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[Backport 2.12] Updates Cohere connector info in connectors.md #6676

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hdhalter merged 1 commit into from
Mar 14, 2024
Merged

[Backport 2.12] Updates Cohere connector info in connectors.md #6676

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18 changes: 10 additions & 8 deletions _ml-commons-plugin/remote-models/connectors.md
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Original file line number Diff line number Diff line change
Expand Up @@ -214,20 +214,21 @@ The `parameters` section requires the following options when using `aws_sigv4` a

### Cohere connector

You can use the following example request to create a standalone Cohere connector:
You can use the following example request to create a standalone Cohere connector using the Embed V3 model. For more information, see [Cohere connector blueprint](https://github.com/opensearch-project/ml-commons/blob/2.x/docs/remote_inference_blueprints/cohere_connector_embedding_blueprint).

```json
POST /_plugins/_ml/connectors/_create
{
"name": "<YOUR CONNECTOR NAME>",
"description": "<YOUR CONNECTOR DESCRIPTION>",
"version": "<YOUR CONNECTOR VERSION>",
"name": "Cohere Embed Model",
"description": "The connector to Cohere's public embed API",
"version": "1",
"protocol": "http",
"credential": {
"cohere_key": "<YOUR COHERE API KEY HERE>"
"cohere_key": "<ENTER_COHERE_API_KEY_HERE>"
},
"parameters": {
"model": "embed-english-v2.0",
"model": "embed-english-v3.0",
"input_type":"search_document",
"truncate": "END"
},
"actions": [
Expand All @@ -236,9 +237,10 @@ POST /_plugins/_ml/connectors/_create
"method": "POST",
"url": "https://api.cohere.ai/v1/embed",
"headers": {
"Authorization": "Bearer ${credential.cohere_key}"
"Authorization": "Bearer ${credential.cohere_key}",
"Request-Source": "unspecified:opensearch"
},
"request_body": "{ \"texts\": ${parameters.texts}, \"truncate\": \"${parameters.truncate}\", \"model\": \"${parameters.model}\" }",
"request_body": "{ \"texts\": ${parameters.texts}, \"truncate\": \"${parameters.truncate}\", \"model\": \"${parameters.model}\", \"input_type\": \"${parameters.input_type}\" }",
"pre_process_function": "connector.pre_process.cohere.embedding",
"post_process_function": "connector.post_process.cohere.embedding"
}
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