Add secure-fraud-detection demo

pom.xml

@@ -198,6 +198,7 @@
         <module>samples/cli-translator</module>
         <module>samples/review-triage</module>
         <module>samples/fraud-detection</module>
+        <module>samples/secure-fraud-detection</module>
         <module>samples/chatbot</module>
         <module>samples/chatbot-easy-rag</module>
         <module>samples/sql-chatbot</module>

samples/secure-fraud-detection/README.md

@@ -0,0 +1,118 @@
+# Secure Fraud Detection Demo
+
+This demo showcases the implementation of a secure fraud detection system which is available only to users authenticated with Google.
+It uses the `gpt-3.5-turbo` LLM, use `quarkus.langchain4j.openai.chat-model.model-name` property to select a different model.
+
+## The Demo
+
+### Setup
+
+The demo requires that your Google account's full name and email are configured.
+You can use system or env properties, see `Running the Demo` section below.
+
+When the application starts, 5 transactions with random amounts between 1 and 1000 are generated for the registered user.
+A random city is also assigned to each transaction.
+
+The setup is defined in the [Setup.java](./src/main/java/io/quarkiverse/langchain4j/samples/Setup.java) class.
+
+The registered user and transactions are stored in a PostgreSQL database. When running the demo in dev mode (recommended), the database is automatically created and populated.
+
+### Content Retrieval
+
+To enable fraud detection, we provide the LLM with access to the custom [FraudDetectionContentRetriever](./src/main/java/io/quarkiverse/langchain4j/samples/FraudDetectionContentRetriever.java) content retriever.
+
+`FraudDetectionContentRetriever` is registered by [FraudDetectionRetrievalAugmentor](./src/main/java/io/quarkiverse/langchain4j/samples/FraudDetectionRetrievalAugmentor.java).
+
+It can only be accessed securely and it retrieves transaction data for the currently authenticated user through two Panache repositories:
+
+- [CustomerRepository.java](./src/main/java/io/quarkiverse/langchain4j/samples/CustomerRepository.java)
+- [TransactionRepository.java](./src/main/java/io/quarkiverse/langchain4j/samples/TransactionRepository.java)
+
+It extracts the authenticated user's name and email from an injected `JsonWebToken` ID token.
+
+### AI Service
+
+This demo leverages the AI service abstraction, with the interaction between the LLM and the application handled through the AIService interface.
+
+The `io.quarkiverse.langchain4j.sample.FraudDetectionAi` interface uses specific annotations to define the LLM:
+
+```java
+@RegisterAiService(retrievalAugmentor = FraudDetectionRetrievalAugmentor.class)
+```
+
+For each message, the prompt is engineered to help the LLM understand the context and answer the request:
+
+```java
+    @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.
+
+            Answer with a **single** JSON document containing:
+            - the customer name in the 'customer-name' key
+            - the transaction limit in the 'transaction-limit' key
+            - the computed sum of all transactions committed during the last 15 minutes in the 'total' key
+            - the 'fraud' key set to true if the computed sum of all transactions is greater than the transaction limit
+            - the 'transactions' key containing an array of JSON objects. Each object must have transaction 'amount', 'city' and formatted 'time' keys.
+            - the 'explanation' key containing an explanation of your answer.
+            - the 'email' key containing the customer email if the fraud was detected. 
+
+           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 detectAmountFraudForCustomer();
+```
+
+_Note:_ You can also use fault tolerance annotations in combination with the prompt annotations.
+
+### Using the AI service
+
+Once defined, you can inject the AI service as a regular bean, and use it:
+
+```java
+package io.quarkiverse.langchain4j.sample;
+
+import io.quarkus.security.Authenticated;
+import jakarta.ws.rs.GET;
+import jakarta.ws.rs.Path;
+
+@Path("/fraud")
+@Authenticated
+public class FraudDetectionResource {
+
+    private final FraudDetectionAi service;
+
+    public FraudDetectionResource(FraudDetectionAi service) {
+        this.service = service;
+    }
+
+    @GET
+    @Path("/amount")
+    public String detectBaseOnAmount() {
+    	return service.detectAmountFraudForCustomer();
+    }
+}
+```
+
+`FraudDetectionResource` can only be accessed by authenticated users.
+
+## Google Authentication
+
+This demo requires users to authenticate with Google.
+All you need to do is to register an application with Google, follow steps listed in the [Quarkus Google](https://quarkus.io/guides/security-openid-connect-providers#google) section.
+Name your Google application as `Quarkus LangChain4j AI`, and make sure an allowed callback URL is set to `http://localhost:8080/login`.
+Google will generate a client id and secret, use them to set `quarkus.oidc.client-id` and `quarkus.oidc.credentials.secret` properties.
+
+## Running the Demo
+
+To run the demo, use the following command:
+
+```shell
+mvn quarkus:dev -Dname="Firstname Familyname" [email protected]
+```
+
+Note, you should use double quotes to register your Google account's full name.
+
+Then, access `http://localhost:8080`, login to Google, and follow a provided application link to check the fraud.
+

