如下图,输入yu if
即雨 辰,结果出现了我们要的震字,且给出了辅助码y
和i
,y
是雨的声母y
,i
是辰的声母ch
功能4 句子中间或者单字输入时需要输入全位辅助码时由于与双拼词语重码,我们此时可以通过追加/的方式使其聚拢,这种方式是由于我们是直接辅助码导致的,如果我们通过一个符号引导辅助码,那么在输入时要每一个都用到符号,而采用这种方式我们只需要在必要的时候使用/节省了输入的按键开支,下面由两个图片说明问题:
其它亮点功能
日期时间: 输入:
date time week datetime timestamp
得到:
2024-07-04 19:37 星期四 2024-07-04T19:38:47+08:00 1720093174
农历: lunar 获得当前日期的农历值Unicode: 大写 U 开头,如 U62fc 得到「拼」。
数字、金额大写: 大写 R 开头,如 R1234 得到「一千二百三十四、壹仟贰佰叁拾肆元整」。
农历指定日期: 大写 N 开头,如 N20240210 得到「二〇二四年正月初一」。
/模式: 通过输入 /sx 快捷输入关于“数学”的特殊符号,具体能输入什么可以打开 symbols.yaml学习。
计算器: 通过输入大写V引导继续输入如:V3+5 候选框就会有8和3+5=8,基础功能
+ - * / % ^
还支持sin(x) cos(x)
等众多运算方式 点击全面学习自动上屏: 例如:三位、四位简码唯一时,自动上屏如
jjkw岌岌可危
zmhu怎么回事
。默认未开启,方案文件中speller:
字段下取消注释这两句开启# auto_select: true # auto_select_pattern: ^[a-z]+/|^[a-df-zA-DF-Z]\w{3}|^e\w{4}
错音错字提示: 例如:输入
gei yu给予
,获得jǐ yǔ
提示,此功能与双拼类型无关全部支持;快符: 例如
'q
通过单引号键引导的26字母快速符号自动上屏,双击''重复上一个符号;辅助码提示: 任意长度候选词的辅助码提示能力,默认开启1个字的辅助码,Ctrl+a开启和关闭辅助码,Ctrl+m墨奇专属拆字辅助,Ctrl+z自然码拆分辅助,这些都是共用配置可在开关中按自己需求配置,保留一个;
音调显示: 在辅助码配置中有tone这一参数,可以将音调拼音显示到注释里,通过Ctrl+s可以使得输入码显示全拼并加音调;
用户词删除: 不管什么删除都不能直接作用于固定词典,使用Ctrl+del是rime系统删除用户词,基于lua的实现:对选中的候选词操作,使用Ctrl+d 删除,Ctrl+x隐藏,Ctrl+j降低词频,删除的词都在lua下文件中记录,你可以清空重新部署恢复,也可以根据列出去清除固定词典的编码,从而持续迭代。
Tab循环切换音节: 当输入多个字词时想要给前面补充辅助码,可以多次按下tab循环切换,这种可能比那些复杂的快捷键好用一些;
翻译模式: 输入状态按下Ctrl+E快捷键进入翻译模式,原理是opencc查表进行中英文互译,能否翻译取决于词表的丰富度;
反查: 支持az、ab引导状态下的显示格式化,az是部件组字,ab是笔画组字。反查模式不受字符集过滤影响,默认开放大字集,也不受辅助码开关影响,会显示注释;
字符集过滤: 默认开启过滤,写在charset.dict.yaml的就是可以通过的字表,默认为8105+𰻞𰻞,如果你想什么字在小字集模式可以通过可以写在这里,配套开关【小、大】,快捷键Ctrl+g 更多功能可以编辑方案文件依据注释说明开启
-
墨奇音形:
墨奇音形是一个基于一种新型开源的字形描述信息、递归拆分至最小字形,最后取首末双形音托的方案。查墨奇码的拆分:加群696353204 ②群10885687 输入“墨奇码拆 想拆的字”。支持4万字
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for rime_wanxiang_pro
Similar Open Source Tools
rime_wanxiang_pro
Rime Wanxiang Pro is an enhanced version of Wanxiang, supporting the 9, 14, and 18-key layouts. It features a pinyin library with optimized word and language models, supporting accurate sentence output with tones. The tool also allows for mixed Chinese and English input, offering various usage scenarios. Users can customize their input method by selecting different decoding and auxiliary code rules, enabling flexible combinations of pinyin and auxiliary codes. The tool simplifies the complex configuration of Rime and provides a unified word library for multiple input methods, enhancing input efficiency and user experience.
