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‎docs/changelog/119580.yaml‎

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pr: 119580
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summary: Do not serialize `EsIndex` in plan
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area: ES|QL
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type: enhancement
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issues: []

‎docs/changelog/119743.yaml‎

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pr: 119743
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summary: POC mark read-only
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area: Engine
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type: enhancement
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issues: []

‎docs/changelog/120250.yaml‎

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pr: 120250
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summary: "Retry internally when CAS upload is throttled [GCS]"
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area: Snapshot/Restore
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type: enhancement
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issues:
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- 116546

‎docs/changelog/120370.yaml‎

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pr: 120370
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summary: "Merge field mappers when updating mappings with [subobjects:false]"
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area: Mapping
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type: bug
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issues:
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- 120216

‎docs/changelog/120458.yaml‎

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pr: 120458
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summary: Do not recommend increasing `max_shards_per_node`
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area: Health
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type: bug
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issues: []

‎docs/reference/inference/inference-apis.asciidoc‎

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For the most up-to-date API details, refer to {api-es}/group/endpoint-inference[{infer-cap} APIs].
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--
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The {infer} APIs enable you to create {infer} endpoints and use {ml} models of
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different providers - such as Amazon Bedrock, Anthropic, Azure AI Studio,
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Cohere, Google AI, Mistral, OpenAI, or HuggingFace - as a service. Use
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the following APIs to manage {infer} models and perform {infer}:
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The {infer} APIs enable you to create {infer} endpoints and integrate with {ml} models of different services - such as Amazon Bedrock, Anthropic, Azure AI Studio, Cohere, Google AI, Mistral, OpenAI, or HuggingFace.
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Use the following APIs to manage {infer} models and perform {infer}:
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* <<delete-inference-api>>
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* <<get-inference-api>>
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manual deployment and apply it to your data at ingestion time through
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<<semantic-search-semantic-text, semantic text>>.
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Choose a model from your provider or use ELSER – a retrieval model trained by
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Elastic –, then create an {infer} endpoint by the <<put-inference-api>>.
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Now use <<semantic-search-semantic-text, semantic text>> to perform
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<<semantic-search, semantic search>> on your data.
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Choose a model from your service or use ELSER – a retrieval model trained by Elastic –, then create an {infer} endpoint by the <<put-inference-api>>.
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Now use <<semantic-search-semantic-text, semantic text>> to perform <<semantic-search, semantic search>> on your data.
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[discrete]
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[[adaptive-allocations]]

‎docs/reference/inference/put-inference.asciidoc‎

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include::inference-shared.asciidoc[tag=task-type]
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--
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Refer to the service list in the <<put-inference-api-desc,API description section>> for the available task types.
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Refer to the integration list in the <<put-inference-api-desc,API description section>> for the available task types.
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--
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[IMPORTANT]
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====
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* When creating an inference endpoint, the associated machine learning model is automatically deployed if it is not already running.
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* When creating an {infer} endpoint, the associated {ml} model is automatically deployed if it is not already running.
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* After creating the endpoint, wait for the model deployment to complete before using it. You can verify the deployment status by using the <<get-trained-models-stats, Get trained model statistics>> API. In the response, look for `"state": "fully_allocated"` and ensure the `"allocation_count"` matches the `"target_allocation_count"`.
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* Avoid creating multiple endpoints for the same model unless required, as each endpoint consumes significant resources.
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====
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The following services are available through the {infer} API.
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You can find the available task types next to the service name.
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Click the links to review the configuration details of the services:
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The following integrations are available through the {infer} API.
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You can find the available task types next to the integration name.
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Click the links to review the configuration details of the integrations:
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* <<infer-service-alibabacloud-ai-search,AlibabaCloud AI Search>> (`completion`, `rerank`, `sparse_embedding`, `text_embedding`)
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* <<infer-service-amazon-bedrock,Amazon Bedrock>> (`completion`, `text_embedding`)
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* <<infer-service-watsonx-ai>> (`text_embedding`)
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* <<infer-service-jinaai,JinaAI>> (`text_embedding`, `rerank`)
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The {es} and ELSER services run on a {ml} node in your {es} cluster. The rest of
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the services connect to external providers.
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The {es} and ELSER services run on a {ml} node in your {es} cluster.
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The rest of the integrations connect to external services.
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[discrete]
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[[adaptive-allocations-put-inference]]
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==== Adaptive allocations
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Adaptive allocations allow inference services to dynamically adjust the number of model allocations based on the current load.
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Adaptive allocations allow inference endpoints to dynamically adjust the number of model allocations based on the current load.
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When adaptive allocations are enabled:
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‎docs/reference/inference/service-alibabacloud-ai-search.asciidoc‎

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[[infer-service-alibabacloud-ai-search]]
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=== AlibabaCloud AI Search {infer} service
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=== AlibabaCloud AI Search {infer} integration
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.New API reference
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[sidebar]

‎docs/reference/inference/service-amazon-bedrock.asciidoc‎

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[[infer-service-amazon-bedrock]]
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=== Amazon Bedrock {infer} service
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=== Amazon Bedrock {infer} integration
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[sidebar]

‎docs/reference/inference/service-anthropic.asciidoc‎

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[[infer-service-anthropic]]
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=== Anthropic {infer} service
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=== Anthropic {infer} integration
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.New API reference
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[sidebar]

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