Merge pull request #268547 from HeidiSteen/heidist-fix

American-Dipper · web-flow · commit 1ddacfd6bd4b · 2024-03-08T16:02:09.000-08:00
BULK EDIT repo name change
diff --git a/articles/search/cognitive-search-skill-custom-entity-lookup.md b/articles/search/cognitive-search-skill-custom-entity-lookup.md
@@ -404,7 +404,7 @@ This warning will be emitted if the number of matches detected is greater than t
 
 ## See also
 
-+ [Custom Entity Lookup sample and readme](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/skill-examples/custom-entity-lookup-skill)
++ [Custom Entity Lookup sample and readme](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skill-examples/custom-entity-lookup-skill)
 + [Built-in skills](cognitive-search-predefined-skills.md)
 + [How to define a skillset](cognitive-search-defining-skillset.md)
 + [Entity Recognition skill (to search for well known entities)](cognitive-search-skill-entity-recognition-v3.md)
diff --git a/articles/search/cognitive-search-tutorial-blob.md b/articles/search/cognitive-search-tutorial-blob.md
@@ -46,7 +46,7 @@ Once content is extracted, the [skillset](cognitive-search-working-with-skillset
 
 + [Sample data files (mixed media)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media)
 
-+ [Sample REST file](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/skillset-tutorial)
++ [Sample REST file](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial)
 
 > [!NOTE]
 > You can use the free service for this tutorial. A free search service limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
@@ -93,7 +93,7 @@ A valid API key establishes trust, on a per request basis, between the applicati
 
 ## Set up your REST file
 
-1. Start Visual Studio Code and open the [skillset-tutorial.rest](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/skillset-tutorial) file. See [Quickstart: Text search using REST](search-get-started-rest.md) if you need help with the REST client.
+1. Start Visual Studio Code and open the [skillset-tutorial.rest](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial) file. See [Quickstart: Text search using REST](search-get-started-rest.md) if you need help with the REST client.
 
 1. Provide values for the variables: search service endpoint, search service admin API key, an index name, a connection string to your Azure Storage account, and the blob container name.
 
diff --git a/articles/search/cognitive-search-tutorial-debug-sessions.md b/articles/search/cognitive-search-tutorial-debug-sessions.md
@@ -33,7 +33,7 @@ If you don't have an Azure subscription, create a [free account](https://azure.m
 
 + [Sample PDFs (clinical trials)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/clinical-trials/clinical-trials-pdf-19).
 
-+ [Sample debug-sessions.rest file](https://github.com/Azure-Samples/azure-search-postman-samples/blob/main/Debug-sessions/debug-sessions.rest) used to create the enrichment pipeline.
++ [Sample debug-sessions.rest file](https://github.com/Azure-Samples/azure-search-rest-samples/blob/main/Debug-sessions/debug-sessions.rest) used to create the enrichment pipeline.
 
 > [!NOTE]
 > This tutorial also uses [Azure AI services](https://azure.microsoft.com/services/cognitive-services/) for language detection, entity recognition, and key phrase extraction. Because the workload is so small, Azure AI services is tapped behind the scenes for free processing for up to 20 transactions. This means that you can complete this exercise without having to create a billable Azure AI services resource.
diff --git a/articles/search/knowledge-store-concept-intro.md b/articles/search/knowledge-store-concept-intro.md
@@ -95,7 +95,7 @@ The wizard automates several tasks. Specifically, both shaping and projections (
 
 ### [**REST**](#tab/kstore-rest)
 
-[**Create a knowledge store using REST**](knowledge-store-create-rest.md) is a tutorial that walks you through the objects and requests belonging to this [knowledge store collection](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/knowledge-store).
+[**Create a knowledge store using REST**](knowledge-store-create-rest.md) is a tutorial that walks you through the objects and requests belonging to this [knowledge store collection](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/knowledge-store).
 
 REST API version `2020-06-30` and higher can be used to create a knowledge store through additions to a skillset.
 
diff --git a/articles/search/knowledge-store-create-rest.md b/articles/search/knowledge-store-create-rest.md
@@ -21,7 +21,7 @@ In this article, you use the REST API to ingest, enrich, and explore a set of cu
 To make the initial data set available, the hotel reviews are first imported into Azure Blob Storage. Post-processing, the results are saved as a knowledge store in Azure Table Storage.
 
