////

[source,console]
----
DELETE _ingest/pipeline/*_embeddings
----
// TEST
// TEARDOWN

////

// tag::cohere[]

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/cohere_embeddings
{
  "processors": [
    {
      "inference": {
        "model_id": "cohere_embeddings", <1>
        "input_output": { <2>
          "input_field": "content",
          "output_field": "content_embedding"
        }
      }
    }
  ]
}
--------------------------------------------------
<1> The name of the inference endpoint you created by using the
<<put-inference-api>>, it's referred to as `inference_id` in that step.
<2> Configuration object that defines the `input_field` for the {infer} process
and the `output_field` that will contain the {infer} results.

// end::cohere[]

// tag::hugging-face[]

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/hugging_face_embeddings
{
  "processors": [
    {
      "inference": {
        "model_id": "hugging_face_embeddings", <1>
        "input_output": { <2>
          "input_field": "content",
          "output_field": "content_embedding"
        }
      }
    }
  ]
}
--------------------------------------------------
<1> The name of the inference endpoint you created by using the
<<put-inference-api>>, it's referred to as `inference_id` in that step.
<2> Configuration object that defines the `input_field` for the {infer} process
and the `output_field` that will contain the {infer} results.

// end::hugging-face[]

// tag::openai[]

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/openai_embeddings
{
  "processors": [
    {
      "inference": {
        "model_id": "openai_embeddings", <1>
        "input_output": { <2>
          "input_field": "content",
          "output_field": "content_embedding"
        }
      }
    }
  ]
}
--------------------------------------------------
<1> The name of the inference endpoint you created by using the
<<put-inference-api>>, it's referred to as `inference_id` in that step.
<2> Configuration object that defines the `input_field` for the {infer} process
and the `output_field` that will contain the {infer} results.

// end::openai[]

// tag::azure-openai[]

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/azure_openai_embeddings
{
  "processors": [
    {
      "inference": {
        "model_id": "azure_openai_embeddings", <1>
        "input_output": { <2>
          "input_field": "content",
          "output_field": "content_embedding"
        }
      }
    }
  ]
}
--------------------------------------------------
<1> The name of the inference endpoint you created by using the
<<put-inference-api>>, it's referred to as `inference_id` in that step.
<2> Configuration object that defines the `input_field` for the {infer} process
and the `output_field` that will contain the {infer} results.

// end::azure-openai[]

// tag::azure-ai-studio[]

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/azure_ai_studio_embeddings
{
  "processors": [
    {
      "inference": {
        "model_id": "azure_ai_studio_embeddings", <1>
        "input_output": { <2>
          "input_field": "content",
          "output_field": "content_embedding"
        }
      }
    }
  ]
}
--------------------------------------------------
<1> The name of the inference endpoint you created by using the
<<put-inference-api>>, it's referred to as `inference_id` in that step.
<2> Configuration object that defines the `input_field` for the {infer} process
and the `output_field` that will contain the {infer} results.

// end::azure-ai-studio[]
