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collections
# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="API_KEY")
pc.create_collection("example-collection", "docs-example")

// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({
  apiKey: 'YOUR_API_KEY'
});

await pc.createCollection({
  name: "example-collection",
  source: "docs-example",
});

import io.pinecone.clients.Pinecone;

public class CreateCollectionExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();

        pc.createCollection("example-collection", "docs-example");
    }
}

PINECONE_API_KEY="YOUR_API_KEY"

curl -s "https://api.pinecone.io/collections" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2024-04" \
  -d '{
        "name": "example-collection",
        "source": "docs-example"
  }'

{
  "name": "example-collection",
  "status": "Initializing",
  "environment": "us-east1-gcp",
  "size": 10000000,
  "dimension": 1536,
  "vector_count": 120000
}
{
  "status": 400,
  "error": {
    "code": "INVALID_ARGUMENT",
    "message": "Metric must be cosine, euclidean, or dotproduct."
  }
}
{
  "status": 401,
  "error": {
    "code": "UNAUTHENTICATED",
    "message": "Invalid API key."
  }
}
{
  "status": 403,
  "error": {
    "code": "FORBIDDEN",
    "message": "Collection exceeds quota. Maximum allowed on your account is 1. Currently have 1."
  }
}
{
  "status": 409,
  "error": {
    "code": "ALREADY_EXISTS",
    "message": "Resource already exists."
  }
}
{
  "status": 422,
  "error": {
    "code": "INVALID_ARGUMENT",
    "message": "Failed to deserialize the JSON body into the target type: missing field `metric` at line 1 column 16"
  }
}
{
  "status": 500,
  "error": {
    "code": "UNKNOWN",
    "message": "Internal server error"
  }
}
# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="API_KEY")
pc.create_collection("example-collection", "docs-example")

// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({
  apiKey: 'YOUR_API_KEY'
});

await pc.createCollection({
  name: "example-collection",
  source: "docs-example",
});

import io.pinecone.clients.Pinecone;

public class CreateCollectionExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();

        pc.createCollection("example-collection", "docs-example");
    }
}

PINECONE_API_KEY="YOUR_API_KEY"

curl -s "https://api.pinecone.io/collections" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2024-04" \
  -d '{
        "name": "example-collection",
        "source": "docs-example"
  }'

Authorizations

​
Api-Key
string
header
required

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

Body

application/json

The desired configuration for the collection.

The configuration needed to create a Pinecone collection.

​
name
string
required

The name of the collection to be created. 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
​
source
string
required

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

Example:

"example-source-index"

Response

The collection has been successfully created.

The CollectionModel describes the configuration and status of a Pinecone collection.

​
name
string
required

The name of the collection.

Example:

"example-collection"

​
status
enum<string>
required

The status of the collection.

Available options:
Initializing,
Ready,
Terminating
Example:

"Initializing"

​
environment
string
required

The environment where the collection is hosted.

Example:

"us-east1-gcp"

​
size
integer<int64>

The size of the collection in bytes.

Example:

10000000

​
dimension
integer<int32>

The dimension of the vectors stored in each record held in the collection.

Required range: 1 <= x <= 2000
Example:

1536

​
vector_count
integer<int32>

The number of records stored in the collection.

Example:

120000