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This diagram shows the percentages of websites using various top level domains among the sites that use Name Hero. See technologies overview for explanations on the methodologies used in the surveys. How to read the diagram: .com is used by 69.4% of all ...

Distribution of top level domains among websites that use Name Hero

This diagram shows the percentages of websites using Name Hero broken down by top level domains. See technologies overview for explanations on the methodologies used in the surveys. How to read the diagram: Name Hero is used by less than 0.1% of all the ...

Usage of Name Hero broken down by top level domains

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NameHero.com

namehero

Hey hey heyyyyyy! Here’s a quick article on how to have beauty link previews, just like Dev.to does. You're gonna get something like this: Yup, was being literal with the " " 😛 I've built something similar for my new project workby.io, and here's how I did it... like dev.to Almost every guide that I found was using , in fact, uses it. It's pretty popular and efficient, BUT, I don't want to pay $14 bucks for each 1k image 😂🐁 htmlcsstoimage.com dev.to So, I'm going to use : A ruby gem to transform HTML into PDFs, PNGs, or JPEGs using Google Puppeteer and Chromium. Grover If you want to build this with, let's say, Node.js, you can also follow me. Puppeteer is popular and easy to use. We're going to build an HTML view and take a screenshot of it. Long story short: You can create a blank Rails project, or just add additional functionality to your current app. Setup Install Grover gem with bundle add grover And the dependency of Grover, , with: Puppeteer yarn add puppeteer Then create an empty controller where you can respond with different link preview templates: rails g controller og-imager dev_to In the action, let's call Grover and let him do the magic dev_to app/controllers/og_imager_controller.rb class OgImagerController < ApplicationController
  # GET /og_imager/dev_to
  # @param {string} title
  # @param {string} avatar
  # @param {string} username
  # @param {string} timestamp
  # @param {array} logos
  # @returns image/png
  def dev_to
    # Get params and set to variable
    # TODO: Retrieve your object instead :p
    @title = params[:title]
    @avatar = params[:avatar]
    @username = params[:username]
    @timestamp = params[:timestamp]
    @logos = params[:logos]

    # Grover.new accepts a URL or inline HTML and optional parameters for Puppeteer
    grover = Grover.new(
      render_to_string
    )

    # Get a screenshot
    png = grover.to_png

    # Render image
    send_data(png, type: 'image/png', disposition: 'inline')
  end
end Here's our view, just simple HTML/CSS app/views/og_imager/dev_to.html.erb <div class="container">
  <div class="card">
    <h1 class="title">
      <%= @title %>
    </h1>
    <div class="details">
      <div class="user">
        <img src="<%= @avatar %>" class="avatar">
        <p class="username">
          <%= @username %> - <%= @timestamp %>
        </p>
      </div>
      <div class="logos">
        <% @logos.each do |logo| %>
          <img src="<%= logo %>" class="logo">
        <% end %>
      </div>
    </div>
  </div>
</div>

<style>
  @import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;500&display=swap');

  *{
    font-family: 'Roboto', sans-serif;
    color: #cd685f;
  }

  .container{
    width: 1128px;
    height: 600px;
    display: flex;
  }

  .card{
    display: flex;
    justify-content: space-between;
    flex-direction: column;
    margin: 2.8rem 4rem 4rem 2.8rem;
    border: 3px solid #c56b61;
    border-radius: 25px 25px 0px 0px;
    box-shadow: 7px 10px 0px 1px #c56b61;
    padding: 3.8rem 1.8rem 1.8rem 1.8rem;
  }

  .title{
    margin: 0px;
    font-weight: 500;
    font-size: 5rem;
    line-height: 80px;
  }

  .details{
    display: flex;
    justify-content: space-between;
  }

  .user{
    display: flex;
    align-items: center;
  }

  .avatar{
    border: 3px solid #c56b61;
    width: 50px;
    height: 50px;
    border-radius: 50%;
    margin-right: 10px;
  }

  .username{
    margin: 0;
    font-size: 2.5rem;
  }

  .logos{
    display: flex;
    justify-content: space-between;
  }

  .logo{
    width: 60px;
    height: 60px;
    margin-left: 20px;
    transform: rotate(5deg);
  }
</style> And finally, create an initializer to set our Browser viewport (final image size). initializers/grover.rb Grover.configure do |config|
  config.options = {
    viewport: {
      width: 1128,
      height: 600
    },
  }
end If you have created a blank project, and want to use this as a micro-service, here's a guide on how to deploy this thing to Heroku. Create the app on your Heroku account (I'm assuming you already have the cli installed): heroku create your_app_name Warn Heroku of our JS library (Puppeteer): heroku buildpacks:add heroku/nodejs --index=1 And also help him to setup Puppeteer dependencies 😛: heroku buildpacks:add jontewks/puppeteer --index=2 Tell Grover to run Puppeteer in the "no-sandbox": heroku config:set GROVER_NO_SANDBOX=true To make use of this image on the link preview, you will need . Just simple meta tags that browsers will look for. The Open Graph protocol Meta tags are always on <head> so, app/views/layouts/application.html.erb <%= yield(:head) %> And then ask ERB to fill the previous block with <%= content_for :head do %>
  <meta property="og:title" content="<%= @article.title %>">
  <meta property="og:image" content="<%= article_link_preview(@article) %>">
  <meta property="og:image:type" content="image/png" />
  <meta property="og:image:width" content="1128">
  <meta property="og:image:height" content="600">
  <meta name="twitter:card" content="summary_large_image" />
<% end %> at your details view. Like: /articles/:id The thing it's because they are fancier on link previews, you can read more about that twitter:card here The previous method it's a simple helper that generates the URL that we are looking for. article_link_preview app/helpers/articles_helper.rb def article_link_preview article
  uri = URI.parse('https://your_app_name.herokuapp.com/ogimage')
  uri.query = URI.encode_www_form(
    title: article.title,
    'images[]': article.tags.collect(&:image),
    timestamp: article.created_at.to_formatted_s(:short),
    ...
  )
  uri.to_s
end You will get something like this: https://your_app_name.herokuapp.com/og_imager/dev_to?title=Real%20Time%20Notification%20System%20with%20Hotwire,%20in%20Rails%207&avatar=https://dev-to-uploads.s3.amazonaws.com/uploads/user/profile_image/369241/a0111bcb-a046-4398-98cd-f4cf0e2f8d0d.png&username=Matias%20Carpintini&timestamp=13%20April&logos[]=https://img.icons8.com/office/80/000000/ruby-gemstone.png&logos[]=https://practicaldev-herokuapp-com.freetls.fastly.net/assets/devlogo-pwa-512.png Here's the of the whole thing. repo This article was first published here.

