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Configure an index

Configure an existing index. For guidance and examples, see Manage indexes.

curl
# EXAMPLE REQUEST 1: Serverless index (on-demand)
# Enable deletion protection and add tags to an 
# existing on-demand index.
PINECONE_API_KEY="YOUR_API_KEY"
INDEX_NAME="YOUR_INDEX_NAME"

curl -X PATCH "https://api.pinecone.io/indexes/$INDEX_NAME" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "deletion_protection": "enabled",
        "tags": {
          "tag1": "value1",
          "tag2": "value2"
        }
      }'

# EXAMPLE REQUEST 2: Serverless index (dedicated)
# Add a replica to an existing dedicated index.
PINECONE_API_KEY="YOUR_API_KEY"
INDEX_NAME="YOUR_INDEX_NAME"

curl -X PATCH "https://api.pinecone.io/indexes/$INDEX_NAME" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "spec": {
          "serverless": {
            "read_capacity": {
              "mode": "Dedicated",
              "dedicated": {
                "node_type": "b1",
                "scaling": "Manual",
                "manual": {
                  "shards": 2,
                  "replicas": 2
                }
              }
            }
          }
        }
      }'
curl
// EXAMPLE RESPONSE 1: Serverless index (on-demand)
// Enable deletion protection and add tags to an 
// existing on-demand index.
{
  "name": "example-serverless-ondemand-index",
  "vector_type": "dense",
  "metric": "cosine",
  "dimension": 1024,
  "status": {
    "ready": true,
    "state": "Ready"
  },
  "host": "example-serverless-ondemand-index-bhnyigt.svc.aped-4627-b74a.pinecone.io",
  "spec": {
    "serverless": {
      "region": "us-east-1",
      "cloud": "aws",
      "read_capacity": {
        "mode": "OnDemand",
        "status": {
          "state": "Ready",
          "current_shards": null,
          "current_replicas": null
        }
      }
    }
  },
  "deletion_protection": "enabled",
  "tags": {
    "tag1": "value1",
    "tag2": "value2"
  },
  "embed": {
    "model": "llama-text-embed-v2",
    "field_map": {
      "text": "text"
    },
    "dimension": 1024,
    "metric": "cosine",
    "write_parameters": {
      "dimension": 1024,
      "input_type": "passage",
      "truncate": "END"
    },
    "read_parameters": {
      "dimension": 1024,
      "input_type": "query",
      "truncate": "END"
    },
    "vector_type": "dense"
  }
}

// EXAMPLE RESPONSE 2: Serverless index (dedicated)
// Add a replica to an existing dedicated index.
{
  "name": "example-serverless-dedicated-index",
  "vector_type": "dense",
  "metric": "cosine",
  "dimension": 1536,
  "status": {
    "ready": true,
    "state": "Ready"
  },
  "host": "example-serverless-dedicated-index-bhnyigt.svc.aped-4627-b74a.pinecone.io",
  "spec": {
    "serverless": {
      "region": "us-east-1",
      "cloud": "aws",
      "read_capacity": {
        "mode": "Dedicated",
        "dedicated": {
          "node_type": "b1",
          "scaling": "Manual",
          "manual": {
            "shards": 1,
            "replicas": 2 <-- desired state
          }
        },
        "status": {
          "state": "Scaling",
          "current_shards": 1,
          "current_replicas": 1 <-- current state
        }
      }
    }
  },
  "deletion_protection": "enabled",
  "tags": {
    "tag0": "value0"
  }
}

PATCH /indexes/{index_name}

Authorizations

Section titled “Authorizations”
Api-Keystringrequired

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

Headers

Section titled “Headers”
X-Pinecone-Api-Versionstringrequired

Required date-based version header

Typestring
Default2025-10

Path Parameters

Section titled “Path Parameters”
index_namestringrequired

The name of the index to configure.

Typestring

Body

Section titled “Body”

The desired pod size and replica configuration for the index.

spec?object
Show child attributes
serverlessobjectrequired

Updated configuration for serverless indexes

Typeobject
Show child attributes
read_capacity?object
Show child attributes
modestringrequired

The mode of the index. Possible values: OnDemand or Dedicated. Defaults to OnDemand. If set to Dedicated, dedicated.node_type, and dedicated.scaling must be specified.

Typestring
deletion_protection?string
Typestring
Defaultdisabled

Whether deletion protection is enabled/disabled for the index. Possible values: disabled or 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.

Typeobject
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.

Show child attributes
model?string

The name of the embedding model to use with the index. The index dimension and model dimension must match, and the index similarity metric must be supported by the model. The index embedding model cannot be changed once set.

Example: multilingual-e5-large

Typestring
field_map?object

Identifies the name of the text field from your document model that will be embedded.

Typeobject
read_parameters?object

The read parameters for the embedding model.

Typeobject
write_parameters?object

The write parameters for the embedding model.

Typeobject

Response

Section titled “Response”

202 — 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.

namestringrequired

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

Typestring
dimension?integer

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

Required range: 1 <= x <= 20000. Example: 1536

Typeinteger
metricstringrequired

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'. Possible values: cosine, euclidean, or dotproduct.

Typestring
hoststringrequired

The URL address where the index is hosted.

Example: semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io

Typestring
private_host?string

The private endpoint URL of an index.

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

Typestring
deletion_protection?string
Typestring
Defaultdisabled

Whether deletion protection is enabled/disabled for the index. Possible values: disabled or 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.

Typeobject
embed?object

The embedding model and document fields mapped to embedding inputs.

Typeobject
Show child attributes
modelstringrequired

The name of the embedding model used to create the index.

Example: multilingual-e5-large

Typestring
metric?string

The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If not specified, the metric will be defaulted according to the model. Cannot be updated once set. Possible values: cosine, euclidean, or dotproduct.

Typestring
dimension?integer

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

Required range: 1 <= x <= 20000. Example: 1536

Typeinteger
vector_type?string

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.

Typestring
Defaultdense
field_map?object

Identifies the name of the text field from your document model that is embedded.

Typeobject
read_parameters?object

The read parameters for the embedding model.

Typeobject
write_parameters?object

The write parameters for the embedding model.

Typeobject
specobjectrequired
Show child attributes
serverlessobjectrequired

Configuration of a serverless index.

Typeobject
Show child attributes
cloudstringrequired

The public cloud where you would like your index hosted. Possible values: gcp, aws, or azure.

Example: aws

Typestring
regionstringrequired

The region where you would like your index to be created.

Example: us-east-1

Typestring
read_capacityobjectrequired
Show child attributes
modestringrequired

The mode of the index. Possible values: OnDemand or Dedicated. Defaults to OnDemand. If set to Dedicated, dedicated.node_type, and dedicated.scaling must be specified.

Typestring
statusobjectrequired

The current status of factors affecting the read capacity of a serverless index

Typeobject
source_collection?string

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

Example: movie-embeddings

Typestring
schema?object

Schema for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when schema is present, only fields which are present in the fields object with a filterable: true are indexed. Note that filterable: false is not currently supported.

Typeobject
Show child attributes
fieldsobjectrequired

A map of metadata field names to their configuration. The field name must be a valid metadata field name. The field name must be unique.

Typeobject
statusobjectrequired

The current status of the index

Typeobject
Show child attributes
readybooleanrequired

Whether the index is ready for use

Typeboolean
statestringrequired

The state of the index. Possible values: Initializing, InitializationFailed, ScalingUp, ScalingDown, ScalingUpPodSize, ScalingDownPodSize, Terminating, Ready, or Disabled.

Typestring
vector_typestringrequired

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.

Typestring
Defaultdense
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