Fetching Images for RSS Responses in SUSI Web Chat

Initially, SUSI Web Chat rendered RSS action type responses like this:

The response from the server initially only contained

  • Title
  • Description
  • Link

We needed to improvise the web search & RSS results display and also add images for the results.

The web search & RSS results are now rendered as :

How was this implemented?

SUSI AI uses Yacy to fetchRSSs feeds. Firstly the server using the console process to return the RSS feeds from Yacy needs to be configured to return images too.

"yacy":{
  "example":"http://127.0.0.1:4000/susi/console.json?q=%22SELECT%20title,%20link%20FROM%20yacy%20WHERE%20query=%27java%27;%22",
  "url":"http://yacy.searchlab.eu/solr/select?wt=yjson&q=",
  "test":"java",
  "parser":"json",
  "path":"$.channels[0].items",
  "license":""
}

In a console process, we provide the URL needed to fetch data from, the query parameter needed to be passed to the URL and the path to look for the answer in the API response.

  • url = <url>   – the URL to the remote JSON service which will be used to retrieve information. It must contain a $query$ string.
  • test = <parameter> – the parameter that will replace the $query$ string inside the given URL. It is required to test the service.

Here the URL used is :

http://yacy.searchlab.eu/solr/select?wt=yjson&q=QUERY

To include images in RSS action responses, we need to parse the images also from the Yacy response. For this, we need to add `image` in the selection rule while calling the console process

"process":[
  {
    "type":"console",
    "expression":"SELECT title,description,link FROM yacy WHERE query='$1$';"
  }
]

Now the response from the server for RSS action type will also include `image` along with title, description, and link. An example response for the query `Google` :

{
  "title": "Terms of Service | Google Analytics \u2013 Google",
  "description": "Read Google Analytics terms of service.",
  "link": "http://www.google.com/analytics/terms/",
  "image":   "https://www.google.com/images/branding/googlelogo/1x/googlelogo_color_116x41dp.png",
}

However, the results at times, do not contain images because there are none stored in the index. This may happen if the result comes from p2p transmission within Yacy where no images are transmitted. So in cases where images are not returned by the server, we use the link preview service to preview the link and fetch the image.

The endpoint for previewing the link is :

BASE_URL+'/susi/linkPreview.json?url=URL'

On the client side, we first search the response for data objects with images in API actions. And the amongst the remaining data objects in answers[0].data, we preview the link to fetch image keeping a check on the count. This needs to be performed for processing the history cognitions too.To preview the remaining links in a loop, we cannot make ajax calls directly in a loop. To handle this, nested ajax calls are made using the function previewURLForImage() where we loop through the remaining links and on the success we decrement the count and call previewURLForImage() on the next link and on error we try previewURLForImage() on the next link without decrementing the count.

success: function (rssResponse) {
  if(rssResponse.accepted){
    respData.image = rssResponse.image;
    respData.descriptionShort = rssResponse.descriptionShort;
    receivedMessage.rssResults.push(respData);
  }
  if(receivedMessage.rssResults.length === count ||
    j === remainingDataIndices.length - 1){
    let message = ChatMessageUtils.getSUSIMessageData(receivedMessage, currentThreadID);
    ChatAppDispatcher.dispatch({
      type: ActionTypes.CREATE_SUSI_MESSAGE,
      message
    });
  }
  else{
    j+=1;
    previewURLForImage(receivedMessage,currentThreadID,
BASE_URL,data,count,remainingDataIndices,j);
  }
},

And we store the results as rssResults which are used in MessageListItems to fetch the data and render. The nested calling of previewURLForImage() ends when we have the required count of results or we have finished trying all links for previewing images. We then dispatch the message to the message store. We now improvise the UI. I used Material UI Cards to display the results and for the carousel like display, react-slick.

<Card className={cardClass} key={i} onClick={() => {
  window.open(tile.link,'_blank')
}}>
  {tile.image &&
    (
      <CardMedia>
        <img src={tile.image} alt="" className='card-img'/>
      </CardMedia>
    )
  }
  <CardTitle title={tile.title} titleStyle={titleStyle}/>
  <CardText>
    <div className='card-text'>{cardText}</div>
    <div className='card-url'>{urlDomain(tile.link)}</div>
  </CardText>
</Card>

We used the full width of the message section to display the results by not wrapping the result in message-list-item class. The entire card is hyperlinked to the link. Along with title and description, the URL info is also shown at the bottom right. To get the domain name from the link, urlDomain() function is used which makes use of the HTML anchor tag to get the domain info.

function urlDomain(data) {
  var a = document.createElement('a');
  a.href = data;
  return a.hostname;
}

To prevent stretching of images we use `object-fit: contain;` to make the images fit the image container and align it to the middle.