Generate Fancy Link Previews With Rails 7

YAML: literally meaning “Yaml ain’t markup language” can mess you up in the beginning. Rails generates this file for you and you have to change it for Heroku. YAML spacing has to be exact and it’s important to know a tab is not the same as four spaces. Here is the obligate to read more.  Just know you will have to add this to your database.yml file. My tip is to ensure your spacing matches the development: section above. YMAL tutorial #  production:
#    url: <%= ENV[ ] %>
production:
  <<: * url: <%= ENV[ ] %>
#username: tempGradientRailsJsonAPIJS
#password: <%= ENV[ ]%> 'DATABASE_URL' default 'DATABASE_URL' 'TEMPGRADIENTRAILSJSONAPIJS_DATABASE_PASSWORD' : This is easy just use [your apps name] + .herokuapp.com. So gave me my saved cities in my database. This makes sense as in my rails routes I have: Endpoints https://boiling-forest-global-warming.herokuapp.com/cities.json get , '/cities.json' to: 'cities#index' [your apps name].herokuapp.com === ‘/’ in terms of endpoints. This is your index. Rails/Rake commands Heroku honors most rails/rake commands. On the Heroku dashboard you can open a console and run rake db:seed for example and put your seeded data into the database. This is the entire reason I wrote this article because there are many resources telling you how to drop your Heroku database online. To do so you need the Heroku dashboard HEROKU DOES NOT LET YOU DROP YOUR TABLE. THERE IS NO rake db:drop ALLOWED. and open your database directly. It will have three options for you. This is if you need to drop your database and you can just . click reset FULL TEXT ARTICLE: includes designing and coding out a full stack Ruby on Rails REST api with a JavaScript front end. That’s fine while you are testing your localhost:3000 endpoints and even getting data from a 3rd party API(openweathermap). I wrote about this . Development here: Development of Boiling-Forest could mean many different things. Let's ask Wikipedia: . Okay that is perfect because just it is just like Computer Science; confusing and not really for human eyes. I’ll use “Putting a site live on the Web” as our definition for production. Heroku is a cloud based platform that will host your application live on the web for you. Under the hood Heroku uses AWS and will take your code, package it, modify it, and spin up a live working version. There is a lot you have to do going from localhost:3000 to https//your-heroku-app/herokuapp.com. Production production in computer science you need to get your database.yml file in order. First When you first generated your rails app it created a lot for you. This includes the database.yml file which contains sections: default: development: test: production: YAML cannot have any extra spaces(no white space) which will crash your Heroku app. Rails does a fairly good job having it almost ready. The only adjustment will be adding and removing a few parts of the production section. The file itself has a comment on this exactly as follows: # On Heroku and other platform providers, you may have a full connection URL # available as an environment variable. For example: # #   DATABASE_URL="postgres://myuser:mypass@localhost/somedatabase" # # You can use this database configuration with: # #  production: #    url: <%= ENV['DATABASE_URL'] %> Literally make your production section exactly that and only that. No extra white space and no extra password or username variables. <%= %> production: <<: *default url: ENV[ ] 'DATABASE_URL' There should be two indent spaces under the production: Once you have database.yml file hooked up to hit the proper production database you are going to need to adjust your endpoints. Endpoints are essentially the URL/URI of the resources you want. The the telephone number of the friend you want to call or your address when you want to go home; This is where you want to go. In development you were hitting localhost:3000. Now that you are going into production you are no longer hitting your local server running on your local machine. This is actually easier than most help articles indicate and it makes sense. Your endpoint is going to be your-apps-name.herokuapp.com. This is the equivalent of ‘/’. So my endpoint was https://boiling-forest-global-warming.herokuapp.com. I did a little trial and error and put https://boiling-forest-global-warming.herokuapp.com/cities.json in the address bar of my browser. What did I get in return? [{ : , : , : , : , : , : },{ : , : , : , : , : , : },{ : , : , : , : , : , : },{ : , : , : , : , : , : },{ : , : , : , : , : , : }] "id" 1 "name" "Phoenix" "region" "southwest" "created_at" "2020-10-27T13:43:21.239-07:00" "updated_at" "2020-10-27T13:43:21.239-07:00" "fetchURL" "https://api.openweathermap.org/data/2.5/weather?q=Phoenix,us&units=imperial&APPID=fe2a775f427aa5fc92ce0379937b9ee9" "id" 2 "name" "Columbus" "region" "Midwest" "created_at" "2020-10-27T13:43:21.250-07:00" "updated_at" "2020-10-27T13:43:21.250-07:00" "fetchURL" "https://api.openweathermap.org/data/2.5/weather?q=Columbus,us&units=imperial&APPID=fe2a775f427aa5fc92ce0379937b9ee9" "id" 3 "name" "Boston" "region" "east" "created_at" "2020-10-27T13:43:21.258-07:00" "updated_at" "2020-10-27T13:43:21.258-07:00" "fetchURL" "https://api.openweathermap.org/data/2.5/weather?q=Boston,us&units=imperial&APPID=fe2a775f427aa5fc92ce0379937b9ee9" "id" 4 "name" "Orlando" "region" "southeast" "created_at" "2020-10-27T13:43:21.267-07:00" "updated_at" "2020-10-27T13:43:21.267-07:00" "fetchURL" "https://api.openweathermap.org/data/2.5/weather?q=Orlando,us&units=imperial&APPID=fe2a775f427aa5fc92ce0379937b9ee9" "id" 5 "name" "Seattle" "region" "northwest" "created_at" "2020-10-27T13:43:21.275-07:00" "updated_at" "2020-10-27T13:43:21.275-07:00" "fetchURL" "https://api.openweathermap.org/data/2.5/weather?q=Seattle,us&units=imperial&APPID=fe2a775f427aa5fc92ce0379937b9ee9" Perfection: I got a JSON response and my PostgreSQL database on Heroku is working! So my endpoints are up and serving out data to the real world. Now once your endpoints are hitting and you have your database.yml file in order you might want to drop your database. I know in development I did this a lot. Sometimes you need to clear out your database and start over. There are many articles describing how to do this. I want to make this crystal clear. You can waist your time trying but it will now work. You have to go to your Heroku dashboard and then open your database here: HEROKU DOES NOT LET YOU DROP YOUR DATABASE. Now from here you mush your database. RESET I created this because there is a ton of information on dropping your database with Heroku. You will waist your time and all you have to do is go to the Heroku dashboard. I hope this helps and will save you your time. Code on Happy Coder, Code on. Also published on: https://software-for-humanity.medium.com/heroku-production-tldr-how-to-go-live-with-your-rails-app-7a7aabf22c4

Heroku Guide: How to Go Live with your Rails App

How to quickly set up a private Node.js package repository with Bit and NPM, and share your components. Setting up a package registry is often the first step towards scaling code-sharing and making life a little bit easier for your team. Node.js Sharing more modules means duplicating less code. It also helps in building more modular and maintainable software. However, the overhead around setting up and maintaining a private registry can be massive. NPM Using Bit, you can remove most of the overhead around a private registry while reducing the overhead around the packaging and publishing process. In this short tutorial, I’ll show you how, using Bit, you can set up a private Node.js registry and publish dozens of components and modules in a just few minutes, in 3 steps. Set up a Node.js package registry in 30 seconds Publish modules/components Install packages with the NPM/Yarn client Let’s get started. You can also check out this short video tutorial. 1. Setup a Node.js package registry for your components Let’s set a private package registry for your team. We’ll use to host the modules we share and the native NPM/Yarn client to install them. Bit’s web platform First thing’s first, set up a registry. . Head over to Click on a bit.dev get started. . . It’s free. b Sign-Up . Create a collection: c To set a private collection, just select “private”. That’s it! You now have a collection in Bit’s web platform, which also functions as a package registry. Let’s see how to publish packages to this registry. _Both public and private components and modules shared with Bit are now made instantly available to install with NPM and…_blog.bitsrc.io Introducing Bit’s NPM Package Registry 2. Publish components or modules Now let’s publish modules and components to our newly created registry. Since we set up the registry on Bit’s platform, we can leverage Bit for this workflow as well, to save precious time and effort. _Easily share code between projects with your team. - teambit/bit_github.com teambit/bit https://docs.bit.dev/ First, install Bit. Then, head over to the project in which you have the packages you want to publish. Note that since we are using Bit, you can without refactoring. publish packages right from any existing project #1 Install Bitnpm install bit-bin -g

