Azure-Samples · haileytap · Feb 10, 2026 · Feb 10, 2026
diff --git a/quickstart-keyword-search/README.md b/quickstart-keyword-search/README.md
@@ -1,64 +1,33 @@
 ---
 page_type: sample
 languages:
-- java
+  - java
 name: "Quickstart: Keyword search in Azure AI Search using Java"
 description: |
   Learn how to create, load, and query an Azure AI Search index using the Azure SDK for Java.
 products:
-- azure
-- azure-cognitive-search
+  - azure
+  - azure-cognitive-search
 urlFragment: java-quickstart-keyword
 ---
 
 # Quickstart: Keyword search in Azure AI Search using Java
 
 ![Flask sample MIT license badge](https://img.shields.io/badge/license-MIT-green.svg)
 
-Learn how to create, load, and query a search index on Azure AI Search using Java and the [com.azure:azure-search-documents](https://search.maven.org/artifact/com.azure/azure-search-documents) package.
+This sample demonstrates the fundamentals of creating, loading, and querying a search index for full-text search, also known as keyword search. The index is modeled on a subset of the hotels dataset, which has been reduced for readability and comprehension.
 
-To run this sample, follow the step-by-step instructions in [Quickstart: Full-text search](https://learn.microsoft.com/azure/search/search-get-started-text?pivots=java).
+## What's in this sample
 
-## Prerequisites
+| File | Description |
+|------|-------------|
+| `pom.xml` | Project file that defines dependencies and build settings |
+| `App.java` | Creates an index, loads documents, and runs queries |
+| `Hotel.java`, `Address.java` | Model classes defining the index schema |
 
-- Azure AI Search. You can [create a search service in the portal](https://docs.microsoft.com/azure/search/search-create-service-portal).
+## Documentation
 
-- Install a Java SDK. This sample was tested on the [Microsoft Build of OpenJDK](https://learn.microsoft.com/java/openjdk/install).
-
-- Choose a strategy for building and running the project using [Maven](https://maven.apache.org/). This sample was tested using [Visual Studio Code](https://code.visualstudio.com/) with the [Java extension](https://marketplace.visualstudio.com/items?itemName=vscjava.vscode-java-pack).
-
-## Set up the sample
-
-1. Clone or download this sample repository.
-
-1. Extract contents if the download is a ZIP file. Make sure the files are read-write.
-
-1. Get the name of your search service. You can find the URL on the search service **Overview** page in the Azure portal.
-
-1. Make sure you have permissions to create, load, and query an index: **Search Service Contributor**, **Search Index Data Contributor**, and **Search Index Data Reader**.
-
-1. Run `az login` to sign in to your Azure account using the Azure CLI.
-
-1. In Visual Studio Code or another IDE, create a Java project.
-
-   - Press Ctrl-Shift-P to open the command palette.
-   - Search for and then select **Java: Create Java Project**.
-   - Select **No Build**.
-
-1. Open **App.java** and configure access to the search service by editing the variable for `searchServiceEndpoint`.
-
-## Run the sample
-
-1. In Visual Studio Code, press F5 to rebuild the app and run the program in its entirety.
-
-The console should show the Maven build and testing process and the output of program execution:
-
-- Deletes an index of the same name, if one already exists.
-- Creates an index.
-- Loads the index with four hotel documents.
-- Executes several  queries.
-
-Finally, the Maven process should exit with a success message.
+This sample accompanies [Quickstart: Full-text search using Java](https://learn.microsoft.com/azure/search/search-get-started-text?pivots=java). Follow the documentation for prerequisites, setup instructions, and detailed explanations.
 
 ## Next step
 

diff --git a/quickstart-semantic-ranking/README.md b/quickstart-semantic-ranking/README.md
@@ -1,26 +1,39 @@
 ---
 page_type: sample
 languages:
-- java
+  - java
 name: "Quickstart: Semantic ranking in Azure AI Search using Java"
 description: |
   Demonstrates semantic ranking capabilities to improve search relevance using Azure AI Search.
 products:
-- azure
-- azure-cognitive-search
+  - azure
+  - azure-cognitive-search
 urlFragment: java-semantic-ranking-quickstart
 ---
 
 # Quickstart: Semantic ranking in Azure AI Search using Java
 
 ![Flask sample MIT license badge](https://img.shields.io/badge/license-MIT-green.svg)
 
-Semantic ranking capabilities to improve search relevance using Azure AI Search. This Java sample demonstrates how to create an index with a semantic configuration, upload documents to the index, and execute queries with semantic ranking to get improved relevance scoring and semantic captions. Requires a search service on the Standard pricing tier or higher with semantic ranking enabled.
+This sample demonstrates how to set up semantic ranking. You add a semantic configuration to a search index, and then you add semantic parameters to a query.
 
