diff --git a/output/openapi/elasticsearch-openapi.json b/output/openapi/elasticsearch-openapi.json index ae49b7b66e..b42de47d98 100644 --- a/output/openapi/elasticsearch-openapi.json +++ b/output/openapi/elasticsearch-openapi.json @@ -20316,7 +20316,7 @@ "inference" ], "summary": "Create a Hugging Face inference endpoint", - "description": "Create an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n ##Required authorization\n* Cluster privileges: `manage_inference`", + "description": "Create an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`\n ##Required authorization\n* Cluster privileges: `manage_inference`", "operationId": "inference-put-hugging-face", "parameters": [ { @@ -20356,6 +20356,9 @@ }, "service_settings": { "$ref": "#/components/schemas/inference._types.HuggingFaceServiceSettings" + }, + "task_settings": { + "$ref": "#/components/schemas/inference._types.HuggingFaceTaskSettings" } }, "required": [ @@ -20368,6 +20371,11 @@ "summary": "A text embedding task", "description": "Run `PUT _inference/text_embedding/hugging-face-embeddings` to create an inference endpoint that performs a `text_embedding` task type.", "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n }\n}" + }, + "PutHuggingFaceRequestExample2": { + "summary": "A rerank task", + "description": "Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type.", + "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n },\n \"task_settings\": {\n \"return_documents\": true,\n \"top_n\": 3\n }\n}" } } } @@ -20902,6 +20910,16 @@ "summary": "Rerank task", "description": "Run `POST _inference/rerank/cohere_rerank` to perform reranking on the example input.", "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\"\n}" + }, + "RerankRequestExample2": { + "summary": "Rerank task", + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": false,\n \"top_n\": 2\n}" + }, + "RerankRequestExample3": { + "summary": "Rerank task", + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": true,\n \"top_n\": 3\n}" } } } @@ -20920,6 +20938,16 @@ "summary": "Rerank task", "description": "A successful response from `POST _inference/rerank/cohere_rerank`.\n", "value": "{\n \"rerank\": [\n {\n \"index\": \"2\",\n \"relevance_score\": \"0.011597361\",\n \"text\": \"leia\"\n },\n {\n \"index\": \"0\",\n \"relevance_score\": \"0.006338922\",\n \"text\": \"luke\"\n },\n {\n \"index\": \"5\",\n \"relevance_score\": \"0.0016166499\",\n \"text\": \"star\"\n },\n {\n \"index\": \"4\",\n \"relevance_score\": \"0.0011695103\",\n \"text\": \"r2d2\"\n },\n {\n \"index\": \"1\",\n \"relevance_score\": \"5.614787E-4\",\n \"text\": \"like\"\n },\n {\n \"index\": \"6\",\n \"relevance_score\": \"3.7850367E-4\",\n \"text\": \"wars\"\n },\n {\n \"index\": \"3\",\n \"relevance_score\": \"1.2508839E-5\",\n \"text\": \"chewy\"\n }\n ]\n}" + }, + "RerankResponseExample2": { + "summary": "Rerank task", + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794\n }\n ]\n}" + }, + "RerankResponseExample3": { + "summary": "Rerank task", + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844,\n \"text\": \"wars\"\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794,\n \"text\": \"star\"\n },\n {\n \"index\": 3,\n \"relevance_score\": 0.004520818,\n \"text\": \"chewy\"\n }\n ]\n}" } } } @@ -84516,6 +84544,7 @@ "enum": [ "chat_completion", "completion", + "rerank", "text_embedding" ] }, @@ -84555,6 +84584,19 @@ "url" ] }, + "inference._types.HuggingFaceTaskSettings": { + "type": "object", + "properties": { + "return_documents": { + "description": "For a `rerank` task, return doc text within the results.", + "type": "boolean" + }, + "top_n": { + "description": "For a `rerank` task, the number of most relevant documents to return.\nIt defaults to the number of the documents.", + "type": "number" + } + } + }, "inference._types.InferenceEndpointInfoHuggingFace": { "allOf": [ { diff --git a/output/openapi/elasticsearch-serverless-openapi.json b/output/openapi/elasticsearch-serverless-openapi.json index e89edae8c0..60e98f2973 100644 --- a/output/openapi/elasticsearch-serverless-openapi.json +++ b/output/openapi/elasticsearch-serverless-openapi.json @@ -11666,7 +11666,7 @@ "inference" ], "summary": "Create a Hugging Face inference endpoint", - "description": "Create an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n ##Required authorization\n* Cluster privileges: `manage_inference`", + "description": "Create an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`\n ##Required authorization\n* Cluster privileges: `manage_inference`", "operationId": "inference-put-hugging-face", "parameters": [ { @@ -11706,6 +11706,9 @@ }, "service_settings": { "$ref": "#/components/schemas/inference._types.HuggingFaceServiceSettings" + }, + "task_settings": { + "$ref": "#/components/schemas/inference._types.HuggingFaceTaskSettings" } }, "required": [ @@ -11718,6 +11721,11 @@ "summary": "A text embedding task", "description": "Run `PUT _inference/text_embedding/hugging-face-embeddings` to create an inference endpoint that performs a `text_embedding` task type.", "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n }\n}" + }, + "PutHuggingFaceRequestExample2": { + "summary": "A rerank task", + "description": "Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type.", + "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n },\n \"task_settings\": {\n \"return_documents\": true,\n \"top_n\": 3\n }\n}" } } } @@ -12252,6 +12260,16 @@ "summary": "Rerank task", "description": "Run `POST _inference/rerank/cohere_rerank` to perform reranking on the example input.", "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\"\n}" + }, + "RerankRequestExample2": { + "summary": "Rerank task", + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": false,\n \"top_n\": 2\n}" + }, + "RerankRequestExample3": { + "summary": "Rerank task", + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": true,\n \"top_n\": 3\n}" } } } @@ -12270,6 +12288,16 @@ "summary": "Rerank task", "description": "A successful response from `POST _inference/rerank/cohere_rerank`.\n", "value": "{\n \"rerank\": [\n {\n \"index\": \"2\",\n \"relevance_score\": \"0.011597361\",\n \"text\": \"leia\"\n },\n {\n \"index\": \"0\",\n \"relevance_score\": \"0.006338922\",\n \"text\": \"luke\"\n },\n {\n \"index\": \"5\",\n \"relevance_score\": \"0.0016166499\",\n \"text\": \"star\"\n },\n {\n \"index\": \"4\",\n \"relevance_score\": \"0.0011695103\",\n \"text\": \"r2d2\"\n },\n {\n \"index\": \"1\",\n \"relevance_score\": \"5.614787E-4\",\n \"text\": \"like\"\n },\n {\n \"index\": \"6\",\n \"relevance_score\": \"3.7850367E-4\",\n \"text\": \"wars\"\n },\n {\n \"index\": \"3\",\n \"relevance_score\": \"1.2508839E-5\",\n \"text\": \"chewy\"\n }\n ]\n}" + }, + "RerankResponseExample2": { + "summary": "Rerank task", + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794\n }\n ]\n}" + }, + "RerankResponseExample3": { + "summary": "Rerank task", + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844,\n \"text\": \"wars\"\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794,\n \"text\": \"star\"\n },\n {\n \"index\": 3,\n \"relevance_score\": 0.004520818,\n \"text\": \"chewy\"\n }\n ]\n}" } } } @@ -54079,6 +54107,7 @@ "enum": [ "chat_completion", "completion", + "rerank", "text_embedding" ] }, @@ -54118,6 +54147,19 @@ "url" ] }, + "inference._types.HuggingFaceTaskSettings": { + "type": "object", + "properties": { + "return_documents": { + "description": "For a `rerank` task, return doc text within the results.", + "type": "boolean" + }, + "top_n": { + "description": "For a `rerank` task, the number of most relevant documents to return.