//// [source,console] ---- DELETE _ingest/pipeline/*_embeddings_pipeline ---- // TEST // TEARDOWN //// // tag::cohere[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/cohere_embeddings_pipeline { "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 <>, 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::elser[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/elser_embeddings_pipeline { "processors": [ { "inference": { "model_id": "elser_embeddings", <1> "input_output": { <2> "input_field": "content", "output_field": "content_embedding" } } } ] } -------------------------------------------------- <1> The name of the inference endpoint you created by using the <>, 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::elser[] // tag::hugging-face[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/hugging_face_embeddings_pipeline { "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 <>, 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_pipeline { "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 <>, 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_pipeline { "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 <>, 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_pipeline { "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 <>, 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[] // tag::google-vertex-ai[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/google_vertex_ai_embeddings_pipeline { "processors": [ { "inference": { "model_id": "google_vertex_ai_embeddings", <1> "input_output": { <2> "input_field": "content", "output_field": "content_embedding" } } } ] } -------------------------------------------------- <1> The name of the inference endpoint you created by using the <>, 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::google-vertex-ai[] // tag::mistral[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/mistral_embeddings_pipeline { "processors": [ { "inference": { "model_id": "mistral_embeddings", <1> "input_output": { <2> "input_field": "content", "output_field": "content_embedding" } } } ] } -------------------------------------------------- <1> The name of the inference endpoint you created by using the <>, 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::mistral[] // tag::amazon-bedrock[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/amazon_bedrock_embeddings_pipeline { "processors": [ { "inference": { "model_id": "amazon_bedrock_embeddings", <1> "input_output": { <2> "input_field": "content", "output_field": "content_embedding" } } } ] } -------------------------------------------------- <1> The name of the inference endpoint you created by using the <>, 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::amazon-bedrock[] // tag::alibabacloud-ai-search[] [source,console] -------------------------------------------------- PUT _ingest/pipeline/alibabacloud_ai_search_embeddings_pipeline { "processors": [ { "inference": { "model_id": "alibabacloud_ai_search_embeddings", <1> "input_output": { <2> "input_field": "content", "output_field": "content_embedding" } } } ] } -------------------------------------------------- <1> The name of the inference endpoint you created by using the <>, 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::alibabacloud-ai-search[]