70 lines
3.6 KiB
Markdown
70 lines
3.6 KiB
Markdown
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---
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layout: default
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title: Update connector
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parent: Connector APIs
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grand_parent: ML Commons APIs
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nav_order: 30
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---
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# Update a connector
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**Introduced 2.12**
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{: .label .label-purple }
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Use this API to update a standalone connector based on the `model_ID`. To update a connector created within a specific model, use the [Update Model API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/model-apis/update-model/).
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Before updating a standalone connector, you must undeploy all models that use the connector. For information about undeploying a model, see [Undeploy Model API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/model-apis/undeploy-model/).
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{: .note}
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Using this API, you can update the connector fields listed in the [Request fields](#request-fields) section and add optional fields to your connector. You cannot delete fields from a connector using this API.
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For information about user access for this API, see [Model access control considerations]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/model-apis/index/#model-access-control-considerations).
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## Path and HTTP methods
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```json
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PUT /_plugins/_ml/connectors/<connector_id>
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```
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## Request fields
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The following table lists the updatable fields. For more information about all connector fields, see [Blueprint configuration parameters]({{site.url}}{{site.baseurl}}/ml-commons-plugin/remote-models/blueprints#configuration-parameters).
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| Field | Data type | Description |
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| :--- | :--- | :--- |
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| `name` | String | The name of the connector. |
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| `description` | String | A description of the connector. |
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| `version` | Integer | The version of the connector. |
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| `protocol` | String | The protocol for the connection. For AWS services, such as Amazon SageMaker and Amazon Bedrock, use `aws_sigv4`. For all other services, use `http`. |
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| `parameters` | JSON object | The default connector parameters, including `endpoint` and `model`. Any parameters included in this field can be overridden by parameters specified in a predict request. |
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| `credential` | JSON object | Defines any credential variables required in order to connect to your chosen endpoint. ML Commons uses **AES/GCM/NoPadding** symmetric encryption to encrypt your credentials. When the connection to the cluster first starts, OpenSearch creates a random 32-byte encryption key that persists in OpenSearch's system index. Therefore, you do not need to manually set the encryption key. |
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| `actions` | JSON array | Defines which actions can run within the connector. If you're an administrator creating a connection, add the [blueprint]({{site.url}}{{site.baseurl}}/ml-commons-plugin/remote-models/blueprints/) for your desired connection. |
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| `backend_roles` | JSON array | A list of OpenSearch backend roles. For more information about setting up backend roles, see [Assigning backend roles to users]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-access-control#assigning-backend-roles-to-users). |
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| `access_mode` | String | Sets the access mode for the model, either `public`, `restricted`, or `private`. Default is `private`. For more information about `access_mode`, see [Model groups]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-access-control#model-groups). |
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#### Example request
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```json
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PUT /_plugins/_ml/connectors/u3DEbI0BfUsSoeNTti-1
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{
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"description": "The connector to public OpenAI model service for GPT 3.5"
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}
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```
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{% include copy-curl.html %}
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#### Example response
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```json
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{
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"_index": ".plugins-ml-connector",
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"_id": "u3DEbI0BfUsSoeNTti-1",
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"_version": 2,
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"result": "updated",
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"_shards": {
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"total": 1,
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"successful": 1,
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"failed": 0
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},
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"_seq_no": 2,
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"_primary_term": 1
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}
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```
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