Add ML connector edits

_ml-commons-plugin/extensibility/blueprints.md

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+---
+layout: default
+title: Building blueprints
+has_children: false
+nav_order: 65
+parent: ML extensibility 
+---
+
+# Building blueprints
+
+All connectors consist of a JSON blueprint created by machine learning (ML) developers. The blueprint allows administrators and data scientists to make connections between OpenSearch and an AI service or model-serving technology. 
+
+The following example shows a blueprint that connects to Amazon SageMaker:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+  "name": "<YOUR CONNECTOR NAME>",
+  "description": "<YOUR CONNECTOR DESCRIPTION>",
+  "version": "<YOUR CONNECTOR VERSION>",
+  "protocol": "aws_sigv4",
+  "credential": {
+    "access_key": "<ADD YOUR AWS ACCESS KEY HERE>",
+    "secret_key": "<ADD YOUR AWS SECRET KEY HERE>",
+    "session_token": "<ADD YOUR AWS SECURITY TOKEN HERE>"
+  },
+  "parameters": {
+    "region": "<ADD YOUR AWS REGION HERE>",
+    "service_name": "sagemaker"
+  },
+  "actions": [
+    {
+      "action_type": "predict",
+      "method": "POST",
+      "headers": {
+        "content-type": "application/json"
+      },
+      "url": "<ADD YOUR Sagemaker MODEL ENDPOINT URL>",
+      "request_body": "<ADD YOUR REQUEST BODY. Example: ${parameters.inputs}>"
+    }
+  ]
+}
+```
+
+
+## Example blueprints
+
+You can find blueprints for each connector in the [ML Commons repository](https://github.com/opensearch-project/ml-commons/tree/2.x/docs/remote_inference_blueprints). 
+
+## Configuration options
+
+The following configuration options are **required** in order to build a connector blueprint. These settings can be used for both external and local connectors.
+
+| Field | Data type | Description |
+| :---  | :--- | :--- |
+| `name` | String | The name of the connector. |
+| `description` | String | A description of the connector. |
+| `version` | Integer | The version of the connector. |
+| `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`. |
+| `parameters` | JSON object | The default connector parameters, including `endpoint` and `model`. Any parameters indicated in this field can be overridden by parameters specified in a predict request. |
+| `credential` | `Map<string, string>` | Defines any credential variables required 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. |
+| `actions` | JSON array | Define what actions can run within the connector. If you're an administrator making a connection, add the [blueprint]({{site.url}}{{site.baseurl}}/ml-commons-plugin/extensibility/blueprints/) for your desired connection. |
+| `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). |
+| `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). |
+| `add_all_backend_roles` | Boolean | When set to `true`, adds all `backend_roles` to the access list, which only a user with admin permissions can adjust. When set to `false`, non-admins can add `backend_roles`. |
+
+The `action` parameter supports the following options.
+
+| Field | Data type | Description |
+| :---  | :--- | :--- |
+| `action_type` | String | Required. Sets the ML Commons API operation to use upon connection. As of OpenSearch 2.9, only `predict` is supported. |
+| `method` | String | Required. Defines the HTTP method for the API call. Supports `POST` and `GET`. |
+| `url` | String | Required. Sets the connection endpoint at which the action takes place. This must match the regex expression for the connection used when [adding trusted endpoints]({{site.url}}{{site.baseurl}}/ml-commons-plugin/extensibility/index#adding-trusted-endpoints). |
+| `headers` | JSON object | Sets the headers used inside the request or response body. Default is `ContentType: application/json`. If your third-party ML tool requires access control, define the required `credential` parameters in the `headers` parameter. |
+| `request_body` | String | Required. Sets the parameters contained inside the request body of the action. The parameters must include `\"inputText\`, which specifies how users of the connector should construct the request payload for the `action_type`. |
+
+## Next step
+
+To see how system administrators and data scientists use blueprints for connectors, see [Creating connectors for third-party ML platforms]({{site.url}}{{site.baseurl}}/ml-commons-plugin/extensibility/connectors/).