We finally have our RSS results with images and an improvised UI. The complete code can be found at SUSI WebChat Repo. Feel free to contribute

Resources

Modifying SUSI Skills using SUSI Skill CMS

SUSI Skill CMS is a complete solution right from creating a skill to modifying the skill. The skills in SUSI are well synced with the remote repository and can be completely modified using the Edit Skill feature of SUSI Skill CMS. Here’s how to Modify a Skill.

  1. Sign Up/Login to the website using your credentials in skills.susi.ai
  2. Choose the SKill which you want to edit and click on the pencil icon.
  3. The following screen allows editing the skill. One can change the Group, Language, Skill Name, Image and the content as well.
  4. After making the changes the commit message can be added to Save the changes.

To achieve the above steps we require the following API Endpoints of the SUSI Server.

  1. http://api.susi.ai/cms/getSkillMetadata.json – This gives us the meta data which populates the various Skill Content, Image, Author etc.
  2. http://api.susi.ai/cms/getAllLanguages.json – This gives us all the languages of a Skill Group.
  3. http://api.susi.ai/cms/getGroups.json – This gives us all the list of Skill Groups whether Knowledge, Entertainment, Smalltalk etc.

Now since we have all the APIs in place we make the following AJAX calls to update the Skill Process.

  1. Since we are detecting changes in all the fields (Group Value, Skill Name, Language Value, Image Value, Commit Message, Content changes and the format of the content), the AJAX call can only be sent when there is a change in the PR and there is no null or undefined value in them. For that, we make various form validations. They are as follows.
    1. We first detect whether the User is in a logged in state.
if (!cookies.get('loggedIn')) {
            notification.open({
                message: 'Not logged In',
                description: 'Please login and then try to create/edit a skill',
                icon: <Icon type="close-circle" style={{ color: '#f44336' }} />,
            });
        }
  1. We check whether the image uploaded matches the format of the Skill image to be stored which is ::image images/imageName.png
if (!new RegExp(/images\/\w+\.\w+/g).test(this.state.imageUrl)) {
            notification.open({
                message: 'Error Processing your Request',
                description: 'image must be in format of images/imageName.jpg',
                icon: <Icon type="close-circle" style={{ color: '#f44336' }} />,
            });
        }
  1. We check if the commit message is not null and notify the user if he forgot to add a message.
if (this.state.commitMessage === null) {
            notification.open({
                message: 'Please make some changes to save the Skill',
                icon: <Icon type="close-circle" style={{ color: '#f44336' }} />,
            });
        }
  1. We also check whether the old values of the skill are completely similar to the new ones, in this case, we do not send the request.
if (toldValues===newValues {
            notification.open({
                message: 'Please make some changes to save the Skill',
                icon: <Icon type="close-circle" style={{ color: '#f44336' }} />,
            });
        }

To check out the complete code, go to this link.

  1. Next, if the above validations are successful, we send a POST request to the server and show the notification to the user accordingly, whether the changes to the Skill Data have been updated or not. Here’s the AJAX call snippet.
// create a form object
let form = new FormData();       
/* Append the following fields from the Skill Component:- OldModel, OldLanguage, OldSkill, NewModel, NewGroup, NewLanguage, NewSkill, changelog, content, imageChanged, old_image_name, new_image_name, image_name_changed, access_token */  
if (image_name_changed) {
            file = this.state.file;
            // append file to image
        }

        let settings = {
            "async": true,
            "crossDomain": true,
            "url": "http://api.susi.ai/cms/modifySkill.json",
            "method": "POST",
            "processData": false,
            "contentType": false,
            "mimeType": "multipart/form-data",
            "data": form
        };
        $.ajax(settings)..done(function (response) {
         //show success
        }.
        .fail(function(response){
         // show failure
        }
  1. To verify all this we head to the commits section of the SUSI Skill Data repo and see the changes we made. The changes can be seen here https://github.com/fossasia/susi_skill_data/commits/master 

Resources

  1. AJAX POST Request – https://api.jquery.com/jquery.post/ 
  2. Material UI – http://material-ui.com 
  3. Notifications – http://www.material-ui.com/#/components/notification 

Change Password for SUSI Accounts Using Access Token and Email-ID

In this blog, I discuss how the SUSI server synchronizes with SUSI Accounts and SUSI webchat for users to Change Password. When a user logs in, the clients store the email id of the user along with the access token in cookies. These are stored once the client gets a positive login response from the server. Both of these are required at the time of making the final call. Web clients store the email id and access token in the following way.

cookies.set('loggedIn', loggedIn, { path: '/', maxAge: time });
cookies.set('emailId', email, { path: '/', maxAge: time });

First, the client has to ask the user to enter their current password. A javascript test is used to validate that at least 6 characters must be entered by the user. A similar test is run on the new password. But while confirming the password, client checks whether the user has entered the same password as new password or not. These are just the basics. In next stage (which is achieved only when all the above conditions are met), client encodes the email id (which it gets from cookies), current password, new password and the access token (which it again extracts from cookies).

