swapnesh-variya / azure-search-postman-samples

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Postman collections for Azure Cognitive Search

This repository provides Postman collections used in REST API walkthroughs:

  • custom-analyzers collection
  • debug-sessions collection
  • index-encrypted-blobs collection
  • indexer-mysql
  • knowledge-store collection
  • projections collection
  • query-examples collection
  • quickstart collection
  • skill-examples collection
  • tutorial collection

All collections are saved in JSON, in the V2 collection format.

To use these collections, import them into Postman and then update the collection variables to use your own search service and admin API key.

Custom analyzer

This Postman collection creates a basic search index and builds a custom analyzer designed for indexing and querying various phone number patterns. The collection and corresponding tutorial walk through the process of testing sample searches, testing how those searches are analyzed, and building an analyzer to intuitively search phone number.

Debug sessions

This Postman collection creates a faulty enrichment pipeline with problems you can fix in Debug sessions. Requests create a data source, index, indexer, and skillset. The data source points to a Blob container that you create, using clinical trial PDFs that you upload. For instructions on how to set up this pipeline, see the readme file for this sample.

Knowledge-store

This Postman collection contains requests for creating and populating an index with hotel reviews data from Kaggle. The collection also includes an indexer and skillset that contains instructions for expressing a knowledge store in Azure Storage.

Indexing encrypted Blob files tutorial

This collection uses the Azure Cognitive Search REST APIs to create the resources necessary to be able to index files that have been encrypted in Azure Blob Storage using Azure Key Vault.

Indexer MySQL

This collection creates an indexer, data source, and index that pulls rows from a SQL database. You can run the SQL script in azure-search-sample-data to create the source data used by this collection.

Projections

Contains requests that demonstrate how to configure table, object and file projections using the REST APIs.

Query examples: Full syntax, Patterns and special characters, Simple syntax

Query requests in these collections demonstrate syntax for a broad range of scenarios described in these articles: Full Lucene syntax examples, Partial term and pattern matching, Simple syntax query examples.

With the exception of Full Syntax, which queries the read-only NYCJobs index hosted in a sandbox service, you must edit a collection to replace placeholder values with an endpoint and API key that is valid for your service.

  1. After importing the collection, expand the (...) action list and select Edit.

  2. Enter the search service name and an admin API key. Admin access is required to create and delete objects on a search service. After saving your changes, you can run each query with no further modification.

Most examples are self-explanatory. For the NOT query, see the Boolean operator section for either simple.

Quickstart collection

Includes 4 requests used to create an index, load documents, search the index, and query system information. Request bodies include JSON documents that provides index and documents.

Tutorial collection

This collection provides the same requests as those used to build an AI enrichment pipeline in Tutorial: Add structure to "unstructured content" using REST APIs.

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