\nIt defaults to the number of the documents.", + "type": "number" + } + } + }, "inference._types.InferenceEndpointInfoHuggingFace": { "allOf": [ { diff --git a/output/schema/schema-serverless.json b/output/schema/schema-serverless.json index 3e3f446e11..59601f3c9b 100644 --- a/output/schema/schema-serverless.json +++ b/output/schema/schema-serverless.json @@ -3628,42 +3628,6 @@ } ] }, - { - "availability": { - "serverless": { - "stability": "stable", - "visibility": "public" - }, - "stack": { - "since": "8.19.0", - "stability": "stable" - } - }, - "description": "Get data stream options.\n\nGet the data stream options configuration of one or more data streams.", - "docTag": "data stream", - "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html", - "name": "indices.get_data_stream_options", - "request": { - "name": "Request", - "namespace": "indices.get_data_stream_options" - }, - "requestBodyRequired": false, - "response": { - "name": "Response", - "namespace": "indices.get_data_stream_options" - }, - "responseMediaType": [ - "application/json" - ], - "urls": [ - { - "methods": [ - "GET" - ], - "path": "/_data_stream/{name}/_options" - } - ] - }, { "availability": { "serverless": { @@ -3983,45 +3947,6 @@ } ] }, - { - "availability": { - "serverless": { - "stability": "stable", - "visibility": "public" - }, - "stack": { - "since": "8.19.0", - "stability": "stable" - } - }, - "description": "Update data stream options.\nUpdate the data stream options of the specified data streams.", - "docTag": "data stream", - "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html", - "name": "indices.put_data_stream_options", - "request": { - "name": "Request", - "namespace": "indices.put_data_stream_options" - }, - "requestBodyRequired": false, - "requestMediaType": [ - "application/json" - ], - "response": { - "name": "Response", - "namespace": "indices.put_data_stream_options" - }, - "responseMediaType": [ - "application/json" - ], - "urls": [ - { - "methods": [ - "PUT" - ], - "path": "/_data_stream/{name}/_options" - } - ] - }, { "availability": { "serverless": { @@ -4494,7 +4419,7 @@ "visibility": "public" } }, - "description": "Perform chat completion inference\n\nThe chat completion inference API enables real-time responses for chat completion tasks by delivering answers incrementally, reducing response times during computation. \nIt only works with the `chat_completion` task type for `openai`, `elastic` and `googlevertexai` inference services.\n\nIMPORTANT: 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.\nFor 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.\n\nNOTE: The `chat_completion` task type is only available within the _stream API and only supports streaming.\nThe Chat completion inference API and the Stream inference API differ in their response structure and capabilities.\nThe Chat completion inference API provides more comprehensive customization options through more fields and function calling support.\nIf you use the `openai` service or the `elastic` service, use the Chat completion inference API.", + "description": "Perform chat completion inference\n\nThe chat completion inference API enables real-time responses for chat completion tasks by delivering answers incrementally, reducing response times during computation. \nIt only works with the `chat_completion` task type for `openai` and `elastic` inference services.\n\nIMPORTANT: 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.\nFor 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.\n\nNOTE: The `chat_completion` task type is only available within the _stream API and only supports streaming.\nThe Chat completion inference API and the Stream inference API differ in their response structure and capabilities.\nThe Chat completion inference API provides more comprehensive customization options through more fields and function calling support.\nIf you use the `openai` service or the `elastic` service, use the Chat completion inference API.", "docId": "inference-api-chat-completion", "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-unified-inference", "name": "inference.chat_completion_unified", @@ -5222,7 +5147,7 @@ "visibility": "public" } }, - "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\n\nYou must first create an inference endpoint on the Hugging Face endpoint page to get an endpoint URL.\nSelect the model you want to use on the new endpoint creation page (for example `intfloat/e5-small-v2`), then select the sentence embeddings task under the advanced configuration section.\nCreate the endpoint and copy the URL after the endpoint initialization has been finished.\n\nThe following models are recommended for the Hugging Face service:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`", + "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\n\nYou must first create an inference endpoint on the Hugging Face endpoint page to get an endpoint URL.\nSelect the model you want to use on the new endpoint creation page (for example `intfloat/e5-small-v2`), then select the sentence embeddings task under the advanced configuration section.\nCreate the endpoint and copy the URL after the endpoint initialization has been finished.\n\nThe following models are recommended for the Hugging Face service:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`", "docId": "inference-api-put-huggingface", "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-put-hugging-face", "name": "inference.put_hugging_face", @@ -24420,7 +24345,7 @@ }, "examples": { "IndicesGetDataLifecycleResponseExample1": { - "description": "A successful response from `GET /_data_stream/{name}/_lifecycle?human&pretty`.", + "description": "A successful response from `GET _lifecycle/stats?human&pretty`.", "value": "{\n \"data_streams\": [\n {\n \"name\": \"my-data-stream-1\",\n \"lifecycle\": {\n \"enabled\": true,\n \"data_retention\": \"7d\"\n }\n },\n {\n \"name\": \"my-data-stream-2\",\n \"lifecycle\": {\n \"enabled\": true,\n \"data_retention\": \"7d\"\n }\n }\n ]\n}" } }, @@ -24562,96 +24487,6 @@ }, "specLocation": "indices/get_data_stream/IndicesGetDataStreamResponse.ts#L22-L24" }, - { - "attachedBehaviors": [ - "CommonQueryParameters" - ], - "body": { - "kind": "no_body" - }, - "description": "Get data stream options.\n\nGet the data stream options configuration of one or more data streams.", - "inherits": { - "type": { - "name": "RequestBase", - "namespace": "_types" - } - }, - "kind": "request", - "name": { - "name": "Request", - "namespace": "indices.get_data_stream_options" - }, - "path": [ - { - "description": "Comma-separated list of data streams to limit the request.\nSupports wildcards (`*`).\nTo target all data streams, omit this parameter or use `*` or `_all`.", - "name": "name", - "required": true, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamNames", - "namespace": "_types" - } - } - } - ], - "query": [ - { - "description": "Type of data stream that wildcard patterns can match.