#写了一个用nodejs来拆词和问答的模块,跪求点赞 #大哥们,谢谢你们了,跪求点赞,下面是链接 #https://github.com/zy445566/CustomerService #为了支持async和await,我这个也建议直接上node的7.7.1以上版本
CustomerService
Question & Answer’Ai
- <a href="#chinese">中文文档</a>
- <a href="#english">english</a>
- <a href="#api">API</a>
<a name=“chinese”></a> 中文文档
- <a href="#intro-zh">介绍</a>
- <a href="#req-zh">要求</a>
- <a href="#install-zh">安装</a>
- <a href="#use-zh">使用</a>
<a name=“intro-zh”></a>
介绍
CustomerService是一个可以从句子里面拆出词汇,并且可以实现问题和回答的相似度匹配的AI系统. 理论上只要词库(中文已有部分)和问答库(未导入)足够的大,就可以实现非常完美的问答.Power By NodeJs.
<a name=“req-zh”></a>
要求
由于使用了async和await,所以nodejs版本要在7.7.1以上.或使用babel.
<a name=“install-zh”></a>
安装
npm install customer-service
<a name=“use-zh”></a>
使用
初始化工具
const CustomerService = require("customer-service");
var customerService = new CustomerService('mylang',2,13);
var sw = customerService.getSplitWord();
var ie = customerService.getImportExport();
var qa = customerService.getQuestionAnswer();
拆词
sw.collisionWord(sw.sentenceToList('我在洗澡,你在干嘛'))
.then((res)=>{
console.log(res);
/* will print
[ { key: 'word:b7669c4218782c0035b6383623e19b29',
word: '我在',
questionList: {} },
{ key: 'word:5ac500cfcc1fe66f7243cad4039281d1',
word: '洗澡',
questionList: {} },
{ key: 'word:9d63b7094c5a502e66fccc79e5fe1f69',
word: '你在',
questionList: {} },
{ key: 'word:c44a42f209fa03606e607994c2321ebd',
word: '干嘛',
questionList: {} } ]
*/
});
库的导入和打印
//导入词库字符串
var chunk = "你好\r\n智能";
ie.stringToLevel(chunk,'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//导入问答字符串
var chunk = "你在洗澡吗?===>>>然而并没有.\r\n你是屌丝吗?===>>>不是屌丝写什么代码.";
ie.stringToLevel(chunk,'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//导入问答字符串
const path = require('path');
//导入词库
ie.readWordToLevel(path.join(__dirname,'word.log'),'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//导入问答
ie.readWordToLevel(path.join(__dirname,'qa.log'),'qa')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//print data
ie.printData({start:'word',limit:10});
获取回答
//获取最佳回答
qa.getAnswer('你是屌丝吗')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
<a name=“english”></a> Document
- <a href="#intro-en">intro</a>
- <a href="#req-en">req</a>
- <a href="#install-en">install</a>
- <a href="#use-en">use</a>
<a name=“intro-en”></a>
intro
CustomerService is a down words from a sentence, and can realize question and answer the similarity matching of AI system. Theoretically as long as the word library (Chinese existing part) and q&a library (import) not enough big, can achieve very perfect answers. The Power By NodeJs.
<a name=“req-en”></a>
req
nodejs’version>7.7.1 or use babel.
<a name=“install-en”></a>
install
npm install customer-service
<a name=“use-en”></a>
use
init
const CustomerService = require("customer-service");
var customerService = new CustomerService('mylang',2,13);
var sw = customerService.getSplitWord();
var ie = customerService.getImportExport();
var qa = customerService.getQuestionAnswer();
split word
sw.collisionWord(sw.sentenceToList('我在洗澡,你在干嘛'))
.then((res)=>{
console.log(res);
/* will print
[ { key: 'word:b7669c4218782c0035b6383623e19b29',
word: '我在',
questionList: {} },
{ key: 'word:5ac500cfcc1fe66f7243cad4039281d1',
word: '洗澡',
questionList: {} },
{ key: 'word:9d63b7094c5a502e66fccc79e5fe1f69',
word: '你在',
questionList: {} },
{ key: 'word:c44a42f209fa03606e607994c2321ebd',
word: '干嘛',
questionList: {} } ]
*/
});
lib import or print
//import word by string
var chunk = "你好\r\n智能";
ie.stringToLevel(chunk,'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//import q&a by string
var chunk = "你在洗澡吗?===>>>然而并没有.\r\n你是屌丝吗?===>>>不是屌丝写什么代码.";
ie.stringToLevel(chunk,'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//import word by file
const path = require('path');
//导入词库
ie.readWordToLevel(path.join(__dirname,'word.log'),'word')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//import q&a by string
ie.readWordToLevel(path.join(__dirname,'qa.log'),'qa')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
//print data
ie.printData({start:'word',limit:10});
get answer
//get best answer
qa.getAnswer('你是屌丝吗')
.then((res)=>{
console.log(res);
})
.catch((err)=>{
console.log(err);
});
<a name=“api”></a> API
- <a href="#customer-service-api">CustomerService</a>
- <a href="#split-word-api">SplitWord</a>
- <a href="#import-export-api">ImportExport</a>
- <a href="#question-answer-api">QuestionAnswer</a>
<a name=“customer-service-api”></a>
CustomerService
FunctionName constructor