#2 Create a local workspace for your project$ cd project-directory$ bit init Instead of having to create a new repository, configure the package etc, let’s use Bit to isolate components and modules from existing projects and publish them as packages. Let’s point Bit to the right packages in the project using the . bit add command Example Let’s track the components , and in the following project’s directory structure. button login logo $ tree.├── App.js├── App.test.js├── favicon.ico├── index.js└── src    └── components        ├── button        │   ├── Button.js        │   ├── Button.spec.js        │   └── index.js        ├── login        │   ├── Login.js        │   ├── Login.spec.js        │   └── index.js        └── logo            ├── Logo.js            ├── Logo.spec.js            └── index.js

5 directories, 13 files To track these files as components we can use with a glob pattern, pointing Bit to the path in which the modules we want to publish are found. bit add $ bit add src/components/*tracking 3 new components Note that Bit will automatically run through the module’s file & package dependancies, and create and isolate environment for the code which contains everything it needs in order to run in other projects. Now, let’s add and environments so that Bit can build and test your packages (on the cloud) and present the results for every package. You can find a list of here. build test pre-made environments Here’s a recommended example for React components. $ bit import bit.envs/compilers/babel --compiler

$ bit import bit.envs/testers/mocha --tester You can also implement your own environments using . For assistance, visit or . Bit’s extension system Bit’s Gitter channel Discourse board Now, let’s tag a version for the packages we are about to publish (following the previous example). $ bit tag --all 1.0.03 components tagged | 3 added, 0 changed, 0 auto-taggedadded components:  components/button@1.0.0, components/login@1.0.0, components/logo@1.0.0 Next, use to authenticate your machine to Bit’s platform. bit login $ bit loginYour browser has been opened to visit: http://bit.dev/bit-login?redirect_uri=http://localhost:8085... Finally, export (publish) the packages. $ bit export user-name.collection-nameexported 3 components to scope user-name.collection-name That’s it! All your packages will now be available in your collection, ready to install using NPM/Yarn in any project. Piece of cake, and we can use this workflow to quickly publish large numbers of packages in very little time. 3. Install packages using the NPM/Yarn client Now that our packages are ready, let’s learn how to install them. First, configure as a scoped registry to your NPM client. bit.dev npm config set '@bit:registry' https://node.bit.dev That’s it :) Any package can now be installed using your native NPM/Yarn client. Head over to the component/module page ( ). Example Check out the pane on the top-right side. Choose the “NPM” tab and copy the command: npm i @bit/user-name.collection-name.namespace.packagename Let’s see an example. shared as a package. Let’s use the following command to install it (user = bit, collection = movie-app, name space = components, package name = hero): Here’s a React Hero component npm i @bit/bit.movie-app.components.hero That’s it. You can now freely share and install these packages just as if you published them to any other NPM registry. The best : You can also use JFrog’s Artifactory as your Bit registry. to see how it’s done. JFrog Artifactory Learn more on JFrog’s blog Distributed Development Workflow Another advantage of installing packages via Bit’s registry is that you can to a version of the actual source code of the packages right from any project you’re working on. use Bit to import and make changes Unlike other registries, which require a cumbersome process for cloning and publishing changes to a package, Bit lets different team members import and modify packages from different projects. It also helps sync changes between them using and a (Git extension). smart updates cross-repo merge utility For example, let’s look at this repo structure. $ tree ..├── bit.json├── package.json└── src    ├── hello-world    │   ├── hello-world.js    │   └── index.js    └── utils        ├── noop.js        └── left-pad.js We’ll use Bit to import the left-pad component into your local project. $ bit init$ bit import bit.utils/string/left-pad --path src/left-pad We can now make the required changes, and them back to the collection (creating a new version) or to a new collection to share. tag export Conclusion In this short tutorial we learned how to: Set up an NPM registry in 30 seconds Publish packages without refactoring or boilerplating Install them with the NPM/Yarn client Make changes anywhere and collaborate Sharing more code in a managed way, while reducing the overhead and time involved in this process, means your team can speed development and simplify the maintenance of your codebase. Feel free to , set up your own registry and share some code. You can check out the or chat with the team on . Thanks! get started project on GitHub Gitter _Easily share reusable components between projects and applications to build faster as a team. Collaborate to develop…_bit.dev Share reusable code components as a team · Bit

