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jatin7gupta/machine_learning_chatbot

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About

The front end uses Angular for UI. The backend consists of three microservices. Dentist Service which handles information about dentists. Timeslot service which handles all the reservations. Chatbot service talks to the frontend and takes the decision to get data from different services, translates JSON into human-friendly statements. Utterances are trained and parsed by WIT.AI

Requirement

  • Node
  • Python3
  • Docker

Install frontend, type in root project:

$ cd chatbot-ui
$ npm install

Run frontend

$ npm start

Install Backend:

Install and run chatbot service, type in root project

$ cd chatbot
$ python3 -m venv ./venv
(*nix) $ source ./venv/bin/activate | (windows) venv\Scripts\activate
$ cd chatbot-app
$ pip3 install -r requirements.txt
$ cd chatbot-service
$ python3 __init__.py

Chatbot service app will run on port 5000

Install and run denstist service, type in root project

$ cd dentist
$ docker build -t dentist:latest .
$ docker run -p 5001:5000 -t dentist:latest

Dentist service app will run on port 5001 for local system

Install and run timeslot service, type in root project

$ cd timeslot
$ docker build -t timeslot:latest .
$ docker run -p 5002:5000 -t timeslot:latest

Timeslot service app will run on port 5002 for local system

Note: python3 may refer to python in your system

This service is dependent on WIT.AI and its token to work. You also need to train your own WIT.AI uttrances. This boilerplate project will only give you a structure to work with.

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