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Open conversational ai framework for building contextual chatbots and ai assistants

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Open conversational ai framework for building contextual chatbots and ai assistants

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Open conversational ai framework for building contextual chatbots and ai assistants

  1. 1. Copyright © 2019 HCL Technologies Limited | www.hcltech.com OPEN CONVERSATIONAL AI FRAMEWORK FOR BUILDING CONTEXTUAL CHATBOTS AND AI ASSISTANTS. BY - PRASANNA VENKATESH JAYAPRAKASH (PRASANNAVJ@HCL.COM)
  2. 2. 2 Copyright © 2019 HCL Technologies Limited | www.hcltech.com AGENDA Conversational AI Framework for building contextual chatbots and AI assistants.  Understanding Chatbot Architecture  Introduction to Current Chatbot Platforms and Industry Problem  Introduction to RASA Framework  introduction to RASA Chatbot Architecture  Natural Language understanding - Components  CORE Components and Structure.  Core - Stories and Dialog management  Integrating with External API  Demonstration using Restaurant Details capture details.  Demonstration integrating with Slack Messaging Platform.
  3. 3. 3 Copyright © 2019 HCL Technologies Limited | www.hcltech.com CHATBOT ARCHITECTURE
  4. 4. 4 Copyright © 2019 HCL Technologies Limited | www.hcltech.com INTRODUCTION TO CURRENT CHATBOT PLATFORMS AND INDUSTRY PROBLEM  Google dialogFlow  IBM  Microsoft  Amazon  Facebook  Industry problem:  To Implement the solution no inhouse platform.  All depend on cloud based learning solution – when enterprise plan to integrate might face problem due to the security and privacy concern of the providers.  Old rule based providers are phasing out  Solution:  Open Source conversational platform enable building and managing the complete chatbot inhouse – one such platform is RASA.
  5. 5. 5 Copyright © 2019 HCL Technologies Limited | www.hcltech.com INTRODUCTION TO RASA FRAMEWORK  Utilizes customizable ML and NLP solution to enable developers to control how and what they wanted to achieve part of the conversation.  Provide option to integrate with external API services, External databases etc.  Provide option to integrate with various prominent chatting/Messaging solution i.e: - Slack, faceBook messenger etc.  Provide both Open Source (RASA Stack) and Commercial Offering (RASA Platform)
  6. 6. 6 Copyright © 2019 HCL Technologies Limited | www.hcltech.com INTRODUCTION TO RASA CHATBOT ARCHITECTURE
  7. 7. 7 Copyright © 2019 HCL Technologies Limited | www.hcltech.com NATURAL LANGUAGE UNDERSTANDING - COMPONENTS Creating using  Entity  Intents  Using RASA NLU Trainer
  8. 8. 8 Copyright © 2019 HCL Technologies Limited | www.hcltech.com RASA CORE COMPONENTS AND STRUCTURE - DIALOG MANAGEMENT  Entity  Intents  Slots  Templates  Actions  Buttons
  9. 9. 9 Copyright © 2019 HCL Technologies Limited | www.hcltech.com ENTITY - Entity allows us to define the list of items that Need to be recognized by Chatbot while conversing
  10. 10. 10 Copyright © 2019 HCL Technologies Limited | www.hcltech.com INTENTS - Intent of the person Interacting with the chatbot
  11. 11. 11 Copyright © 2019 HCL Technologies Limited | www.hcltech.com SLOTS - Recognized by chatbot and filled by the bot for further processing.
  12. 12. 12 Copyright © 2019 HCL Technologies Limited | www.hcltech.com ACTIONS - Action to be carried out by Chatbot on specific input - Searching for restaurant - Connecting with back end Db etc.
  13. 13. 13 Copyright © 2019 HCL Technologies Limited | www.hcltech.com TEMPLATES - Possible options for display To the used based on the Specific intent
  14. 14. 14 Copyright © 2019 HCL Technologies Limited | www.hcltech.com DIALOG MANAGEMENT MODULE - STORIES  Stories - Potential option for conversation flow is detailed In the conversation.
  15. 15. 15 Copyright © 2019 HCL Technologies Limited | www.hcltech.com CONVERSATION EXAMPLE - DEMO  Demo of solution:  Video Link: https://www.youtube.com/watch?v=qi0o3jwMjvo&t=26s  Live demo will be conducted during the presentation session.  Starting from setting up the NLU  Setting up core  Integrating with Zomato API  Integrating with SLACK
  16. 16. 16 Copyright © 2019 HCL Technologies Limited | www.hcltech.com THANK YOU PRASANNA VENKATESH JAYAPRAKASH PRASANNAVJ@HCL.COM LINKEDIN – HTTPS://WWW.LINKEDIN.COM/IN/PRASANNA-VENKATESH-JAYAPRAKASH-454133A/ TWITTER - @PRASANNA_VRI

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