- Return void
- Description 构造函数
- Param
name | type | require | default | Description |
---|---|---|---|---|
namespace | string | option | ‘mylang’ | 选择的命名空间 |
minContinue | number | option | 1 | 拆词的最小长度 |
maxContinue | number | option | 13 | 拆词的最大长度 |
FunctionName getSplitWord
- Return <SplitWord>splitWord
- Description 获取分词工具
- Param empty
FunctionName getImportExport
- Return <ImportExport>importExport
- Description 获取导入导出工具
- Param empty
FunctionName getQuestionAnswer
- Return <QuestionAnswer>questionAnswer
- Description 获取提问回答工具
- Param empty
<a name=“split-word-api”></a>
SplitWord
FunctionName sentenceToList
- Return <Object>singleWordList
- Description 将句子拆成所有可能的词汇
- Param
name | type | require | default | Description |
---|---|---|---|---|
sentence | string | must | empty | 要拆的句子 |
FunctionName collisionWord
- Return <Array>hitWordList
- Description 将句子所有可能的词汇去碰撞词库得到正确的词汇
- Param
name | type | require | default | Description |
---|---|---|---|---|
singleWordList | Object | must | empty | 句子所有可能的词汇 |
FunctionName sentenceToUnsigned
- Return <String>sentence
- Description 将句子去除所有符号
- Param
name | type | require | default | Description |
---|---|---|---|---|
sentence | string | must | empty | 要去除符号的句子 |
<a name=“import-export-api”></a>
ImportExport
FunctionName getData
- Return <Promise>tmpData
- Description 获取当前数据库数据
- attend 这个方法可能回导致内存溢出,请务必传option
- Param
name | type | require | default | Description |
---|---|---|---|---|
option | Object | option | {} | 筛选选项 |
Additionally, you can supply an options object as the first parameter to createReadStream()
with the following options:
'gt'
(greater than),'gte'
(greater than or equal) define the lower bound of the range to be streamed. Only records where the key is greater than (or equal to) this option will be included in the range. Whenreverse=true
the order will be reversed, but the records streamed will be the same.'lt'
(less than),'lte'
(less than or equal) define the higher bound of the range to be streamed. Only key/value pairs where the key is less than (or equal to) this option will be included in the range. Whenreverse=true
the order will be reversed, but the records streamed will be the same.'start', 'end'
legacy ranges - instead use'gte', 'lte'
'reverse'
(boolean, default:false
): a boolean, set true and the stream output will be reversed. Beware that due to the way LevelDB works, a reverse seek will be slower than a forward seek.'keys'
(boolean, default:true
): whether the'data'
event should contain keys. If set totrue
and'values'
set tofalse
then'data'
events will simply be keys, rather than objects with a'key'
property. Used internally by thecreateKeyStream()
method.'values'
(boolean, default:true
): whether the'data'
event should contain values. If set totrue
and'keys'
set tofalse
then'data'
events will simply be values, rather than objects with a'value'
property. Used internally by thecreateValueStream()
method.'limit'
(number, default:-1
): limit the number of results collected by this stream. This number represents a maximum number of results and may not be reached if you get to the end of the data first. A value of-1
means there is no limit. Whenreverse=true
the highest keys will be returned instead of the lowest keys.'fillCache'
(boolean, default:false
): whether LevelDB’s LRU-cache should be filled with data read.'keyEncoding'
/'valueEncoding'
(string): the encoding applied to each read piece of data.
FunctionName readWordToLevel
- Return <Promise>true
- Description 将文件读入数据库
- Param
name | type | require | default | Description |
---|---|---|---|---|
libPath | string | option | empty | 文件地址 |
type | string | option | ‘word’ | 词使用’word’,提问回答使用’qa’ |
FunctionName stringToLevel
- Return <Promise>true
- Description 将字符串导入数据库
- Param
name | type | require | default | Description |
---|---|---|---|---|
chunk | string | must | empty | 要导入的字符串 |
type | string | option | ‘word’ | 词使用’word’,提问回答使用’qa’ |
<a name=“question-answer-api”></a>
QuestionAnswer
FunctionName getQuestionList
- Return <Promise>questionObject
- Description 通过问句获取所有被碰撞中的问题和回答
- Param
name | type | require | default | Description |
---|---|---|---|---|
questionQuery | string | must | empty | 提问的语句 |
FunctionName getAnswer
- Return <Promise>beQuestion
- Description 通过问句获取最大可能的问题和回答
- Param
name | type | require | default | Description |
---|---|---|---|---|
questionQuery | string | must | empty | 提问的语句 |