Private NPM Registry in 30 Seconds with Bit

Going live In Part 1 of this tutorial we set up our page on Facebook and hooked it to a Sinatra server running on our machine through ngrok . We introduced the facebook-messenger gem from Hyperoslo and we hooked our bot to Google Geocoding API . In Part 2 we added new features to our bot and saw the complexity of our code increase, so we had to refactor. We added two different sets of menus to make interaction with our bot easier. T we’ll teach our bot to use . We will also admit some design mistakes we made previously, refactor yet again, and finally set our bot free from the tethers of your computer by deploying it to . You will be also guided through , so your own bot can one day go live. his time our current location Heroku Facebook verification process If you did not follow steps from last two parts, you can pick up the code to begin with . here Here’s what we are building today: Our bot by the end of this tutorial Keeping secrets Remember how we had to type in our like or by hand each time we opened a new terminal window to launch our bot on localhost? Well, some readers pointed out there is a gem for that and it will work with any Ruby project (doesn’t have to be Rails, as is the case with the popular gem). Meet . First, install it on your system: environment variables ACCESS_TOKEN VERIFY_TOKEN figaro dotenv gem install dotenv Then require it on top of and files both app.rb bot.rb require 'dotenv/load' Create a file named in your project folder and put exactly the same environment variables declaration that you used to set in your terminal. ( ) .env Reminder: both tokens can be found in your Facebook developer console, see Part 1 for details VERIFY_TOKEN=here_comes_YOUR_verify_tokenACCESS_TOKEN=here_comes_YOUR_access_token Now add another file to your project folder, called . Put inside (yes, just the name of .env file) so that your tokens are not pushed to Github for the whole world to see. I assume you track your project with Git, that would be essential for our deployment to Heroku. .gitignore .env Great, now you every time your launch your local server with a command your environment variables will be set automatically, no need to worry about closing and reopening your terminal window. rackup Where am I? You have to admit, the of our bot was not very useful: you had to manually type in an address in order to lookup GPS coordinates. Nice to learn random things like the latitude of an Eiffel Tower, but not really helpful when you need to answer the question, old as humanity itself, . last iteration “Where am I?” The question everyone asks oneself sometimes: “Where the hell am I?” Your phone has GPS, right? Well, Facebook lets us use it. Here’s there own example of how to enable location sharing. Messenger API curl -X POST -H "Content-Type: application/json" -d '{"recipient":{"id":"USER_ID"},"message":{"text":"Please share your location:","quick_replies":[{"content_type":"location",}]}}' "https://graph.facebook.com/v2.6/me/messages?access_token=PAGE_ACCESS_TOKEN" But we are not accessing Facebook JSON endpoints directly, all this work is done behind the scenes by the gem that we use. However, we are able to reason deductively and what do we see by looking at this raw JSON? We see that the part enabling user to send his/her location is in the set of quick replies. That means, we need to send any message to the user first and attach a location query to it. facebook-messenger “content_type”:”location” You will also need to enable a webhook under tab in your Facebook developer console. location Webhooks We already have a wrapper over the JSON request in a form of helper that we introduced in a . Here’s how it looked like: say previous part As you can see, this method takes an optional argument that is an array of replies. We used it construct our “menu” of quick replies to show basic commands to our user. Meaning, we can pass (that’s right, Hash inside an Array) to this method and voilà, we’ll send exactly the same JSON we saw above to Facebook API. That’s code reuse! quick_replies [{ content_type: ‘location’ }] Also, remember that we can examine any messages our bot sends us with . Try adding this line to the top of your method inside , right before line: message.inspect wait_for_any_input bot.rb sender_id = message.sender[‘id’] puts "Received '#{message.inspect}' from #{message.sender}" Now, if you open Messenger on your mobile phone, connect to your bot and send your location instead of text, then by examining your logs you can see how the location message looks like to our Santa’s little helper. You should see something like this: rackup facebook-messenger Received '#<Facebook::Messenger::Incoming::Message:0x007fad3890be00 @messaging={"sender"=>{"id"=>"1295486190524658"}, "recipient"=>{"id"=>"1614495692193246"}, "timestamp"=>1484597226465, "message"=>{"mid"=>"mid.1484597226465:b335687852", "seq"=>59617, "attachments"=>[{"title"=>"Andy's Location", "url"=>"https://www.facebook.com/l.php?u=https%3A%2F%2Fwww.bing.com%2Fmaps%2Fdefault.aspx%3Fv%3D2%26pc%3DFACEBK%26mid%3D8100%26where1%3D55.772721087%252C%2B37.683347132677%26FORM%3DFBKPL1%26mkt%3Den-US&h=ATNEWzpLzUVPzSBK4oIF9rpOfG1IDaYzKtbNpDNcLAG9729MvTMvXETHmOTMdhnrQEw5Af2Pg8Ct2uTwXnQoTRI4DbmXWMH-p1ajjeAXhcvMLmMjvsyhCFgMDMM9xkHrFPVTTeg&s=1&enc=AZOftxHdpeOTr32oSlm8KEimjwBgrzLEPiUtBmE5a0pwZZ2BTsgizwnV6p3b8D3HvtE7dmT-hQuRh7Vn8x-vWNPe", "type"=>"location", "payload"=>{"coordinates"=>{"lat"=>55.772721087, "long"=>37.683347132677}}}]}}>' from {"id"=>"1295486190524658"} If we dig in deep enough, we can get coordinates, we don’t even have to make a call to Geocoding anymore! By trial and error we discover that key containing a hash with latitude and longitude values can be accessed from our program like so: Google “coordinates” Ruby message.attachments.first['payload']['coordinates'] Great! Let’s write some new methods. Add this to : bot.rb As you can see, we use helper method to add attach ‘Send Location’ label to your message. In the interface it will look like so: say We will also have to make sure that whatever reply we get in is indeed a location and not a plain old text in order to process it further. lookup_location(sender_id) Add this helper method to : bot.rb Now let’s get down to business and put our main logic in another method: Nice, now our bot is able to (in theory, we haven’t yet hooked this methods up to any bot conversation logic) extract your current GPS coordinates from the location you’ve sent. Let’s take it one step further. What if we could also guess full address based on location? Sure, we can! also lets us do something called . From the sound of it — exactly what we’re looking for! In order to use it we need to send a GET request to a different URL, so let’s create another constant on top of our , next to where we declared . I’ll call it for consistency, but I admit it’s not the best naming. Google Geocoding API reverse geocoding bot.rb API_URL REVERSE_API_URL REVERSE_API_URL = 'https://maps.googleapis.com/maps/api/geocode/json?latlng=' Note: Remember we’re only using Geocoding API without an API key for development and testing. For production you should get it as instructed . Now, let’s update our method to reverse-geocode our coordinates. Note we are reusing and methods that we created earlier. handle_user_location(message) get_parsed_response extract_full_address Great, we have all we need for the feature, now let’s add it to the interface. The simplest place to add it is a persistent menu, defined in your thread settings on top of . Update it: bot.rb Now add a postback to payload that will call our new functionality. Update your block. LOCATION Bot.on :postback Also, add this constant somewhere on top of your file to avoid retyping everywhere we need it: [{ content_type: ‘location’ }] TYPE_LOCATION = [{ content_type: 'location' }] Now whenever a user picks ‘Location lookup’ from the persistent menu, we ask for a location and invite him/her to send it to us. We were also interacting with the user through the set of quick replies. Update it to include a reference to location command: We handle quick replies like any other user command from inside the method. Let’s account for location (and change previous naming while doing so): wait_for_command Notice we start adding to all method calls. That’s because we want to add ‘Send Location’ label to all of our bot’s functions. After all, for a postal address lookup user may want to type partial address in, or just send his/hers current location. Same goes for manual GPS lookup. Now we have to handle location inside and methods. We will have to revisit what we’ve already done. TYPE_LOCATION say show_coordinates show_full_addres Keeping it simple An important principle in code (and in life) OK. It’s time to admit sometimes you can your code. As some of my more experienced readers pointed out to me, introduction of with argument inside the method in was atrocious, because even if it helps us DRY-out 8 or so repeating lines, it makes our code . Also, if at some point we want our features to develop more separate functionality, we want to be able to modify them independent of each other. Let’s work on our mistakes: get rid of method and rewrite two features. over-refactor yield handle_api_request Part 2 very difficult to reason about handle_api_request Overthinking is a form of stupidity. Take-away: Here, we keep all our conditional logic inside our block, we also add a separate method for each lookup in order to follow the and reduce nesting. Bot.on :message SRP That was a lot of code! Whenever you feel lost, go to to see the latest good version of the file. this tutorial’s Github bot.rb Going international You must have noticed the method that we haven’t yet introduced. As of , our bot would just take whatever a user texted and append it to API URL, assuming all is good. But, if you try using international characters in your address (“Красная площадь“ or 東京都), your bot will throw this: encode_ascii Part 2 ERROR URI::InvalidURIError: URI must be ascii only "https://maps.googleapis.com/maps/api/geocode/json?address=\u{424}\u{440}. \u{42d}\u{43d}\u{433}\u{435}\u{43b}\u{44c}\u{441}\u{430}, \u{414}. 23" This error comes from Ruby standard library module that is used by (the gem we use to make HTTP requests). We need a way to convert a string that comes from a user into the URL-friendly ASCII format. uri HTTParty For that, we will use the gem. It has a method to perform on an URL, but you can also do it on any string. Add line to your and in . Then add method, it’s a one-liner. addressable percent-encoding gem ‘addressable’ Gemfile require ‘addressable/uri’ bot.rb ensode_ascii(s) Now a string will turn into . Google API is smart enough to decode it back once you make a request. “Красная площадь, д.1” “%D0%9A%D1%80%D0%B0%D1%81%D0%BD%D0%B0%D1%8F%20%D0%BF%D0%BB%D0%BE%D1%89%D0%B0%D0%B4%D1%8C,%20%D0%B4.1” The alternative is to use gem that will try to any string so will turn into , which is close enough, but will turn into , which has nothing to do with Tokyo (for which that three Japanese characters stood in the first place). Actually, for the transliterated version of Google API will return some address in Florida. That’s probably not what you want. unidecoder transliterate “Красная площадь” “Krasnaia ploshchad’” “東京都” “Dong Jing Du“ “東京都” Robot abuse You always have to assume that your , either because of sheer curiosity, or just by chance, because you did not account for some behaviour. Currently, if you ask user for an address and he/she sends you an image or a video, instead of text, as a reply — your bot is broken. To account for that, you’ll need to introduce a tiny new method: users will do everything they can to break your bot Then perform this check in every action, like so: Why humans have to be so cruel? Spring cleaning Okay, now our bot is well over 200 lines long. That makes our code difficult to maintain. It’s time to put some of common functionality into separate files. We can use classes or modules to break our program into pieces. We will use a simple class wrapper with a class method to invoke part of code ( ). The idea is to do something like this: that’s debatable, and I’d like to hear more about the actual best practice in comments And then call at the top of your . I leave the details to you, in I created two files: and to collect all actions. Greetings.enable bot.rb my project greetings.rb persistent_menu.rb Facebook::Messenger::Thread.set Commencing countdown, engines on Our bot goes to Heroku cloud Now after we tested all we could on localhost ( ) we are ready to send our bot into the world. We will use for deployment. Go to Heroku’s and . yes, I know bot testing is kind of hell Heroku website sign up for free Then, install if you haven’t done it before by following . Also, make sure your project folder is tracked with Git. If not, run: Heroku CLI these instructions git initgit add .git commit -m "First commit" Then authenticate your machine with and create your heroku app by running this command: heroku login heroku create YOUR_BOT_NAME It will create a web address in the form of and add heroku as a remote Git repository. Check if all went well by running: YOUR_BOT_NAME.herokuapp.com git remote -v You should see that two new references (fetch and push) to your . heroku remote Now, and : line both in and . gem does not work with Heroku ( ). Then in your pick your newly created app, go to its and scroll to . Reveal them and type in your and like so: this is important comment out require ‘dotenv/load’ bot.rb app.rb dotenv there’s a fork that does, you can look it up, but I found it easier to set variables directly in the dashboard Heroku dashboard Settings Config variables ACCESS_TOKEN VERIFY_TOKEN Now, the moment of truth. If you followed all the steps then the contents of file should be enough to successfully deploy. Run: config.ru git push heroku master …and behold the magic happening as Heroku creates a functional web app from your code. All you have to do now is to go to Facebook developer’s console and change the address for a webhook from your ngrok URL to your new Heroku app, something like: https://your-bot-name.herokuapp.com/webhook If the webhook verification goes well — ! you have successfully deployed your bot Hooray! For now you can test your bot yourself or add other Facebook users as testers under tab in your Facebook developer console. If you are truly ready to make your bot available to the whole world, you need to go through the . Meaning, actual live people at Facebook HQ will look at your bot (though, briefly) and check if it doesn’t do anything nasty. Go to tab and make your bot “live”. Then go to tab and under add to submission. Follow the provided checklist. Roles verification process App Review Messenger App Review for Messenger pages_messaging You just need to review your pages_messaging in our case You will need a privacy policy for your app that can be easily generated on numerous websites. I found to be most straightforward. Also, you need to supply an icon for your app and it must be exactly 1024x1024 in resolution. this one Now cross fingers and wait. In my case, Facebook reviewers cleared my bot in (I did it on Friday morning, Eastern time). Sometimes reviewers may ask you to record a of your bot, which is done easily with QuickTime. less than 15 minutes screencast Ahoy, Captain! Of course, our Coordinator bot does not provide the best user experience and some people may find it’s interface confusing. The conversation flow is rather rigid and if you make a mistake, you have to start over. However, I feel that some features, like a postal address lookup or finding the name of the street you’re on just by a single message can prove useful (at least, I find myself using them from time to time). You can play with the latest version of this tutorial’s bot by following . this link This project started with a contrived example to play around with the gem as a personal exercise in Ruby. Later I realised it may help and started working on this tutorial. facebook-messenger beginners like me My job was, more than anything, to stimulate your imagination and inspire you to build your own things. So I was happy to learn that one of my readers used this very tutorial to create a bot that . helps navigate Paris subway bot, inspired by this very tutorial Captain Metro If you live in Paris, you can test Captain Metro here . : About me I’m a beginner programmer and ex senior international TV correspondent. I am looking for my first proper job as a developer . Currently, I am having hard time getting employed in Russia, where engineers are extremely good, and it seems no one wants to hire beginners . If you want a motivated coder with well-developed human language skills for your team, I’ll be glad to join, even remotely. You can also invite me for an internship. I recently graduated top of the class from an excellent Le Wagon coding bootcamp in Paris and co-authored HALFWAY.ninja as a graduate project there. It’s an airfare comparator for couples. Go check it out! You can find me on Github , Twitter and Instagram . I speak English, Russian, French, Ruby, JavaScript, Python and Swift and I am currently based in Moscow, Russian Federation. Feel free to write me directly with any offers. P.S. I also write poetry (Russian knowledge required).

