import * as pulumi from "@pulumi/pulumi";
import * as inputs from "../types/input";
export interface CollectionTimeouts {
    /**
     * Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
     */
    create?: pulumi.Input<string>;
    /**
     * Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
     */
    delete?: pulumi.Input<string>;
}
export interface GetEmbed {
    /**
     * The dimension of the embedding model, specifying the size of the output vector.
     */
    dimension?: number;
    /**
     * Identifies the name of the text field from your document model that will be embedded.
     */
    fieldMap?: {
        [key: string]: string;
    };
    /**
     * The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector*type' is 'sparse', the metric must be 'dotproduct'. If the vector*type is dense, the metric defaults to 'cosine'.
     */
    metric?: string;
    /**
     * the name of the embedding model to use for the index.
     */
    model?: string;
    /**
     * The read parameters for the embedding model.
     */
    readParameters?: {
        [key: string]: string;
    };
    /**
     * The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.
     */
    vectorType?: string;
    /**
     * The write parameters for the embedding model.
     */
    writeParameters?: {
        [key: string]: string;
    };
}
export interface GetEmbedArgs {
    /**
     * The dimension of the embedding model, specifying the size of the output vector.
     */
    dimension?: pulumi.Input<number>;
    /**
     * Identifies the name of the text field from your document model that will be embedded.
     */
    fieldMap?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
    /**
     * The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector*type' is 'sparse', the metric must be 'dotproduct'. If the vector*type is dense, the metric defaults to 'cosine'.
     */
    metric?: pulumi.Input<string>;
    /**
     * the name of the embedding model to use for the index.
     */
    model?: pulumi.Input<string>;
    /**
     * The read parameters for the embedding model.
     */
    readParameters?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
    /**
     * The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.
     */
    vectorType?: pulumi.Input<string>;
    /**
     * The write parameters for the embedding model.
     */
    writeParameters?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
}
export interface GetSpec {
    /**
     * Configuration needed to deploy a pod-based index.
     */
    pod?: inputs.GetSpecPod;
    /**
     * Configuration needed to deploy a serverless index.
     */
    serverless?: inputs.GetSpecServerless;
}
export interface GetSpecArgs {
    /**
     * Configuration needed to deploy a pod-based index.
     */
    pod?: pulumi.Input<inputs.GetSpecPodArgs>;
    /**
     * Configuration needed to deploy a serverless index.
     */
    serverless?: pulumi.Input<inputs.GetSpecServerlessArgs>;
}
export interface GetSpecPod {
    /**
     * The environment where the index is hosted.
     */
    environment?: string;
    /**
     * Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.
     */
    metadataConfig?: inputs.GetSpecPodMetadataConfig;
    /**
     * The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.
     */
    podType?: string;
    /**
     * The number of pods to be used in the index. This should be equal to shards x replicas.'
     */
    pods?: number;
    /**
     * The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.
     */
    replicas?: number;
    /**
     * The number of shards. Shards split your data across multiple pods so you can fit more data into an index.
     */
    shards?: number;
    /**
     * The name of the collection to create an index from.
     */
    sourceCollection?: string;
}
export interface GetSpecPodArgs {
    /**
     * The environment where the index is hosted.
     */
    environment?: pulumi.Input<string>;
    /**
     * Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.
     */
    metadataConfig?: pulumi.Input<inputs.GetSpecPodMetadataConfigArgs>;
    /**
     * The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.
     */
    podType?: pulumi.Input<string>;
    /**
     * The number of pods to be used in the index. This should be equal to shards x replicas.'
     */
    pods?: pulumi.Input<number>;
    /**
     * The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.
     */
    replicas?: pulumi.Input<number>;
    /**
     * The number of shards. Shards split your data across multiple pods so you can fit more data into an index.
     */
    shards?: pulumi.Input<number>;
    /**
     * The name of the collection to create an index from.
     */
    sourceCollection?: pulumi.Input<string>;
}
export interface GetSpecPodMetadataConfig {
    /**
     * The indexed fields.
     */
    indexeds?: string[];
}
export interface GetSpecPodMetadataConfigArgs {
    /**
     * The indexed fields.
     */
    indexeds?: pulumi.Input<pulumi.Input<string>[]>;
}
export interface GetSpecServerless {
    /**
     * Ready.
     */
    cloud?: string;
    /**
     * Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready
     */
    region?: string;
}
export interface GetSpecServerlessArgs {
    /**
     * Ready.
     */
    cloud?: pulumi.Input<string>;
    /**
     * Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready
     */
    region?: pulumi.Input<string>;
}
export interface GetStatus {
    /**
     * Ready.
     */
    ready?: boolean;
    /**
     * Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready
     */
    state?: string;
}
export interface GetStatusArgs {
    /**
     * Ready.
     */
    ready?: pulumi.Input<boolean>;
    /**
     * Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready
     */
    state?: pulumi.Input<string>;
}
export interface IndexEmbed {
    /**
     * The dimension of the embedding model, specifying the size of the output vector.
     */
    dimension?: pulumi.Input<number>;
    /**
     * Identifies the name of the text field from your document model that will be embedded.
     */
    fieldMap?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
    /**
     * The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector*type' is 'sparse', the metric must be 'dotproduct'. If the vector*type is dense, the metric defaults to 'cosine'.
     */
    metric?: pulumi.Input<string>;
    /**
     * the name of the embedding model to use for the index.
     */
    model?: pulumi.Input<string>;
    /**
     * The read parameters for the embedding model.
     */
    readParameters?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
    /**
     * The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.
     */
    vectorType?: pulumi.Input<string>;
    /**
     * The write parameters for the embedding model.
     */
    writeParameters?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
}
export interface IndexSpec {
    /**
     * Configuration needed to deploy a pod-based index.
     */
    pod?: pulumi.Input<inputs.IndexSpecPod>;
    /**
     * Configuration needed to deploy a serverless index.
     */
    serverless?: pulumi.Input<inputs.IndexSpecServerless>;
}
export interface IndexSpecPod {
    /**
     * The environment where the index is hosted.
     */
    environment: pulumi.Input<string>;
    /**
     * Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.
     */
    metadataConfig?: pulumi.Input<inputs.IndexSpecPodMetadataConfig>;
    /**
     * The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.
     */
    podType: pulumi.Input<string>;
    /**
     * The number of pods to be used in the index. This should be equal to shards x replicas.'
     */
    pods?: pulumi.Input<number>;
    /**
     * The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.
     */
    replicas?: pulumi.Input<number>;
    /**
     * The number of shards. Shards split your data across multiple pods so you can fit more data into an index.
     */
    shards?: pulumi.Input<number>;
    /**
     * The name of the collection to create an index from.
     */
    sourceCollection?: pulumi.Input<string>;
}
export interface IndexSpecPodMetadataConfig {
    /**
     * The indexed fields.
     */
    indexeds: pulumi.Input<pulumi.Input<string>[]>;
}
export interface IndexSpecServerless {
    /**
     * The public cloud where you would like your index hosted. [gcp|aws|azure]
     */
    cloud: pulumi.Input<string>;
    /**
     * The region where you would like your index to be created.
     */
    region: pulumi.Input<string>;
}
export interface IndexStatus {
    /**
     * Ready.
     */
    ready?: pulumi.Input<boolean>;
    /**
     * Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready
     */
    state?: pulumi.Input<string>;
}
export interface IndexTimeouts {
    /**
     * Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
     */
    create?: pulumi.Input<string>;
    /**
     * Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).
     */
    delete?: pulumi.Input<string>;
}