PATCH
/
indexes
/
{index_name}
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    pod_type="p1.x2", 
    replicas=4,
    deletion_protection="enabled"
)

{
    "name": "docs-example",
    "metric": "cosine",
    "dimension": 1536,
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "host": "docs-example1-4zo0ijk.svc.dev-us-west2-aws.pinecone.io",
    "spec": {
        "serverless": {
            "region": "us-east-1",
            "cloud": "aws"
        },
    "tags": {
            "example": "tag",
            "environment": "production"
        }
    }
}

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    pod_type="p1.x2", 
    replicas=4,
    deletion_protection="enabled"
)

{
    "name": "docs-example",
    "metric": "cosine",
    "dimension": 1536,
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "host": "docs-example1-4zo0ijk.svc.dev-us-west2-aws.pinecone.io",
    "spec": {
        "serverless": {
            "region": "us-east-1",
            "cloud": "aws"
        },
    "tags": {
            "example": "tag",
            "environment": "production"
        }
    }
}

Authorizations

​
Api-Key
string
header
required

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

Path Parameters

​
index_name
string
required

The name of the index to configure.

Body

application/json

The desired pod size and replica configuration for the index.

Configuration used to scale an index.

​
spec
object
​
deletion_protection
enum<string>
default:disabled

Whether deletion protection is enabled/disabled for the index.

Available options:
disabled,
enabled
​
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" }
​
embed
object

Configure the integrated inference embedding settings for this index.

You can convert an existing index to an integrated index by specifying the embedding model and field_map. The index vector type and dimension must match the model vector type and dimension, and the index similarity metric must be supported by the model. Refer to the model guide for available models and model details.

You can later change the embedding configuration to update the field map, read parameters, or write parameters. Once set, the model cannot be changed.

Example:
{
  "field_map": { "text": "your-text-field" },
  "model": "multilingual-e5-large",
  "read_parameters": { "input_type": "query", "truncate": "NONE" },
  "write_parameters": { "input_type": "passage" }
}

Response

The request to configure the index has been accepted. Check the index status to see when the change has been applied.

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

​
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"

​
metric
enum<string>
required

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'.

Available options:
cosine,
euclidean,
dotproduct
​
host
string
required

The URL address where the index is hosted.

Example:

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

​
spec
object
required
Example:
{
  "pod": {
    "environment": "us-east-1-aws",
    "metadata_config": {
      "indexed": ["genre", "title", "imdb_rating"]
    },
    "pod_type": "p1.x1",
    "pods": 1,
    "replicas": 1,
    "shards": 1
  }
}
​
status
object
required
Example:
{
  "ready": true,
  "state": "ScalingUpPodSize"
}
​
vector_type
string
default:dense
required

The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension should not be specified.

​
dimension
integer

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

Required range: 1 <= x <= 20000
Example:

1536

​
private_host
string

The private endpoint URL of an index.

Example:

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

​
deletion_protection
enum<string>
default:disabled

Whether deletion protection is enabled/disabled for the index.

Available options:
disabled,
enabled
​
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" }
​
embed
object

The embedding model and document fields mapped to embedding inputs.

Example:
{
  "field_map": { "text": "your-text-field" },
  "metric": "cosine",
  "model": "multilingual-e5-large",
  "read_parameters": { "input_type": "query", "truncate": "NONE" },
  "write_parameters": { "input_type": "passage" }
}