 > [!TIP]
-> This article uses REST for detailed explanations of each step. [Download the REST file](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/knowledge-store) if you want to just run the commands. Alternatively, you can also [create a knowledge store in Azure portal](knowledge-store-create-portal.md).
+> This article uses REST for detailed explanations of each step. [Download the REST file](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/knowledge-store) if you want to just run the commands. Alternatively, you can also [create a knowledge store in Azure portal](knowledge-store-create-portal.md).
 
 ## Prerequisites
 
diff --git a/articles/search/knowledge-store-projection-example-long.md b/articles/search/knowledge-store-projection-example-long.md
@@ -27,7 +27,7 @@ Create a blob container in Azure Storage and upload all 14 items.
 
 While in Azure Storage, copy a connection string.
 
-You can use the [`projections.rest`](https://github.com/Azure-Samples/azure-search-postman-samples/blob/main/projections/) file to run the examples in this article.
+You can use the [`projections.rest`](https://github.com/Azure-Samples/azure-search-rest-samples/blob/main/projections/) file to run the examples in this article.
 
 ## Example skillset
 
diff --git a/articles/search/samples-rest.md b/articles/search/samples-rest.md
@@ -23,19 +23,19 @@ You can use any client that supports HTTP calls. [Here's a quickstart](search-ge
 
 ## Doc samples
 
-Code samples from the Azure AI Search team demonstrate features and workflows. Many of these samples are referenced in tutorials, quickstarts, and how-to articles. You can find these samples in [**Azure-Samples/azure-search-postman-samples**](https://github.com/Azure-Samples/azure-search-postman-samples) on GitHub.
+Code samples from the Azure AI Search team demonstrate features and workflows. Many of these samples are referenced in tutorials, quickstarts, and how-to articles. You can find these samples in [**Azure-Samples/azure-search-rest-samples**](https://github.com/Azure-Samples/azure-search-rest-samples) on GitHub.
 
 | Samples | Description |
 |---------|---------|
-| [Quickstart](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/Quickstart) | Source code for [Quickstart: Text search using REST](search-get-started-rest.md). This sample  covers the basic workflow for creating, loading, and querying a search index using sample data. |
-| [Quickstart-vectors](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/Quickstart-vectors) | Source code for [Quickstart: Vector search using REST APIs](search-get-started-vector.md). This sample  covers the basic workflow for indexing and querying vector data. |
-| [Tutorial](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/Tutorial) | Source code for [Tutorial: Use REST and AI to generate searchable content from Azure blobs](cognitive-search-tutorial-blob.md). This sample  shows you how to create a skillset that iterates over Azure blobs to extract information and infer structure.|
-| [Debug-sessions](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/Debug-sessions) | Source code for [Tutorial: Diagnose, repair, and commit changes to your skillset](cognitive-search-tutorial-debug-sessions.md). This sample  shows you how to use a skillset debug session in the Azure portal. REST is used to create the objects used during debug.|
-| [custom-analyzers](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/custom-analyzers) | Source code for [Tutorial: Create a custom analyzer for phone numbers](tutorial-create-custom-analyzer.md). This sample  explains how to use analyzers to preserve patterns and special characters in searchable content.|
-| [knowledge-store](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/knowledge-store) | Source code for [Create a knowledge store using REST and Postman](knowledge-store-create-rest.md). This sample  explains the necessary steps for populating a knowledge store used for knowledge mining workflows. |
-| [semantic ranker](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/semantic-search) | Source code for [Define projections in a knowledge store](knowledge-store-projections-examples.md). This sample creates a basic search index with a semantic configuration, loads data into the index, and then creates a semantic query.|
-| [projections](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/projections) | Source code for [Define projections in a knowledge store](knowledge-store-projections-examples.md). This sample explains how to specify the physical data structures in a knowledge store.|
-| [index-encrypted-blobs](https://github.com/Azure-Samples/azure-search-postman-samples/commit/f5ebb141f1ff98f571ab84ac59dcd6fd06a46718) | Source code for [How to index encrypted blobs using blob indexers and skillsets](search-howto-index-encrypted-blobs.md). This article shows how to index documents in Azure Blob Storage that have been previously encrypted using Azure Key Vault. |
+| [Quickstart](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart) | Source code for [Quickstart: Text search using REST](search-get-started-rest.md). This sample  covers the basic workflow for creating, loading, and querying a search index using sample data. |
+| [Quickstart-vectors](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-vectors) | Source code for [Quickstart: Vector search using REST APIs](search-get-started-vector.md). This sample  covers the basic workflow for indexing and querying vector data. |
+| [Tutorial](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Tutorial) | Source code for [Tutorial: Use REST and AI to generate searchable content from Azure blobs](cognitive-search-tutorial-blob.md). This sample  shows you how to create a skillset that iterates over Azure blobs to extract information and infer structure.|
+| [Debug-sessions](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Debug-sessions) | Source code for [Tutorial: Diagnose, repair, and commit changes to your skillset](cognitive-search-tutorial-debug-sessions.md). This sample  shows you how to use a skillset debug session in the Azure portal. REST is used to create the objects used during debug.|
+| [custom-analyzers](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/custom-analyzers) | Source code for [Tutorial: Create a custom analyzer for phone numbers](tutorial-create-custom-analyzer.md). This sample  explains how to use analyzers to preserve patterns and special characters in searchable content.|
+| [knowledge-store](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/knowledge-store) | Source code for [Create a knowledge store using REST](knowledge-store-create-rest.md). This sample  explains the necessary steps for populating a knowledge store used for knowledge mining workflows. |
+| [semantic ranker](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/semantic-search) | Source code for [Define projections in a knowledge store](knowledge-store-projections-examples.md). This sample creates a basic search index with a semantic configuration, loads data into the index, and then creates a semantic query.|
+| [projections](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/projections) | Source code for [Define projections in a knowledge store](knowledge-store-projections-examples.md). This sample explains how to specify the physical data structures in a knowledge store.|
+| [index-encrypted-blobs](https://github.com/Azure-Samples/azure-search-rest-samples/commit/f5ebb141f1ff98f571ab84ac59dcd6fd06a46718) | Source code for [How to index encrypted blobs using blob indexers and skillsets](search-howto-index-encrypted-blobs.md). This article shows how to index documents in Azure Blob Storage that have been previously encrypted using Azure Key Vault. |
 
