Java V2 FSA

.doc_gen/cross-content/cross_FSA_Java_block.xml

@@ -0,0 +1,33 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE chapter PUBLIC "-//OASIS//DTD DocBook XML V4.5//EN" "file://zonbook/docbookx.dtd" [
+  <!ENTITY % phrases-shared SYSTEM "file://AWSShared/common/phrases-shared.ent">
+  %phrases-shared;
+]>
+<block>
+  <para>
+    This example application analyzes and stores customer feedback cards. Specifically,
+    it fulfills the need of a fictitious hotel in New York City. The hotel receives feedback
+    from guests in various languages in the form of physical comment cards. That feedback
+    is uploaded into the app through a web client.
+
+    After an image of a comment card is uploaded, the following steps occur:
+  </para>
+  <itemizedlist>
+    <listitem>
+      <para>Text is extracted from the image using &TEXTRACT;.</para>
+    </listitem>
+    <listitem>
+      <para>&CMP; determines the sentiment of the extracted text and its language.</para>
+    </listitem>
+    <listitem>
+      <para>The extracted text is translated to French using &TSL;.</para>
+    </listitem>
+    <listitem>
+      <para>&POL; synthesizes an audio file from the extracted text.</para>
+    </listitem>
+  </itemizedlist>
+  <para> The full app can be deployed with the &CDK;. For source code and deployment
+    instructions, see the project in <ulink
+      url="https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/creating_fsa_app">
+    GitHub</ulink>. </para>
+</block>

.doc_gen/metadata/cross_metadata.yaml

@@ -6,6 +6,10 @@ cross_FSA:
             their original language, determines their sentiment, and generates an audio file
             from the translated text.
   languages:
+    Java:
+      versions:
+        - sdk_version: 2
+          block_content: cross_FSA_Java_block.xml
     Ruby:
       versions:
         - sdk_version: 3

.github/pre_validate/pre_validate.py

@@ -103,6 +103,7 @@
     'AKIAIOSFODNN7EXAMPLE',
     'APKAEIBAERJR2EXAMPLE',
     'AppStreamUsageReportsCFNGlueAthenaAccess',
+    'examples/blob/main/applications/feedback',
     'aws/acm/model/DescribeCertificateRequest',
     'aws/cloudtrail/model/LookupEventsRequest',
     'aws/codebuild/model/BatchGetBuildsResult',

applications/feedback_sentiment_analyzer/README.md

@@ -16,6 +16,7 @@ This application has been implemented with the following AWS SDKs.
 
 - [Ruby](../../ruby/cross_service_examples/feedback_sentiment_analyzer/README.md)
 - [JavaScript](../../javascriptv3/example_code/cross-services/feedback-sentiment-analyzer/README.md)
+- [Java](../../javav2/usecases/creating_fsa_app/README.md)
 
 To deploy one of these implementations, follow the [Deployment instructions](#deployment-instructions).
 

applications/feedback_sentiment_analyzer/cdk/lib/functions.ts

@@ -6,7 +6,6 @@
 import {resolve} from "path";
 import {BundlingOutput, Duration} from "aws-cdk-lib";
 import {Code, Runtime} from "aws-cdk-lib/aws-lambda";
-
 import {AppFunctionConfig} from "./constructs/app-lambdas";
 
 const BASE_APP_FUNCTION: AppFunctionConfig = {
@@ -55,7 +54,7 @@ const EXAMPLE_LANG_FUNCTIONS: AppFunctionConfig[] = [
       return Code.fromInline(`
         exports.handler = async (event) => {
           console.log("AnalyzeSentiment", event);
-          return { translated_text: "Bonjour", source_language: "en" }
+          return { translated_text: "Bonjour", source_language: "en"}
         }
     `);
     },
@@ -164,14 +163,63 @@ const JAVASCRIPT_FUNCTIONS = [
   },
 ];
 
+const JAVA_BUNDLING_CONFIG = {
+  command: [
+    "bash",
+    "-c",
+    "mvn install -DskipTests && cp target/creating_fsa_app-1.0-SNAPSHOT.jar /asset-output/",
+  ],
+  output: BundlingOutput.ARCHIVED,
+  user: "root",
+  image: Runtime.JAVA_11.bundlingImage,
+  volumes: [
+    {
+      hostPath: `${process.env.HOME}/.m2/`,
+      containerPath: "/root/.m2",
+    },
+  ],
+};
+
+const COMMON_JAVA_FUNCTION_CONFIG = {
+  ...BASE_APP_FUNCTION,
+  runtime: Runtime.JAVA_11,
+  codeAsset: () => {
+    const source = resolve("../../../javav2/usecases/creating_fsa_app");
+    return Code.fromAsset(source, {
+      bundling: JAVA_BUNDLING_CONFIG,
+    });
+  },
+};
+
+const JAVA_FUNCTIONS: AppFunctionConfig[] = [
+  {
+    ...COMMON_JAVA_FUNCTION_CONFIG,
+    name: "ExtractText",
+    handler: "com.example.fsa.handlers.ExtractTextHandler::handleRequest",
+  },
+  {
+    ...COMMON_JAVA_FUNCTION_CONFIG,
+    name: "AnalyzeSentiment",
+    handler: "com.example.fsa.handlers.AnalyzeSentimentHandler::handleRequest",
+  },
+  {
+    ...COMMON_JAVA_FUNCTION_CONFIG,
+    name: "TranslateText",
+    handler: "com.example.fsa.handlers.TranslateTextHandler::handleRequest",
+  },
+  {
+    ...COMMON_JAVA_FUNCTION_CONFIG,
+    name: "SynthesizeAudio",
+    handler: "com.example.fsa.handlers.SynthesizeAudioHandler::handleRequest",
+  },
+];
+
 const FUNCTIONS: Record<string, AppFunctionConfig[]> = {
   examplelang: EXAMPLE_LANG_FUNCTIONS,
-  // Add more languages here. For example
-  // javascript: JAVASCRIPT_FUNCTIONS,
   ruby: RUBY_FUNCTIONS,
+  java: JAVA_FUNCTIONS,
   javascript: JAVASCRIPT_FUNCTIONS,
 };
-
 export function getFunctions(language: string = ""): AppFunctionConfig[] {
   return FUNCTIONS[language] ?? FUNCTIONS.examplelang;
 }

javav2/README.md

@@ -25,7 +25,9 @@ The **javav2** folder in this repository contains examples of complete use cases
 
 In the **use_cases** folder, find step-by-step development tutorials that use multiple AWS services. By following these tutorials, you will gain a deeper understanding of how to create Java-based applications that use the AWS SDK for Java. Most of these AWS SDK for Java tutorials use the Synchronous Java client.
 
-If you are interested in using the Asynchronous Java client, see one of these tutorials:
+If you are interested in using Asynchronous Java service clients, see one of these tutorials:
+
++ [Creating a Feedback Sentiment Analyzer application using the SDK for Java](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/creating_fsa_app) - Discusses how to develop a Feedback Sentiment Analyzer application using Machine Learning AWS services. The application solves a fictitious use case of a hotel that receives guest feedback on comment cards in a variety of languages. The application is developed by using the AWS SDK for Java (v2) and asynchronous Java clients.
 
 + [Creating a dynamic web application that asynchronously analyzes photos using the AWS SDK for Java](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/creating_photo_analyzer_async) - Discusses using the AWS SDK for Java (asynchronous client) and various AWS services, such as the Amazon Rekognition service, to analyze images. This web MVC application can analyze many images and generate a report that breaks down each image into a series of labels.