Skip to content

Latest commit

 

History

History
100 lines (54 loc) · 2.82 KB

README.md

File metadata and controls

100 lines (54 loc) · 2.82 KB
Raw

ViennaChatBot

This is a project for the course "Open Data & Data Ethics" at University of Applied Sciences Technikum Vienna.

The bot is called @vienna_service_bot and can be added in Telegram private chats and group chats.

Starting the bot with /start Next city bike station
small-corrPlot small-corrPlot

Members: Nils Bauroth, Sigrid Huemer, Linus Schneider

Goal: creating a Telegram chatbot which lists you interesting points in Vienna near your location. Think of it like a “Vienna Service” Bot. You can list ViennaCityBikes near you or drinking fountains, public toilets etc

Used Data: It may be that we do not manage to include all the datasets, but those are the ones we are interested in (checked boxes are implemented):

  • ViennaCityBikes
  • Public Toilets
  • Drinking Fountains
  • Cool Streets
  • Recycling places

Tech Stack:

  • Telegram BotFather
  • Telegraf.js (Telegram Bot Framework)
  • Node.js (JavaScript)
  • Redis Database
  • Google Firebase deployment possible (see branch firebase)

Have a look at our Wiki for more information about the project and the deployment steps.

Running the application

1. Create a .env file

You need two environment variables (.env file inside the root directory).

You can get the telegram bot token by creating a bot with Telegram Botfather (Telegram: How do I create a bot).

The redis user password can be retreived from your created free database (e.g. on https://redislabs.com/ - it's free).

For geocoding addresses (address <-> coordinates) we use the service from https://opencagedata.com.

BOT_TOKEN=<YOUR_TELEGRAM_BOT_TOKEN>
REDIS_PASSWORT=<YOUR_REDIS_USER_PASSWORD>
OPENCAGE_API_KEY=<YOUR_OPEN_CAGE_KEY>

2. Start the application (with Docker)

The application also runs with Docker. Run this command: docker compose up -d (with Compose V2) or docker-compose up -d

2. Start the application (without Docker)

First install all required libraries with

npm install

Then start the app with

npm run start

Building the application for production

You can build the application with

npm run build

This creates a dist folder with the babel-transpiled files.

After that, run

npm run start:prod

to run the files from the dist folder.