samples/secure-fraud-detection/pom.xml

@@ -0,0 +1,134 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+
+    <groupId>io.quarkiverse.langchain4j</groupId>
+    <artifactId>quarkus-langchain4j-sample-secure-fraud-detection</artifactId>
+    <name>Quarkus LangChain4j - Sample - Secure Fraud Detection</name>
+    <version>1.0-SNAPSHOT</version>
+
+    <properties>
+        <compiler-plugin.version>3.13.0</compiler-plugin.version>
+        <maven.compiler.parameters>true</maven.compiler.parameters>
+        <maven.compiler.release>17</maven.compiler.release>
+        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+        <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
+        <quarkus.platform.artifact-id>quarkus-bom</quarkus.platform.artifact-id>
+        <quarkus.platform.group-id>io.quarkus</quarkus.platform.group-id>
+        <quarkus.platform.version>3.9.4</quarkus.platform.version>
+        <skipITs>true</skipITs>
+        <surefire-plugin.version>3.2.5</surefire-plugin.version>
+        <quarkus-langchain4j.version>0.15.1</quarkus-langchain4j.version>
+    </properties>
+
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>${quarkus.platform.group-id}</groupId>
+                <artifactId>${quarkus.platform.artifact-id}</artifactId>
+                <version>${quarkus.platform.version}</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
+
+    <dependencies>
+        <dependency>
+            <groupId>io.quarkus</groupId>
+            <artifactId>quarkus-resteasy-reactive-jackson</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>io.quarkus</groupId>
+            <artifactId>quarkus-oidc</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>io.quarkiverse.langchain4j</groupId>
+            <artifactId>quarkus-langchain4j-openai</artifactId>
+            <version>${quarkus-langchain4j.version}</version>
+        </dependency>
+        <dependency>
+             <groupId>io.quarkus</groupId>
+             <artifactId>quarkus-smallrye-fault-tolerance</artifactId>
+         </dependency>
+        <dependency>
+            <groupId>io.quarkus</groupId>
+            <artifactId>quarkus-jdbc-postgresql</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>io.quarkus</groupId>
+            <artifactId>quarkus-hibernate-orm-panache</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>io.quarkus</groupId>
+            <artifactId>quarkus-resteasy-reactive-qute</artifactId>
+        </dependency>
+    </dependencies>
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>io.quarkus</groupId>
+                <artifactId>quarkus-maven-plugin</artifactId>
+                <version>${quarkus.platform.version}</version>
+                <executions>
+                    <execution>
+                        <goals>
+                            <goal>build</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+            <plugin>
+                <artifactId>maven-compiler-plugin</artifactId>
+                <version>${compiler-plugin.version}</version>
+            </plugin>
+            <plugin>
+                <artifactId>maven-surefire-plugin</artifactId>
+                <version>3.2.5</version>
+                <configuration>
+                    <systemPropertyVariables>
+                        <java.util.logging.manager>org.jboss.logmanager.LogManager</java.util.logging.manager>
+                        <maven.home>${maven.home}</maven.home>
+                    </systemPropertyVariables>
+                </configuration>
+            </plugin>
+        </plugins>
+    </build>
+
+    <profiles>
+        <profile>
+            <id>native</id>
+            <activation>
+                <property>
+                    <name>native</name>
+                </property>
+            </activation>
+            <build>
+                <plugins>
+                    <plugin>
+                        <artifactId>maven-failsafe-plugin</artifactId>
+                        <version>3.2.5</version>
+                        <executions>
+                            <execution>
+                                <goals>
+                                    <goal>integration-test</goal>
+                                    <goal>verify</goal>
+                                </goals>
+                                <configuration>
+                                    <systemPropertyVariables>
+                                        <native.image.path>${project.build.directory}/${project.build.finalName}-runner</native.image.path>
+                                        <java.util.logging.manager>org.jboss.logmanager.LogManager</java.util.logging.manager>
+                                        <maven.home>${maven.home}</maven.home>
+                                    </systemPropertyVariables>
+                                </configuration>
+                            </execution>
+                        </executions>
+                    </plugin>
+                </plugins>
+            </build>
+            <properties>
+                <quarkus.package.type>native</quarkus.package.type>
+            </properties>
+        </profile>
+    </profiles>
+</project>

