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Prasanna Venkatesh Jayaprakash
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Open conversational ai framework for building contextual chatbots and ai assistants
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Build contextual chatbots with RASA framework
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 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 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com CHATBOT ARCHITECTURE
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 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 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com INTRODUCTION TO RASA CHATBOT ARCHITECTURE
7.
7 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com NATURAL LANGUAGE UNDERSTANDING - COMPONENTS Creating using Entity Intents Using RASA NLU Trainer
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 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 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com INTENTS - Intent of the person Interacting with the chatbot
11.
11 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com SLOTS - Recognized by chatbot and filled by the bot for further processing.
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 Copyright ©
2019 HCL Technologies Limited | www.hcltech.com TEMPLATES - Possible options for display To the used based on the Specific intent
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 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 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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