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="serverless-index",
dimension=1536,
metric="cosine",
spec=ServerlessSpec(
cloud="aws",
region="us-east-1"
)
)
# Pod-based index
from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec
pc = Pinecone(api_key="YOUR_API_KEY")
pc.create_index(
name="pod-index",
dimension=1536,
metric="cosine",
spec=PodSpec(
environment="us-west1-gcp",
pod_type="p1.x1",
pods=1
)
)// 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'
}
}
});
// Pod-based index
await pc.createIndex({
name: 'pod-index',
dimension: 1536,
metric: 'cosine',
spec: {
pod: {
environment: 'us-west1-gcp',
podType: 'p1.x1',
pods: 1
}
}
});import io.pinecone.clients.Pinecone;
// Serverless index
public class CreateServerlessIndexExample {
public static void main(String[] args) {
Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
pc.createServerlessIndex("serverless-index", "cosine", 1536, "aws", "us-east-1");
}
}
// Pod-based index
public class CreatePodIndexExample {
public static void main(String[] args) {
Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
pc.createPodsIndex("pod-index", 1536, "us-west1-gcp",
"p1.x1", "cosine");
}
}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: 2024-04" \
-d '{
"name": "serverless-index",
"dimension": 1536,
"metric": "cosine",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
}
}'
# 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: 2024-04" \
-d '{
"name": "pod-index",
"dimension": 1536,
"metric": "cosine",
"spec": {
"pod": {
"environment": "us-west1-gcp",
"pod_type": "p1.x1",
"pods": 1
}
}
}'
# Serverless index
{
"name": "serverless-index",
"metric": "cosine",
"dimension": 1536,
"status": {
"ready": true,
"state": "Ready"
},
"host": "serverless-index-4zo0ijk.svc.dev-us-west2-aws.pinecone.io",
"spec": {
"serverless": {
"region": "us-east-1",
"cloud": "aws"
}
}
}
# Pod-based index
{
"name": "pod-index",
"metric": "cosine",
"dimension": 1536,
"status": {
"ready": true,
"state": "Ready"
},
"host": "pod-index-4zo0ijk.svc.us-west1-gcp.pinecone.io",
"spec": {
"pod": {
"replicas": 1,
"shards": 1,
"pods": 1,
"pod_type": "p1.x1",
"environment": "us-west1-gcp"
}
}
}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, required) — 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'.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 b
Responses
Section titled “Responses”201— The index has been successfully created.400401403404409— Index of given name already exists.422500