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AWS LetsEncrypt Lambda or Why I Wrote a Custom TLS Provider for AWS Using OpenTofu and Go

AWS LetsEncrypt Lambda বা কেন আমি OpenTofu এবং Go ব্যবহার করে AWS এর জন্য একটি কাস্টম TLS প্রদানকারী লিখেছি

AWS LetsEncrypt Lambda oder warum ich mit OpenTofu und Go einen benutzerdefinierten TLS-Anbieter für AWS geschrieben habe

AWS LetsEncrypt Lambda o por qué escribí un proveedor TLS personalizado para AWS usando OpenTofu and Go

AWS LetsEncrypt Lambda ou pourquoi j'ai écrit un fournisseur TLS personnalisé pour AWS à l'aide d'OpenTofu and Go

AWS LetsEncrypt लैम्ब्डा या मैंने OpenTofu और Go का उपयोग करके AWS के लिए एक कस्टम TLS प्रदाता क्यों लिखा

AWS LetsEncrypt Lambda または OpenTofu と Go を使用して AWS 用のカスタム TLS プロバイダーを作成した理由

AWS LetsEncrypt Lambda 또는 OpenTofu 및 Go를 사용하여 AWS용 사용자 지정 TLS 공급자를 작성한 이유

AWS LetsEncrypt Lambda ou por que escrevi um provedor TLS personalizado para AWS usando OpenTofu and Go

AWS LetsEncrypt Lambda или почему я написал собственный TLS-провайдер для AWS с использованием OpenTofu и Go

AWS LetsEncrypt Lambda veya OpenTofu ve Go'yu Kullanarak AWS için Neden Özel bir TLS Sağlayıcısı Yazdım?

AWS LetsEncrypt Lambda hoặc Tại sao tôi viết Nhà cung cấp TLS tùy chỉnh cho AWS bằng OpenTofu và Go

