Getting Started
Configuring channels
Authoring conversations
Conversational interactions
Natural language understanding
Server installation
Custom ActionsExtending RasaContributing to BotfrontInstallRunDocumentationRunning and writing testsUsing the loggerCreating a logger

Contributing to Botfront

If you wish to contribute to Botfront or to make custom changes, here is the recommended way to install and run it on your local machine.


  1. Botfront is a Meteor app, so the first step is to install Meteor
  2. Then clone this repo and install the dependencies
git clone
cd botfront/botfront
meteor npm install

Don't run tests if you have valuable data in your DB

Meteor comes with its own Node.js and NPM. When installing dependencies, it is better to use the Meteor NPM by running meteor npm install than using your local one (npm install)


Since Botfront is made of several services you need to start all other services with docker-compose from a regular project.

  1. Create a Botfront project with botfront init (not in the repo, anywhere else on your machine)
  2. Start your project with botfront up -e botfront. This will run all services except the Botfront app, since you are going to run it with Meteor locallyé
  3. Reset meteor from Botfront root folder with meteor reset (this will wipe the database).
  4. Run Botfront with meteor npm run Botfront will be available at http://localhost:3000


The documentation is located in the botfront/docs folder. If you wish to edit the doumentation and preview your changes your can run the documentation on your machine with npm run docs:dev.

If you need to build it: npm run docs:build

The docs are built with Vuepress

Running and writing tests

You can run our integration test suite with npx cypress run or interactively with npx cypress open

Don't run tests if you have valuable data in your DB

The test suite starts by testing the setup process and will wipe the database.

Using the logger

When contributing you will most certainly need to log some information. Under the hood, we use Winston. You can create an instance of a logger with one of the helper functions found here. We use one logger instance per file and one per method.

The logging is only done on the server-side part of the application. Our logger supports 4 severity levels:

  • error
  • warn
  • info
  • debug

You can also add metadata to the log statement to provide more details. However, we limit the metadata you can log to:

  • userId (prefilled by helper)
  • file (prefilled by helper)
  • method (prefilled by helper)
  • url
  • data
  • args (prefilled by helper)
  • params
  • status
  • error

If you already have access to a logger instance in your method, here is a quick extract of the winston doc showing usage. Otherwise, refer to Creating a logger

level: 'info',
message: 'Hello log files!'
// Same as the previous statement'Hello again logs');
// a logging statement with metadata'Everything is alright !', {status: 200});
logger.error('Oh no, something went wrong', {status: 500});

Log statement are formated as follows. Empty fields do not appear.

<timestamp> [<level>] : <message> user: <userId> <file> - <method> with <args> <status> url: <url> params: <params> data: <data> error: <error>

For example, it looks like this

2020-02-14T17:23:28.025Z [info] : Training project bf... user: Hv45jp24J7i3ncaZW /imports/api/instances/instances.methods.js - rasa.train with {"projectId":"bf","instance":{"_id":"vcS4JMdx4LTTr9T65","name":"Default","host":"http://rasa:5005","projectId":"bf","type":"server"}}

Creating a logger

To create a logger instance we have three helper functions, getAppLoggerForFile, getAppLoggerForMethod and addLoggingInterceptors

import {
} from 'botfront/server/logger.js'; // change to yours

If you want to see some real usage you can look into the botfront/botfront/imports/api/instances/instances.methods.js file

Here are the details for each function.


This method will create a logger for the whole file, it just creates a logger with the file metadata prefilled

  • filename: the name of the file your logging from, should be __filename most of the time

the returned instance will most likely be used in the next method. It’s very unlikely that you log using this instance.

getAppLoggerForMethod(fileLogger, method, userId, callingArgs)

This method will create a logger for a specific method, and it is from this one that you will get the instance for logging

  • fileLogger: an logger instance previously created with the above function
  • method: the method name your are in
  • userId: userId, most of the time it will be Meteor.userId()
  • callingArgs: arguments used to call the method you are in
const filelogger = getAppLoggerForMethod(__filename);
const aMethod = (a,b) => {
const methodLogger = getAppLoggerForMethod(fileLogger, 'aMethod', Meteor.userId(), {a,b});'Stated to work')
// 2020-01-01T12:00:00.00Z [info] : Stated to work user: user1 .../example.js - aMethod with {a: 'a', b: 'b'}

addLoggingInterceptors(axiosClient, logger)

This helper is specificatly designed to be used with axios, and it will log at request time and response time.

  • axiosClient: the instance of axios that you want to log data from created throught axios.create()
  • logger: an instance of a logger created throught getAppLoggerForMethod
const logger = getAppLoggerForMethod(...);
const client = axios.create();
addLoggingInterceptors(client, logger);, payload); // this call will create reponse and request logs
🖊️ Edit this page on Github