Now, Client just has to make an ajax request to the server. The response is processed and sent back to the client. Let us now look at PasswordChange Servlet.

The base user role is defined as USER. Initial steps of the servlet are to extract the values form the request it receives. The values extracted from the request are in turn used to make a client’s identity. Before that, server checks if current and new password have same values or not. If not, then server returns a JSON response to user stating, “Your current password and new password matches”. Otherwise, it will continue its control flow as it is. Look at the code snippet below:

if(password.equals(newpassword)){
            result.put("message", "Your current password and new password matches");
            result.put("accepted", false);
            return new ServiceResponse(result);
        }

The reader here may think that they have discovered a hack. But they have not. Why? Because this is just the first step. In later stages, the hash of passwords are used to match to see whether the passwords match or not. To obtain a proper client identity, first a Client credentials object is made with support from the email id which is received in ‘changepassword’ attribute. Using the ClientCredentials object made above, an object of Authentication class is made. This object uses a method defined in its class to return a valid client identity. Using the client identity, value of password hash is extracted from the database along with the salt used to hash the password. If any error is encountered while extracting the client’s password hash value and/or salt value, an error is thrown towards the client, with a message stating “invalid credentials”.

ClientCredential pwcredential = new ClientCredential(ClientCredential.Type.passwd_login, useremail);
            Authentication authentication = DAO.getAuthentication(pwcredential);
            ClientCredential emailcred = new ClientCredential(ClientCredential.Type.passwd_login,
                authentication.getIdentity().getName());
            ClientIdentity identity = authentication.getIdentity();
            String passwordHash;
            String salt;

            try {
                passwordHash = authentication.getString("passwordHash");
                salt = authentication.getString("salt");
            } catch (Throwable e) {
                Log.getLog().info("Invalid password try for user: " + identity.getName() + " from host: " + post.getClientHost() + " : password or salt missing in database");
                result.put("message", "invalid credentials");
                throw new APIException(422, "Invalid credentials");
            }

Using the same salt value that was used earlier, a hash for password entered by the user will be generated which now matches  the previous value. This is the point where the hack you were thinking you found, failed. Again the server throws an error message if user’s credential did not match. Passwords are hard to handle and easy to guess. So here we have used quite many tests before changing them. Users are not allowed to use their email id as a password as well.

If the server is clear on all the above facts and tests, It finally generates a new hashed value of the password received in the parameter ‘newpassword’ and replaces the old hash value with the new one. To notify the clients that password change exited with a success response, it sends a JSON object with message “Your password has been changed!” and accepted flag set to true.

if (DAO.hasAuthentication(emailcred)) {
                    Authentication emailauth = DAO.getAuthentication(emailcred);
                    String newsalt = createRandomString(20);
                    emailauth.remove("passwordHash");
                    emailauth.put("passwordHash", getHash(newpassword, salt));
                    Log.getLog().info("password change for user: " + identity.getName() + " via newpassword from host: " + post.getClientHost());
                    result.put("message", "Your password has been changed!");
                    result.put("accepted", true);
                }

 

Additional Resources:

Wikipedia article: What is DAO?

Including a Graph Component in the Remote Access Framework for PSLab

The remote-lab software of the pocket science lab enables users to access their devices remotely via the Internet. It includes an API server designed with Python Flask, and a web-app designed with EmberJS that allows users to access the API and carry out various tasks such as writing and executing Python scripts. In a series of blog posts, various aspects of this framework such as  remote execution of function strings, automatic deployment on various domains, creating and submitting python scripts which will be run on the remote server etc have already been explored.  This blog post deals with the inclusion of a graph component in the webapp that will be invoked when the user utilises the `plot` command in their scripts.

The JQPLOT library is being used for this purpose, and has been found to be quite lightweight and has a vast set of example code .

Task list for enabling the plotting feature
  • Add a plot method to the codeEvaluator module in the API server and allow access to it by adding it to the evalGlobals dictionary
  • Create an EmberJS component for handling plots
    • Create a named div in the template
    • Invoke the Jqplot initializer from the JS file and pass necessary arguments and data to the jqplot instance
  • Add a conditional statement to include the jqplot component whenever a plot subsection is present in the JSON object returned by the API server after executing a script
Adding a plot method to the API server

Thus far, in addition to the functions supported by the sciencelab.py instance of PSLab, users had access to print, print_, and button functions. We shall now add a plot function.

def plot(self,x,y,**kwargs):
self.generatedApp.append({"type":"plot","name":kwargs.get('name','myPlot'),"data":[np.array([x,y]).T.tolist()]})

 

The X,Y datasets provided by the user are stacked in pairs because jqplot requires [x,y] pairs . not separate datasets.

