Link Preview Service from SUSI Server

 SUSI Webchat, SUSI Android app, SUSI iOS app are various SUSI clients which depend on response from SUSI Server. The most common response of SUSI Server is in form of links. Clients usually need to show the preview of the links to the user. This preview may include featured image, description and the title of the link.  Clients show this information by using various 3rd party APIs and libraries. We planned to create an API endpoint for this on SUSI Server to give the preview of the link. This service is called LinkPreviewService.
String url = post.get("url", "");
        if(url==null || url.isEmpty()){
            jsonObject.put("message","URL Not given");
            jsonObject.put("accepted",false);
            return new ServiceResponse(jsonObject);
        }

This API Endpoint accept only 1 get parameter which is the URL whose preview is to be shown.

Here we also check if no parameter or wrong URL parameter was sent. If that was the the case then we return an error message to the user.

 SourceContent sourceContent =     TextCrawler.scrape(url,3);
        if (sourceContent.getImages() != null) jsonObject.put("image", sourceContent.getImages().get(0));
        if (sourceContent.getDescription() != null) jsonObject.put("descriptionShort", sourceContent.getDescription());
        if(sourceContent.getTitle()!=null)jsonObject.put("title", sourceContent.getTitle());
        jsonObject.put("accepted",true);
        return new ServiceResponse(jsonObject);
    }

The TextCrawler function accept two parameters. One is the url of the website which is to be scraped for the preview data and the other is depth. To get the images, description and title there are methods built in. Here we just call those methods and set them in our JSON Object.

 private String htmlDecode(String content) {
        return Jsoup.parse(content).text();
    }

Text Crawler is based on Jsoup. Jsoup is a java library that is used to scrape HTML pages.

To get anything from Jsoup we need to decode the content of HTML to Text.

public List<String> getImages(Document document, int imageQuantity) {
        Elements media = document.select("[src]");
        while(var5.hasNext()) {
            Element srcElement = (Element)var5.next();
            if(srcElement.tagName().equals("img")) {
                ((List)matches).add(srcElement.attr("abs:src"));
            }
        }

 The getImages method takes the HTML document from the JSoup and find the image tags in that. We have given the imageQuantity parameter in the function, so accordingly it returns the src attribute of the first n images it find.

This API Endpoint can be seen working on

http://127.0.0.1:4000/susi/linkPreview.json?url=<ANY URL>

A real working example of this endpoint would be http://api.susi.ai/susi/linkPreview.json?url=https://techcrunch.com/2017/07/23/dear-tech-dudes-stop-being-such-idiots-about-women/

Resources:

Web Crawlers: https://www.promptcloud.com/data-scraping-vs-data-crawling/

JSoup: https://jsoup.org/

JSoup Api Docs: https://jsoup.org/apidocs/

Parsing HTML with JSoup: http://www.baeldung.com/java-with-jsoup

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Adding Servlet for SUSI Service

Whenever we ask anything to SUSI, we get a intelligent reply. The API endpoints which clients uses to give the reply to users is http://api.susi.ai/susi/chat.json, and this API endpoint is defined in SUSIService.java. In this blog post I will explain how any query is processed by SUSI Server and the output is sent to clients.

public class SusiService extends AbstractAPIHandler implements APIHandler

This is a public class and just like every other servlet in SUSI Server, this extends AbstractAPIHandler class, which provides us many options including AAA related features.

    public String getAPIPath() {
           return "/susi/chat.json";
    }

The function above defines the endpoint of the servlet. In this case it is  “/susi/chat.json”. The final API Endpoint will be API http://api.susi.ai/susi/chat.json.

This endpoint accepts 6 parameters in GET request . “q” is the query “parameter”, “timezoneOffset” and “language” parameters are for giving user a reply according to his local time and local language, “latitude” and “longitude” are used for getting user’s location.

      String q = post.get("q", "").trim();
        int count = post.get("count", 1);
        int timezoneOffset = post.get("timezoneOffset", 0); // minutes, i.e. -60
        double latitude = post.get("latitude", Double.NaN); // i.e. 8.68
        double longitude = post.get("longitude", Double.NaN); // i.e. 50.11
        String language = post.get("language", "en"); // ISO 639-1

After getting all the parameters we do a database update of the skill data. This is done using DAO.susi.observe() function.

Then SUSI checks that whether the reply was to be given from a etherpad dream, so we check if we are dreaming something.

if (etherpad_dream != null && etherpad_dream.length() != 0) {
    String padurl = etherpadUrlstub + "/api/1/getText?apikey=" + etherpadApikey + "&padID=$query$";

If SUSI is dreaming something then we call the etherpad API with the API key and padID.

