With this type of index, you provide source text, and Pinecone uses a [hosted embedding model](/guides/index-data-create-an-index#embedding-models) to convert the text automatically during [upsert](/guides/database-data-plane-upsert-records) and [search](/guides/database-data-plane-search-records).

For guidance and examples, see [Create an index](/guides/index-data-create-an-index#integrated-embedding).

:::code-group
```python Python
# pip install --upgrade pinecone
from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_name = "integrated-dense-py"

index_model = pc.create_index_for_model(
    name=index_name,
    cloud="aws",
    region="us-east-1",
    embed={
        "model":"llama-text-embed-v2",
        "field_map":{"text": "chunk_text"}
    }
)

# Import specific classes to get type hints and autocompletions
from pinecone import CloudProvider, AwsRegion, IndexEmbed, EmbedModel

index_model = pc.create_index_for_model(
    name=index_name,
    cloud=CloudProvider.AWS,
    region=AwsRegion.US_EAST_1,
    embed=IndexEmbed(
        model=EmbedModel.Multilingual_E5_Large,
        field_map={"text": "chunk_text"},
        metric='cosine'
    )
)
```

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

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

await pc.createIndexForModel({
  name: 'integrated-dense-js',
  cloud: 'aws',
  region: 'us-east-1',
  embed: {
    model: 'llama-text-embed-v2',
    fieldMap: { text: 'chunk_text' },
  },
  waitUntilReady: true,
});
```

```java Java
import io.pinecone.clients.Pinecone;
import org.openapitools.db_control.client.ApiException;
import org.openapitools.db_control.client.model.CreateIndexForModelRequest;
import org.openapitools.db_control.client.model.CreateIndexForModelRequestEmbed;
import org.openapitools.db_control.client.model.DeletionProtection;
import org.openapitools.db_control.client.model.IndexModel;

import java.util.HashMap;
import java.util.Map;

public class CreateIntegratedIndex {
    public static void main(String[] args) throws ApiException {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        String indexName = "integrated-dense-java";
        String region = "us-east-1";
        HashMap<String, String> fieldMap = new HashMap<>();
        fieldMap.put("text", "chunk_text");
        CreateIndexForModelRequestEmbed embed = new CreateIndexForModelRequestEmbed()
                .model("llama-text-embed-v2")
                .fieldMap(fieldMap);
        Map<String, String> tags = new HashMap<>();
        tags.put("environment", "development");
        IndexModel index = pc.createIndexForModel(
                indexName,
                CreateIndexForModelRequest.CloudEnum.AWS,
                region,
                embed,
                DeletionProtection.DISABLED,
                tags
        );
        System.out.println(index);
    }
}
```

```go Go
package main

import (
    "context"
    "fmt"
    "log"

    "github.com/pinecone-io/go-pinecone/v4/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)
    }

  	indexName := "integrated-dense-go"
    DeletionProtection: &deletionProtection,

    index, err := pc.CreateIndexForModel(ctx, &pinecone.CreateIndexForModelRequest{
		Name:   indexName,
		Cloud:  pinecone.Aws,
		Region: "us-east-1",
		Embed: pinecone.CreateIndexForModelEmbed{
			Model:    "llama-text-embed-v2",
			FieldMap: map[string]interface{}{"text": "chunk_text"},
		},
    DeletionProtection: &deletionProtection,
    Tags:   &pinecone.IndexTags{ "environment": "development" },
	})
    if err != nil {
        log.Fatalf("Failed to create serverless integrated index: %v", idx.Name)
    } else {
        fmt.Printf("Successfully created serverless integrated index: %v", idx.Name)
    }
}
```

