Create an index with integrated embedding

With this type of index, you provide source text, and Pinecone uses a hosted embedding model to convert the text automatically during upsert and search.
For guidance and examples, see Create an index.

PINECONE_API_KEY="YOUR_API_KEY"

curl https://api.pinecone.io/indexes/create-for-model \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2026-04" \
  -d '{
        "name": "integrated-dense-curl",
        "cloud": "aws",
        "region": "us-east-1",
        "embed": {
          "model": "llama-text-embed-v2",
          "metric": "cosine",
          "field_map": {
            "text": "chunk_text"
          },
          "write_parameters": {
            "input_type": "passage",
            "truncate": "END"
          },
          "read_parameters": {
            "input_type": "query",
            "truncate": "END"
          }
        }
      }'

{
  "id": "9dabb7cb-ec0a-4e2e-b79e-c7c997e592ce",
  "name": "integrated-dense-curl",
  "metric": "cosine",
  "dimension": 1024,
  "status": {
    "ready": false,
    "state": "Initializing"
  },
  "host": "integrated-dense-curl-govk0nt.svc.aped-4627-b74a.pinecone.io",
  "spec": {
    "serverless": {
      "region": "us-east-1",
      "cloud": "aws"
    }
  },
  "deletion_protection": "disabled",
  "tags": null,
  "embed": {
    "model": "llama-text-embed-v2",
    "field_map": {
      "text": "chunk_text"
    },
    "dimension": 1024,
    "metric": "cosine",
    "write_parameters": {
      "input_type": "passage",
      "truncate": "END"
    },
    "read_parameters": {
      "input_type": "query",
      "truncate": "END"
    }
  }
}

POST /indexes/create-for-model

• X-Pinecone-Api-Version (header, string, required) — Required date-based version header

• 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 '-'.
• cloud (body, string, required) — The public cloud where you would like your index hosted. Possible values: gcp, aws, or azure.
• region (body, string, required) — The region where you would like your index to be created.
• deletion_protection (body, string) — Whether deletion protection is enabled/disabled for the index. Possible values: disabled or enabled.
• 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.
• schema (body, 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.
• read_capacity (body, object) — By default the index will be created with read capacity mode OnDemand. If you prefer to allocate dedicated read nodes for your workload, you must specify mode Dedicated and additional configurations for node_type and scaling.
• embed (body, object, required) — Specify the integrated inference embedding configuration for the index. Once set the model cannot be changed, but you can later update the embedding configuration for an integrated inference index including field map, read parameters, or write parameters. Refer to the model guide for available models and model details.

• 201 — The index has successfully been created for the embedding model.
• 400 — Bad request. The request body included invalid request parameters.
• 401 — Unauthorized. Possible causes: Invalid API key.
• 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.