List indexes

GET

indexes

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_list = pc.list_indexes()

print(index_list)

[{
    "name": "example-sparse-index",
    "metric": "dotproduct",
    "host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "sparse",
    "dimension": null,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}, {
    "name": "example-dense-index",
    "metric": "cosine",
    "host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "dense",
    "dimension": 1536,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}]

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_list = pc.list_indexes()

print(index_list)

[{
    "name": "example-sparse-index",
    "metric": "dotproduct",
    "host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "sparse",
    "dimension": null,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}, {
    "name": "example-dense-index",
    "metric": "cosine",
    "host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "dense",
    "dimension": 1536,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}]

Authorizations

Api-Key

string

header

required

An API Key is required to call Pinecone APIs. Get yours from the console.

Response

200

application/json

This operation returns a list of all the indexes that you have previously created, and which are associated with the given project

The list of indexes that exist in the project.

indexes

object[]

The IndexModel describes the configuration and status of a Pinecone index.

indexes.name

string

required

The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'.

Required string length: 1 - 45

Example:

"example-index"

indexes.dimension

integer

required

The dimensions of the vectors to be inserted in the index.

Required range: 1 <= x <= 20000

Example:

1536

indexes.metric

enum<string>

default:cosine

required

The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'.

Available options:

cosine,

euclidean,

dotproduct

indexes.host

string

required

The URL address where the index is hosted.

Example:

"semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io"

indexes.spec

object

required

indexes.spec.pod

object

Configuration needed to deploy a pod-based index.

indexes.spec.pod.environment

string

required

The environment where the index is hosted.

Example:

"us-east1-gcp"

indexes.spec.pod.pod_type

string

default:p1.x1

required

The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.

indexes.spec.pod.replicas

integer

default:1

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.

Required range: x >= 1

indexes.spec.pod.shards

integer

default:1

The number of shards. Shards split your data across multiple pods so you can fit more data into an index.

Required range: x >= 1

indexes.spec.pod.pods

integer

default:1

The number of pods to be used in the index. This should be equal to shards x replicas.'

Required range: x >= 1

Example:

1

indexes.spec.pod.metadata_config

object

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.

Example:

{
  "indexed": ["genre", "title", "imdb_rating"]
}

indexes.spec.pod.source_collection

string

The name of the collection to be used as the source for the index.

Example:

"movie-embeddings"

Example:

{
  "environment": "us-east1-gcp",
  "metadata_config": {
    "indexed": ["genre", "title", "imdb_rating"]
  },
  "pod_type": "p1.x1",
  "pods": 1,
  "replicas": 1,
  "shards": 1,
  "source_collection": "movie-embeddings"
}

indexes.spec.serverless

object

Configuration needed to deploy a serverless index.

Example:

{
  "pod": {
    "environment": "us-east-1-aws",
    "metadata_config": {
      "indexed": ["genre", "title", "imdb_rating"]
    },
    "pod_type": "p1.x1",
    "pods": 1,
    "replicas": 1,
    "shards": 1
  }
}

indexes.status

object

required

Example:

{
  "ready": true,
  "state": "ScalingUpPodSize"
}

indexes.deletion_protection

enum<string>

default:disabled

Whether deletion protection is enabled/disabled for the index.

Available options:

disabled,

enabled

indexes.tags

object

Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or '-'. Values must be alphanumeric, ';', '@', '', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string.

Example:

{ "tag0": "val0", "tag1": "val1" }

Errors Create an index

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_list = pc.list_indexes()

print(index_list)

[{
    "name": "example-sparse-index",
    "metric": "dotproduct",
    "host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "sparse",
    "dimension": null,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}, {
    "name": "example-dense-index",
    "metric": "cosine",
    "host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "dense",
    "dimension": 1536,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}]

APIs

Database

Inference

SDKs

Architecture

Tools

Authorizations

Response