PATCH /indexes/{index_name}
Configure an existing index. For guidance and examples, see Manage indexes.
Servers
- https://api.pinecone.io
Path parameters
| Name | Type | Required | Description |
|---|---|---|---|
index_name |
String | Yes |
The name of the index to configure. |
Request headers
| Name | Type | Required | Description |
|---|---|---|---|
Content-Type |
String | Yes |
The media type of the request body.
Default value: "application/json" |
X-Pinecone-Api-Version |
String | Yes |
Required date-based version header Default value: "2025-10" |
Request body fields
| Name | Type | Required | Description |
|---|---|---|---|
deletion_protection |
String | No |
Whether deletion protection is enabled/disabled for the index.
Possible values: Default value: "disabled" |
spec |
No |
The spec object defines how the index should be deployed. Only some attributes of an index's spec may be updated. In general, you can modify settings related to scaling and configuration but you cannot change the cloud or region where the index is hosted. |
|
tags |
Object | No |
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. |
embed |
Object | No |
Configure the integrated inference embedding settings for this index. You can convert an existing index to an integrated index by specifying the embedding model and field_map. The index vector type and dimension must match the model vector type and dimension, and the index similarity metric must be supported by the model. Refer to the model guide for available models and model details. You can later change the embedding configuration to update the field map, read parameters, or write parameters. Once set, the model cannot be changed. |
embed.field_map |
Object | No |
Identifies the name of the text field from your document model that will be embedded. |
embed.write_parameters |
Object | No |
The write parameters for the embedding model. |
embed.model |
String | No |
The name of the embedding model to use with the index. The index dimension and model dimension must match, and the index similarity metric must be supported by the model. The index embedding model cannot be changed once set. |
embed.read_parameters |
Object | No |
The read parameters for the embedding model. |
How to start integrating
- Add HTTP Task to your workflow definition.
- Search for the API you want to integrate with and click on the name.
- This loads the API reference documentation and prepares the Http request settings.
- Click Test request to test run your request to the API and see the API's response.