This repository contains many notebooks that explain how Azure AI Search works, including several showcasing how vector search works.
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Run
azd up
on azure-search-openai-demo with GPT-4-vision enabled. This will create the necessary resources for the Azure OpenAI, Azure AI Search services, and the Computer Vision service. -
Create a .env with these variables, and the values taken from
.azure/ENV-NAME/.env
AZURE_OPENAI_SERVICE=YOUR-SERVICE-NAME AZURE_OPENAI_DEPLOYMENT_NAME=YOUR-OPENAI-DEPLOYMENT-NAME AZURE_OPENAI_ADA_DEPLOYMENT=YOUR-EMBED-DEPLOYMENT-NAME AZURE_SEARCH_SERVICE=YOUR-SEARCH-SERVICE-NAME AZURE_COMPUTERVISION_SERVICE=YOUR-COMPUTERVISION-SERVICE-NAME
-
Login to the Azure Developer CLI:
azd auth login
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If you deployed your resource group to a tenant other than your home tenant, set the tenant ID:
export TENANT_ID=YOUR-TENANT-ID
These are the available notebooks, in suggested order:
- Vector Embeddings Notebook
- Azure AI Search Notebook
- Image Search Notebook
- Azure AI Search Relevance Notebook
- RAG with Azure AI Search
- RAG Evaluation
You can find video recordings going through the notebooks here.