Update blueprints.md (#9889) (#9890)

Author: opensearch-trigger-bot[bot]

_ml-commons-plugin/remote-models/blueprints.md

@@ -80,7 +80,7 @@ The `actions` parameter supports the following options.
 | `url` | String      | Required. Specifies the connection endpoint at which the action occurs. This must match the regex expression for the connection used when [adding trusted endpoints]({{site.url}}{{site.baseurl}}/ml-commons-plugin/remote-models/index#adding-trusted-endpoints).|
 | `request_body` | String | Required. Sets the parameters contained in 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`.  |
 | `pre_process_function`  | String | Optional. A built-in or custom Painless script used to preprocess the input data. OpenSearch provides the following built-in preprocess functions that you can call directly:<br> - `connector.pre_process.cohere.embedding` for [Cohere](https://cohere.com/) embedding models<br> - `connector.pre_process.openai.embedding` for [OpenAI](https://platform.openai.com/docs/guides/embeddings) embedding models <br> - `connector.pre_process.default.embedding`, which you can use to preprocess documents in neural search requests so that they are in the format that ML Commons can process with the default preprocessor (OpenSearch 2.11 or later). For more information, see [Built-in functions](#built-in-pre--and-post-processing-functions). |
-| `post_process_function` | String   | Optional. A built-in or custom Painless script used to post-process the model output data. OpenSearch provides the following built-in post-process functions that you can call directly:<br> - `connector.pre_process.cohere.embedding` for [Cohere text embedding models](https://docs.cohere.com/reference/embed)<br> - `connector.pre_process.openai.embedding` for [OpenAI text embedding models](https://platform.openai.com/docs/api-reference/embeddings) <br> - `connector.post_process.default.embedding`, which you can use to post-process documents in the model response so that they are in the format that neural search expects (OpenSearch 2.11 or later). For more information, see [Built-in functions](#built-in-pre--and-post-processing-functions). |
+| `post_process_function` | String   | Optional. A built-in or custom Painless script used to post-process the model output data. OpenSearch provides the following built-in post-process functions that you can call directly:<br> - `connector.post_process.cohere.embedding` for [Cohere text embedding models](https://docs.cohere.com/reference/embed)<br> - `connector.post_process.openai.embedding` for [OpenAI text embedding models](https://platform.openai.com/docs/api-reference/embeddings) <br> - `connector.post_process.default.embedding`, which you can use to post-process documents in the model response so that they are in the format that neural search expects (OpenSearch 2.11 or later). For more information, see [Built-in functions](#built-in-pre--and-post-processing-functions). |
 | `headers` | JSON object | Specifies the headers used in 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. |
 
 The `client_config` parameter supports the following options.