diff --git a/quickstart-keyword-search/README.md b/quickstart-keyword-search/README.md index 8a8a46c..735c801 100644 --- a/quickstart-keyword-search/README.md +++ b/quickstart-keyword-search/README.md @@ -1,13 +1,13 @@ --- 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 --- @@ -15,50 +15,19 @@ urlFragment: java-quickstart-keyword ![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 index 893b143..5a6de8f 100644 --- a/quickstart-semantic-ranking/README.md +++ b/quickstart-semantic-ranking/README.md @@ -1,13 +1,13 @@ --- 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 --- @@ -15,12 +15,25 @@ urlFragment: java-semantic-ranking-quickstart ![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 index 908d3d6..9026a22 100644 --- a/quickstart-vector-search/README.md +++ b/quickstart-vector-search/README.md @@ -1,13 +1,13 @@ --- 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 --- @@ -15,12 +15,24 @@ urlFragment: java-vector-quickstart ![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).