Rasa是一套对话机器人的开源框架，主要用于构建面向任务（Task Oriented）的对话系统。
NLU自然语言理解
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基于规则
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神经网络方法
DIET(Dual Intent Entity Transformer)
在Rasa中两种方法都可以使用，但神经网络方法是核心
一个rasa项目包含的文件：
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domain
包含了聊天机器人需要知道的所有东西
- Responses: these are the things the assistant can say to users
- Intents: These are categories of things users say
- Slots: These are variables remembered over the course of a conversation
- Entities: these are pieces of information extracted from incoming text
- Forms and Actions: These add application logic and extend what your assistant can do
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Stories
training data to teach your assistant what is should do next
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Rules
a way to describe short pieces of conversations that always go the same way
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config
- language 指定机器人使用的语言
- pipeline 定义用于检测意图和实体的步骤
- policies 指定如何响应用户输入的对话管理技术
Do
- Use actual user conversations as stories
- Have small stories that aren’t full conversations
- Use rules for one-off interactions(checking account balance, checking if this is a bot)
Don’t文章来源：https://www.toymoban.com/news/detail-480299.html
- Use rules for multi-turn interactions
- Use OR statements and checkpointing often
- Write out every possible conversation flow start to finish
- Delay user testing
Rasa style CDD:文章来源地址https://www.toymoban.com/news/detail-480299.html
- You only need to start with the most popular, important intents & a way to handle things outside them
- Continue to build from there if that’s what users need
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