Merge pull request #542 from wcmc-its/development

Merging the model and other code chanegs to the production.

k8-buildspec.yml

@@ -9,6 +9,21 @@ phases:
       - java -version 
   pre_build:
       commands:
+        # Fetch Docker credentials from AWS Secrets Manager
+        - echo "Fetching Docker credentials from AWS Secrets Manager"
+        - SECRET=$(aws secretsmanager get-secret-value --secret-id docker-hub-credentials --query "SecretString" --output text)
+
+        # Extract username and password from the JSON response
+        - DOCKER_USERNAME=$(echo $SECRET | sed -n 's/.*"username":"\([^"]*\)".*/\1/p')
+        - DOCKER_PASSWORD=$(echo $SECRET | sed -n 's/.*"password":"\([^"]*\)".*/\1/p')
+
+        # Print the Docker username to the CodeBuild log
+        - echo "Docker Username $DOCKER_USERNAME"
+
+        # Log in to Docker registry
+        - echo "Logging in to Docker registry"
+        - echo "$DOCKER_PASSWORD" | docker login --username $DOCKER_USERNAME --password-stdin
+
         - TAG="$CODEBUILD_BUILD_NUMBER.$(date +%Y-%m-%d.%H.%M.%S).$(echo $CODEBUILD_RESOLVED_SOURCE_VERSION | head -c 8)"
         - echo $TAG
         - sed -i.bak -e 's@CONTAINER_IMAGE@'"$REPOSITORY_URI:$TAG"'@' kubernetes/k8-deployment.yaml
@@ -31,11 +46,14 @@ phases:
         if expr "${BRANCH}" : ".*master" >/dev/null || expr "${BRANCH}" : ".*dev" >/dev/null; then
           docker build --tag $REPOSITORY_URI:$TAG .
           docker push $REPOSITORY_URI:$TAG
+          # Log out from the Docker registry to clear credentials
+          docker logout $REPOSITORY_URI
           aws eks update-kubeconfig --name $EKS_CLUSTER_NAME --region us-east-1 --role-arn $EKS_KUBECTL_ROLE_ARN
         fi
         if expr "${BRANCH}" : ".*master" >/dev/null; then
           kubectl set image deployment/reciter-prod reciter=$REPOSITORY_URI:$TAG -n $EKS_CLUSTER_NAME
         fi
         if expr "${BRANCH}" : ".*dev" >/dev/null; then
           kubectl set image deployment/reciter-dev reciter=$REPOSITORY_URI:$TAG -n $EKS_CLUSTER_NAME
-        fi
+          
+        fi

src/main/java/reciter/algorithm/cluster/article/scorer/ReCiterArticleScorer.java

@@ -491,8 +491,11 @@ private static double getAuthorsCountScore(AuthorCountEvidence evidence)
 
  	private static double getEducationYearScore(EducationYearEvidence evidence) {
  	    return Optional.ofNullable(evidence)
- 	            .map(EducationYearEvidence::getDiscrepancyDegreeYearDoctoralScore)
- 	            .orElse(0.0);
+ 	    				.map(EducationYearEvidence::getDiscrepancyDegreeYearDoctoralScore)
+ 	    				.filter(score -> score != 0.0)  
+ 	    				.orElseGet(() -> Optional.ofNullable(evidence)
+                                 				 .map(EducationYearEvidence::getDiscrepancyDegreeYearBachelorScore)
+                                 				 .orElse(0.0));
  	}
 
  	private static double getEmailMatchScore(EmailEvidence evidence) {

src/main/java/reciter/algorithm/feedback/article/scorer/ReciterFeedbackArticleScorer.java

@@ -576,7 +576,11 @@ private List<ReCiterArticle> executePythonScriptForArticleFeedbackTotal(List<ReC
 			  JSONArray articlesIdentityFeedbackScoreTotal = nnmodel.executeArticleScorePredictor("FeedbackIdentityScore", "feedbackIdentityScoreArticles.py",fileName,feedbackIdentityS3BucketName,isS3UploadRequiredString);
 			  log.info("articlesIdentityFeedbaclScoreTotal length",articlesIdentityFeedbackScoreTotal!=null?articlesIdentityFeedbackScoreTotal.length():0);
 			  if(articlesIdentityFeedbackScoreTotal!=null && articlesIdentityFeedbackScoreTotal.length() > 0)
-				  return mapAuthorshipLikelihoodScore(reCiterArticles, articlesIdentityFeedbackScoreTotal);
+			  {  
+				  List<ReCiterArticle> articlesScores =  mapAuthorshipLikelihoodScore(reCiterArticles, articlesIdentityFeedbackScoreTotal);
+			  		articlesScores.forEach(article -> log.info("articleId :", article.getArticleId(), "authorshipLikelihoodScore : ", article.getAuthorshipLikelihoodScore() ));
+			  	 return articlesScores;	
+			  }  	
 
 
 		} catch (IOException e) {
@@ -653,7 +657,10 @@ private static double getAuthorsCountScore(AuthorCountEvidence evidence)
 	private static double getEducationYearScore(EducationYearEvidence evidence) {
 	    return Optional.ofNullable(evidence)
 	            .map(EducationYearEvidence::getDiscrepancyDegreeYearDoctoralScore)
-	            .orElse(0.0);
+	            .filter(score -> score != 0.0)  
+	            .orElseGet(() -> Optional.ofNullable(evidence)
+	                                      .map(EducationYearEvidence::getDiscrepancyDegreeYearBachelorScore)
+	                                      .orElse(0.0));   
 	}
 
 	private static double getEmailMatchScore(EmailEvidence evidence) {
@@ -711,6 +718,7 @@ private static List<ReCiterArticle> mapAuthorshipLikelihoodScore(List<ReCiterArt
 				 				 .map(article -> {
 				 					 // Find the JSON object that corresponds to this article's ID
 				 		        	ReCiterArticle reCiterArticle = findJSONObjectById(authorshipLikelihoodScoreArray, article);
+				 		        	log.info("After setting the score to article***",reCiterArticle.getAuthorshipLikelihoodScore());
 				 		            // count the targetAuthors per article
 				 		        	 	long targetAuthorCount = article.getArticleCoAuthors().getAuthors().stream()
 				 		                     .filter(ReCiterAuthor::isTargetAuthor)  // Filter target authors
@@ -736,11 +744,14 @@ else if (reCiterArticle == null) {
 	private static ReCiterArticle findJSONObjectById(JSONArray jsonArray, ReCiterArticle article) {
 	    for (int i = 0; i < jsonArray.length(); i++) {
 	        JSONObject jsonObject = jsonArray.getJSONObject(i);
+	        log.info("ArticleId from JSONArray: ", jsonObject.getLong("id") , ", Article Id from ReCiterArticle: " , article.getArticleId());
 	        if (jsonObject.getLong("id") == article.getArticleId()) {
 	            /*article.setAuthorshipLikelihoodScore(BigDecimal.valueOf(jsonObject.getDouble("scoreTotal")*100)
 	                    .setScale(3, RoundingMode.DOWN)
 	                    .doubleValue());*/
+	        	log.info("both articleIds are matching and Score is ***",jsonObject.getDouble("scoreTotal"));
 	        	article.setAuthorshipLikelihoodScore(jsonObject.getDouble("scoreTotal")*100);
+	        	log.info("After setting the score to article***",article.getAuthorshipLikelihoodScore());
 	            return article; // Return the modified article
 	        }
 	    }