Create an index
For guidance and examples, see Create an index.
# pip install "pinecone[grpc]"
# Serverless index
from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec
pc = Pinecone(api_key="YOUR_API_KEY")
pc.create_index(
name="docs-example1",
dimension=1536,
metric="cosine",
spec=ServerlessSpec(
cloud="aws",
region="us-east-1"
),
deletion_protection="disabled",
tags={
"environment": "development"
}
)
# Pod-based index
from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec
pc = Pinecone(api_key="YOUR_API_KEY")
pc.create_index(
name="docs-example2",
dimension=1536,
metric="cosine",
spec=PodSpec(
environment="us-west1-gcp",
pod_type="p1.x1",
pods=1,
),
deletion_protection="disabled",
tags={
"environment": "development"
}
)// npm install @pinecone-database/pinecone
// Serverles index
import { Pinecone } from '@pinecone-database/pinecone'
const pc = new Pinecone({
apiKey: 'YOUR_API_KEY'
});
await pc.createIndex({
name: 'serverless-index',
dimension: 1536,
metric: 'cosine',
spec: {
serverless: {
cloud: 'aws',
region: 'us-east-1'
}
},
deletionProtection: 'disabled',
tags: { environment: 'development' },
});
// Pod-based index
await pc.createIndex({
name: 'docs-example2',
dimension: 1536,
metric: 'cosine',
spec: {
pod: {
environment: 'us-west1-gcp',
podType: 'p1.x1',
pods: 1
}
},
deletionProtection: 'disabled',
tags: { environment: 'development' },
});import io.pinecone.clients.Pinecone;
import org.openapitools.db_control.client.model.DeletionProtection;
import java.util.HashMap;
// Serverless index
public class CreateServerlessIndexExample {
public static void main(String[] args) {
Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
HashMap<String, String> tags = new HashMap<>();
tags.put("environment", "development");
pc.createServerlessIndex("docs-example1", "cosine", 1536, "aws",
"us-east-1", DeletionProtection.DISABLED, tags);
}
}
// Pod-based index
public class CreatePodIndexExample {
public static void main(String[] args) {
Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
HashMap<String, String> tags = new HashMap<>();
tags.put("environment", "development");
pc.createPodsIndex("docs-example2", 1536, "us-west1-gcp",
"p1.x1", "cosine", DeletionProtection.DISABLED, tags);
}
}package main
import (
"context"
"fmt"
"log"
"github.com/pinecone-io/go-pinecone/v3/pinecone"
)
func main() {
ctx := context.Background()
pc, err := pinecone.NewClient(pinecone.NewClientParams{
ApiKey: "YOUR_API_KEY",
})
if err != nil {
log.Fatalf("Failed to create Client: %v", err)
}
// Serverless index
indexName1 := "docs-example1"
vectorType := "dense"
dimension1 := int32(1536)
metric1 := pinecone.Cosine
deletionProtection1 := pinecone.DeletionProtectionDisabled
idx1, err := pc.CreateServerlessIndex(ctx, &pinecone.CreateServerlessIndexRequest{
Name: indexName1,
VectorType: &vectorType,
Dimension: &dimension,
Metric: &metric,
Cloud: pinecone.Aws,
Region: "us-east-1",
DeletionProtection: &deletionProtection,
})
if err != nil {
log.Fatalf("Failed to create serverless index: %v", idx1.Name)
} else {
fmt.Printf("Successfully created serverless index: %v", idx1.Name)
}
// Pod-based index
indexName2 := "docs-example2"
metric2 := pinecone.Dotproduct
deletionProtection2 := pinecone.DeletionProtectionDisabled
idx2, err := pc.CreatePodIndex(ctx, &pinecone.CreatePodIndexRequest{
Name: indexName2,
Metric: &metric2,
Dimension: 1536,
Environment: "us-east1-gcp",
PodType: "p1.x1",
DeletionProtection: &deletionProtection2,
})
if err != nil {
log.Fatalf("Failed to create pod-based index: %v", idx2.Name)
} else {
fmt.Printf("Successfully created pod-based index: %v", idx2.Name)
}
}using Pinecone;
var pinecone = new PineconeClient("YOUR_API_KEY");
// Serverless index
var createIndexRequest = await pinecone.CreateIndexAsync(new CreateIndexRequest
{
Name = "docs-example1",
Dimension = 1536,
Metric = CreateIndexRequestMetric.Cosine,
Spec = new ServerlessIndexSpec
{
Serverless = new ServerlessSpec
{
Cloud = ServerlessSpecCloud.Aws,
Region = "us-east-1",
}
},
DeletionProtection = DeletionProtection.Disabled,
Tags = new Dictionary<string, string>
{
{ "environment", "development" }
}
});
// Pod-based index
var createIndexRequest = await pinecone.CreateIndexAsync(new CreateIndexRequest
{
Name = "pod index",
Dimension = 1536,
Metric = CreateIndexRequestMetric.Cosine,
Spec = new PodIndexSpec
{
Pod = new PodSpec
{
Environment = "us-east1-gcp",
PodType = "p1.x1",
Pods = 1,
}
},
DeletionProtection = DeletionProtection.Disabled,
Tags = new Dictionary<string, string>
{
{ "environment", "development" }
}
});PINECONE_API_KEY="YOUR_API_KEY"
# Serverless index
curl -s "https://api.pinecone.io/indexes" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-01" \
-d '{
"name": "docs-example1",
"dimension": 1536,
"metric": "cosine",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"tags": {
"environment": "development"
},
"deletion_protection": "disabled"
}'
# Pod-based index
curl -s "https://api.pinecone.io/indexes" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-01" \
-d '{
"name": "docs-example2",
"dimension": 1536,
"metric": "cosine",
"spec": {
"pod": {
"environment": "us-west1-gcp",
"pod_type": "p1.x1",
"pods": 1
}
},
"tags": {
"environment": "development"
},
"deletion_protection": "disabled"
}'
# Serverless index
{
"name": "docs-example1",
"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": {
"environment": "development"
}
}
}
# Pod-based index
{
"name": "docs-example2",
"metric": "cosine",
"dimension": 1536,
"status": {
"ready": true,
"state": "Ready"
},
"host": "docs-example2-4zo0ijk.svc.us-west1-gcp.pinecone.io",
"spec": {
"pod": {
"replicas": 1,
"shards": 1,
"pods": 1,
"pod_type": "p1.x1",
"environment": "us-west1-gcp"
},
"tags": {
"environment": "development"
}
}
}POST /indexes
Request body
Section titled “Request body”name(body, 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 '-'.dimension(body, integer) — The dimensions of the vectors to be inserted in the index.metric(body, 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 thevector_typeisdense, the metric defaults to 'cosine'.deletion_protection(body, string) — Whether deletion protection is enabled/disabled for the index.tags(body, 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.spec(body, object, required) — The spec object defines how the index should be deployed. For serverless indexes, you define only the cloud and region where the index should be hosted. For pod-based indexes, you define the environment where the index should bevector_type(body, 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.
Responses
Section titled “Responses”201— The index has been successfully created.400— Bad request. The request body included invalid request parameters.401— Unauthorized. Possible causes: Invalid API key.402— Payment required. Organization is on a paid plan and is delinquent on payment.403— You've exceed your pod quota.404— Unknown cloud or region when creating a serverless index.409— Index of given name already exists.422— Unprocessable entity. The request body could not be deserialized.500— Internal server error.