PineconeChatExtensionConfiguration interface

Package:

@azure/openai

A specific representation of configurable options for Pinecone when using it as an Azure OpenAI chat extension.

Properties

authentication	The authentication method to use when accessing the defined data source. Each data source type supports a specific set of available authentication methods; please see the documentation of the data source for supported mechanisms. If not otherwise provided, On Your Data will attempt to use System Managed Identity (default credential) authentication.
embeddingDependency	The embedding dependency for vector search.
environment	The environment name of Pinecone.
fieldsMapping	Customized field mapping behavior to use when interacting with the search index.
indexName	The name of the Pinecone database index.
inScope	Whether queries should be restricted to use of indexed data.
roleInformation	Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit.
strictness	The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer.
topNDocuments	The configured top number of documents to feature for the configured query.
type	The type label to use when configuring Azure OpenAI chat extensions. This should typically not be changed from its default value for Pinecone.

Property Details

authentication

The authentication method to use when accessing the defined data source. Each data source type supports a specific set of available authentication methods; please see the documentation of the data source for supported mechanisms. If not otherwise provided, On Your Data will attempt to use System Managed Identity (default credential) authentication.

authentication?: OnYourDataAuthenticationOptions

Property Value

OnYourDataAuthenticationOptions

embeddingDependency

The embedding dependency for vector search.

embeddingDependency: OnYourDataVectorizationSourceUnion

Property Value

OnYourDataVectorizationSourceUnion

environment

The environment name of Pinecone.

environment: string

Property Value

string

fieldsMapping

Customized field mapping behavior to use when interacting with the search index.

fieldsMapping: PineconeFieldMappingOptions

Property Value

PineconeFieldMappingOptions

indexName

The name of the Pinecone database index.

indexName: string

Property Value

string

inScope

Whether queries should be restricted to use of indexed data.

inScope?: boolean

Property Value

boolean

roleInformation

Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit.

roleInformation?: string

Property Value

string

strictness

The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer.

strictness?: number

Property Value

number

topNDocuments

The configured top number of documents to feature for the configured query.

topNDocuments?: number

Property Value

number

type

The type label to use when configuring Azure OpenAI chat extensions. This should typically not be changed from its default value for Pinecone.

type: "pinecone"

Property Value

"pinecone"