This repository provides Postman collections used in REST API walkthroughs. All collections are saved in JSON, in the V2 collection format.
To use these collections, import them into Postman.
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.
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.
Contains requests that demonstrate how to configure table, object and file projections using the REST APIs.
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.
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After importing the collection, expand the (
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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.
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.
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.
This Postman collection creates a basic search index and builds an analyzer designed for searching phone numbers. 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.