WeChat 0.1.4 release - open source enterprise IM and online customer service system based on AI

Source: contribution
Author: Code sum
2024-05-27 08:55:00

Open source enterprise IM and online customer service system based on AI.

language

introduce

Enterprise instant messaging/IM

  • Multi tier organizational structure
  • Role management
  • Permission management
  • Chat record management

Online Service

  • Support multi-channel, multiple routing strategies and detailed assessment indicators
  • Seating workbench
  • Work order system
  • Agent management
  • Data Kanban
  • Artificial knowledge base
  • Skill group management
  • Real time monitoring
  • Announcement
  • Sensitive words
  • CRM、
  • Report function,
  • Provide customers with integrated customer service workbench services

Big model AI assistant

  • More suitable for team use, one person configuration, company wide use

LAN file transfer

  • No need to log in, no need to connect to the Internet, and use WiFi/hotspot to transfer files across platforms

Quick Start

 #Note: This open source version is at an early stage, many functions have not been perfected or tested, and the documentation is still to be perfected. Do not use it in the production environment
 git clone  https://github.com/Bytedesk/bytedesk.git
 #Configuration file: bytedesk/starter/src/main/resources/application-dev.properties
 cd bytedesk/starter
 mvn spring-boot:run
 #Package the jar and run it:
 cd bytedesk/starter
 mvn package -Dmaven .test.skip = true
 java -jar bytedesk-starter-0.0.1-SNAPSHOT.jar
 #Background operation
 nohup java -jar bytedesk-starter-0.0.1-SNAPSHOT.jar
 #
 #Local Preview
 Developer Portal: http://localhost:9003/dev
 web:  http://localhost:9003/
 Management background: http://localhost:9003/admin , User name: admin@email.com , password: admin
 WebIM/customer service: http://localhost:9003/chat , User name: admin@email.com , password: admin
 Guest dialog window: http://localhost:9003/v
 Api documentation: http://localhost:9003/swagger -ui/index.html
 actuator:  http://localhost:9003/actuator
 H2 database: http://localhost:9003/h2 -Console, path:/ h2db/weiyuim,  User name: sa, password: sa
 

file

preview

Management background

organization customer service ai

Desktop Client

Sign in dialogue mail list set up

Online customer service - visitor SDK

Client&customer service

Technology stack - based on financial cloud native architecture

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