 > [!TIP]
 > Try the [Samples browser](/samples/browse/?expanded=azure&languages=http&products=azure-cognitive-search) to search for Microsoft code samples in GitHub, filtered by product, service, and language.
@@ -46,4 +46,4 @@ The following samples are also published by the Azure AI Search team, but aren't
 
 | Samples | Description |
 |---------|-------------|
-| [Query-examples](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/Query-examples) | Postman collections demonstrating the various query techniques, including fuzzy search, RegEx and wildcard search, autocomplete, and so on. |
+| [Query-examples](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Query-examples) | Postman collections demonstrating the various query techniques, including fuzzy search, RegEx and wildcard search, autocomplete, and so on. |
diff --git a/articles/search/search-get-started-rest.md b/articles/search/search-get-started-rest.md
@@ -19,7 +19,7 @@ ms.custom:
 
 Learn how to use the [Search REST APIs](/rest/api/searchservice) to create, load, and query a search index in Azure AI Search. 
 
-[Download a REST sample](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/quickstart) to send the requests in this quickstart, or create requests manually using the instructions in this article.
+[Download a REST sample](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/quickstart) to send the requests in this quickstart, or create requests manually using the instructions in this article.
 
 If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/?WT.mc_id=A261C142F) before you begin.
 
diff --git a/articles/search/search-get-started-vector.md b/articles/search/search-get-started-vector.md
@@ -17,7 +17,7 @@ Learn how to use the [Search REST APIs](/rest/api/searchservice) to create, load
 
 In Azure AI Search, a [*vector store*](vector-store.md) has an index schema that defines vector and nonvector fields, a vector configuration for algorithms that create the embedding space, and settings on vector field definitions that are used in query requests. The [Create Index](/rest/api/searchservice/indexes/create-or-update) API creates the vector store.
 
-[Download a REST sample](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/quickstart-vectors) to send the requests in this quickstart, or create requests manually to adapt the instructions for your own data.
+[Download a REST sample](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/quickstart-vectors) to send the requests in this quickstart, or create requests manually to adapt the instructions for your own data.
 