\nSupports comma-separated values, such as `open,hidden`.\nValid values are: `all`, `open`, `closed`, `hidden`, `none`.", - "name": "expand_wildcards", - "required": false, - "serverDefault": "open", - "type": { - "kind": "instance_of", - "type": { - "name": "ExpandWildcards", - "namespace": "_types" - } - } - }, - { - "description": "Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.", - "name": "master_timeout", - "required": false, - "serverDefault": "30s", - "type": { - "kind": "instance_of", - "type": { - "name": "Duration", - "namespace": "_types" - } - } - } - ], - "specLocation": "indices/get_data_stream_options/IndicesGetDataStreamOptionsRequest.ts#L24-L62" - }, - { - "body": { - "kind": "properties", - "properties": [ - { - "name": "data_streams", - "required": true, - "type": { - "kind": "array_of", - "value": { - "kind": "instance_of", - "type": { - "name": "DataStreamWithOptions", - "namespace": "indices.get_data_stream_options" - } - } - } - } - ] - }, - "kind": "response", - "name": { - "name": "Response", - "namespace": "indices.get_data_stream_options" - }, - "specLocation": "indices/get_data_stream_options/IndicesGetDataStreamOptionsResponse.ts#L23-L25" - }, { "attachedBehaviors": [ "CommonQueryParameters" @@ -25538,115 +25373,6 @@ }, "specLocation": "indices/put_data_lifecycle/IndicesPutDataLifecycleResponse.ts#L22-L25" }, - { - "attachedBehaviors": [ - "CommonQueryParameters" - ], - "body": { - "kind": "properties", - "properties": [ - { - "description": "If defined, it will update the failure store configuration of every data stream resolved by the name expression.", - "name": "failure_store", - "required": false, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamFailureStore", - "namespace": "indices._types" - } - } - } - ] - }, - "description": "Update data stream options.\nUpdate the data stream options of the specified data streams.", - "inherits": { - "type": { - "name": "RequestBase", - "namespace": "_types" - } - }, - "kind": "request", - "name": { - "name": "Request", - "namespace": "indices.put_data_stream_options" - }, - "path": [ - { - "description": "Comma-separated list of data streams used to limit the request.\nSupports wildcards (`*`).\nTo target all data streams use `*` or `_all`.", - "name": "name", - "required": true, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamNames", - "namespace": "_types" - } - } - } - ], - "query": [ - { - "description": "Type of data stream that wildcard patterns can match.\nSupports comma-separated values, such as `open,hidden`.\nValid values are: `all`, `hidden`, `open`, `closed`, `none`.", - "name": "expand_wildcards", - "required": false, - "serverDefault": "open", - "type": { - "kind": "instance_of", - "type": { - "name": "ExpandWildcards", - "namespace": "_types" - } - } - }, - { - "description": "Period to wait for a connection to the master node. If no response is\nreceived before the timeout expires, the request fails and returns an\nerror.", - "name": "master_timeout", - "required": false, - "serverDefault": "30s", - "type": { - "kind": "instance_of", - "type": { - "name": "Duration", - "namespace": "_types" - } - } - }, - { - "description": "Period to wait for a response.\nIf no response is received before the timeout expires, the request fails and returns an error.", - "name": "timeout", - "required": false, - "serverDefault": "30s", - "type": { - "kind": "instance_of", - "type": { - "name": "Duration", - "namespace": "_types" - } - } - } - ], - "specLocation": "indices/put_data_stream_options/IndicesPutDataStreamOptionsRequest.ts#L25-L80" - }, - { - "body": { - "codegenName": "result", - "kind": "value", - "value": { - "kind": "instance_of", - "type": { - "name": "AcknowledgedResponseBase", - "namespace": "_types" - } - } - }, - "kind": "response", - "name": { - "name": "Response", - "namespace": "indices.put_data_stream_options" - }, - "specLocation": "indices/put_data_stream_options/IndicesPutDataStreamOptionsResponse.ts#L22-L25" - }, { "attachedBehaviors": [ "CommonQueryParameters" @@ -27683,7 +27409,7 @@ } } }, - "description": "Perform chat completion inference\n\nThe chat completion inference API enables real-time responses for chat completion tasks by delivering answers incrementally, reducing response times during computation. \nIt only works with the `chat_completion` task type for `openai`, `elastic` and `googlevertexai` inference services.\n\nIMPORTANT: 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.\nFor 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.\n\nNOTE: The `chat_completion` task type is only available within the _stream API and only supports streaming.\nThe Chat completion inference API and the Stream inference API differ in their response structure and capabilities.\nThe Chat completion inference API provides more comprehensive customization options through more fields and function calling support.\nIf you use the `openai` service or the `elastic` service, use the Chat completion inference API.", + "description": "Perform chat completion inference\n\nThe chat completion inference API enables real-time responses for chat completion tasks by delivering answers incrementally, reducing response times during computation. \nIt only works with the `chat_completion` task type for `openai` and `elastic` inference services.\n\nIMPORTANT: 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.\nFor 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.\n\nNOTE: The `chat_completion` task type is only available within the _stream API and only supports streaming.\nThe Chat completion inference API and the Stream inference API differ in their response structure and capabilities.\nThe Chat completion inference API provides more comprehensive customization options through more fields and function calling support.\nIf you use the `openai` service or the `elastic` service, use the Chat completion inference API.", "examples": { "PostChatCompletionRequestExample1": { "description": "Run `POST _inference/chat_completion/openai-completion/_stream` to perform a chat completion on the example question with streaming.", @@ -29638,12 +29364,17 @@ } ] }, - "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\n\nYou must first create an inference endpoint on the Hugging Face endpoint page to get an endpoint URL.\nSelect the model you want to use on the new endpoint creation page (for example `intfloat/e5-small-v2`), then select the sentence embeddings task under the advanced configuration section.\nCreate the endpoint and copy the URL after the endpoint initialization has been finished.\n\nThe following models are recommended for the Hugging Face service:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`", + "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\n\nYou must first create an inference endpoint on the Hugging Face endpoint page to get an endpoint URL.\nSelect the model you want to use on the new endpoint creation page (for example `intfloat/e5-small-v2`), then select the sentence embeddings task under the advanced configuration section.\nCreate the endpoint and copy the URL after the endpoint initialization has been finished.