You are currently viewing Using SUSI AI Server to Store User Feedback for a Skill

Using SUSI AI Server to Store User Feedback for a Skill

User feedback is valuable information that plays an important  role in improving the quality of service. In SUSI AI server we are planning to make a feedback mechanism to see if the user liked the answer or not. The result of that user input (which can be given using a vote button) will be then learned to enhance the future use of the rule. So as a first step for implementation of  skill rating system with guided learning, we need to store the user rating of a skill . In this blogpost we will learn how to make an endpoint for getting skill rating from user. This API endpoint will be used  by its web and mobile clients.
Before the implementation of API  let’s look how data is stored in SUSI AI Susi_server uses DAO in which skill rating is stored as JSONTray. 

 public JsonTray(File file_persistent, File file_volatile, int cachesize) throws IOException {
        this.per = new JsonFile(file_persistent);
        this.vol = new CacheMap<String, JSONObject>(cachesize);
        this.file_volatile = file_volatile;
        if (file_volatile != null && file_volatile.exists()) try {
            JSONObject j = JsonFile.readJson(file_volatile);
            for (String key: j.keySet()) this.vol.put(key, j.getJSONObject(key));
        } catch (IOException e) {

JsonTray takes three parameters the persistent file, volatile file and cache size to store them as cache map in String and JsonObject pairs. The HttpServlet class which provides methods, such as doGet and doPost, for handling HTTP-specific services.In Susi Server an abstract class AbstractAPIHandler extending HttpServelets and implementing API handler interface is provided. Next we will inherit our RateSkillService class from AbstractAPIHandler and implement APIhandler interface.

public class RateSkillService extends AbstractAPIHandler implements APIHandler {
    private static final long serialVersionUID =7947060716231250102L;
    public BaseUserRole getMinimalBaseUserRole() {
        return BaseUserRole.ANONYMOUS;

    public JSONObject getDefaultPermissions(BaseUserRole baseUserRole) {
        return null;

    public String getAPIPath() {
        return "/cms/rateSkill.json";


The getMinimalBaseRole method tells the minimum Userrole required to access this servlet it can also be ADMIN, USER. In our case it is Anonymous. A User need not to log in to access this endpoint. The getAPIPath() methods sets the API endpoint path, it gets appended to base path which is for local host .

Next we will implement serviceImpl method

    public ServiceResponse serviceImpl(Query call, HttpServletResponse response, Authorization rights, final JsonObjectWithDefault permissions) {

        String model_name = call.get("model", "general");
        File model = new File(DAO.model_watch_dir, model_name);
        String group_name = call.get("group", "knowledge");
        File group = new File(model, group_name);
        String language_name = call.get("language", "en");
        File language = new File(group, language_name);
        String skill_name = call.get("skill", null);
        File skill = new File(language, skill_name + ".txt");
        String skill_rate = call.get("rating", null);

        JSONObject result = new JSONObject();
        result.put("accepted", false);
        if (!skill.exists()) {
            result.put("message", "skill does not exist");
            return new ServiceResponse(result);

        JsonTray skillRating = DAO.skillRating;
        JSONObject modelName = new JSONObject();
        JSONObject groupName = new JSONObject();
        JSONObject languageName = new JSONObject();
        if (skillRating.has(model_name)) {
            modelName = skillRating.getJSONObject(model_name);
            if (modelName.has(group_name)) {
                groupName = modelName.getJSONObject(group_name);
                if (groupName.has(language_name)) {
                    languageName = groupName.getJSONObject(language_name);
                    if (languageName.has(skill_name)) {
                        JSONObject skillName = languageName.getJSONObject(skill_name);
                        skillName.put(skill_rate, skillName.getInt(skill_rate) + 1 + "");
                        languageName.put(skill_name, skillName);
                        groupName.put(language_name, languageName);
                        modelName.put(group_name, groupName);
                        skillRating.put(model_name, modelName, true);
                        result.put("accepted", true);
                        result.put("message", "Skill ratings updated");
                        return new ServiceResponse(result);
        languageName.put(skill_name, createRatingObject(skill_rate));
        groupName.put(language_name, languageName);
        modelName.put(group_name, groupName);
        skillRating.put(model_name, modelName, true);
        result.put("accepted", true);
        result.put("message", "Skill ratings added");
        return new ServiceResponse(result);


    /* Utility function*/
    public JSONObject createRatingObject(String skill_rate) {
        JSONObject skillName = new JSONObject();
        skillName.put("positive", "0");
        skillName.put("negative", "0");
        skillName.put(skill_rate, skillName.getInt(skill_rate) + 1 + "");
        return skillName;


One can access any skill based on four tuples parameters model, group, language, skill. Before rating a skill we must ensure whether it exists or not. We can get the required parameters through call.get() method where first parameter is the key for which we want to get the value and second parameter is the default value. If skill.exists() method return false we generate error message stating “No such skill exists”. Otherwise check if the skill exist in our skillRating.json file if so, update the current ratings otherwise create a new json object and add it to rating file based on model, group and language. After successful implementation go ahead and test your endpoint on http://localhost:4000/cms/rateSkill.json?model=general&group=knowledge&skill=who&rating=positive

You can also check for the updated json file in  susi_server/data/skill_rating/skillRating.json 

{"general": {
 "assistants": {"en": {
   "language_translation": {
     "negative": "1",
     "positive": "0"
 "smalltalk": {"en": {
   "aboutsusi": {
   "negative": "0",
   "positive": "1"
 "knowledge": {"en": {
   "who": {
     "negative": "2",
     "positive": "4"

And if the skill is not present if will generate error message

We have successfully implemented the API endpoint for storing the user skill’s feedback. For more information take a look at Susi server and join gitter chat channel for discussions.


Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.