Code-Interpreter-Api
Code Interpreter API is a project that combines a scheduling center with a sandbox environment, dedicated to creating the world's best code interpreter. It aims to provide a secure, reliable API interface for remotely running code and obtaining execution results, accelerating the development of various AI agents, and being a boon to many AI enthusiasts. The project innovatively combines Docker container technology to achieve secure isolation and execution of Python code. Additionally, the project supports storing generated image data in a PostgreSQL database and accessing it through API endpoints, providing rich data processing and storage capabilities.
bedrock-book
This repository contains sample code for hands-on exercises related to the book 'Amazon Bedrock 生成AIアプリ開発入門'. It allows readers to easily access and copy the code. The repository also includes directories for each chapter's hands-on code, settings, and a 'requirements.txt' file listing necessary Python libraries. Updates and error fixes will be provided as needed. Users can report issues in the repository's 'Issues' section, and errata will be published on the SB Creative official website.
Long-Novel-GPT
Long-Novel-GPT is a long novel generator based on large language models like GPT. It utilizes a hierarchical outline/chapter/text structure to maintain the coherence of long novels. It optimizes API calls cost through context management and continuously improves based on self or user feedback until reaching the set goal. The tool aims to continuously refine and build novel content based on user-provided initial ideas, ultimately generating long novels at the level of human writers.
MarkMap-OpenAi-ChatGpt
MarkMap-OpenAi-ChatGpt is a Vue.js-based mind map generation tool that allows users to generate mind maps by entering titles or content. The application integrates the markmap-lib and markmap-view libraries, supports visualizing mind maps, and provides functions for zooming and adapting the map to the screen. Users can also export the generated mind map in PNG, SVG, JPEG, and other formats. This project is suitable for quickly organizing ideas, study notes, project planning, etc. By simply entering content, users can get an intuitive mind map that can be continuously expanded, downloaded, and shared.
AI-Drug-Discovery-Design
AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.
awesome-chatgpt-zh
The Awesome ChatGPT Chinese Guide project aims to help Chinese users understand and use ChatGPT. It collects various free and paid ChatGPT resources, as well as methods to communicate more effectively with ChatGPT in Chinese. The repository contains a rich collection of ChatGPT tools, applications, and examples.
AIMedia
AIMedia is a fully automated AI media software that automatically fetches hot news, generates news, and publishes on various platforms. It supports hot news fetching from platforms like Douyin, NetEase News, Weibo, The Paper, China Daily, and Sohu News. Additionally, it enables AI-generated images for text-only news to enhance originality and reading experience. The tool is currently commercialized with plans to support video auto-generation for platform publishing in the future. It requires a minimum CPU of 4 cores or above, 8GB RAM, and supports Windows 10 or above. Users can deploy the tool by cloning the repository, modifying the configuration file, creating a virtual environment using Conda, and starting the web interface. Feedback and suggestions can be submitted through issues or pull requests.
AHU-AI-Repository
This repository is dedicated to the learning and exchange of resources for the School of Artificial Intelligence at Anhui University. Notes will be published on this website first: https://www.aoaoaoao.cn and will be synchronized to the repository regularly. You can also contact me at [email protected].