\n\nThe following models are recommended for the Hugging Face service:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`", "examples": { "PutHuggingFaceRequestExample1": { "description": "Run `PUT _inference/text_embedding/hugging-face-embeddings` to create an inference endpoint that performs a `text_embedding` task type.", "summary": "A text embedding task", "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n }\n}" + }, + "PutHuggingFaceRequestExample2": { + "description": "Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type.", + "summary": "A rerank task", + "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n },\n \"task_settings\": {\n \"return_documents\": true,\n \"top_n\": 3\n }\n}" } }, "inherits": { @@ -29684,7 +29415,7 @@ } ], "query": [], - "specLocation": "inference/put_hugging_face/PutHuggingFaceRequest.ts#L29-L85" + "specLocation": "inference/put_hugging_face/PutHuggingFaceRequest.ts#L29-L95" }, { "body": { @@ -30376,6 +30107,16 @@ "description": "Run `POST _inference/rerank/cohere_rerank` to perform reranking on the example input.", "summary": "Rerank task", "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\"\n}" + }, + "RerankRequestExample2": { + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "summary": "Rerank task", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": false,\n \"top_n\": 2\n}" + }, + "RerankRequestExample3": { + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "summary": "Rerank task", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": true,\n \"top_n\": 3\n}" } }, "inherits": { @@ -30437,6 +30178,16 @@ "description": "A successful response from `POST _inference/rerank/cohere_rerank`.\n", "summary": "Rerank task", "value": "{\n \"rerank\": [\n {\n \"index\": \"2\",\n \"relevance_score\": \"0.011597361\",\n \"text\": \"leia\"\n },\n {\n \"index\": \"0\",\n \"relevance_score\": \"0.006338922\",\n \"text\": \"luke\"\n },\n {\n \"index\": \"5\",\n \"relevance_score\": \"0.0016166499\",\n \"text\": \"star\"\n },\n {\n \"index\": \"4\",\n \"relevance_score\": \"0.0011695103\",\n \"text\": \"r2d2\"\n },\n {\n \"index\": \"1\",\n \"relevance_score\": \"5.614787E-4\",\n \"text\": \"like\"\n },\n {\n \"index\": \"6\",\n \"relevance_score\": \"3.7850367E-4\",\n \"text\": \"wars\"\n },\n {\n \"index\": \"3\",\n \"relevance_score\": \"1.2508839E-5\",\n \"text\": \"chewy\"\n }\n ]\n}" + }, + "RerankResponseExample2": { + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "summary": "Rerank task", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794\n }\n ]\n}" + }, + "RerankResponseExample3": { + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "summary": "Rerank task", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844,\n \"text\": \"wars\"\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794,\n \"text\": \"star\"\n },\n {\n \"index\": 3,\n \"relevance_score\": 0.004520818,\n \"text\": \"chewy\"\n }\n ]\n}" } }, "kind": "response", @@ -106149,7 +105900,7 @@ "name": "GoogleVertexAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L873-L875" + "specLocation": "inference/_types/CommonTypes.ts#L871-L873" }, { "kind": "enum", @@ -106159,19 +105910,13 @@ }, { "name": "text_embedding" - }, - { - "name": "completion" - }, - { - "name": "chat_completion" } ], "name": { "name": "GoogleVertexAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L866-L871" + "specLocation": "inference/_types/CommonTypes.ts#L866-L869" }, { "kind": "enum", @@ -106184,11 +105929,14 @@ "name": "HuggingFaceServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L904-L906" + "specLocation": "inference/_types/CommonTypes.ts#L903-L905" }, { "kind": "enum", "members": [ + { + "name": "rerank" + }, { "name": "text_embedding" } @@ -106197,7 +105945,7 @@ "name": "HuggingFaceTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L900-L902" + "specLocation": "inference/_types/CommonTypes.ts#L898-L901" }, { "kind": "enum", @@ -106210,7 +105958,7 @@ "name": "JinaAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L967-L969" + "specLocation": "inference/_types/CommonTypes.ts#L966-L968" }, { "kind": "enum", @@ -106229,7 +105977,7 @@ "name": "JinaAISimilarityType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L971-L975" + "specLocation": "inference/_types/CommonTypes.ts#L970-L974" }, { "kind": "enum", @@ -106245,7 +105993,7 @@ "name": "JinaAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L962-L965" + "specLocation": "inference/_types/CommonTypes.ts#L961-L964" }, { "kind": "enum", @@ -106267,7 +106015,7 @@ "name": "JinaAITextEmbeddingTask", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L977-L982" + "specLocation": "inference/_types/CommonTypes.ts#L976-L981" }, { "codegenNames": [ @@ -106349,7 +106097,7 @@ "name": "MistralServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1017-L1019" + "specLocation": "inference/_types/CommonTypes.ts#L1016-L1018" }, { "kind": "enum", @@ -106362,7 +106110,7 @@ "name": "MistralTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1013-L1015" + "specLocation": "inference/_types/CommonTypes.ts#L1012-L1014" }, { "kind": "enum", @@ -106375,7 +106123,7 @@ "name": "OpenAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1079-L1081" + "specLocation": "inference/_types/CommonTypes.ts#L1078-L1080" }, { "kind": "enum", @@ -106394,7 +106142,7 @@ "name": "OpenAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1073-L1077" + "specLocation": "inference/_types/CommonTypes.ts#L1072-L1076" }, { "kind": "type_alias", @@ -106519,7 +106267,7 @@ "name": "VoyageAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1147-L1149" + "specLocation": "inference/_types/CommonTypes.ts#L1146-L1148" }, { "kind": "enum", @@ -106535,7 +106283,7 @@ "name": "VoyageAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1142-L1145" + "specLocation": "inference/_types/CommonTypes.ts#L1141-L1144" }, { "kind": "enum", @@ -106548,7 +106296,7 @@ "name": "WatsonxServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1194-L1196" + "specLocation": "inference/_types/CommonTypes.ts#L1193-L1195" }, { "kind": "enum", @@ -106561,7 +106309,7 @@ "name": "WatsonxTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1190-L1192" + "specLocation": "inference/_types/CommonTypes.ts#L1189-L1191" }, { "kind": "enum", @@ -116710,7 +116458,7 @@ } } ], - "specLocation": "cluster/_types/ComponentTemplate.ts#L28-L31" + "specLocation": "cluster/_types/ComponentTemplate.ts#L27-L30" }, { "kind": "interface", @@ -116766,7 +116514,7 @@ } } ], - "specLocation": "cluster/_types/ComponentTemplate.ts#L33-L42" + "specLocation": "cluster/_types/ComponentTemplate.ts#L32-L41" }, { "kind": "interface", @@ -116873,41 +116621,9 @@ "namespace": "indices._types" } } - }, - { - "availability": { - "serverless": { - "stability": "stable" - }, - "stack": { - "since": "8.19.0", - "stability": "stable" - } - }, - "name": "data_stream_options", - "required": false, - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "DataStreamOptionsTemplate", - "namespace": "indices._types" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } } ], - "specLocation": "cluster/_types/ComponentTemplate.ts#L44-L61" + "specLocation": "cluster/_types/ComponentTemplate.ts#L43-L55" }, { "attachedBehaviors": [ @@ -120544,148 +120260,6 @@ ], "specLocation": "indices/_types/DataStreamLifecycle.ts#L60-L72" }, - { - "description": "Data stream options template contains the same information as DataStreamOptions but allows them to be set explicitly to