Use ContentRetriever

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/Customer.java

@@ -13,5 +13,4 @@ public class Customer {
     public String name;
     public String email;
     public int transactionLimit;
-    public int distanceLimit;
 }

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/CustomerRepository.java

@@ -13,11 +13,4 @@ public int getTransactionLimit(String customerName, String customerEmail) {
         		customerName,
         		customerEmail).firstResult().transactionLimit;
     }
-
-	@Tool("Get the distance limit for a given customer")
-    public int getDistanceLimit(String customerName, String customerEmail) {
-		return find("name = ?1 and email = ?2", 
-        		customerName,
-        		customerEmail).firstResult().distanceLimit;
-    }
 }

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/FraudDetectionAi.java

@@ -8,26 +8,19 @@
 import dev.langchain4j.service.UserMessage;
 import io.quarkiverse.langchain4j.RegisterAiService;
 
-@RegisterAiService(tools = { TransactionRepository.class, CustomerRepository.class })
+@RegisterAiService(retrievalAugmentor = FraudDetectionRetrievalAugmentor.class)
 public interface FraudDetectionAi {
 
     @SystemMessage("""
             You are a bank account fraud detection AI. You have to detect frauds in transactions.
             """)
     @UserMessage("""
-            Your task is to detect whether a fraud was committed for the customer {{customerName}}.
-
-            To detect a fraud, perform the following actions:
-            1 - Retrieve the transaction limit for the customer {{customerName}} with the {{customerEmail}} email address.
-            2 - Retrieve the transactions for the customer {{customerName}} with the {{customerEmail}} email address for the last 15 minutes.
-            3 - Sum the amount of all of these transactions. Make sure the sum is correct.
-            4 - If the amount is greater than the transaction limit for this customer, a fraud is detected.
+            Your task is to detect whether a fraud was committed for the customer {{customerName}} with the {{customerEmail}} email.
 
             Answer with a **single** JSON document containing:
             - the customer name in the 'customer-name' key
-            - the 'returning-customer' key set to a boolean value indicating if the same query was already issued before 
             - the transaction limit in the 'transaction-limit' key
-            - the computed sum in the 'total' key
+            - the computed sum of all transactions in the 'total' key
             - the 'fraud' key set to a boolean value indicating if a fraud was detected
             - the 'transactions' key containing the list of transaction amounts
             - the 'explanation' key containing a explanation of your answer, including how the sum is computed.
@@ -37,37 +30,4 @@ public interface FraudDetectionAi {
             """)
     @Timeout(value = 2, unit = ChronoUnit.MINUTES)
     String detectAmountFraudForCustomer(String customerName, String customerEmail);
-
-    @SystemMessage("""
-            You are a bank account fraud detection AI. You have to detect frauds in transactions.
-            """)
-    @UserMessage("""
-            Detect frauds based on the distance between two transactions for the customer: {{customerName}}.
-
-            To detect a fraud, perform the following actions:
-            1 - Retrieve the distance limit in kilometers for the customer {{customerName}} with the {{customerEmail}} email address.
-            2 - Retrieve the transactions for the customer {{customerName}} with the {{customerEmail}} email address for the last 15 minutes.
-            3 - Retrieve the city for each transaction.
-            4 - Check if the distance between 2 cities is greater than the distance limit, if so, a fraud is detected.
-            5 - If a fraud is detected, find the two transactions associated with these cities.
-
-            Answer with a **single** JSON document containing:
-            - the customer name in the 'customer-name' key
-            - the distance limit in the 'distance-limit' key
-            - the amount of the first transaction in the 'first-amount' key
-            - the amount of the second transaction in the 'second-amount' key
-            - the city of the first transaction in the 'first-city' key
-            - the city of the second transaction in the 'second-city' key
-            - the 'fraud' key set to a boolean value indicating if a fraud was detected (so the distance is greater than the distance limit)
-            - the 'distance' key set to the distance between the two cities
-            - the 'explanation' key containing a explanation of your answer.
-            - the 'cities' key containing all the cities for the transactions for the customer {{customerName}} in the last 15 minutes.
-            - if there is a fraud, the 'email' key containing an email to the customer {{customerName}} to warn about the fraud.
-
-            Your response must be just the raw JSON document, without ```json, ``` or anything else.  Do not use null JSON properties.
-
-            """)
-    @Timeout(value = 2, unit = ChronoUnit.MINUTES)
-    String detectDistanceFraudForCustomer(String customerName, String customerEmail);
-
 }

