From fd56b7de8f10202feb3be3d3c833b244501dc435 Mon Sep 17 00:00:00 2001 From: pquentin <42327+pquentin@users.noreply.github.com> Date: Sat, 12 Apr 2025 04:06:53 +0000 Subject: [PATCH] Update rest-api-spec --- output/openapi/elasticsearch-openapi.json | 4 ++-- .../openapi/elasticsearch-serverless-openapi.json | 4 ++-- output/schema/schema-serverless.json | 15 +++++++-------- output/schema/schema.json | 9 ++++----- 4 files changed, 15 insertions(+), 17 deletions(-) diff --git a/output/openapi/elasticsearch-openapi.json b/output/openapi/elasticsearch-openapi.json index 4bbe109381..d73ead59c7 100644 --- a/output/openapi/elasticsearch-openapi.json +++ b/output/openapi/elasticsearch-openapi.json @@ -17707,7 +17707,7 @@ "inference" ], "summary": "Perform inference on the service", - "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "operationId": "inference-inference", "parameters": [ { @@ -17804,7 +17804,7 @@ "inference" ], "summary": "Perform inference on the service", - "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "operationId": "inference-inference-1", "parameters": [ { diff --git a/output/openapi/elasticsearch-serverless-openapi.json b/output/openapi/elasticsearch-serverless-openapi.json index ab292aff01..1da46d07ea 100644 --- a/output/openapi/elasticsearch-serverless-openapi.json +++ b/output/openapi/elasticsearch-serverless-openapi.json @@ -9663,7 +9663,7 @@ "inference" ], "summary": "Perform inference on the service", - "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "operationId": "inference-inference", "parameters": [ { @@ -9760,7 +9760,7 @@ "inference" ], "summary": "Perform inference on the service", - "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "This API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "operationId": "inference-inference-1", "parameters": [ { diff --git a/output/schema/schema-serverless.json b/output/schema/schema-serverless.json index 5fd75e87dc..1e10889c41 100644 --- a/output/schema/schema-serverless.json +++ b/output/schema/schema-serverless.json @@ -4674,9 +4674,9 @@ "visibility": "public" } }, - "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "docId": "inference-api-post", - "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-inference", + "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/{branch}/post-inference-api.html", "name": "inference.inference", "privileges": { "cluster": [ @@ -8264,7 +8264,7 @@ "description": "Update a data frame analytics job.", "docId": "update-dfanalytics", "docTag": "ml data frame", - "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-ml-update-data-frame-analytics", + "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/v8/operation/operation-ml-update-data-frame-analytics", "name": "ml.update_data_frame_analytics", "privileges": { "cluster": [ @@ -8451,7 +8451,7 @@ "description": "Update a trained model deployment.", "docId": "update-trained-model-deployment", "docTag": "ml trained model", - "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-ml-update-trained-model-deployment", + "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/v8/operation/operation-ml-update-trained-model-deployment", "name": "ml.update_trained_model_deployment", "privileges": { "cluster": [ @@ -11266,7 +11266,7 @@ }, "description": "Update a transform.\nUpdates certain properties of a transform.\n\nAll updated properties except `description` do not take effect until after the transform starts the next checkpoint,\nthus there is data consistency in each checkpoint. To use this API, you must have `read` and `view_index_metadata`\nprivileges for the source indices. You must also have `index` and `read` privileges for the destination index. When\nElasticsearch security features are enabled, the transform remembers which roles the user who updated it had at the\ntime of update and runs with those privileges.", "docId": "update-transform", - "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-transform-update-transform", + "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/v8/operation/operation-transform-update-transform", "name": "transform.update_transform", "privileges": { "cluster": [ @@ -27992,7 +27992,7 @@ } ] }, - "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "inherits": { "type": { "name": "RequestBase", @@ -28045,11 +28045,10 @@ } } ], - "specLocation": "inference/inference/InferenceRequest.ts#L26-L89" + "specLocation": "inference/inference/InferenceRequest.ts#L26-L91" }, { "body": { - "codegenName": "result", "kind": "value", "value": { "kind": "instance_of", diff --git a/output/schema/schema.json b/output/schema/schema.json index 8689ae96c9..6d13e580a9 100644 --- a/output/schema/schema.json +++ b/output/schema/schema.json @@ -9349,9 +9349,9 @@ "visibility": "public" } }, - "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "docId": "inference-api-post", - "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-inference", + "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/{branch}/post-inference-api.html", "name": "inference.inference", "privileges": { "cluster": [ @@ -153438,7 +153438,7 @@ } ] }, - "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", + "description": "Perform inference on the service.\n\nThis API enables you to use machine learning models to perform specific tasks on data that you provide as an input.\nIt returns a response with the results of the tasks.\nThe inference endpoint you use can perform one specific task that has been defined when the endpoint was created with the create inference API.\n\nFor details about using this API with a service, such as Amazon Bedrock, Anthropic, or HuggingFace, refer to the service-specific documentation.\n\n> info\n> The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.", "inherits": { "type": { "name": "RequestBase", @@ -153490,13 +153490,12 @@ } } ], - "specLocation": "inference/inference/InferenceRequest.ts#L26-L89" + "specLocation": "inference/inference/InferenceRequest.ts#L26-L91" }, { "kind": "response", "body": { "kind": "value", - "codegenName": "result", "value": { "kind": "instance_of", "type": {