We also need to add this to evalGlobals, so we shall modify the __init__ routine slightly:

self.evalGlobals['plot']=self.plot
Building an Ember component for handling plots

First, well need to install jqplot:   bower install –save jqplot

And this must be followed by including the following files using app.import statements in ember-cli-build.js

  • bower_components/jqplot/jquery.jqplot.min.js
  • bower_components/jqplot/plugins/jqplot.cursor.js
  • bower_components/jqplot/plugins/jqplot.highlighter.js
  • bower_components/jqplot/plugins/jqplot.pointLabels.js
  • bower_components/jqplot/jquery.jqplot.min.css

In addition to the jqplot js and css files, we have also included a couple of plugins we shall use later.

Now we need to set up a new component : ember g component jqplot-graph

Our component will accept an object as an input argument. This object will contain the various configuration options for the plot

Add the following line in templates/components/jqplot-graph.hbs:

style="solid gray 1px;" id="{{data.name}}">

The JS file for this template must invoke the jqplot function in order to insert a complete plot into the previously defined <div> after it has been created. Therefore, the initialization routine must override the didInsertElement routine of the component.

components/jqplot-graph.js

import Ember from 'ember';

export default Ember.Component.extend({
  didInsertElement () {
    Ember.$.jqplot(this.data.name,this.data.data,{
        title: this.title,

        axes: {
          xaxis: {
            tickInterval: 1,
            rendererOptions: {
            minorTicks: 4
            }
          },
        },
        highlighter: {
          show: true, 
          showLabel: true, 

          tooltipAxes: 'xy',
          sizeAdjust: 9.5 , tooltipLocation : 'ne'
        },				  
        legend: {
          show: true,
          location: 'e',
          rendererOptions: {
            numberColumns: 1,
          }
        },
        cursor:{ 
          show: true,
          zoom:true, 
          showTooltip:false
          } 

    });
  }
});

Our component is now ready to be used , and we must make the necessary changes to user-home.hbs in order to include the plot component if the output JSON of a script executed on the server contains it.

The following excerpt from the results modal shows how the plot component can be inserted

{{#each codeResults as |element|}}
	{{#if (eq element.type 'text')}}
		{{element.value}}<br>
	{{/if}}
	{{#if (eq element.type 'plot')}}
		{{jqplot-graph data=element}}
	{{/if}}
{{/each}}            

Most of the other components such as buttons and spans have been removed for clarity. Note that the element object is passed to the jqplot-graph component as an argument so that the component may configure itself accordingly.

In conclusion, the following screencast shows what we have created. A simple plot command creates a fancy plot in the output which includes data point highlighting, and can be easily configured to do a lot more. In the next blog post we shall explore how to use this plot to create a persistent application such as an oscilloscope.

Resources:

 

Enhancing the Functionality of User Submitted Scripts in the PSLab-remote framework

The remote-lab framework of the pocket science lab enables users to access their devices remotely via the internet. Its design involves an API server built with Python-Flask and a webapp that uses EmberJS. This post is the latest in a series of blog posts which have explored and elaborated various aspect of the remote-lab such as designing the API server and testing with Postman, remote execution of function strings, automatic deployment on various domains etc. It also supports creating and submitting python scripts which will be run on the remote server, and the console output relayed to the webapp.

In this post, we shall take a look at how we can extend the functionality by providing support for object oriented code in user submitted scripts.

Let’s take an example of a Python script where the user wishes to create a button which when clicked will read a voltage via the API server, and display the value to the remote user. Clearly, an interpreter that only provides the console output is not enough for this task. We need the interpreter to generate an app structure that also includes callbacks for widgets such as buttons, and JSON objects are an obvious choice for relaying such a structure to the webapp.

In a nutshell, we had earlier created an API method that could execute a python script and return a string output, and now we will modify this method to return a JSON encoded structure which will be parsed by the webapp in order to display an output.

Let’s elaborate this with an example : Example.py

print ('testing')
print ('testing some changes..... ')
print_('highlighted print statement')

 

JSON returned by the API [localhost:8000/runScriptById] , for the above script:

{"Date": "Tue, 01 Aug 2017 21:39:12 GMT", "Filename": "example.py", "Id": 4,
 "result": [
  {"name": "print", "type": "span", "value": "('testing',)"},
  {"name": "print", "type": "span", "value": "('testing some changes..... ',)"},
  {"class": "row well", "name": "print", "type": "span", "value": "highlighted print statement"}
  ],
"status": true}
Screenshot of the EmberJS webapp showing the output rendered with the above JSON

Adding Support for Widgets

In the previous section, we laid the groundwork for a flexible platform. Instead of returning a string, the webapp accepts a JSON object and parses it. We shall now add support for a clickable button which can be associated with a valid PSLab function.