null.", - "kind": "interface", - "name": { - "name": "DataStreamOptionsTemplate", - "namespace": "indices._types" - }, - "properties": [ - { - "name": "failure_store", - "required": false, - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "DataStreamFailureStoreTemplate", - "namespace": "indices._types" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } - } - ], - "specLocation": "indices/_types/DataStreamOptions.ts#L36-L41" - }, - { - "description": "Template equivalent of DataStreamFailureStore that allows nullable values.", - "kind": "interface", - "name": { - "name": "DataStreamFailureStoreTemplate", - "namespace": "indices._types" - }, - "properties": [ - { - "description": "If defined, it turns the failure store on/off (`true`/`false`) for this data stream. A data stream failure store\nthat's disabled (enabled: `false`) will redirect no new failed indices to the failure store; however, it will\nnot remove any existing data from the failure store.", - "name": "enabled", - "required": false, - "serverDefault": "true", - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } - }, - { - "description": "If defined, it specifies the lifecycle configuration for the failure store of this data stream.", - "name": "lifecycle", - "required": false, - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "FailureStoreLifecycleTemplate", - "namespace": "indices._types" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } - } - ], - "specLocation": "indices/_types/DataStreamFailureStore.ts#L39-L54" - }, - { - "description": "Template equivalent of FailureStoreLifecycle that allows nullable values.", - "kind": "interface", - "name": { - "name": "FailureStoreLifecycleTemplate", - "namespace": "indices._types" - }, - "properties": [ - { - "description": "If defined, every document added to this data stream will be stored at least for this time frame.\nAny time after this duration the document could be deleted.\nWhen empty, every document in this data stream will be stored indefinitely.", - "name": "data_retention", - "required": false, - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "Duration", - "namespace": "_types" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } - }, - { - "description": "If defined, it turns data stream lifecycle on/off (`true`/`false`) for this data stream. A data stream lifecycle\nthat's disabled (enabled: `false`) will have no effect on the data stream.", - "name": "enabled", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - } - ], - "specLocation": "indices/_types/DataStreamFailureStore.ts#L74-L90" - }, { "kind": "interface", "name": { @@ -125732,133 +125306,6 @@ ], "specLocation": "indices/_types/DataStream.ts#L141-L146" }, - { - "kind": "interface", - "name": { - "name": "DataStreamWithOptions", - "namespace": "indices.get_data_stream_options" - }, - "properties": [ - { - "name": "name", - "required": true, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamName", - "namespace": "_types" - } - } - }, - { - "name": "options", - "required": false, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamOptions", - "namespace": "indices._types" - } - } - } - ], - "specLocation": "indices/get_data_stream_options/IndicesGetDataStreamOptionsResponse.ts#L27-L30" - }, - { - "description": "Data stream options contain the configuration of data stream level features for a given data stream, for example,\nthe failure store configuration.", - "kind": "interface", - "name": { - "name": "DataStreamOptions", - "namespace": "indices._types" - }, - "properties": [ - { - "description": "If defined, it specifies configuration for the failure store of this data stream.", - "name": "failure_store", - "required": false, - "type": { - "kind": "instance_of", - "type": { - "name": "DataStreamFailureStore", - "namespace": "indices._types" - } - } - } - ], - "specLocation": "indices/_types/DataStreamOptions.ts#L25-L34" - }, - { - "description": "Data stream failure store contains the configuration of the failure store for a given data stream.", - "kind": "interface", - "name": { - "name": "DataStreamFailureStore", - "namespace": "indices._types" - }, - "properties": [ - { - "description": "If defined, it turns the failure store on/off (`true`/`false`) for this data stream. A data stream failure store\nthat's disabled (enabled: `false`) will redirect no new failed indices to the failure store; however, it will\nnot remove any existing data from the failure store.", - "name": "enabled", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - }, - { - "description": "If defined, it specifies the lifecycle configuration for the failure store of this data stream.", - "name": "lifecycle", - "required": false, - "type": { - "kind": "instance_of", - "type": { - "name": "FailureStoreLifecycle", - "namespace": "indices._types" - } - } - } - ], - "specLocation": "indices/_types/DataStreamFailureStore.ts#L22-L37" - }, - { - "description": "The failure store lifecycle configures the data stream lifecycle configuration for failure indices.", - "kind": "interface", - "name": { - "name": "FailureStoreLifecycle", - "namespace": "indices._types" - }, - "properties": [ - { - "description": "If defined, every document added to this data stream will be stored at least for this time frame.\nAny time after this duration the document could be deleted.\nWhen empty, every document in this data stream will be stored indefinitely.", - "name": "data_retention", - "required": false, - "type": { - "kind": "instance_of", - "type": { - "name": "Duration", - "namespace": "_types" - } - } - }, - { - "description": "If defined, it turns data stream lifecycle on/off (`true`/`false`) for this data stream. A data stream lifecycle\nthat's disabled (enabled: `false`) will have no effect on the data stream.", - "name": "enabled", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - } - ], - "specLocation": "indices/_types/DataStreamFailureStore.ts#L56-L72" - }, { "kind": "interface", "name": { @@ -126035,7 +125482,7 @@ } } ], - "specLocation": "indices/_types/IndexTemplate.ts#L29-L82" + "specLocation": "indices/_types/IndexTemplate.ts#L28-L81" }, { "kind": "interface", @@ -126110,41 +125557,9 @@ "namespace": "indices._types" } } - }, - { - "availability": { - "serverless": { - "stability": "stable" - }, - "stack": { - "since": "8.19.0", - "stability": "stable" - } - }, - "name": "data_stream_options", - "required": false, - "type": { - "items": [ - { - "kind": "instance_of", - "type": { - "name": "DataStreamOptionsTemplate", - "namespace": "indices._types" - } - }, - { - "kind": "instance_of", - "type": { - "name": "null", - "namespace": "_builtins" - } - } - ], - "kind": "union_of" - } } ], - "specLocation": "indices/_types/IndexTemplate.ts#L97-L124" + "specLocation": "indices/_types/IndexTemplate.ts#L96-L118" }, { "kind": "interface", @@ -126180,7 +125595,7 @@ } } ], - "specLocation": "indices/_types/IndexTemplate.ts#L84-L95" + "specLocation": "indices/_types/IndexTemplate.ts#L83-L94" }, { "kind": "interface", @@ -129154,7 +128569,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L877-L898" + "specLocation": "inference/_types/CommonTypes.ts#L875-L896" }, { "kind": "interface", @@ -129216,7 +128631,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L908-L937" + "specLocation": "inference/_types/CommonTypes.ts#L907-L936" }, { "kind": "interface", @@ -129262,7 +128677,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L939-L960" + "specLocation": "inference/_types/CommonTypes.ts#L938-L959" }, { "inherits": { @@ -129364,7 +128779,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L984-L1011" + "specLocation": "inference/_types/CommonTypes.ts#L983-L1010" }, { "kind": "interface", @@ -129451,7 +128866,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1021-L1063" + "specLocation": "inference/_types/CommonTypes.ts#L1020-L1062" }, { "kind": "interface", @@ -129473,7 +128888,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1065-L1071" + "specLocation": "inference/_types/CommonTypes.ts#L1064-L1070" }, { "kind": "interface", @@ -129537,7 +128952,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1083-L1114" + "specLocation": "inference/_types/CommonTypes.ts#L1082-L1113" }, { "kind": "interface", @@ -129597,7 +129012,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1116-L1140" + "specLocation": "inference/_types/CommonTypes.ts#L1115-L1139" }, { "kind": "interface", @@ -129685,7 +129100,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1151-L1188" + "specLocation": "inference/_types/CommonTypes.ts#L1150-L1187" }, { "description": "Defines the response for a rerank request.", diff --git a/output/schema/schema.json b/output/schema/schema.json index ba73433b4a..f646ee6dc0 100644 --- a/output/schema/schema.json +++ b/output/schema/schema.json @@ -10069,7 +10069,7 @@ "visibility": "public" } }, - "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`", + "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`", "docId": "inference-api-put-huggingface", "docUrl": "https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-put-hugging-face", "name": "inference.put_hugging_face", @@ -156309,7 +156309,41 @@ "name": "HuggingFaceServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L917-L919" + "specLocation": "inference/_types/CommonTypes.ts#L930-L932" + }, + { + "kind": "interface", + "name": { + "name": "HuggingFaceTaskSettings", + "namespace": "inference._types" + }, + "properties": [ + { + "description": "For a `rerank` task, return doc text within the results.", + "name": "return_documents", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "For a `rerank` task, the number of most relevant documents to return.\nIt defaults to the number of the documents.", + "name": "top_n", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + } + ], + "specLocation": "inference/_types/CommonTypes.ts#L911-L921" }, { "kind": "enum", @@ -156320,6 +156354,9 @@ { "name": "completion" }, + { + "name": "rerank" + }, { "name": "text_embedding" } @@ -156328,7 +156365,7 @@ "name": "HuggingFaceTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L911-L915" + "specLocation": "inference/_types/CommonTypes.ts#L923-L928" }, { "kind": "interface", @@ -157291,7 +157328,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L921-L950" + "specLocation": "inference/_types/CommonTypes.ts#L934-L963" }, { "kind": "enum", @@ -157304,7 +157341,7 @@ "name": "JinaAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L980-L982" + "specLocation": "inference/_types/CommonTypes.ts#L993-L995" }, { "kind": "enum", @@ -157323,7 +157360,7 @@ "name": "JinaAISimilarityType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L984-L988" + "specLocation": "inference/_types/CommonTypes.ts#L997-L1001" }, { "kind": "interface", @@ -157369,7 +157406,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L952-L973" + "specLocation": "inference/_types/CommonTypes.ts#L965-L986" }, { "kind": "enum", @@ -157385,7 +157422,7 @@ "name": "JinaAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L975-L978" + "specLocation": "inference/_types/CommonTypes.ts#L988-L991" }, { "kind": "enum", @@ -157407,7 +157444,7 @@ "name": "JinaAITextEmbeddingTask", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L990-L995" + "specLocation": "inference/_types/CommonTypes.ts#L1003-L1008" }, { "kind": "interface", @@ -157565,7 +157602,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L997-L1024" + "specLocation": "inference/_types/CommonTypes.ts#L1010-L1037" }, { "kind": "enum", @@ -157578,7 +157615,7 @@ "name": "MistralServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1032-L1034" + "specLocation": "inference/_types/CommonTypes.ts#L1045-L1047" }, { "kind": "enum", @@ -157597,7 +157634,7 @@ "name": "MistralTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1026-L1030" + "specLocation": "inference/_types/CommonTypes.ts#L1039-L1043" }, { "kind": "interface", @@ -157684,7 +157721,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1036-L1078" + "specLocation": "inference/_types/CommonTypes.ts#L1049-L1091" }, { "kind": "enum", @@ -157697,7 +157734,7 @@ "name": "OpenAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1094-L1096" + "specLocation": "inference/_types/CommonTypes.ts#L1107-L1109" }, { "kind": "interface", @@ -157719,7 +157756,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1080-L1086" + "specLocation": "inference/_types/CommonTypes.ts#L1093-L1099" }, { "kind": "enum", @@ -157738,7 +157775,7 @@ "name": "OpenAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1088-L1092" + "specLocation": "inference/_types/CommonTypes.ts#L1101-L1105" }, { "kind": "interface", @@ -158578,7 +158615,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1098-L1129" + "specLocation": "inference/_types/CommonTypes.ts#L1111-L1142" }, { "kind": "enum", @@ -158591,7 +158628,7 @@ "name": "VoyageAIServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1162-L1164" + "specLocation": "inference/_types/CommonTypes.ts#L1175-L1177" }, { "kind": "interface", @@ -158651,7 +158688,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1131-L1155" + "specLocation": "inference/_types/CommonTypes.ts#L1144-L1168" }, { "kind": "enum", @@ -158667,7 +158704,7 @@ "name": "VoyageAITaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1157-L1160" + "specLocation": "inference/_types/CommonTypes.ts#L1170-L1173" }, { "kind": "interface", @@ -158755,7 +158792,7 @@ } } ], - "specLocation": "inference/_types/CommonTypes.ts#L1166-L1203" + "specLocation": "inference/_types/CommonTypes.ts#L1179-L1216" }, { "kind": "enum", @@ -158768,7 +158805,7 @@ "name": "WatsonxServiceType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1209-L1211" + "specLocation": "inference/_types/CommonTypes.ts#L1222-L1224" }, { "kind": "enum", @@ -158781,7 +158818,7 @@ "name": "WatsonxTaskType", "namespace": "inference._types" }, - "specLocation": "inference/_types/CommonTypes.ts#L1205-L1207" + "specLocation": "inference/_types/CommonTypes.ts#L1218-L1220" }, { "kind": "request", @@ -160781,16 +160818,33 @@ "namespace": "inference._types" } } + }, + { + "description": "Settings to configure the inference task.\nThese settings are specific to the task type you specified.", + "name": "task_settings", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "HuggingFaceTaskSettings", + "namespace": "inference._types" + } + } } ] }, - "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`", + "description": "Create a Hugging Face inference endpoint.\n\nCreate an inference endpoint to perform an inference task with the `hugging_face` service.\nSupported tasks include: `text_embedding`, `completion`, and `chat_completion`.