Audience
This documentation describes the features of Live Chat Sentiment Analysis Accelerator for B2C Service and provides the configuration steps required to implement it.
This document is intended for software developers or similar technical roles interested in implementing Live Chat Sentiment Analysis Accelerator experiences that leverage the Oracle B2C Service and OCI Data Science.
Live Chat Sentiment Analysis Accelerator customization requires an experience level of technical know-how to implement. You should have the following skills to understand the topics discussed in this guide:
| Toolkit | Skill | Skill Level | Comments |
|---|---|---|---|
| Python | Intermediate/Advanced | OCI jobs for fetching, training, and deploying model is developed in Python. | |
| PHP | Intermediate/Advanced | Custom Process Model (CPM) scripts used in B2C Service Cloud side are developed in PHP. | |
| Terraform | Intermediate/Advanced | Automation of creating OCI resources and OCI jobs is achieved using Terraform. | |
| Type Script | Intermediate/Advanced | Agent Insight customization is done using Type Script. | |
| All | Oracle Cloud Infrastructure | Intermediate | Required for configuration of Incident classifier. |
| All | Oracle B2C Service | Intermediate | Option for providing Service Request (SR) functionality to the Incident classifier. |