wehub-resource-syncStarting With Semantic Kernel Vector Stores
This project contains a step by step guide to get started using Vector Stores with the Semantic Kernel.
The examples can be run as integration tests but their code can also be copied to stand-alone programs.
Configuring Secrets
Most of the examples will require secrets and credentials, to access OpenAI, Azure OpenAI, Vector Stores and other resources. We suggest using .NET Secret Manager to avoid the risk of leaking secrets into the repository, branches and pull requests. You can also use environment variables if you prefer.
To set your secrets with Secret Manager:
cd dotnet/samples/GettingStartedWithVectorStores
dotnet user-secrets init
dotnet user-secrets set "AzureOpenAIEmbeddings:DeploymentName" "..."
dotnet user-secrets set "AzureOpenAIEmbeddings:Endpoint" "..."
dotnet user-secrets set "AzureAISearch:Endpoint" "..."
dotnet user-secrets set "AzureAISearch:ApiKey" "..."
To set your secrets with environment variables, use these names:
AzureOpenAIEmbeddings__DeploymentName
AzureOpenAIEmbeddings__Endpoint
AzureAISearch__Endpoint
AzureAISearch__ApiKey