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[VFS 2019] Building chatbot with RASA


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Chatbot is now one of the most popular applications of AI so how to build one will be a questions attracting a lot of attention

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[VFS 2019] Building chatbot with RASA

  1. 1. Building chatbot with RASA Nguyễn Chiến Thắng, Mì AI Blog Vietnam Frontier Summit 2019
  2. 2. — Dave Waters “Machine learning will automate jobs that most people thought could only be done by people.”
  3. 3. About Mì AI
  4. 4. What is this? It’s math in Ai, ML and DL Source: Andrew Ng
  5. 5. - Founded in August 5th, 2019 - A place to share and help each other learn AI - Learning AI in the style of “instant noodles”
  6. 6. 7,000 users | 25,000 views Fanpage Mì AI Blog: 1,300 likes Group Mì Ai: 1,500 members Youtube Mì AI: 3,500 views
  7. 7. Building chatbot with RASA
  8. 8. 8 1. What is Chatbot? ● A chatbot is a piece of software that conducts a conversation via auditory or textual methods. (Wikipedia) or ● A chatbot is an artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone.
  9. 9. 9 2. What is RASA? RASA stack is an open-source AI tool and being an opensource framework, It is easy to customize.
  10. 10. - Rasa NLU: A natural language understanding solution which takes the user input and tries to infer the intent and extract the available entities.
  11. 11. “Hello” - Intent: Greeting - Entities: None “What day is today?” - Intent: find_day - Entities: today “I want to order a book?” - Intent: goods_order - Entities: book
  12. 12. ## intent:greet - Hi - Hey ## intent: goods_order - I want to order a [book](product) - I want to buy a [mobile](product) ## intent:bye - Bye - Goodbye Build NLU file and train RASA NLU
  13. 13. - Rasa Core: A dialog management solution tries to build a probability model which decides the set of actions to perform based on the previous set of user inputs.
  14. 14. - Actions: An operation which can be performed by the bot. It could be replying something in return, querying a database or any other thing possible by code. - Stories: Sample interaction between the user and bot, defined in terms of intents captured and actions performed.
  15. 15. ## Ask for goods * greet - utter_greet * goods_order{”product":”book"} - utter_answer_book * goods_order{”product":”mobile"} - utter_answer_mobile * goods_order{”product":”tissue"} - utter_answer_dont_have * bye - utter_bye Build Stories file and train RASA Core
  16. 16. More details at:
  17. 17. Does anyone have any questions? email: website: THANKS!