 If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/?WT.mc_id=A261C142F) before you begin.
 
@@ -240,7 +240,7 @@ Creating and loading the index are separate steps. In Azure AI Search, the index
 The URI is extended to include the `docs` collection and `index` operation.
 
 > [!IMPORTANT]
-> The following example isn't runnable code. For readability, we excluded vector values because each one contains 1536 embeddings, which is too long for this article. Copy runnable code from the [sample on GitHub](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/quickstart-vectors) if you want to try this step.
+> The following example isn't runnable code. For readability, we excluded vector values because each one contains 1536 embeddings, which is too long for this article. Copy runnable code from the [sample on GitHub](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/quickstart-vectors) if you want to try this step.
 
 ```http
 ### Upload documents
@@ -399,7 +399,7 @@ The vector queries in this section are based on two strings:
 The vector query string is semantically similar to the search string, but includes terms that don't exist in the search index. If you do a keyword search for "classic lodging near running trails, eateries, retail", results are zero. We use this example to show how you can get relevant results even if there are no matching terms.
 
 > [!IMPORTANT]
-> The following examples aren't runnable code. For readability, we excluded vector values because each array contains 1536 embeddings, which is too long for this article. Copy runnable code from the [sample on GitHub](https://github.com/Azure-Samples/azure-search-postman-samples/tree/main/quickstart-vectors) if you want to try these queries.
+> The following examples aren't runnable code. For readability, we excluded vector values because each array contains 1536 embeddings, which is too long for this article. Copy runnable code from the [sample on GitHub](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/quickstart-vectors) if you want to try these queries.
 
 ### Single vector search
 
diff --git a/articles/search/search-howto-index-encrypted-blobs.md b/articles/search/search-howto-index-encrypted-blobs.md
@@ -115,7 +115,7 @@ Install and set up Postman.
 
 ### Download and install Postman
 
-1. Download the [Postman collection source code](https://github.com/Azure-Samples/azure-search-postman-samples/blob/main/index-encrypted-blobs/Index%20encrypted%20Blob%20files.postman_collection.json).
+1. Download the [Postman collection source code](https://github.com/Azure-Samples/azure-search-rest-samples/blob/main/index-encrypted-blobs/Index%20encrypted%20Blob%20files.postman_collection.json).
 
 1. Select **File** > **Import** to import the source code into Postman.
 
diff --git a/articles/search/search-query-partial-matching.md b/articles/search/search-query-partial-matching.md
@@ -24,7 +24,7 @@ The solution is to invoke an analyzer during indexing that preserves a complete
 If you need to support search scenarios that call for analyzed and non-analyzed content, consider creating two fields in your index, one for each scenario. One field undergoes lexical analysis. The second field stores an intact string, using a content-preserving analyzer that emits whole-string tokens for pattern matching.
 
 > [!TIP]
-> If you are familiar with Postman and REST APIs, [download the query examples collection](https://github.com/Azure-Samples/azure-search-postman-samples/) to query partial terms and special characters described in this article.
+> If you are familiar with Postman and REST APIs, [download the query examples collection](https://github.com/Azure-Samples/azure-search-rest-samples/) to query partial terms and special characters described in this article.
 
 ## About partial term search
 
@@ -229,7 +229,7 @@ The following example illustrates a custom analyzer that provides the keyword to
 
 Once you've defined an index with analyzers and field definitions that support your scenario, load documents that have representative strings so that you can test partial string queries.
 
-If you're familiar with Postman and REST APIs, [download the query examples collection](https://github.com/Azure-Samples/azure-search-postman-samples/) to query partial terms and special characters described in this article. The collection includes REST API requests for index creation and deletion, sample documents and an upload documents request, a test analyzer request, and queries. 
+If you're familiar with Postman and REST APIs, [download the query examples collection](https://github.com/Azure-Samples/azure-search-rest-samples/) to query partial terms and special characters described in this article. The collection includes REST API requests for index creation and deletion, sample documents and an upload documents request, a test analyzer request, and queries. 
 
 The previous sections explained the logic. This section steps through each API you should call when testing your solution. As previously noted, if you use an interactive web test tool such as Postman, you can step through these tasks quickly.
 
diff --git a/articles/search/tutorial-create-custom-analyzer.md b/articles/search/tutorial-create-custom-analyzer.md