```csharp C#
using Pinecone;

var pinecone = new PineconeClient("YOUR_API_KEY");

var createIndexRequest = await pinecone.CreateIndexForModelAsync(
    new CreateIndexForModelRequest
    {
        Name = "integrated-dense-dotnet",
        Cloud = CreateIndexForModelRequestCloud.Aws,
        Region = "us-east-1",
        Embed = new CreateIndexForModelRequestEmbed
        {
            Model = "llama-text-embed-v2",
            FieldMap = new Dictionary<string, object?>() { { "text", "chunk_text" } },
        },
        DeletionProtection = DeletionProtection.Disabled,
        Tags = new Dictionary<string, string> 
        { 
            { "environment", "development" }
        }
    }
);
```

```shell curl
PINECONE_API_KEY="YOUR_API_KEY"

curl -X POST https://api.pinecone.io/indexes/create-for-model \
     -H "Content-Type: application/json" \
     -H "Api-Key: $PINECONE_API_KEY" \
     -H "X-Pinecone-Api-Version: 2025-04" \
     -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"
             }
           }
         }'
```

```bash CLI
# Target the project where you want to create the index.
pc target -o "example-org" -p "example-project"
# Create the index.
pc index create \
  --name "integrated-dense-cli" \
  --dimension 1024 \
  --metric "cosine" \
  --cloud "aws" \
  --region "us-east-1" \
  --model "llama-text-embed-v2" \
  --field_map "text=chunk_text"
```
:::

:::code-group
```python Python
{'deletion_protection': 'disabled',
 'dimension': 1024,
 'embed': {'dimension': 1024,
           'field_map': {'text': 'chunk_text'},
           'metric': 'cosine',
           'model': 'llama-text-embed-v2',
           'read_parameters': {'input_type': 'query', 'truncate': 'END'},
           'write_parameters': {'input_type': 'passage', 'truncate': 'END'}},
 'host': 'integrated-dense-py-govk0nt.svc.aped-4627-b74a.pinecone.io',
 'id': '9dabb7cb-ec0a-4e2e-b79e-c7c997e592ce',
 'metric': 'cosine',
 'name': 'integrated-dense-py',
 'spec': {'serverless': {'cloud': 'aws', 'region': 'us-east-1'}},
 'status': {'ready': True, 'state': 'Ready'},
 'tags': None}
```

```javascript JavaScript
{
  "name": "integrated-dense-js",
  "dimension": 1024,
  "metric": "cosine",
  "host": "integrated-dense-js-govk0nt.svc.aped-4627-b74a.pinecone.io",
  "deletionProtection": "disabled",
  "tags": undefined,
  "embed": {
    "model": "llama-text-embed-v2",
    metric: 'cosine',
    dimension: 1024,
    vectorType: 'dense',
    fieldMap: { text: 'chunk_text' },
    readParameters: { input_type: 'query', truncate: 'END' },
    writeParameters: { input_type: 'passage', truncate: 'END' }
  },
  spec: { pod: undefined, serverless: { cloud: 'aws', region: 'us-east-1' } },
  status: { ready: true, state: 'Ready' },
  vectorType: 'dense'
}
```

```java Java
class IndexModel {
    name: integrated-dense-java
    dimension: 1024
    metric: cosine
    host: integrated-dense-java-govk0nt.svc.aped-4627-b74a.pinecone.io
    deletionProtection: disabled
    tags: {environment=development}
    embed: class ModelIndexEmbed {
        model: llama-text-embed-v2
        metric: cosine
        dimension: 1024
        vectorType: dense
        fieldMap: {text=chunk_text}
        readParameters: {dimension=1024.0, input_type=query, truncate=END}
        writeParameters: {dimension=1024.0, input_type=passage, truncate=END}
        additionalProperties: null
    }
    spec: class IndexModelSpec {
        byoc: null
        pod: null
        serverless: class ServerlessSpec {
            cloud: aws
            region: us-east-1
            additionalProperties: null
        }
        additionalProperties: null
    }
    status: class IndexModelStatus {
        ready: false
        state: Initializing
        additionalProperties: null
    }
    vectorType: dense
    additionalProperties: null
}
```