AWS LetsEncrypt Lambda 或为什么我使用 OpenTofu 和 Go 为 AWS 编写自定义 TLS 提供程序

Let’s say you’re an engineer at a large company tasked with productionizing a for a new client-facing chat interface. large language model (LLM) While pre-trained models are the best place to start in most cases, as time goes on, you may want to control the overall behavior and “feel” of chatting with this model beyond what the base model offers. This can be done through clever . However, it can severely limit the length of the input chat, and costs for every inference call will increase. There is another option—you can fine-tune your model on a dataset and instill new behavioral patterns in your model without having to do prompt engineering at all. prompt engineering How to fine-tune a Mistral 7B model In this tutorial, we'll guide you through the process of fine-tuning a open-source LLM. We'll use MindsDB to interact with the model and Anyscale Endpoints to host it. If you needed to fine-tune another model, the process would be somewhat similar. Mistral7B Please reach out to us via for help. Slack What is MindsDB? is an open-source AI platform for developers that connects AI/ML models with real-time data. It provides tools and automation to easily build and maintain personalized AI solutions. MindsDB With MindsDB, you can bring state-of-the-art AI models—like OpenAI, LLama2, Cohere, Mistral, and others—together with hundreds of data sources, including enterprise databases and third-party apps like PostgreSQL, MongoDB, Snowflake, Slack, Shopify, and more. The platform offers to various data sources, APIs, and machine learning frameworks. hundreds of integrations What is Anyscale? In this last category, Anyscale Endpoints come into play. It is a service offered by , creators of the Ray framework, which powers some of the most cutting-edge AI products in the world, like OpenAI’s ChatGPT. Their endpoints enable easy and optimized access (think fast and cheaper than alternatives) to open-source LLMs like the Mistral 7B model. Anyscale In what follows, we will compare the resulting fine-tuned model against its original version, inspecting differences in behavior and explaining what is actually happening behind the scenes. We will also take a look at how fine-tuning relates to prompt engineering, another fundamental component when building robust pipelines for generative AI applications in the LLM era. The tutorial is structured in steps to facilitate following along. Let’s get started: Step 1: Get your prerequisites in order Get a local deployment of MindsDB working in your machine. Make sure you install the requirements for the . Anyscale Endpoints integration Additionally, you need to . sign up for Anyscale Endpoints Step 2: Load data We will be using , which contains triples of context-question-answers that relate a SQL table (its original “create” query) with a natural language question prompted by a user and a ground truth “correct” answer query that returns the information this user is after. this dataset Even though the dataset contains well over 70,000 examples, for the purposes of this tutorial, we will consider only the first 300 examples. The data is rearranged into a “long” format, with conversations/chats being vertically stacked as rows. That is, every row has a “content” message and a “role," which can be “system,” “assistant,” (our model) or “user.” The content of each row is where we define a couple of things: system that the task is to translate a question into a SQL query, and what is the relevant reference SQL table creation statement? Notice that rows are our definition of what a perfect answer would be. assistant Data can be easily checked by entering the following: SELECT * FROM example_db.demo_data.anyscale_endpoints_ft_sample_data LIMIT 10; This retrieves a sample from our example Postgres database, which should look similar to the screenshot below: Notice how the assistant’s answers are the queries, without any accompanying explanations. This is the main effect we want to observe when compared to the starting base model. Now, let’s set that up. Step 3: Set up the base model Create an instance of the Anyscale integration in your MindsDB project: a. CREATE ML_ENGINE anyscale_endpoints FROM anyscale_endpoints; . Create a vanilla Mistral 7B model with it (the specific model name we’re using here is ): b mistralai/Mistral-7B-Instruct-v0.1 CREATE MODEL ft_sql
PREDICT answer
USING
engine = 'anyscale_endpoints',
model_name = 'mistralai/Mistral-7B-Instruct-v0.1',
prompt_template = '{{content}}',
api_key = 'your-api-key-here'; At this point, you can already query the model and get some answers out of it, like this: c. SELECT answer FROM ft_sql WHERE content = 'hi!'; In fact, why not try one of the many examples we left out from the original dataset? Let’s see: d. SELECT answer FROM ft_sql WHERE content = 'Hi! I have created a SQL table with this command: “CREATE TABLE employees (country VARCHAR)”. How should I query my database to know how many employees are living in Canada?'; You should get back something like: While the above is a correct answer, it is a bit verbose. It's also perhaps not the best output format if you’re deploying this model in the context of a broader software application like a code co-pilot. What if we wanted the output to be succinct? At this point, we should highlight that the main effect of fine-tuning as executed on a pre-trained large language model is that it will tend to affect the overall behavior and alignment of it, rather than perfectly memorizing all factual information contained in new examples. This, of course, depends on many variables, but it is the overall trend when dealing with large datasets. If, instead, what you need is to extract specific real data as stored somewhere else, then your best bet would be to use . Do note these are not mutually exclusive, you definitely can employ both techniques at the same time. a RAG setup : Step 4 Fine-tune the model With this dataset in hand and the simplicity of both MindsDB and Anyscale Endpoints, we can fine-tune a Mistral 7B large language model with a single SQL command: e. FINETUNE ft_sql FROM example_db (
SELECT * FROM demo_data.anyscale_endpoints_ft_sample_data LIMIT 300
); This command will trigger a fine-tuning run on the Anyscale Endpoints platform. As the model has 7 billion parameters and the dataset is tiny, this process should take around 15 minutes, but depending on these two things, it could take longer. f. You will get a notification in the email you used to sign up for Anyscale Endpoints (like in the screenshot), after which the MindsDB model will also show as ready to go. Visually, the exact pipeline built here will look like the following diagram: At this point, we can expand on what is happening. Mistral 7B is a large neural network that closely follows the architecture. “transformer” For such a model, “supervised fine-tuning” roughly means slightly modifying some weights of the pre-trained base model. It will do this by trying to minimize an error metric on a portion of the new data, along with some special considerations (e.g., lower learning rate). One fundamental difference compared to the base pre-training stage is that data is labeled, as opposed to unlabeled (the label provides “supervision.”) As you can see from the steps above, we provide the response expected of an ideal “assistant,” and this will inform the training procedure to obtain a model that is better at producing these answers than the original one. It is also crucial that, moving forward, users interact with the model in a similar way to that shown in the data used for fine-tuning. We can try the model out like this: SELECT answer FROM ft_sql WHERE content = 'Hi! I have created a SQL table with this command: “CREATE TABLE employees (country VARCHAR)”. How should I query my database to know how many employees are living in Canada?'; Output column should be: . Much more succinct! answer SELECT COUNT(*) FROM employees WHERE country = "Canada" MindsDB features automatic model version control, and you can access previous model versions through the notation. We can already see how the answer is much more direct and to the point when compared to the original version, which you can retrigger by entering: MODEL_NAME.VERSION SELECT answer FROM ft_sql.1 WHERE content = 'Hi! I have created a SQL table with this command: “CREATE TABLE employees (country VARCHAR)”. How should I query my database to know how many employees are living in Canada?' USING max_tokens=1000; This will give you a similar answer to the one in section 3.d. As further clarification, while our newly fine-tuned model does behave quite differently, it is important to still check accuracy metrics empirically, as it is known that LLMs need “space” to produce better answers. This space is measured in tokens, which directly leads to a lengthier response. This means that while lengthy answers may be more difficult to parse, depending on the task, this could actually be a desirable property to increase accuracy in downstream tasks. (So, evaluate accordingly.) Step 5: What about prompt engineering? There is another interesting observation here. As demonstrated back when OpenAI released GPT-2, large language models can effectively learn “in-context,” which in today’s parlance equates to the so-called “prompt.” This is why prompt engineering has been described as absolutely crucial in setting up LLM pipelines. (And with good reason.) Evidence shows that one well-picked in-context example could have as much impact as dozens or hundreds of particular instances over which a model has been fine-tuned. We’re in a perfect position to actually try this out. Let’s take the base model once more and modify the prompt so that it reads slightly differently: CREATE MODEL ft_sql_succinct
PREDICT answer
USING
engine = 'anyscale_endpoints',
model_name = 'mistralai/Mistral-7B-Instruct-v0.1',
prompt_template = 'Answer with the correct SQL query only, no explanations whatsoever. Here is the question: {{content}}'; If you query this model with the same input, you will get: “SELECT COUNT(*) FROM employees WHERE country = 'Canada';,” which is precisely the effect we’re after. content This shows that for simple cases, good prompt templating can go a long way. When is prompt engineering not enough? Most LLM providers recommend you start with prompt engineering before performing any fine-tuning, and with good reason. We’ve just seen how effective it can be. When you fine-tune, you’re generating a new set of artifacts that make up your new model somewhere. In this case, the MindsDB-Anyscale stack handles the infrastructure overhead, but additional training and serving concerns are introduced (i.e., your solution is now more expensive to run) when compared to a single flexible prompt that can be used on base models at inference time. The flipside is that if you have tons of data to fine-tune on, or if your behavioral constraints are such that prompt engineering won’t cut it, then fine-tunes become a much more attractive option. For example, your base model could have a particularly short token limit, let’s say 2K tokens total. This means your prompt cannot include many examples, and depending on the nature of your LLM application, the intended behavior may require more data before the model is able to achieve this behavior. Or perhaps there one such prompt that works, but it is so long that its added cost on inference is very high. In both these scenarios, it will make sense to fine-tune first (perhaps complemented with a good prompt). is On the other hand (and as previously mentioned) if what you need is recalling facts, then RAG is pretty much a necessary complement. It will massively help the model in avoiding fabricated information. We will explore RAG more closely in an upcoming guide. Tips for getting started As a final note, this fine-tuning run used 1.6 million tokens in our experiment. As of December 2023, the pricing for LLM fine-tuning in Anyscale Endpoints works out to a grand total of $6.6 US dollars for the run. Not bad! Even so, when trying this out yourself, be careful to start small and set hard limits to avoid a huge unexpected bill at the end of the month. We’ve seen how MindsDB and Anyscale Endpoints are a powerful combination to fine-tune open-source large language models with your own data in a cost-effective and simple way. We’ve also explored the impact of fine-tuning on a model’s behavior and how it relates to prompt engineering. We hope this is useful, and good luck with your projects. Check us out . on GitHub Also published . here

