Little Window

Little window is a clever little cat chatbot that directs women to the information they are looking for as quickly as possible. Think of it like google search on turbo for all of Chayn’s resources and those provided by our friends too. We want to drastically reduce the time women take to search for information which in many cases can save lives.

Currently in active development

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Development

.env files

You will need to create a .env file in both the root directory and the client directory.

Client .env file

• SKIP_PREFLIGHT_CHECK=true

Root .env file

• PORT
• DATABASE_URL
• DIALOGFLOW_PROJECT_ID
• DIALOGFLOW_CLIENT_EMAIL
• DIALOGFLOW_PRIVATE_KEY
• ROLLBAR_TOKEN
• ROLLBAR_ENV
• STORYBLOK_TOKEN
• CONTENT_PREVIEW_MODE
• kickoffSupportMessageStoryblokId
• freeTextSupportRequestStoryblokId
• radioButtonSupportRequestStoryblokId
• resourceStoryblokId
• additionalResourcesStoryblokId
• anythingElseStoryblokId
• finalMessageStoryblokId

Running locally

Install dependancies npm install cd client && npm install

Create a postgres server locally and store it's URL in your root .env file. Migrations to populate the db will automatically run.

Run the server and the client separately, using only the following commands to ensure correct binaries are used. Server: npm run start or npm run start:dev Client: cd client && npm run start

Testing

Server: npm run test Client: cd client && npm run test

Formatting and Linting

Server: npm run format and npm run lint Client: cd client && npm run lint

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Architecture

Server

• NestJS
• Typescript
• PostgreSQL
• Typeorm
• DialogFlow for natural language processing
• Storyblok as CMS for conversation content
• Jest for testing

Client

• React

Deployment

• Heroku

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Conversation Structure

The Little Window conversation is structured into three distinct sections.

1. Setup All of the questions required to setup the conversation including GDPR & Language settings. These must be set before we can deliver any more content to the user.
2. Support The bulk of the conversation. This is where Little Window determines what the user wants and sends them relevant resources. Little Window determines what the user wants via either NLP or directly offering a selection of it's knowledge.
3. Feedback At the end of the conversation we collect feedback to improve Little Window with four questions.

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Support Us

Little Window is created by Chayn a global volunteer network with over 400 volunteers from 15 countries. If you like what you see and you want to join our team of volunteers get in touch. Or you can donate; all proceeds go to improving Little Window and building more tools and resources at ChaynHQ.