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

@@ -0,0 +1,16 @@
+package io.quarkiverse.langchain4j.sample;
+
+import jakarta.persistence.Entity;
+import jakarta.persistence.GeneratedValue;
+import jakarta.persistence.Id;
+
+@Entity
+public class Customer {
+
+    @Id
+    @GeneratedValue
+    public Long id;
+    public String name;
+    public String email;
+    public int transactionLimit;
+}

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

@@ -0,0 +1,11 @@
+package io.quarkiverse.langchain4j.sample;
+
+import io.smallrye.config.ConfigMapping;
+
+@ConfigMapping(prefix = "customer")
+public interface CustomerConfig {
+
+    String name();
+
+    String email();
+}

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

@@ -0,0 +1,19 @@
+package io.quarkiverse.langchain4j.sample;
+
+import io.quarkus.hibernate.orm.panache.PanacheRepository;
+import jakarta.enterprise.context.ApplicationScoped;
+
+@ApplicationScoped
+public class CustomerRepository implements PanacheRepository<Customer> {
+
+    /*
+     * Transaction limit for the customer.
+     */
+    public int getTransactionLimit(String customerName, String customerEmail) {
+        Customer customer = find("name = ?1 and email = ?2", customerName, customerEmail).firstResult();
+        if (customer == null) {
+            throw new MissingCustomerException();
+        }
+        return customer.transactionLimit;
+    }
+}

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

@@ -0,0 +1,33 @@
+package io.quarkiverse.langchain4j.sample;
+
+import java.time.temporal.ChronoUnit;
+
+import org.eclipse.microprofile.faulttolerance.Timeout;
+
+import dev.langchain4j.service.SystemMessage;
+import dev.langchain4j.service.UserMessage;
+import io.quarkiverse.langchain4j.RegisterAiService;
+
+@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.
+
+             Answer with a **single** JSON document containing:
+             - the customer name in the 'customer-name' key
+             - the transaction limit in the 'transaction-limit' key
+             - the computed sum of all transactions committed during the last 15 minutes in the 'total' key
+             - the 'fraud' key set to true if the computed sum of all transactions is greater than the transaction limit
+             - the 'transactions' key containing an array of JSON objects. Each object must have transaction 'amount', 'city' and formatted 'time' keys.
+             - the 'explanation' key containing an explanation of your answer.
+             - the 'email' key containing the customer email if the fraud was detected.
+
+            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 detectAmountFraudForCustomer();
+}