After we get the response from the etherpad API we parse the JSON and store the text from the skill in a local variable.

JSONObject json = new JSONObject(serviceResponse);
String text = json.getJSONObject("data").getString("text");

After that, we fill an empty SUSI mind with the dream. SUSI susi_memory_dir is a folder named as “susi” in the data folder, present at the server itself.

SusiMind dream = new SusiMind(DAO.susi_memory_dir); 

We need the memory directory here to get a share on the memory of previous dialogues, otherwise, we cannot test call-back questions.

JSONObject rules = SusiSkill.readEzDSkill(new BufferedReader(new InputStreamReader(new ByteArrayInputStream(text.getBytes(StandardCharsets.UTF_8)), StandardCharsets.UTF_8)));
dream.learn(rules, new File("file://" + etherpad_dream));

When we call dream.learn function, Susi starts dreaming. Now we will try to find an answer out of the dream.

The SusiCognition takes all the parameters including the dream name, query and user’s identity and then try to find the answer to that query based on the skill it just learnt.

    SusiCognition cognition = new SusiCognition(dream, q, timezoneOffset, latitude, longitude, language, count, user.getIdentity());

If SUSI finds an answer then it replies back with that answers else it tries to answer with built-in intents. These intents are both existing SUSI Skills and internal console services.

if (cognition.getAnswers().size() > 0) {          DAO.susi.getMemories().addCognition(user.getIdentity().getClient(), cognition);
    return new ServiceResponse(cognition.getJSON());
}

This is how any query is processed by SUSI Server and the output is sent to clients.

Currently people use Etherpad (http://dream.susi.ai/) to make their own skills, but we are also working on SUSI CMS where we can edit and test the skills on the same web application.

References

Java Servlet Docs: http://docs.oracle.com/javaee/6/tutorial/doc/bnafd.html

Embedding Jetty: http://www.eclipse.org/jetty/documentation/9.4.x/embedding-jetty.html

Server-Side Java: http://www.javaworld.com/article/2077634/java-web-development/how-to-get-started-with-server-side-java.html

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Pie Chart Responses from SUSI Server

Giving out responses in charts and graphs is a very common reply of various assistants. We also have it in SUSI. We can show users the output of stocks, market covers and various percentages output in Pie Charts.  

A pie chart is a circular chart/graph which is divided in some segments like a pie. The segments in a pie chart shows the share of each object or category.

The PieChartServlet  in SUSI Server is a servlet that takes the JSON data of a the pie chart components as input parameters and returns an Image of the rendered Pie Chart..

public class PieChartServlet extends HttpServlet {

This is a simple HttpServlet. It does not require any authentication or base user role. So we extend the HttpServlet here.

    @Override
    protected void doGet(HttpServletRequest request, HttpServletResponse response) throws  IOException {

doGet is a method which is triggered whenever the PieChartServlet receives a GET Query. This will contain all the code that we will need to render the final output.

{"ford":"17.272992","toyota":"27.272992","renault":"47.272992"}

This is the sample JSON that we send to the PieChartServlet. This contains the names of the pie chart components and their respective percentages. After we receive these parameters we parse them and store them in our local variables.
These variables are then further used to plot the pie chart.

To plot these values in pie chart we have used a library JFreeChart.

This is a free and well documented Java chart library. This library supports PNGs and JPEGs as well as vector graphics file formats

JFreeChart chart = getChart(json, legendBit, tooltipBit);

From here we call a function getChart This function accept 3 parameters. The json which we sent as the GET parameter, legendBit and tooltilBit. These are also sent as GET parameters. In this example I will use legendBit as true and tooltipBit as false.

        JFreeChart chart = ChartFactory.createPieChart("SUSI Visualizes -   PieChart", dataset, legend, tooltips, urls);

        chart.setBorderPaint(Color.BLACK);
        chart.setBorderStroke(new BasicStroke(5.0f));
        chart.setBorderVisible(true);

        return chart;

 This is the function getChart. It creates a chart using the ChartFactory method and set sets the SUSI branding on it as “SUSI Visualizes – PieChart”. It accepts the datasets, legends and tool tips. The variable, dataset is nothing but the json keys and their values.

After the ChartFactory returns the chart we set the border of the chart and returns a pie chart back the function where it was called.

ChartUtilities.writeChartAsPNG(outputStream, chart, width, height);

Finally we write the chart as a PNG image and send it to the user.

Output

This can be tested at

https://api.susi.ai/vis/piechart.png?data={%22ford%22:%2217.272992%22,%22toyota%22:%2227.272992%22,%22renault%22:%2247.272992%22}&width=1000&height=1000&legend=true&tooltip=false

References

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