Fine-Tuning Mistral 7B: Enhance Open-Source Language Models with MindsDB and Anyscale Endpoints

WOW Summit Dubai 2023, the World of WEB3 Summit, recently concluded with resounding success at the opulent Atlantis the Royal in Dubai. This event showcased an extraordinary lineup of speakers and esteemed sponsors, leaving an indelible mark on the world of blockchain and Web3 technology. , Global CEO of WOW Summit, expressed his enthusiasm, stating, Ivan Ivanov "WOW Summit Dubai 2023 has exceeded our wildest expectations. It was a landmark gathering that brought together Web3 enthusiasts, industry leaders, and government officials to shape the future of blockchain technology." The event featured some amazing panel discussions and keynotes that illuminated the path forward for blockchain and Web3 technology. The Summit featured an array of captivating panel discussions and keynote presentations. Among the standout topics were, Exploring the Fusion of AI, Metaverse, Gaming, Fashion, and NFTs, Global Strategies for Amplifying Revenue: Unlocking the Potential of Corporate Blockchain Providers, Early-Stage Funding Opportunities in Web3 Projects and Acceleration, Current State of Decentralized Media, Advancements in Web3 Protocols: Pioneering the Path to Innovation and Progress and several others. The event's sponsors, Farcana, Unicoin, Fastex, demonstrated their unwavering commitment to fostering innovation in the blockchain industry. Their visionary leadership and strategic expertise set the stage for transformative discussions on the potential of blockchain. Our sponsors were represented at the event as speakers and boosters in the exhibition hall. This exemplified their commitment to advancing the blockchain industry. Among the sponsors of the event we note such companies as: Darwinbit, ChainUp, Sastana, Beezfi (BizTrip), P2PBet,  Hacken, ICP, EXOLO. Unicoin, a next-generation cryptocurrency, stands out from its predecessors by embracing transparency, SEC compliance, and being backed by a diversified asset portfolio, including real estate and equity in high-growth companies. In contrast, Farcana, a Dubai-based AAA game development studio, is in the process of creating a game bearing the same name. Farcana's unique 4v4, ability-based arena shooter redefines the gaming experience with its innovative 4-role system, strategic gameplay, and full integration of Web3 technology, all while maintaining the high-quality standards associated with AAA gaming. Fastex is a complete Web3-driven ecosystem that introduces diverse centralized and decentralised products and solutions, including Fasttoken (FTN), Fastex Exchange, Fastexverse, Fastex Pay, and ftNFT Marketplace. Driven by constant changes in the world of technologies, the Fastex ecosystem always thinks one step ahead and aims to bring businesses and communities closer to Web3 technologies, making them more accessible than ever. Joining as speakers were also a group of outstanding individuals contributing significantly to the payments industry on Blockchain instead, including (Darwinbit), (Trust Wallet), (Hacken), (P2P Labs), and (Kinetex Network). Their support underscored the collaborative spirit of WOW Summit Dubai 2023. Jeff Zhao Eowyn Chen Igor Bershadskiy Marat Salimov Tigran Bolshoi The event featured distinguished speakers, including (Animoca Brands), (Dubai Blockchain Centre), (Director at EMARATSEC, Co-chair at the WEF global future council, Director for Center at Cyber Security New York University AD), (MENA Fintech Association), (Circle), (Chainanalysis), (Crypto Valley Partners), (UNICOIN), (Farcana), (Oracle), and other luminaries who shared profound insights and valuable discussions. Yat Siu Dr. Marwan Alzarouni Dr. Hoda Alkhzaimi Nameer Khan Miriam Kiwan Mohamed Issa Sam Katiela Julian Sperring-Toy Islam Shazhaev Joy John Prominent figures such as , , , , also graced the event, adding to its prestige. Michael Terpin Gurvinder Ahluwalia Christian Gleich Nick Spanos Mansoor Madhavji The Summit was honored by the presence of distinguished guests and esteemed media personalities, including , the esteemed from Moongames, as well as the notable presence of and (GuyWay events). Sheikh Ali Rashed Ali Saeed Al Maktoum Carl Runefelt Davinci Jeremie Guy Yanpolskiy The results of the WOW Summit Dubai Startup competition serves as a glittering showcase, highlighting the brilliant innovations and rising stars within the dynamic realms of blockchain and Web3 technology. From a pool of over a hundred spirited startup contenders, the selection of the top 10 was an inclusive and decentralized process, driven by the vibrant community using Cyrator (available at cyrator.com). This online platform became the epicenter of independent decentralized reviews, inquiries, and profound insights, all thoughtfully validated, and endorsed by esteemed experts. These well-considered deliberations are closely scrutinized by a committee of discerning investors. They're thrilled to introduce the distinguished winner of their Startup competition, hailing all the way from France, the brilliant minds behind the tokenized investment fund named Petale. This remarkable achievement has garnered the attention of MMPro Trust and its esteemed investors, who are now contemplating an investment of up to $1 million in the Petale project. Additionally, the project is set to embark on a series of meetings with tier-1 investment funds in Dubai. In an added boost of support, the Petale project has secured three months of invaluable market-making assistance, comprehensive listing maintenance, and expert trade strategy management courtesy of Market Making Pro, all as a well-deserved reward for emerging triumphant in the WOW Summit Startup Competition. This accomplishment underlines WOW Summit's steadfast dedication not only to recognizing exceptional talent but also to providing a vital launchpad for entrepreneurial aspirations. Furthermore, their victorious startups have not only earned the prestigious accolade but have also been generously rewarded with a slew of prizes from industry leaders such as AWS and various other esteemed partners. The WOW GROWTH program has also extended its nurturing hand to the top 10 finalists, offering a three-month acceleration program complete with comprehensive business development support and guidance on investor relations. This support will span across regions of interest, including Asia (HK Hub), the MENA region (UAE Hub), and Europe (Swiss Hub). In a groundbreaking collaboration with the Internet Computer Protocol (ICP), WOW Summit and GROWTH have launched an exciting Ideathon program, designed to cater to companies in their early stages, enabling them to test their innovative concepts and find the perfect tech team to bring these ideas to life. The Ideathon is now open for participation throughout the months of October and November 2023, while the forthcoming hackathon is scheduled to take place during the WOW Summit in Hong Kong 2024. The exclusive media zone, featuring moderators from Ana Solana (JETA agency) and Adel Bhurtun from Web3TV, provided a platform for in-depth coverage and analysis of the event's key moments. WOW Summit Dubai 2023's art zone showcased an impressive array of digital and NFT artists. Amrita Sethi, the event's headliner, crafted five unique works and is recognized as the UAE's first NFT artist, as well as a top-tier Physical and Digital Artist. For the WOW Summit, Amrita Sethi unveiled her latest masterpiece series titled "Art and Tech" aiBYTEs, representing a captivating evolution of her distinctive style. In a remarkable fusion of art and technology, she collaborated with ChatGPT to craft a poetic narrative that envisions how the transition from Web2 to Web3 will inspire our world. Subsequently, she harnessed the creative power of Midjourney to transform this narrative into stunning visual imagery. Vesa, a renowned digital art pioneer for over 15 years, is considered one of the initial artists to delve into crypto art and NFTs. His notable awards include NFT Artist of the Year (AIBC Summit, 2023) and top Web3 Artists accolades from L’Officiel Arabia. Naama Pozniak, the CEO of Paz Holding, Inc., and LetzGetPhygital, stood out as a Web3 Educator, NFT Artist, and multifaceted professional known for her contributions to the art world. WOW Summit Dubai 2023 lived up to its promise as an unmissable Web3 event that will undoubtedly shape the future of blockchain technology. Attendees were treated to a unique experience filled with knowledge sharing, networking opportunities, and exploration of cutting-edge developments in the Web3 ecosystem. WOW Summit is now gearing up for their Hong Kong edition in 2024, scheduled for March 26-27. Secure your super now. early bird tickets About WOW Summit: WOW Summit is a leading global Web3 event that unites distinguished industry titans, esteemed government officials, visionary funds, venture capitalists, NFT and digital artists, entrepreneurs, and multinational corporations. The Summit drives the innovative trajectory of Web3, covering cutting-edge trends and innovations in technology. It explores themes including the Web2 - Web3 transition, CBDCs, regulatory landscapes, asset tokenization, and the societal impact of blockchain and DLT technologies. Hosted by GuyWay, powered by MarketMakingPro, and co-organized by Uvecon.vc and Quantum Leap Strategy, WOW Summit has a history of hosting distinguished speakers.

