I call it “backend” but it is usually the traditional pair Step 2: Build a chatbot with DialogFlowĭialogFlow is a Google platform for Natural Language Processing (NLP) -say the equivalent of SAP Conversational AI in our landscape. Your backend is reached by the fulfillment server, through Cloud Connector.Connectivity to your backend is enabled through Cloud Connector, acting as a kind of reverse proxy between your private network and SAP Cloud Platform.These functionalities must be exposed as REST services to the outside world, so you may add another layer with API Management to expose, monitor consumptions, manage authorizations, etc. Natural Language Processing (NLP) remains in SAP CAI, but whenever some information is needed from your backend S/4, this is where connexion happens. The fulfillment server is where some parts of the business intelligence take place.This is done through “webhooks”: SAP CAI will call REST services hosted in a “Fulfillment Server” From time to time it will need to “request” information/action to your backend. SAP Conversational AI -we will call it CAI– is available as a SaaS, somewhere in the outside cloud.In case of on-premise, “standard” architecture to integrate with SAP Conversational AI is as follows (credits to this tutorial for the picture that I have modified): Here is a preview of the expected result:
Step3: Implement chatbot business logic in Firebase Cloud Function.I will describe the steps to build a simple chatbot for Google Hangout Chat to lookup for business partners in S/4HANA: I have tried to simplify as much as possible the approach and have considered some simplified assumptions. I would like to share my own variant of chatbot integration. I have recently read a couple of blog posts from Sudip Ghosh, and I found them really inspiring.
0 kommentar(er)