```go Go
{
  "name": "integrated-dense-go",
  "host": "integrated-dense-go-govk0nt.svc.aped-4627-b74a.pinecone.io",
  "metric": "cosine",
  "vector_type": "dense",
  "deletion_protection": "disabled",
  "dimension": 1024,
  "spec": {
    "serverless": {
      "cloud": "aws",
      "region": "us-east-1"
    }
  },
  "status": {
    "ready": true,
    "state": "Ready"
  },
  "embed": {
    "model": "llama-text-embed-v2",
    "dimension": 1024,
    "metric": "cosine",
    "vector_type": "dense",
    "field_map": {
      "text": "chunk_text"
    },
    "read_parameters": {
      "input_type": "query",
      "truncate": "END"
    },
    "write_parameters": {
      "input_type": "passage",
      "truncate": "END"
    }
  }
}
```

```csharp C#
{
  "name": "integrated-dense-dotnet",
  "dimension": 1024,
  "metric": "cosine",
  "host": "integrated-dense-dotnet-govk0nt.svc.aped-4627-b74a.pinecone.io",
  "deletion_protection": "disabled",
  "tags": {
    "environment": "development"
  },
  "embed": {
    "model": "llama-text-embed-v2",
    "metric": "cosine",
    "dimension": 1024,
    "vector_type": "dense",
    "field_map": {
      "text": "chunk_text"
    },
    "read_parameters": {
      "dimension": 1024,
      "input_type": "query",
      "truncate": "END"
    },
    "write_parameters": {
      "dimension": 1024,
      "input_type": "passage",
      "truncate": "END"
    }
  },
  "spec": {
    "serverless": {
      "cloud": "aws",
      "region": "us-east-1"
    }
  },
  "status": {
    "ready": true,
    "state": "Ready"
  },
  "vector_type": "dense"
}
```

```json curl
{
  "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"
    }
  }
}
```

```text CLI
[SUCCESS] Index integrated-dense-cli created successfully. Run pc index describe --name integrated-dense-cli to check status.

ATTRIBUTE              VALUE
Name                   integrated-dense-cli
Dimension              1024
Metric                 cosine
Deletion Protection    disabled
Vector Type            dense

State                  Initializing
Ready                  false
Host                   integrated-dense-cli-1c6ab6aa.svc.aped-4627-b74a.pinecone.io
Private Host           <none>

Spec                   serverless
Cloud                  aws
Region                 us-east-1
Source Collection      <none>