An elementary JS twiddle has been made by Niranjan Rajendran which will help newbies to understand how to render dynamic templates via JSON objects retrieved from APIs. The twiddle uses two API endpoints; one to retrieve the compiled JSON output, and another to act as a voltmeter method which returns a voltage value.

To understand how this works in pslab-remote, consider a one line script called button.py:

button('get voltage',"get_voltage('CH1')")

The objective is to create a button with the text ‘get voltage’ on it , and which when clicked will run the command ‘get_voltage(‘CH1’)’ on the API server, and display the result.

When this script is run on the API server, it returns a JSON object with the following structure:

{"Date": "Tue, 01 Aug 2017 21:39:12 GMT", "Filename": "example.py", "Id": 4,
 "result": [  {"type":"button","name":"button-id0","label":"get_voltage","fetched_value":"","action":{"type":"POST","endpoint":"get_voltage('CH1')","success":{"datapoint":'result',"type":"display_number", "target":"button-id0-label"}}},
  {"name": "button-id0label", "type": "label", "value": ""},
  ],
"status": true}

The above JSON object is parsed by the webapp’s user-home template, and a corresponding button and label are generated. The following section of code from user-home.hbs renders the JSON object

{{#each codeResults as |element|}}
  {{#if (eq element.type 'label')}}
    <label  id="{{element.name}}" class="{{element.class}}">{{element.value}}</label>
  {{/if}}
  {{#if (eq element.type 'button')}}
    <button id="{{element.name}}" {{action 'runButtonAction' element.action}}>{{element.label}}</button>
  {{/if}}
{{/each}}    

An action was also associated with the the created button, and this is the “get_voltage(‘CH1’)” string which we had specified in our one line script.

For the concluding section, we shall see how this action is invoked when the button is clicked, and how the returned value is used to update the contents of the label that was generated as part of this button.

Action defined in controllers/user-home.js :

runButtonAction(actionDefinition) {
  if(actionDefinition.type === 'POST') {
    Ember.$.post('/evalFunctionString',{'function':actionDefinition.endpoint},this,"json")
      .then(response => {
        const resultValue = Ember.get(response, actionDefinition.success.datapoint);
        if (actionDefinition.success.type === 'display_number') {
           Ember.$('#' + actionDefinition.success.target).text(resultValue.toFixed(3));
        }
      });
  }
}

The action string is passed to the evalFunctionString endpoint of the API, and the contents are mapped to the display label.

Screencast of the above process
Resources:

Implementing the Feedback Functionality in SUSI Web Chat

SUSI AI now has a feedback feature where it collects user’s feedback for every response to learn and improve itself. The first step towards guided learning is building a dataset through a feedback mechanism which can be used to learn from and improvise the skill selection mechanism responsible for answering the user queries.

The flow behind the feedback mechanism is :

  1. For every SUSI response show thumbs up and thumbs down buttons.
  2. For the older messages, the feedback thumbs are disabled and only display the feedback already given. The user cannot change the feedback already given.
  3. For the latest SUSI response the user can change his feedback by clicking on thumbs up if he likes the response, else on thumbs down, until he gives a new query.
  4. When the new query is given by the user, the feedback recorded for the previous response is sent to the server.

Let’s visit SUSI Web Chat and try this out.

We can find the feedback thumbs for the response messages. The user cannot change the feedback he has already given for previous messages. For the latest message the user can toggle feedback until he sends the next query.

How is this implemented?

We first design the UI for feedback thumbs using Material UI SVG Icons. We need a separate component for the feedback UI because we need to store the state of feedback as positive or negative because we are allowing the user to change his feedback for the latest response until a new query is sent. And whenever the user clicks on a thumb, we update the state of the component as positive or negative accordingly.

import ThumbUp from 'material-ui/svg-icons/action/thumb-up';
import ThumbDown from 'material-ui/svg-icons/action/thumb-down';

feedbackButtons = (
  <span className='feedback' style={feedbackStyle}>
    <ThumbUp
      onClick={this.rateSkill.bind(this,'positive')}
      style={feedbackIndicator}
      color={positiveFeedbackColor}/>
    <ThumbDown
      onClick={this.rateSkill.bind(this,'negative')}
      style={feedbackIndicator}
      color={negativeFeedbackColor}/>
  </span>
);

The next step is to store the response in Message Store using saveFeedback Action. This will help us later to send the feedback to the server by querying it from the Message Store. The Action calls the Dispatcher with FEEDBACK_RECEIVED ActionType which is collected in the MessageStore and the feedback is updated in the Message Store.

