refactor predict class

backend/src/main/java/com/example/BriefMe/BriefMeApplication.java

@@ -13,8 +13,5 @@ public class BriefMeApplication {
 	public static void main(String[] args) throws IOException {
 
 		SpringApplication.run(BriefMeApplication.class, args);
-		PredictTextSummarizationSample predictTextSummarization = new PredictTextSummarizationSample();
-		predictTextSummarization.predict();
-
 	}
 }

backend/src/main/java/com/example/BriefMe/properties/VertexAIProperties.java

@@ -0,0 +1,34 @@
+package com.example.BriefMe.properties;
+
+import lombok.Getter;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Component;
+
+@Component
+@Getter
+public class VertexAIProperties {
+
+    @Value("${google.vertex-ai.project}")
+    String project;
+
+    @Value("${google.vertex-ai.location}")
+    String location;
+
+    @Value("${google.vertex-ai.publisher}")
+    String publisher;
+
+    @Value("${google.vertex-ai.model}")
+    String model;
+
+    @Value("${google.vertex-ai.model.temperature}")
+    Double temperature;
+
+    @Value("${google.vertex-ai.model.max-output-token}")
+    Integer maxOutputToken;
+
+    @Value("${google.vertex-ai.model.top-p}")
+    Double topP;
+
+    @Value("${google.vertex-ai.model.top-k}")
+    Integer topK;
+}

backend/src/main/java/com/example/BriefMe/request/VertexAIPrompt.java → backend/src/main/java/com/example/BriefMe/request/VertexAIData.java

@@ -5,6 +5,6 @@
 
 @Data
 @AllArgsConstructor
-public class VertexAIPrompt {
+public class VertexAIData {
     String prompt;
 }

backend/src/main/java/com/example/BriefMe/service/impl/PredictTextSummarizationSample.java

@@ -1,9 +1,15 @@
 package com.example.BriefMe.service.impl;
 
+import com.example.BriefMe.properties.VertexAIProperties;
 import com.example.BriefMe.request.VertexAIParameters;
-import com.example.BriefMe.request.VertexAIPrompt;
+import com.example.BriefMe.request.VertexAIData;
+import com.example.BriefMe.service.client.TextSummarizer;
+import com.fasterxml.jackson.core.JsonProcessingException;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import java.io.IOException;
+import javax.print.DocFlavor.STRING;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 import com.google.cloud.aiplatform.v1beta1.EndpointName;
 import com.google.cloud.aiplatform.v1beta1.PredictResponse;
@@ -16,67 +22,83 @@
 
 
 @Service
-public class PredictTextSummarizationSample {
-    public void predict() throws IOException {
-        String text ="";
-        VertexAIPrompt vertexAIPrompt = new VertexAIPrompt("Provide a short summary in five numeric bullet points:" + text);
-        ObjectMapper objectMapper = new ObjectMapper();
-        String vertexAIRequestString = objectMapper.writeValueAsString(vertexAIPrompt);
+@Slf4j
+public class PredictTextSummarizationSample implements TextSummarizer {
 
-        VertexAIParameters vertexAIParameters = new VertexAIParameters(0.2, 256, 0.95, 40);
-        String vertexAIParamsString = objectMapper.writeValueAsString(vertexAIParameters);
+    //TODO: Set vaules in application.properties
+    @Autowired
+    VertexAIProperties vertexAIProperties;
+    @Override
+    public String generateSummary(String text, int numberOfLines) {
+        try{
+            String prompt = createPromptString(text, numberOfLines);
+            String parameters= createParametersString();
 
-
-        String project = "artful-lane-419217";
-        String location = "us-central1";
-        String publisher = "google";
-        String model = "text-bison@001";
+            String endpoint = String.format("%s-aiplatform.googleapis.com:443", vertexAIProperties.getLocation());
+            PredictionServiceSettings predictionServiceSettings =
+                    PredictionServiceSettings.newBuilder()
+                            .setEndpoint(endpoint)
+                            .build();
 
