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Scalable Open Source Chatbot Platform. Build multiple Chatbots with NLP, Behavior Rules, API Connector, Templating. Developed in Java, provided with Docker, orchestrated with Kubernetes or Openshift.

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README.md

E.D.D.I

Scalable Open Source Chatbot Platform. Build multiple Chatbots with NLP, Behavior Rules, API Connector, Templating. Developed in Java, provided with Docker, orchestrated with Kubernetes or Openshift.

v4.8.3 - STABLE

License: Apache License 2.0

Visit here for further references about the project.

For professional support, check out: here

Check out the full documentation here.

Codacy Badge CircleCI

Why choose E.D.D.I over other technologies

We have asked that question to our users and here are some reasons they mentioned

  • it is open source 💚
  • the configuration is extremely open and flexible
  • the code is self-explanatory and easy to extend
  • eddi is channel independent, therefore can be used anywhere
  • the (NLP) parser is extremely cool
  • the framework is focused and does not pretend to be the magic bullet that solves it all
  • great tech stack, when you want to build a chatbot product yourself

Intro

The Chatbot System - E.D.D.I (Enhanced Dialog Driven Intelligence), has been developed with the focus on the use in enterprise applications as well as the ease of connecting it to other resources (such as databases or other Services).

This platform has been developed for over many years and completely restructured from scratch four times because of logical "dead ends" in the art of building chatbots - thus version 4.

The most outstanding features are:

  • Flexible in NLP and Behavior
  • Fluently connect to REST APIs
  • Powerful Templating
  • Reuse Conversation Flows in multiple bots

technical spec:

  • Resource- / REST-oriented architecture
  • OAuth 2.0 / Basic Authentication
  • Java
  • JAX-RS
  • Dependency Injection
  • Embedded Jetty
  • NoSQL
  • HTML, CSS, Javascript, JSON

Prerequirements

  • Java 11
  • Maven 3
  • MongoDB >3.5

Build project with maven

Go to the root directory and execute

mvn clean install

Start Servers

  1. Setup a local mongodb (> v3.0)

  2. launch with VM options

     -DEDDI_ENV=[development/production] -Duser.dir=[LOCAL_PATH_TO_EDDI]\apiserver ai.labs.api.ApiServer
    
  3. Go to Browser --> http://localhost:7070

Note: If running locally inside an IDE you need lombok to be enabled (otherwise you will get compile errors complaining about missing constructors). Either download as plugin (e.g. inside Intellij) or follow instructions here https://projectlombok.org/

Docker

For development, use

docker-compose -f docker-compose.yml -f docker-compose.local.yml up

after running mvn package. This builds a local image of EDDI.

For integration testing run

./integration-tests.sh

or

docker-compose -f docker-compose.yml -f docker-compose.local.yml -f docker-compose.testing.yml -p ci up -d

For running in cloud (with authentication), check: https://hub.docker.com/r/labsai/eddi

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