WOW Summit Dubai 2023: A Massive Success Shaping the Future of Blockchain Technology

In this article, I’ll show you how to deploy a app and associate it with a domain. Node.js Let’s get right to it! 1. Buying everything we need: Server (VPS): I bought it on Digital Ocean because I have 200$ free on this service, and I can also , but you can also buy a VPS on sites such as: give you 200$ hostinger.com contabo.com Domain: I got a free one on namecheap.com, but you can also buy a domain on sites such as: hostinger.com godaddy.com domain.com 2. Setting up a VPS: Server settings: The server settings depend on the load your site will be under and the complexity of the project. Since I will be deploying a simple site, I chose the most minimal settings. For the authentication method, I chose a password. Once our server is up and running, we can start connecting to it. Copy the IPv4 or IPv6 address, then open a terminal and enter the following command: Ssh root@164.90.218.8(instead of 164.90.218.8 put your IPv4) After this, it will ask you to enter the password that you set when creating the VPS: When you successfully log in, you will see something similar to this: From there, we have two ways to transfer our project folder. If you have it in a zip file on your local computer, you can use these commands to transfer the zip file with your project to the server. #if you have authentication method thought password
scp your-archive.zip root@164.90.218.8:~/
#if you have authentication method thought ssh key
scp -i ~/.ssh your-archive.zip root@164.90.218.8:~/ However, I suggest that you use GitHub. Log in to and use “git clone” to put your project in the global directory. For example, I will use my Node.js project called “ ”. GitHub qr_code_hunt_challenge Then, we need to install packages. Use the following commands on our VPS: #to update everything
sudo apt update
#after it shows us that we have packages that we can upgrade
sudo apt upgrade
#when you get Do you want to continue? [Y/n], you just write Y After this, go to the git repository using this link and choose the version of Node.js you need. In my case, I will use the latest LTS version. Press the copy button next to the commands and insert them in our VPS: If you encounter any errors: sudo apt-get update
sudo apt-get install -f
sudo apt-get clean
sudo apt-get install -y nodejs
sudo apt Then: #to install vim, zip, nginx
sudo apt install vim zip nginx Now, we need to make some changes in the firewall settings: sudo ufw allow 'OpenSSH'
sudo ufw allow 'Nginx HTTP'
sudo ufw enable 
#after all this commands you need to write
sudo ufw status
#and you will get something like this
Status: active

To                         Action      From
--                         ------      ----
OpenSSH                    ALLOW       Anywhere                  
Nginx HTTP                 ALLOW       Anywhere                  
OpenSSH (v6)               ALLOW       Anywhere (v6)             
Nginx HTTP (v6)            ALLOW       Anywhere (v6) 3. Setting up a domain: First, we need to input our domain on the VPS hosting service. In my case, it is DigitalOcean. Go to the dashboard where you can check your VPS and start: When you insert the domain name and click “Add Domain,” you need to point to DigitalOcean in your nameservers. You can follow the guide from DigitalOcean using this . link In my case, I go to my dashboard in Namecheap and add everything as instructed in the guide: Second, we need to create a directory: sudo mkdir /var/www/your_domain.com
sudo chown -R $USER:$USER /var/www/your_domain.com/
sudo vim /etc/nginx/sites-available/your_domain.com The last command will open Vim, and here we need to insert this Nginx configuration: server {
    server_name your_domain.com www.your_domain.com;

    location / {
        proxy_pass http://localhost:3000;#here you need to change to your port
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_cache_bypass $http_upgrade;
    }
} Then, use these commands: rm -rf /etc/nginx/sites-available/default
rm -rf /etc/nginx/sites-enabled/default
sudo ln -s /etc/nginx/sites-available/your_domain.com /etc/nginx/sites-enabled/your_domain.com
#by next command you can check if everything okay
nginx -t
#now we need to reload our nginx
nginx -s reload Now, we need to move our Node.js project to another directory: cd /var/www/your_domain.com
mv ~/name_of_your_project_folder After using “ls,” you will see the folder or “.zip” file in your directory. If you just moved the “.zip” file, you need to unzip it using the command “unzip your_file.zip.” Now, we need to move all files from this directory: mv name_of_your_project_folder/* .
#and now we can delete this directory
rm -rf name_of_your_project_folder After that, use these commands: npm install
#and if you need some packages you can install now, in my case i will use:
npm init
npm install express
npm install ejs
npm install path
#and when you installed everything that you need, you can start your node.js
node server.js To make this site work without stopping: sudo npm install pm2@latest -g

pm2 startup systemd

pm2 start /var/www/your_domain.com/server.js

pm2 save

pm2 status
#after last command you should see If everything is okay, start using these commands: sudo systemctl start pm2-root

sudo systemctl reboot 4. Setting up HTTPS: To use HTTPS on our app, use these commands: sudo ufw allow 'Nginx Full'

sudo apt install certbot python3-certbot-nginx

sudo certbot --nginx -d your_domain.com -d www.your_domain.com

sudo systemctl status certbot.timer

sudo certbot renew --dry-run

sudo ufw delete allow 'Nginx HTTP'

#and if you upload some file on your app
sudo vim /etc/nginx/nginx.conf
#and here you need to insert in http {}
client_max_body_size 1000M; #here you can input any amout of megabytes

#and after all this
 nginx -t && nginx -s reload Now, our Node.js app is deployed and reachable through our domain, and everything is working. Finishing Up I hope you understood the instructions correctly. If you have any thoughts on this article, I will be waiting for your comments. If I really helped you, I kindly ask you to subscribe to my and provide feedback on this article. LinkedIn Also published here.

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