\n\nTo configure the endpoint, first visit the Hugging Face Inference Endpoints page and create a new endpoint.\nSelect a model that supports the task you intend to use.\n\nFor Elastic's `text_embedding` task:\nThe selected model must support the `Sentence Embeddings` task. On the new endpoint creation page, select the `Sentence Embeddings` task under the `Advanced Configuration` section.\nAfter the endpoint has initialized, copy the generated endpoint URL.\nRecommended models for `text_embedding` task:\n\n* `all-MiniLM-L6-v2`\n* `all-MiniLM-L12-v2`\n* `all-mpnet-base-v2`\n* `e5-base-v2`\n* `e5-small-v2`\n* `multilingual-e5-base`\n* `multilingual-e5-small`\n\nFor Elastic's `chat_completion` and `completion` tasks:\nThe selected model must support the `Text Generation` task and expose OpenAI API. HuggingFace supports both serverless and dedicated endpoints for `Text Generation`. When creating dedicated endpoint select the `Text Generation` task.\nAfter the endpoint is initialized (for dedicated) or ready (for serverless), ensure it supports the OpenAI API and includes `/v1/chat/completions` part in URL. Then, copy the full endpoint URL for use.\nRecommended models for `chat_completion` and `completion` tasks:\n\n* `Mistral-7B-Instruct-v0.2`\n* `QwQ-32B`\n* `Phi-3-mini-128k-instruct`\n\nFor Elastic's `rerank` task:\nThe selected model must support the `sentence-ranking` task and expose OpenAI API.\nHuggingFace supports only dedicated (not serverless) endpoints for `Rerank` so far.\nAfter the endpoint is initialized, copy the full endpoint URL for use.\nTested models for `rerank` task:\n\n* `bge-reranker-base`\n* `jina-reranker-v1-turbo-en-GGUF`", "examples": { "PutHuggingFaceRequestExample1": { "description": "Run `PUT _inference/text_embedding/hugging-face-embeddings` to create an inference endpoint that performs a `text_embedding` task type.", "method_request": "PUT _inference/text_embedding/hugging-face-embeddings", "summary": "A text embedding task", "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n }\n}" + }, + "PutHuggingFaceRequestExample2": { + "description": "Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type.", + "summary": "A rerank task", + "value": "{\n \"service\": \"hugging_face\",\n \"service_settings\": {\n \"api_key\": \"hugging-face-access-token\", \n \"url\": \"url-endpoint\" \n },\n \"task_settings\": {\n \"return_documents\": true,\n \"top_n\": 3\n }\n}" } }, "inherits": { @@ -160830,7 +160884,7 @@ } ], "query": [], - "specLocation": "inference/put_hugging_face/PutHuggingFaceRequest.ts#L29-L97" + "specLocation": "inference/put_hugging_face/PutHuggingFaceRequest.ts#L30-L113" }, { "kind": "response", @@ -161532,6 +161586,16 @@ "method_request": "POST _inference/rerank/cohere_rerank", "summary": "Rerank task", "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\"\n}" + }, + "RerankRequestExample2": { + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "summary": "Rerank task", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": false,\n \"top_n\": 2\n}" + }, + "RerankRequestExample3": { + "description": "Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face", + "summary": "Rerank task", + "value": "{\n \"input\": [\"luke\", \"like\", \"leia\", \"chewy\",\"r2d2\", \"star\", \"wars\"],\n \"query\": \"star wars main character\",\n \"return_documents\": true,\n \"top_n\": 3\n}" } }, "inherits": { @@ -161594,6 +161658,16 @@ "method_request": "POST _inference/rerank/cohere_rerank", "summary": "Rerank task", "value": "{\n \"rerank\": [\n {\n \"index\": \"2\",\n \"relevance_score\": \"0.011597361\",\n \"text\": \"leia\"\n },\n {\n \"index\": \"0\",\n \"relevance_score\": \"0.006338922\",\n \"text\": \"luke\"\n },\n {\n \"index\": \"5\",\n \"relevance_score\": \"0.0016166499\",\n \"text\": \"star\"\n },\n {\n \"index\": \"4\",\n \"relevance_score\": \"0.0011695103\",\n \"text\": \"r2d2\"\n },\n {\n \"index\": \"1\",\n \"relevance_score\": \"5.614787E-4\",\n \"text\": \"like\"\n },\n {\n \"index\": \"6\",\n \"relevance_score\": \"3.7850367E-4\",\n \"text\": \"wars\"\n },\n {\n \"index\": \"3\",\n \"relevance_score\": \"1.2508839E-5\",\n \"text\": \"chewy\"\n }\n ]\n}" + }, + "RerankResponseExample2": { + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "summary": "Rerank task", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794\n }\n ]\n}" + }, + "RerankResponseExample3": { + "description": "A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.\n", + "summary": "Rerank task", + "value": "{\n \"rerank\": [\n {\n \"index\": 6,\n \"relevance_score\": 0.50955844,\n \"text\": \"wars\"\n },\n {\n \"index\": 5,\n \"relevance_score\": 0.084341794,\n \"text\": \"star\"\n },\n {\n \"index\": 3,\n \"relevance_score\": 0.004520818,\n \"text\": \"chewy\"\n }\n ]\n}" } }, "name": { diff --git a/output/typescript/types.ts b/output/typescript/types.ts index b84d027513..b51a6e1d2a 100644 --- a/output/typescript/types.ts +++ b/output/typescript/types.ts @@ -13671,7 +13671,12 @@ export interface InferenceHuggingFaceServiceSettings { export type InferenceHuggingFaceServiceType = 'hugging_face' -export type InferenceHuggingFaceTaskType = 'chat_completion' | 'completion' | 'text_embedding' +export interface InferenceHuggingFaceTaskSettings { + return_documents?: boolean + top_n?: integer +} + +export type InferenceHuggingFaceTaskType = 'chat_completion' | 'completion' | 'rerank' | 'text_embedding' export interface InferenceInferenceChunkingSettings { max_chunk_size?: integer @@ -14161,6 +14166,7 @@ export interface InferencePutHuggingFaceRequest extends RequestBase { chunking_settings?: InferenceInferenceChunkingSettings service: InferenceHuggingFaceServiceType service_settings: InferenceHuggingFaceServiceSettings + task_settings?: InferenceHuggingFaceTaskSettings } } diff --git a/package-lock.json b/package-lock.json index 29b3d8da90..e357c81019 100644 --- a/package-lock.json +++ b/package-lock.json @@ -10,9 +10,9 @@ } }, "node_modules/@asyncapi/specs": { - "version": "6.8.1", - "resolved": "https://registry.npmjs.org/@asyncapi/specs/-/specs-6.8.1.tgz", - "integrity": "sha512-czHoAk3PeXTLR+X8IUaD+IpT+g+zUvkcgMDJVothBsan+oHN3jfcFcFUNdOPAAFoUCQN1hXF1dWuphWy05THlA==", + "version": "4.3.1", + "resolved": "https://registry.npmjs.org/@asyncapi/specs/-/specs-4.3.1.tgz", + "integrity": "sha512-EfexhJu/lwF8OdQDm28NKLJHFkx0Gb6O+rcezhZYLPIoNYKXJMh2J1vFGpwmfAcTTh+ffK44Oc2Hs1Q4sLBp+A==", "license": "Apache-2.0", "dependencies": { "@types/json-schema": "^7.0.11" @@ -22,7 +22,6 @@ "version": "7.27.1", "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz", "integrity": "sha512-cjQ7ZlQ0Mv3b47hABuTevyTuYN4i+loJKGeV9flcCgIK37cCXRh+L1bd3iBHlynerhQ7BhCkn2BPbQUL+rGqFg==", - "license": "MIT", "dependencies": { "@babel/helper-validator-identifier": "^7.27.1", "js-tokens": "^4.0.0", @@ -36,16 +35,14 @@ "version": "7.27.1", "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.27.1.tgz", "integrity": "sha512-D2hP9eA+Sqx1kBZgzxZh0y1trbuU+JoDkiEwqhQ36nodYqJwyEIhPSdMNd7lOm/4io72luTPWH20Yda0xOuUow==", - "license": "MIT", "engines": { "node": ">=6.9.0" } }, "node_modules/@babel/runtime": { - "version": "7.27.6", - "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.27.6.tgz", - "integrity": "sha512-vbavdySgbTTrmFE+EsiqUTzlOr5bzlnJtUv9PynGCAKvfQqjIXbvFdumPM/GxMDfyuGMJaJAU6TO4zc1Jf1i8Q==", - "license": "MIT", + "version": "7.27.3", + "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.27.3.tgz", + "integrity": "sha512-7EYtGezsdiDMyY80+65EzwiGmcJqpmcZCojSXaRgdrBaGtWTgDZKq69cPIVped6MkIM78cTQ2GOiEYjwOlG4xw==", "engines": { "node": ">=6.9.0" } @@ -54,7 +51,6 @@ "version": "1.2.2", "resolved": "https://registry.npmjs.org/@emotion/is-prop-valid/-/is-prop-valid-1.2.2.tgz", "integrity": "sha512-uNsoYd37AFmaCdXlg6EYD1KaPOaRWRByMCYzbKUX4+hhMfrxdVSelShywL4JVaAeM/eHUOSprYBQls+/neX3pw==", - "license": "MIT", "dependencies": { "@emotion/memoize": "^0.8.1" } @@ -62,26 +58,22 @@ "node_modules/@emotion/memoize": { "version": "0.8.1", "resolved": "https://registry.npmjs.org/@emotion/memoize/-/memoize-0.8.1.tgz", - "integrity": "sha512-W2P2c/VRW1/1tLox0mVUalvnWXxavmv/Oum2aPsRcoDJuob75FC3Y8FbpfLwUegRcxINtGUMPq0tFCvYNTBXNA==", - "license": "MIT" + "integrity": "sha512-W2P2c/VRW1/1tLox0mVUalvnWXxavmv/Oum2aPsRcoDJuob75FC3Y8FbpfLwUegRcxINtGUMPq0tFCvYNTBXNA==" }, "node_modules/@emotion/unitless": { "version": "0.8.1", "resolved": "https://registry.npmjs.org/@emotion/unitless/-/unitless-0.8.1.tgz", - "integrity": "sha512-KOEGMu6dmJZtpadb476IsZBclKvILjopjUii3V+7MnXIQCYh8W3NgNcgwo21n9LXZX6EDIKvqfjYxXebDwxKmQ==", - "license": "MIT" + "integrity": "sha512-KOEGMu6dmJZtpadb476IsZBclKvILjopjUii3V+7MnXIQCYh8W3NgNcgwo21n9LXZX6EDIKvqfjYxXebDwxKmQ==" }, "node_modules/@exodus/schemasafe": { "version": "1.3.0", "resolved": "https://registry.npmjs.org/@exodus/schemasafe/-/schemasafe-1.3.0.tgz", - "integrity": "sha512-5Aap/GaRupgNx/feGBwLLTVv8OQFfv3pq2lPRzPg9R+IOBnDgghTGW7l7EuVXOvg5cc/xSAlRW8rBrjIC3Nvqw==", - "license": "MIT" + "integrity": "sha512-5Aap/GaRupgNx/feGBwLLTVv8OQFfv3pq2lPRzPg9R+IOBnDgghTGW7l7EuVXOvg5cc/xSAlRW8rBrjIC3Nvqw==" }, "node_modules/@faker-js/faker": { "version": "7.6.0", "resolved": "https://registry.npmjs.org/@faker-js/faker/-/faker-7.6.0.tgz", "integrity": "sha512-XK6BTq1NDMo9Xqw/YkYyGjSsg44fbNwYRx7QK2CuoQgyy+f1rrTDHoExVM5PsyXCtfl2vs2vVJ0MN0yN6LppRw==", - 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"license": "MIT", "dependencies": { "@nodelib/fs.scandir": "2.1.5", "fastq": "^1.6.0" @@ -476,7 +460,6 @@ "version": "8.11.2", "resolved": "https://registry.npmjs.org/@redocly/ajv/-/ajv-8.11.2.tgz", "integrity": "sha512-io1JpnwtIcvojV7QKDUSIuMN/ikdOUd1ReEnUnMKGfDVridQZ31J0MmIuqwuRjWDZfmvr+Q0MqCcfHM2gTivOg==", - "license": "MIT", "dependencies": { "fast-deep-equal": "^3.1.1", "json-schema-traverse": "^1.0.0", @@ -530,17 +513,42 @@ "npm": ">=9.5.0" } }, + "node_modules/@redocly/cli/node_modules/yargs": { + "version": "17.0.1", + "resolved": "https://registry.npmjs.org/yargs/-/yargs-17.0.1.tgz", + "integrity": "sha512-xBBulfCc8Y6gLFcrPvtqKz9hz8SO0l1Ni8GgDekvBX2ro0HRQImDGnikfc33cgzcYUSncapnNcZDjVFIH3f6KQ==", + "license": "MIT", + "dependencies": { + "cliui": "^7.0.2", + "escalade": "^3.1.1", + "get-caller-file": "^2.0.5", + "require-directory": "^2.1.1", + "string-width": "^4.2.0", + "y18n": "^5.0.5", + "yargs-parser": "^20.2.2" + }, + "engines": { + "node": ">=12" + } + }, + "node_modules/@redocly/cli/node_modules/yargs-parser": { + "version": "20.2.9", + "resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-20.2.9.tgz", + "integrity": "sha512-y11nGElTIV+CT3Zv9t7VKl+Q3hTQoT9a1Qzezhhl6Rp21gJ/IVTW7Z3y9EWXhuUBC2Shnf+DX0antecpAwSP8w==", + "license": "ISC", + "engines": { + "node": ">=10" + } + }, "node_modules/@redocly/config": { "version": "0.22.2", "resolved": "https://registry.npmjs.org/@redocly/config/-/config-0.22.2.tgz", - 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These settings are specific to the `hugging_face` service. */ service_settings: HuggingFaceServiceSettings + /** + * Settings to configure the inference task. + * These settings are specific to the task type you specified. + */ + task_settings?: HuggingFaceTaskSettings } } diff --git a/specification/inference/put_hugging_face/examples/request/PutHuggingFaceRequestExample2.yaml b/specification/inference/put_hugging_face/examples/request/PutHuggingFaceRequestExample2.yaml new file mode 100644 index 0000000000..b525dbeabe --- /dev/null +++ b/specification/inference/put_hugging_face/examples/request/PutHuggingFaceRequestExample2.yaml @@ -0,0 +1,16 @@ +summary: A rerank task +description: Run `PUT _inference/rerank/hugging-face-rerank` to create an inference endpoint that performs a `rerank` task type. +# method_request: "PUT _inference/rerank/hugging-face-rerank" +# type: "request" +value: |- + { + "service": "hugging_face", + "service_settings": { + "api_key": "hugging-face-access-token", + "url": "url-endpoint" + }, + "task_settings": { + "return_documents": true, + "top_n": 3 + } + } diff --git a/specification/inference/rerank/examples/request/RerankRequestExample2.yaml b/specification/inference/rerank/examples/request/RerankRequestExample2.yaml new file mode 100644 index 0000000000..4489ae9045 --- /dev/null +++ b/specification/inference/rerank/examples/request/RerankRequestExample2.yaml @@ -0,0 +1,11 @@ +summary: Rerank task +description: Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face +# method_request: "POST _inference/rerank/bge-reranker-base-mkn" +# type: "request" +value: |- + { + "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"], + "query": "star wars main character", + "return_documents": false, + "top_n": 2 + } diff --git a/specification/inference/rerank/examples/request/RerankRequestExample3.yaml b/specification/inference/rerank/examples/request/RerankRequestExample3.yaml new file mode 100644 index 0000000000..f7cca4324d --- /dev/null +++ b/specification/inference/rerank/examples/request/RerankRequestExample3.yaml @@ -0,0 +1,11 @@ +summary: Rerank task +description: Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face +# method_request: "POST _inference/rerank/bge-reranker-base-mkn" +# type: "request" +value: |- + { + "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"], + "query": "star wars main character", + "return_documents": true, + "top_n": 3 + } diff --git a/specification/inference/rerank/examples/response/RerankResponseExample2.yaml b/specification/inference/rerank/examples/response/RerankResponseExample2.yaml new file mode 100644 index 0000000000..98af71f40a --- /dev/null +++ b/specification/inference/rerank/examples/response/RerankResponseExample2.yaml @@ -0,0 +1,18 @@ +summary: Rerank task +description: > + A successful response from `POST _inference/rerank/bge-reranker-base-mkn`. +# type: "response" +# response_code: +value: |- + { + "rerank": [ + { + "index": 6, + "relevance_score": 0.50955844 + }, + { + "index": 5, + "relevance_score": 0.084341794 + } + ] + } diff --git a/specification/inference/rerank/examples/response/RerankResponseExample3.yaml b/specification/inference/rerank/examples/response/RerankResponseExample3.yaml new file mode 100644 index 0000000000..a8790df956 --- /dev/null +++ b/specification/inference/rerank/examples/response/RerankResponseExample3.yaml @@ -0,0 +1,25 @@ +summary: Rerank task +description: > + A successful response from `POST _inference/rerank/bge-reranker-base-mkn`. +# type: "response" +# response_code: +value: |- + { + "rerank": [ + { + "index": 6, + "relevance_score": 0.50955844, + "text": "wars" + }, + { + "index": 5, + "relevance_score": 0.084341794, + "text": "star" + }, + { + "index": 3, + "relevance_score": 0.004520818, + "text": "chewy" + } + ] + }