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Azure AI Search Index provides a mechanism to search and retrieve text that uses vector embeddings for the search scenarios. Hybrid search is the ability to query text and vectors simultaneously. In this session, we explore the hybrid search abilities with in AI search index after exploring basics of building vectors using Azure OpenAI embeddings

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AZURE-AI-SEARCH

This repository contains a demo project for Azure AI Search. It includes scripts for creating an Azure AI Search index with Vector Search and Semantic Search capabilities.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Python 3.11 or later
  • Azure account
  • Azure AI Search service instance

Installation

  1. Clone the repository and run the notebook vectors.ipynb
  2. All Utility classes are under utils

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Azure AI Search Index provides a mechanism to search and retrieve text that uses vector embeddings for the search scenarios. Hybrid search is the ability to query text and vectors simultaneously. In this session, we explore the hybrid search abilities with in AI search index after exploring basics of building vectors using Azure OpenAI embeddings

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ai azure aisearch

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