@attribute [Route(Routes.ASSISTANT_ERI)]
@using MudExtensions
@inherits AssistantBaseCore
You can imagine it like this: Hypothetically, when Wikipedia implemented the ERI, it would vectorize
all pages using an embedding method. All of Wikipedia’s data would remain with Wikipedia, including the
vector database (decentralized approach). Then, any AI Studio user could add Wikipedia as a data source to
significantly reduce the hallucination of the LLM in knowledge questions.
Related links:
ERI repository with example implementation in .NET and C#
Interactive documentation aka Swagger UI
@foreach (var version in Enum.GetValues())
{
@version
}
Download specification
@foreach (var language in Enum.GetValues())
{
@language.Name()
}
@if (this.selectedProgrammingLanguage is ProgrammingLanguages.OTHER)
{
}
@foreach (var dataSource in Enum.GetValues())
{
@dataSource.Name()
}
@if (this.selectedDataSource is DataSources.CUSTOM)
{
}
@if(this.selectedDataSource > DataSources.FILE_SYSTEM)
{
}
@if (this.NeedHostnamePort())
{
@if (this.dataSourcePort < 1024)
{
Warning: Ports below 1024 are reserved for system services. Your ERI server need to run with elevated permissions (root user).
}
}
@foreach (var authMethod in Enum.GetValues())
{
@authMethod.Name()
}
@if (this.selectedAuthenticationMethods.Contains(Auth.KERBEROS))
{
@foreach (var os in Enum.GetValues())
{
@os.Name()
}
}