let feedback = this.state.skill;

if(!(Object.keys(feedback).length === 0 &&    
feedback.constructor === Object)){
  feedback.rating = rating;
  this.props.message.feedback.rating = rating;
  Actions.saveFeedback(feedback);
}

case ActionTypes.FEEDBACK_RECEIVED: {
  _feedback = action.feedback;
  MessageStore.emitChange();
  break;
}

The final step is to send the feedback to the server. The server endpoint to store feedback for a skill requires other parameters apart from feedback to identify the skill. The server response contains an attribute `skills` which gives the path of the skill used to answer that query. From that path we need to parse :

  • Model : Highest level of abstraction for categorising skills
  • Group : Different groups under a model
  • Language : Language of the skill
  • Skill : Name of the skill

For example, for the query `what is the capital of germany` , the skills object is

"skills": ["/susi_skill_data/models/general/smalltalk/en/English-Standalone-aiml2susi.txt"]

So, for this skill,

    • Model : general
    • Group : smalltalk
    • Language : en
    • Skill : English-Standalone-aiml2susi

The server endpoint to store feedback for a particular skill is :

BASE_URL+'/cms/rateSkill.json?model=MODEL&group=GROUP&language=LANGUAGE&skill=SKILL&rating=RATING'

Where Model, Group, Language and Skill are parsed from the skill attribute of server response as discussed above and the Rating is either positive or negative and is collected from the user when he clicks on feedback thumbs.

When a new query is sent, the sendFeedback Action is triggered with the required attributes to make the server call to store feedback on server. The client then makes an Ajax call to the rateSkill endpoint to send the feedback to the server.

let url = BASE_URL+'/cms/rateSkill.json?'+
          'model='+feedback.model+
          '&group='+feedback.group+
          '&language='+feedback.language+
          '&skill='+feedback.skill+
          '&rating='+feedback.rating;

$.ajax({
  url: url,
  dataType: 'jsonp',
  crossDomain: true,
  timeout: 3000,
  async: false,
  success: function (response) {
    console.log(response);
  },
  error: function(errorThrown){
    console.log(errorThrown);
  }
});

This is how the feedback feedback mechanism works in SUSI Web Chat. The entire code can be found at SUSI Web Chat Repository.

Resources

 

PSLab Remote Lab: Automatically deploying the EmberJS WebApp and Flask API Server to different domains

The remote-lab software of the pocket science lab enables users to access their devices remotely via the internet. Its design involves an API server designed with Python Flask, and a web-app designed with EmberJS that allows users to access the API and carry out various tasks such as writing and executing Python scripts. For testing purposes, the repository needed to be setup to deploy both the backend as well as the webapp automatically when a build passes, and this blog post deals with how this can be achieved.

Deploying the API server

The Heroku PaaS was chosen due to its ease of use with a wide range of server software, and support for postgresql databases. It can be configured to automatically deploy branches from github repositories, and conditions such as passing of a linked CI can also be included. The following screenshot shows the Heroku configuration page of an app called pslab-test1. Most of the configuration actions can be carried out offline via the Heroku-Cli

 

In the above page, the pslab-test1 has been set to deploy automatically from the master branch of github.com/jithinbp/pslab-remote . The wait for CI to pass before deploy has been disabled since a CI has not been setup on the repository.

Files required for Heroku to deploy automatically

Once the Heroku PaaS has copied the latest commit made to the linked repository, it searches the base directory for a configuration file called runtime.txt which contains details about the language of the app and the version of the compiler/interpretor to use, and a Procfile which contains the command to launch the app once it is ready. Since the PSLab’s API server is written in Python, we also have a requirements.txt which is a list of dependencies to be installed before launching the application.

Procfile

web: gunicorn app:app –log-file –

runtime.txt

python-3.6.1

requirements.txt

gunicorn==19.6.0
flask >= 0.10.1
psycopg2==2.6.2
flask-sqlalchemy
SQLAlchemy>=0.8.0
numpy>=1.13
flask-cors>=3.0.0

But wait, our app cannot run yet, because it requires a postgresql database, and we did not do anything to set up one. The following steps will set up a postgres database using the heroku-cli usable from your command prompt.

  • Point Heroku-cli to our app
    $ heroku git:remote -a pslab-test1
  • Create a postgres database under the hobby-dev plan available for free users.
    $ heroku addons:create heroku-postgresql:hobby-dev

    Creating heroku-postgresql:hobby-dev on ⬢ pslab-test1… free
    Database has been created and is available
    ! This database is empty. If upgrading, you can transfer
    ! data from another database with pg:copy
    Created postgresql-slippery-81404 as HEROKU_POSTGRESQL_CHARCOAL_URL
    Use heroku addons:docs heroku-postgresql to view documentation

  • The previous step created a database along with an environment variable HEROKU_POSTGRESQL_CHARCOAL_URL . As a shorthand, we can also refer to it simply as CHARCOAL .
  • In order to make it our primary database, it must be promoted

    $ heroku pg:promote HEROKU_POSTGRESQL_CHARCOAL_URL
    The database will now be available via the environment variable DATABASE_URL

  • Further documentation on creating and modifying postgres databases on Heroku can be found in the articles section .