Model                  llama-text-embed-v2
Field Map              {"text":"chunk_text"}
Read Parameters        {"dimension":1024,"input_type":"query","truncate":"END"}
Write Parameters       {"dimension":1024,"input_type":"passage","truncate":"END"}
```
:::

`POST /indexes/create-for-model`

#### Authorizations

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `Api-Key` | `string` | - |  |

An API Key is required to call Pinecone APIs. Get yours from the [console](https://app.pinecone.io/).

#### Body

The desired configuration for the index and associated embedding model.

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `name` | `string` | - | 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 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `cloud` | `enum<string>` | - | The public cloud where you would like your index hosted. Available options: gcp, aws, azure. Example: aws |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `region` | `string` | - | The region where you would like your index to be created. Example: us-east-1 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `deletion_protection?` | `enum<string>` | `disabled` | Available options: disabled, enabled |

Whether [deletion protection](/guides/manage-data-manage-indexes#configure-deletion-protection) is enabled/disabled for the index.

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `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. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `embed` | `object` | - |  |

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](/guides/index-data-create-an-index#embedding-models) for available models and model details.

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `model` | `string` | - | The name of the embedding model to use for the index. Example: multilingual-e5-large |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `metric?` | `enum<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. Available options: cosine, euclidean, dotproduct |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `field_map` | `object` | - | Identifies the name of the text field from your document model that will be embedded. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `dimension?` | `integer` | - | The dimension of embedding vectors produced for the index. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `read_parameters?` | `object` | - | The read parameters for the embedding model. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `write_parameters?` | `object` | - | The write parameters for the embedding model. |
:::

#### Response

`201` — The index has successfully been created for the embedding model.

The IndexModel describes the configuration and status of a Pinecone index.

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `name` | `string` | - | 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 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `dimension?` | `integer` | - | The dimensions of the vectors to be inserted in the index. Required range: 1 <= x <= 20000. Example: 1536 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `metric` | `enum<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 the vector_type is dense, the metric defaults to 'cosine'. Available options: cosine, euclidean, dotproduct |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `host` | `string` | - | The URL address where the index is hosted. Example: semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `private_host?` | `string` | - | The private endpoint URL of an index. Example: semantic-search-c01b5b5.svc.private.us-west1-gcp.pinecone.io |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `deletion_protection?` | `enum<string>` | `disabled` | Available options: disabled, enabled |

Whether [deletion protection](/guides/manage-data-manage-indexes#configure-deletion-protection) is enabled/disabled for the index.

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `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. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `embed?` | `object` | - | The embedding model and document fields mapped to embedding inputs. |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `model` | `string` | - | The name of the embedding model used to create the index. Example: multilingual-e5-large |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `metric?` | `enum<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. Available options: cosine, euclidean, dotproduct |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `dimension?` | `integer` | - | The dimensions of the vectors to be inserted in the index. Required range: 1 <= x <= 20000. Example: 1536 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `vector_type?` | `string` | `dense` | 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. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `field_map?` | `object` | - | Identifies the name of the text field from your document model that is embedded. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `read_parameters?` | `object` | - | The read parameters for the embedding model. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `write_parameters?` | `object` | - | The write parameters for the embedding model. |
:::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `spec` | `object` | - |  |

:::::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `byoc?` | `object` | - | Configuration needed to deploy an index in a BYOC environment. |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `environment` | `string` | - | The environment where the index is hosted. Example: aws-us-east-1-b921 |
:::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `pod?` | `object` | - | Configuration needed to deploy a pod-based index. |

::::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `environment` | `string` | - | The environment where the index is hosted. Example: us-east1-gcp |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `replicas?` | `integer` | `1` | The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change. Required range: 1 <= x |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `shards?` | `integer` | `1` | The number of shards. Shards split your data across multiple pods so you can fit more data into an index. Required range: 1 <= x |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `pod_type` | `string` | `p1.x1` | The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `pods?` | `integer` | `1` | The number of pods to be used in the index. This should be equal to shards x replicas.' Required range: 1 <= x. Example: 1 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `metadata_config?` | `object` | - | Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata_config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes. |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `indexed?` | `string[]` | - | By default, all metadata is indexed; to change this behavior, use this property to specify an array of metadata fields that should be indexed. |
:::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `source_collection?` | `string` | - | The name of the collection to be used as the source for the index. Example: movie-embeddings |
::::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `serverless?` | `object` | - | Configuration needed to deploy a serverless index. |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `cloud` | `enum<string>` | - | The public cloud where you would like your index hosted. Available options: gcp, aws, azure. Example: aws |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `region` | `string` | - | The region where you would like your index to be created. Example: us-east-1 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `source_collection?` | `string` | - | The name of the collection to be used as the source for the index. |
:::
:::::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `status` | `object` | - |  |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `ready` | `boolean` | - |  |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `state` | `enum<string>` | - | Available options: Initializing, InitializationFailed, ScalingUp, ScalingDown, ScalingUpPodSize, ScalingDownPodSize, Terminating, Ready, Disabled |
:::

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `vector_type` | `string` | `dense` | 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. |

## Related pages

- [Account management](./account-management-index.md)
- [Admin](./admin-2-index.md)
- [Admin](./admin-index.md)
- [APIs](./apis-index.md)
- [Architecture](./architecture-index.md)
- [Bring Your Own Cloud](./bring-your-own-cloud-index.md)
- [Build an assistant](./build-an-assistant-index.md)
- [Build an integration](./build-an-integration-index.md)
- [Changelog](./changelog-index.md)
- [Changelog](../changelog.md)

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