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C# samples for Azure AI Search

This repository contains C# code samples used in Azure AI Search documentation. Unless noted otherwise, all samples run on the shared (free) pricing tier of an Azure AI Search service.

In this repository

Sample Related article Description
quickstart-agentic-retrieval Quickstart: Agentic retrieval Sets up a knowledge base in Azure AI Search to integrate LLM reasoning into query planning.
quickstart-keyword-search Quickstart: Full-text search Learn the fundamental tasks of working with a search index: create, load, and query for full-text search scenarios. This quickstart is a console application. The index is modeled on a subset of the Hotels dataset, widely used in Azure AI Search samples, but reduced to just four hotels for readability and comprehension.
quickstart-semantic-ranking Quickstart: Semantic ranking Adds semantic ranking to an existing hotels-sample index and formulates semantic queries.
quickstart-vector-search Quickstart: Vector search Creates a small hotels index that includes vectorized descriptions and formulates vector queries.
embedding-model-migration Tutorial: Embedding model migration Creates a strict baseline backup/restore, supports additive in-place migration, and supports regeneration/restore to a new target index.
tutorial-ai-enrichment C# Tutorial: Use skillsets to generate searchable content Creates an AI enrichment pipeline consisting of an index, indexer, data source, and skillset. The skillset calls Azure AI Services image analysis and OCR, and natural language processing, extract information and structure from heterogeneous blob content, making it searchable in Azure AI Search.
image-serving-example Surface document-embedded images in agentic retrieval (preview) Runs managed ingestion, compares retrieval with image serving disabled and enabled, and independently queries and downloads an indexed image asset from Azure Blob Storage.

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