At this point, if the app is in good shape, Heroku will automatically deploy its contents to pslab-test1.herokuapp.com. We can test it using a developer tool such as Postman, or make our own webapp to use it.

Deploying the EmberJS WebApp

Since we are using the free plan on Heroku which only allows one dyno, our EmberJS webapp which shares the repository cannot be deployed on the same heroku server. Therefore, we must look for other domains where the frontend can be deployed.

Surge.sh allows easy deployment of Ember apps, and we shall set up our CI’s configuration file .travis.yml to do this for us when a pull request is made, and the build passes

This excerpt from .travis.yml only shows parts relevant to deployment on Surge.sh

after_success:
– pushd frontend
– bash surge_deploy.sh
– popd

Once the build has passed, the after_success hook executes a script called surge_deploy.sh which is located in the directory of the webapp.

Contents of surge_deploy.sh

#!/usr/bin/env bash
if [ “$TRAVIS_PULL_REQUEST” == “false” ]; then
echo “Not a PR. Skipping surge deployment”
exit 0
fi

ember build –environment=’production’

export REPO_SLUG_ARRAY=(${TRAVIS_REPO_SLUG//\// })
export REPO_OWNER=${REPO_SLUG_ARRAY[0]}
export REPO_NAME=${REPO_SLUG_ARRAY[1]}

npm i -g surge

# Details of a dummy account. So can be added to vcs.
export SURGE_LOGIN=j********r@gmail.com
export SURGE_TOKEN=4********************************f
export DEPLOY_DOMAIN=https://${REPO_NAME}.surge.sh
surge –project ./dist –domain $DEPLOY_DOMAIN;

The variables SURGE_LOGIN and SURGE_TOKEN must be specified, otherwise Surge will open a login prompt, and since there is no way to feed details into a prompt in a Travis build, it will timeout and fail. The surge token can be obtained with a simple `surge login` followed by `surge token` on your system’s terminal.

Final Application

A user’s homepage on the webapp deployed at pslab-remote.surge.sh . The EmberJS app has been configured to send all AJAX requests to the API server located at pslab-remote.herokuapp.com .

Resources

Designing a Remote Laboratory with PSLab using Python Flask Framework

In the introductory post about remote laboratories, a general set of tools to create a framework and handle its various aspects was also introduced. In this blog post, we will explore the implementation of several aspects of the backend app designed with python-flask, and the frontend based on EmberJS. A clear separation of the frontend and backend facilitates minimal disruption of either sections due to the other.

Implementing API methods in Python-Flask

In the Flask web server, page requests are handled via ‘routes’ , which are essentially URLs linked to a python function. Routes are also capable of handling payloads such as POST data, and various return types are also supported.

We shall use an example to demonstrate how a Sign-Up request sent from the sign-up form in the remote lab frontend for PSLab is handled.

@app.route('/signUp',methods=['POST'])
def signUp():
	"""Sign Up for Virtual Lab

	POST: Submit sign-up parameters. The following must be present:
	 inputName : The name of your account. does not need to be unique
	 inputEmail : e-mail ID used for login . must be unique.
	 inputPassword: password .
	Returns HTTP 404 when data does not exist.
	"""
	# read the posted values from the UI
	_name = request.form['inputName']
	_email = request.form['inputEmail']
	_password = request.form['inputPassword']

	# validate the received values
	if _name and _email and _password:
		_hashed_password = generate_password_hash(_password)
		newUser = User(_email, _name,_hashed_password)
		try:
			db.session.add(newUser)
			db.session.commit()
			return json.dumps({'status':True,'message':'User %s created successfully. e-mail:%s !'%(_name,_email)})
		except Exception as exc:
			reason = str(exc)
			return json.dumps({'status':False,'message':str(reason)})

 

In this example, the first line indicates that all URL requests made to <domain:port>/signUp will be handled by the function signUp . During development, we host the server on localhost, and use the default PORT number 8000, so sign-up forms must be submitted to 127.0.0.1:8000/signUp .

For deployment on a globally accessible server, a machine with a static IP, and a DNS record must be used. An example for such a deployment would be the heroku subdomain where pslab-remote is automatically deployed ; https://pslab-stage.herokuapp.com/signUp

A closer look at the above example will tell you that POST data can be accessed via the request.form dictionary, and that the sign-up routine requires inputName,inputEmail, and inputPassword. A password hash is generated before writing the parameters to the database.

Testing API methods using the Postman chrome extension

The route described in the above example requires form data to be submitted along with the URL, and we will use a rather handy developer tool called Postman to help us do this. In the frontend apps , AJAX methods are usually employed to do such tasks as well as handle the response from the server.