-        predictTextSummarization(vertexAIRequestString, vertexAIParamsString, project, location, publisher, model);
-    }
-
-    // Get summarization from a supported text model
-    public void predictTextSummarization(
-            String instance,
-            String parameters,
-            String project,
-            String location,
-            String publisher,
-            String model)
-            throws IOException {
-        String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
+            // Initialize client
+            try (PredictionServiceClient predictionServiceClient =
+                    PredictionServiceClient.create(predictionServiceSettings)) {
+                final EndpointName endpointName =
+                        EndpointName.ofProjectLocationPublisherModelName(
+                                vertexAIProperties.getProject(),
+                                vertexAIProperties.getLocation(),
+                                vertexAIProperties.getPublisher(),
+                                vertexAIProperties.getModel());
 
-        PredictionServiceSettings predictionServiceSettings =
-                PredictionServiceSettings.newBuilder()
-                        .setEndpoint(endpoint)
-                        .build();
+                // Use Value.Builder to convert prompt to a dynamically typed value
+                Value.Builder instanceValue = Value.newBuilder();
+                JsonFormat.parser().merge(prompt, instanceValue);
+                List<Value> instances = new ArrayList<>();
+                instances.add(instanceValue.build());
 
-        // Initialize client that will be used to send requests. This client only needs to be created
-        // once, and can be reused for multiple requests.
-        try (PredictionServiceClient predictionServiceClient =
-                PredictionServiceClient.create(predictionServiceSettings)) {
-            final EndpointName endpointName =
-                    EndpointName.ofProjectLocationPublisherModelName(project, location, publisher, model);
+                // Use Value.Builder to convert parameter to a dynamically typed value
+                Value.Builder parameterValueBuilder = Value.newBuilder();
+                JsonFormat.parser().merge(parameters, parameterValueBuilder);
+                Value parameterValue = parameterValueBuilder.build();
 
-            // Use Value.Builder to convert instance to a dynamically typed value that can be
-            // processed by the service.
-            Value.Builder instanceValue = Value.newBuilder();
-            JsonFormat.parser().merge(instance, instanceValue);
-            List<Value> instances = new ArrayList<>();
-            instances.add(instanceValue.build());
+                PredictResponse predictResponse =
+                        predictionServiceClient.predict(endpointName, instances, parameterValue);
 
-            // Use Value.Builder to convert parameter to a dynamically typed value that can be
-            // processed by the service.
-            Value.Builder parameterValueBuilder = Value.newBuilder();
-            JsonFormat.parser().merge(parameters, parameterValueBuilder);
-            Value parameterValue = parameterValueBuilder.build();
+                //TODO: Fetch and return data
+                System.out.println("Predict Response");
+                System.out.println(predictResponse);
+            }
 
-            PredictResponse predictResponse =
-                    predictionServiceClient.predict(endpointName, instances, parameterValue);
+        } catch (Exception e) {
+            throw new RuntimeException(e);
+        }
+        return "Nothing to summarize";
+    }
 
-            System.out.println("Predict Response");
-            System.out.println(predictResponse);
+    private String createPromptString(String text, int numberOfLines){
+        try{
+            String prompt = "Provide a short summary in "+ numberOfLines +" numeric bullet points:" + text;
+            VertexAIData vertexAIData = new VertexAIData(prompt);
+            ObjectMapper objectMapper = new ObjectMapper();
+            return objectMapper.writeValueAsString(vertexAIData);
+        } catch (JsonProcessingException e) {
+            log.error("Exception occurred while creating prompt string {}", e.getMessage());
+            throw new RuntimeException(e);
         }
     }
 
+    private String createParametersString(){
+        try{
+            ObjectMapper objectMapper = new ObjectMapper();
+            VertexAIParameters vertexAIParameters = new VertexAIParameters(
+                    vertexAIProperties.getTemperature(),
+                    vertexAIProperties.getMaxOutputToken(),
+                    vertexAIProperties.getTopP(),
+                    vertexAIProperties.getTopK());
+            return objectMapper.writeValueAsString(vertexAIParameters);
+        } catch (JsonProcessingException e) {
+            log.error("Exception occurred while creating parameters string {}", e.getMessage());
+            throw new RuntimeException(e);
+        }
+    }
 }