pmnlp

说明

支持中文语句的模版匹配。可以理解为，简单版本的百度unit或者科大讯飞的AIUI

对于，简单语句的自然语言理解也是很方便的。欢迎大家试用。

对于不喜欢调用API，喜欢在自己代码中嵌入的人是蛮好用的。

用例

```
from pmnlp.word import build_sentence_word_dict
from pmnlp.sentence import SentenceTplTrie

# 初始化，用于记录用户配置的词槽，以及语句的模版匹配。
user_word_dict = {'num': ['一杯', '两杯'], 'coffee': [
    '拿铁', '拿铁咖啡'], 'common': [], 'phone': ['re\d+']}
sentent_intent_tpl = {
    'coffee': '[common:0-4][num][common:0-10][coffee]'
}

# 建立模型
sentence_word_dict = build_sentence_word_dict(word_dict=user_word_dict)
test_tree = SentenceTplTrie(word_dict=sentence_word_dict)
test_tree.build(sentence_tpl_dict=sentent_intent_tpl, common_key='common')


# 理解用户输入
_, intent, result = test_tree.sep('我要一杯热啊啊啊啊啊啊拿铁咖啡',common_key='common')
if isinstance(intent, str):
    print(intent, result)
else:
    print(intent, result)
```

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