-This sample is built on the [Microsoft Build of OpenJDK](https://learn.microsoft.com/java/openjdk/install) using the [Maven](https://maven.apache.org/) build system. This sample has dependencies on the [Azure AI Search](https://search.maven.org/artifact/com.azure/azure-search-documents) and [Azure Identity](https://search.maven.org/artifact/com.azure/azure-identity) client libraries.
+## What's in this sample
 
-To run this sample, follow the step-by-step instructions in [Quickstart: Semantic ranking](https://learn.microsoft.com/azure/search/search-get-started-semantic?pivots=java).
+| File | Description |
+|------|-------------|
+| `pom.xml` | Project file that defines dependencies and build settings |
+| `application.properties` | Configuration file for search service endpoint |
+| `SearchConfig.java` | Configuration class for search service connection |
+| `GetIndexSettings.java` | Retrieves index schema and semantic configuration |
+| `UpdateIndexSettings.java` | Adds semantic configuration to an index |
+| `SemanticQuery.java` | Runs basic semantic ranking queries |
+| `SemanticQueryWithCaptions.java` | Runs semantic queries with captions and highlights |
+| `SemanticAnswer.java` | Returns semantic answers from query results |
+
+## Documentation
+
+This sample accompanies [Quickstart: Semantic ranking using Java](https://learn.microsoft.com/azure/search/search-get-started-semantic?pivots=java). Follow the documentation for prerequisites, setup instructions, and detailed explanations.
 
 ## Next step
 
-You can learn more about Azure AI Search and semantic ranking on the [official documentation site](https://learn.microsoft.com/azure/search) and [semantic ranking overview](https://learn.microsoft.com/azure/search/semantic-search-overview).
+You can learn more about Azure AI Search on the [official documentation site](https://learn.microsoft.com/azure/search).
diff --git a/quickstart-vector-search/README.md b/quickstart-vector-search/README.md
@@ -1,26 +1,38 @@
 ---
 page_type: sample
 languages:
-- java
+  - java
 name: "Quickstart: Vector search in Azure AI Search using Java"
 description: |
   Demonstrates vector search capabilities using Azure AI Search with HNSW algorithm.
 products:
-- azure
-- azure-cognitive-search
+  - azure
+  - azure-cognitive-search
 urlFragment: java-vector-quickstart
 ---
 
 # Quickstart: Vector search in Azure AI Search using Java
 
 ![Flask sample MIT license badge](https://img.shields.io/badge/license-MIT-green.svg)
 
-Vector search capabilities using Azure AI Search with the HNSW algorithm. This Java sample demonstrates how to create an index with vector field configurations, upload documents with pre-computed embeddings to the index, and execute vector similarity searches and hybrid queries. Requires a search service on any pricing tier, though Basic or higher is recommended for larger data files.
+This sample demonstrates the fundamentals of vector search, including creating a vector index, loading documents with embeddings, and running vector and hybrid queries.
 
-This sample is built on Java 21 (LTS) from the [Microsoft Build of OpenJDK](https://learn.microsoft.com/java/openjdk/install) using the [Maven](https://maven.apache.org/) build system. This sample has dependencies on the [Azure AI Search](https://search.maven.org/artifact/com.azure/azure-search-documents) and [Azure Identity](https://search.maven.org/artifact/com.azure/azure-identity) client libraries.
+## What's in this sample
 
-To run this sample, follow the step-by-step instructions in [Quickstart: Vector search](https://learn.microsoft.com/azure/search/search-get-started-vector?tabs=keyless&pivots=java).
+| File | Description |
+|------|-------------|
+| `pom.xml` | Project file that defines dependencies and build settings |
+| `application.properties` | Configuration file for search service endpoint |
+| `CreateIndex.java` | Creates a search index with vector field configurations |
+| `DeleteIndex.java` | Deletes an existing search index |
+| `UploadDocuments.java` | Uploads documents with precomputed embeddings |
+| `QueryVector.java` | Precomputed sample query vector |
+| `Search*.java` | Runs vector, hybrid, and semantic hybrid queries |
+
+## Documentation
+
+This sample accompanies [Quickstart: Vector search using Java](https://learn.microsoft.com/azure/search/search-get-started-vector?pivots=java). Follow the documentation for prerequisites, setup instructions, and detailed explanations.
 
 ## Next step
 
-You can learn more about Azure AI Search and vector search on the [official documentation site](https://learn.microsoft.com/azure/search) and [vector search overview](https://learn.microsoft.com/azure/search/vector-search-overview).
+You can learn more about Azure AI Search on the [official documentation site](https://learn.microsoft.com/azure/search).