Artspiration API

The backend portion of a fun online application to rate and find cool artwork!

About The Project • Tools Used • Set Up • Installation • How To Use • Database Schema • Contributing • Acknowledgements

About The Project

The backend of Artspiration consumes the Artsy API and Google Cloud Vision API to power a recommendation engine that connects users with exciting artwork based on their preferences. We expose endpoints that package up this material for frontend consumption to display to our users as a web application.

Learning Goals

• Using an Agile process throughout development
• Setting up continuous integration and continous deployment
• Using project management tool Github Project
• Demoing project ot project manager
• Building a backend API for frontend consumption
• Consuming endpoints and manipulating the JSON responses
• Handling large group dynamics with short 3 day sprints
• Working with Machine Learning outputs and implementing into app
• Consuming Google Cloud Vision API

Tools Used

Development	Testing	Gems
Ruby 2.7.2	RSpec	Pry
Rails 5.2.5	WebMock	ShouldaMatchers
JSON	VCR	Faraday
Atom	SimpleCov	Figaro
Github	FactoryBot	FastJSON
TravisCI	Faker
Heroku

Set Up

1. To clone and run this application, you'll need Ruby 2.7.2 and Rails 2.5.3. Using rbenv you can install Ruby 2.7.2 (if you don't have it already) with:

rbenv install 2.7.2

2. With rbenv you can set up your Ruby version for a directory and all subdirectories within it. Change into a directory that will eventually contain this repo and then run:

rbenv local 2.7.2

You can check that your Ruby version is correct with ruby -v

3. Once you have verified your Ruby version is 2.7.2, check if you have Rails. From the command line:

rails -v

4. If you get a message saying rails is not installed or you do not have version 5.2.5, run

gem install rails --version 5.2.5

5. You may need to quit and restart your terminal session to see these changes show up

Installation

1. Get a free API Key at Artsy API
2. Get a free (with limits) Google Vision API KEY by following directions here
3. Fork this repo
4. Clone your new repo

   git clone https://github.com/#{your_github_username}/ArtspirationBE.git

5. Install gems

   bundle install

6. Install figaro

   bundle exec figaro install

7. Enter your API KEYS in application.yml

   artsy_api_key = <ENTER YOUR API KEY>
   google_api_key = <ENTER YOUR API KEY>
   key = <ENTER YOUR API KEY>

8. Setup the database

   rails db:create
   rails db:migrate

How To Use

The Artspiration Backend can be used to retrieve user preferences for artwork, as well as make calls to the Artsy API for specific artwork information including: title, artist, image(jpg). The backend can also provide daily recommendations for a piece of art based on past user preferences. Preferences are generated through label and image properties determined by the Google Cloud Vision API. The recommendation engine is built using a combination of collaborative filtering as well as sorting through the saved user preferences.

Endpoint Documentation

User Endpoint
Request: /api/v1/users/:id

Response:

{
  "data": {
  "id": "133",
  "type": "user",
  "attributes": {
    "name": "Melanie Swaniawski",
    "email": "shameka_goyette@bartell.co"
    }
  }
}

Recommeded Art Endpoint
Request: /api/v1/users/:id/recommendations

Response:

{
  "data": [
    {
      "id": 168,
      "type": "recommended_art",
      "attributes": {
        "title": "Virgin of the Rocks",
        "image": "https://d32dm0rphc51dk.cloudfront.net/Jv-e1fhDjg61OYhhsMoiQg/{image_version}.jpg",
        "user_id": 133
      }
    }
  ]
}

Rated Art Index Endpoint
Request: /api/v1/users/:id/rated_arts

Response:

{
  "data": [
      {
        "id": 175,
        "type": "rated_art",
        "attributes": {
          "title": "La Grande Odalisque",
          "image": "https://d32dm0rphc51dk.cloudfront.net/crVj8GvGliFrpExNfHWl4Q/medium.jpg",
          "liked": true,
          "user_id": 145
        }
      },
      {
        "id": 184,
        "type": "rated_art",
        "attributes": {
          "title": "L'Embarquement pour Cythère (The Embarkation for Cythera)",
          "image": "https://d32dm0rphc51dk.cloudfront.net/Ux_L_UKjxgR-gJ6XZYVgVg/medium.jpg",
          "liked": true,
          "user_id": 145
        }
      }
   ]
}

Rated Art Show Endpoint
Request: /api/v1/users/:id/rated_arts/:art_id

Response:

{
  "data": {
    "id": 106,
    "type": "rated_art",
    "attributes": {
      "title": "The Tête à Tête",
      "image": "https://d32dm0rphc51dk.cloudfront.net/5KJ7_u7BPqeltkfEnyijIw/medium.jpg",
      "liked": true,
      "user_id": 145
    }
  }
}

Database Schema

Contributing

👤 Jacob Piland

• GitHub
• LinkedIn

👤 Marla Schulz

• GitHub
• LinkedIn

👤 Kim Abcouwer

• GitHub
• LinkedIn

👤 Jason Knoll

• GitHub
• LinkedIn

👤 Alex Klick

• GitHub
• LinkedIn

👤 Dee H

• GitHub
• LinkedIn

Acknowledgements

• Turing School of Software and Design
  • Project created for completion towards Backend Engineering Program
• Artsy API
• Google Cloud Vision API