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/FraudDetectionContentRetriever.java

@@ -0,0 +1,30 @@
+package io.quarkiverse.langchain4j.sample;
+
+import java.util.List;
+
+import org.eclipse.microprofile.jwt.JsonWebToken;
+import org.jboss.logging.Logger;
+
+import dev.langchain4j.rag.content.Content;
+import dev.langchain4j.rag.content.retriever.ContentRetriever;
+import dev.langchain4j.rag.query.Query;
+import jakarta.enterprise.context.ApplicationScoped;
+import jakarta.inject.Inject;
+
+@ApplicationScoped
+public class FraudDetectionContentRetriever implements ContentRetriever {
+	private static final Logger log = Logger.getLogger(FraudDetectionContentRetriever.class);
+
+	@Inject
+	TransactionRepository transactionRepository;
+
+	@Inject
+	CustomerRepository customerRepository;
+
+	@Override
+    public List<Content> retrieve(Query query) {
+        JsonWebToken idToken = (JsonWebToken)query.metadata().chatMemoryId();
+        // User the customer name and email to retrive the content and return it as JSON
+        return List.of();
+    }
+}

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/FraudDetectionResource.java

@@ -28,10 +28,4 @@ public FraudDetectionResource(FraudDetectionAi service) {
     public String detectBaseOnAmount() {
     	return service.detectAmountFraudForCustomer(idToken.getName(), idToken.getClaim(Claims.email));
     }
-
-    @GET
-    @Path("/distance")
-    public String detectBasedOnDistance() {
-        return service.detectDistanceFraudForCustomer(idToken.getName(), idToken.getClaim(Claims.email));
-    }
 }

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/FraudDetectionRetrievalAugmentor.java

@@ -0,0 +1,22 @@
+package io.quarkiverse.langchain4j.sample;
+
+import java.util.function.Supplier;
+
+import dev.langchain4j.rag.DefaultRetrievalAugmentor;
+import dev.langchain4j.rag.RetrievalAugmentor;
+import jakarta.enterprise.context.ApplicationScoped;
+import jakarta.inject.Inject;
+
+@ApplicationScoped
+public class FraudDetectionRetrievalAugmentor implements Supplier<RetrievalAugmentor> {
+
+    @Inject
+    FraudDetectionContentRetriever contentRetriever;
+
+    @Override
+    public RetrievalAugmentor get() {
+        return DefaultRetrievalAugmentor.builder()
+            .contentRetriever(contentRetriever)
+            .build();
+    }
+}

samples/secure-fraud-detection/src/main/java/io/quarkiverse/langchain4j/sample/Setup.java

@@ -4,12 +4,11 @@
 import java.util.List;
 import java.util.Random;
 
+import io.quarkus.runtime.StartupEvent;
 import jakarta.enterprise.context.ApplicationScoped;
 import jakarta.enterprise.event.Observes;
 import jakarta.transaction.Transactional;
 
-import io.quarkus.runtime.StartupEvent;
-
 @ApplicationScoped
 public class Setup {
 
@@ -29,21 +28,18 @@ public void init(@Observes StartupEvent ev, CustomerRepository customers, Transa
             customer1.name = "Clement Escofier";
             customer1.email = "[email protected]";
             customer1.transactionLimit = 10000;
-            customer1.distanceLimit = 500;
             customers.persist(customer1);
 
             var customer2 = new Customer();
             customer2.name = "Georgios Andrianakis";
             customer2.email = "[email protected]";
             customer2.transactionLimit = 1000;
-            customer1.distanceLimit = 300;
             customers.persist(customer2);
 
             var customer3 = new Customer();
             customer3.name = "Sergey Beryozkin";
             customer3.email = "[email protected]";
             customer1.transactionLimit = 500;
-            customer1.distanceLimit = 100;
             customers.persist(customer3);
         }