LLMLanding
LLMLanding is a repository focused on practical implementation of large models, covering topics from theory to practice. It provides a structured learning path for training large models, including specific tasks like training 1B-scale models, exploring SFT, and working on specialized tasks such as code generation, NLP tasks, and domain-specific fine-tuning. The repository emphasizes a dual learning approach: quickly applying existing tools for immediate output benefits and delving into foundational concepts for long-term understanding. It offers detailed resources and pathways for in-depth learning based on individual preferences and goals, combining theory with practical application to avoid overwhelm and ensure sustained learning progress.
MoneyPrinterTurbo
MoneyPrinterTurbo is a tool that can automatically generate video content based on a provided theme or keyword. It can create video scripts, materials, subtitles, and background music, and then compile them into a high-definition short video. The tool features a web interface and an API interface, supporting AI-generated video scripts, customizable scripts, multiple HD video sizes, batch video generation, customizable video segment duration, multilingual video scripts, multiple voice synthesis options, subtitle generation with font customization, background music selection, access to high-definition and copyright-free video materials, and integration with various AI models like OpenAI, moonshot, Azure, and more. The tool aims to simplify the video creation process and offers future plans to enhance voice synthesis, add video transition effects, provide more video material sources, offer video length options, include free network proxies, enable real-time voice and music previews, support additional voice synthesis services, and facilitate automatic uploads to YouTube platform.
aimoneyhunter
AiMoneyHunter is a comprehensive collection of information on AI side hustle opportunities, covering various methods, technologies, tools, platforms, and channels for making money with AI. It aims to break information barriers in the AI era, enabling everyone to leverage AI intelligence for side hustles and earn extra income. The repository includes curated AI-related content sources, tips on starting a side hustle, and insights on using AI technologies for various money-making tasks.
MINI_LLM
This project is a personal implementation and reproduction of a small-parameter Chinese LLM. It mainly refers to these two open source projects: https://github.com/charent/Phi2-mini-Chinese and https://github.com/DLLXW/baby-llama2-chinese. It includes the complete process of pre-training, SFT instruction fine-tuning, DPO, and PPO (to be done). I hope to share it with everyone and hope that everyone can work together to improve it!
NGCBot
NGCBot is a WeChat bot based on the HOOK mechanism, supporting scheduled push of security news from FreeBuf, Xianzhi, Anquanke, and Qianxin Attack and Defense Community, KFC copywriting, filing query, phone number attribution query, WHOIS information query, constellation query, weather query, fishing calendar, Weibei threat intelligence query, beautiful videos, beautiful pictures, and help menu. It supports point functions, automatic pulling of people, ad detection, automatic mass sending, Ai replies, rich customization, and easy for beginners to use. The project is open-source and periodically maintained, with additional features such as Ai (Gpt, Xinghuo, Qianfan), keyword invitation to groups, automatic mass sending, and group welcome messages.
AivisSpeech
AivisSpeech is a Japanese text-to-speech software based on the VOICEVOX editor UI. It incorporates the AivisSpeech Engine for generating emotionally rich voices easily. It supports AIVMX format voice synthesis model files and specific model architectures like Style-Bert-VITS2. Users can download AivisSpeech and AivisSpeech Engine for Windows and macOS PCs, with minimum memory requirements specified. The development follows the latest version of VOICEVOX, focusing on minimal modifications, rebranding only where necessary, and avoiding refactoring. The project does not update documentation, maintain test code, or refactor unused features to prevent conflicts with VOICEVOX.
For similar tasks
rime_wanxiang_pro
Rime Wanxiang Pro is an enhanced version of Wanxiang, supporting the 9, 14, and 18-key layouts. It features a pinyin library with optimized word and language models, supporting accurate sentence output with tones. The tool also allows for mixed Chinese and English input, offering various usage scenarios. Users can customize their input method by selecting different decoding and auxiliary code rules, enabling flexible combinations of pinyin and auxiliary codes. The tool simplifies the complex configuration of Rime and provides a unified word library for multiple input methods, enhancing input efficiency and user experience.
For similar jobs
sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.