 

The above screenshot shows Postman being used to submit form data to /signUp on our API server running at localhost:8000 . The fields inputName, inputDescription, and inputPassword are also posted along with it.

In the bottom section, one can see that the server returned a positive status variable, as well as a descriptive message.

Submitting the sign up form via an Ember controller.
  • Setting up a template
    We first need to set up a template that we shall call sign-up.hbs , and add the following form to it. This form contains the details essential for signing up , and its submit action is linked to an action called `signMeUp` . This action will be defined in the controller which we shall explore shortly

<form class="form-signin" {{action "signMeUp" on="submit"}} >
        <label for="inputName" class="sr-only">Your Name</label>
        {{input value=inputName type="text" name="inputName" id="inputName" class="form-control" placeholder="name" required=true autofocus=true}}
        <label for="inputEmail" class="sr-only">Email address</label>
        {{input value=inputEmail type="email" name="inputEmail" id="inputEmail" class="form-control" placeholder="Email address" required=true autofocus=true}}
        <label for="inputPassword" class="sr-only">Password</label>
        {{input value=inputPassword type="password" name="inputPassword" id="inputPassword" class="form-control" placeholder="Password" required=true autofocus=true}}
         
        <button class="btn btn-lg btn-primary btn-block" type="submit">Sign Up</button>
</form>

 

  • Defining the controller
    The controller contains the actions and variables that the template links to. In this case, we require an action called signMeUp. The success, failure, and error handlers are hidden for clarity.

import Ember from 'ember';
export default Ember.Controller.extend({
  actions:{
    signMeUp() {
        var request = Ember.$.post("/signUp",
 this.getProperties("inputName","inputEmail","inputPassword"),this,'json');
        request.then(this.success.bind(this), this.failure.bind(this),
this.error.bind(this));
    },
  },
});

The signMeUp action submits the contents of the form to the signUp route on the API server, and the results are handled by functions called success, failure, or error depending on the type of response from the backend server.

Resources:

 

Implementing Search Bar Using GitHub API In Yaydoc CI

In Yaydoc’s, documentation will be generated by typing the URL of the git repository to the input box from where user can generate documentation for any public repository, they can see the preview and if they have access, they can push the documentation to the github pages on one click. But In Yaydoc CI user can register the repository only if he has access to the specific repository, so I decided to show the list to the repository where user can select from the list but then it also has one problem that Github won’t give us all the user repository data in one api hit and then I made a search bar in which user can search repository and can register to the Yaydoc CI.

var search = function () {
  var username = $("#orgs").val().split(":")[1];
  const searchBarInput = $("#search_bar");
  const searchResultDiv = $("#search_result");

  searchResultDiv.empty();
  if (searchBarInput.val() === "") {
    searchResultDiv.append('<p class="text-center">Please enter the repository name<p>');
    return;
  }

  searchResultDiv.append('<p class="text-center">Fetching data<p>');

  $.get(`https://api.github.com/search/repositories?q=user:${username}+fork:true+${searchBarInput.val()}`, function (result) {
    searchResultDiv.empty();
    if (result.total_count === 0) {
      searchResultDiv.append(`<p class="text-center">No results found<p>`);
      styles.disableButton("btnRegister");
    } else {
      styles.disableButton("btnRegister");
      var select = '<label class="control-label" for="repositories">Repositories:</label>';
      select += '<select class="form-control" id="repositories" name="repository" required>';
      select += `<option value="">Please select</option>`;
      result.items.forEach(function (x){
        select += `<option value="${x.full_name}">${x.full_name}</option>`;
      });
      select += '</select>';
      searchResultDiv.append(select);
    }
  });
};

$(function() {
  $("#search").click(function () {
    search();
  });
});

In the above snippet I have defined search function which will get executed when user clicks the search button. The search function will get the search query from input box, if the search query is empty it’ll show the message as “Please enter repository name”, if it is not empty it’ll hit the GitHub API to fetch user repositories. If the GitHub returns empty array it’ll show “No results found”. In between searching time “Fetching data” will be shown.

$('#search_bar').on('keyup keypress', function(e) {
    var keyCode = e.keyCode || e.which;
    if (keyCode === 13) {
      search();
    }
  });

  $('#ci_register').on('keyup keypress', function(e) {
    var keyCode = e.keyCode || e.which;
    if (keyCode === 13) {
      e.preventDefault();
      return false;
    }
  });

Still we faced some problem, like on click enter button form is automatically submitting. So I’m registering event listener. In that listener I’m checking whether the key code is 13 or not. Key code 13 represent enter key, so if the key code is 13 then i’ll prevent the form from submitting. You can see the working of the search bar in the Yaydoc CI.

Resources: