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explore-analyze/elastic-inference/eis.md

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@@ -11,20 +11,30 @@ The Elastic {{infer-cap}} Service (EIS) enables you to leverage AI-powered searc
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With EIS, you don't need to manage the infrastructure and resources required for large language models (LLMs) by adding, configuring, and scaling {{ml}} nodes.
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Instead, you can use {{ml}} models in high-throughput, low-latency scenarios independently of your {{es}} infrastructure.
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Currently, you can perform chat completion tasks through EIS using the {{infer}} API.
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% TO DO: Link to the EIS inference endpoint reference docs when it's added to the OpenAPI spec. (Comming soon) %
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## Available task types
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EIS offers the following {{infer}} task types to perform:
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* Chat completion
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## How to use EIS [using-eis]
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Your Elastic deployment comes with default endpoints for EIS that you can use performing {{infer}} tasks.
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You can either do it by calling the {{infer}} API or using the default `Elastic LLM` model in the AI Assistant, Attack Discovery UI, and Search Playground.
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% TO DO: Link to the EIS inference endpoint reference docs when it's added to the OpenAPI spec. (Comming soon) %
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## Default EIS endpoints [default-eis-inference-endpoints]
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Your {{es}} deployment includes a preconfigured EIS endpoint, making it easier to use chat completion via the {{infer}} API:
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* `rainbow-sprinkles-elastic`: uses Anthropic's Claude Sonnet 3.5 model for chat completion {{infer}} tasks.
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* `rainbow-sprinkles-elastic`
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::::{note}
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* The model appears as `Elastic LLM` in the AI Assistant, Attack Discovery UI, preconfigured connectors list, and the Search Playground.
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* To fine-tune prompts sent to `rainbow-sprinkles-elastic`, optimize them for Claude Sonnet 3.5.
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::::
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For more details on AWS regions, refer to the [AWS Global Infrastructure](https://aws.amazon.com/about-aws/global-infrastructure/regions_az/) and the [supported cross-region {{infer}} profiles](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-support.html) documentation.
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## LLM hosts [llm-hosts]
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The LLM used with EIS is hosted by [Amazon Bedrock](https://aws.amazon.com/bedrock/).
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## Examples
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The following example demonstrates how to perform a `chat_completion` task through EIS by using the `.rainbow-sprinkles-elastic` default {{infer}} endpoint.
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],
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"temperature": 0.7,
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"max_completion_tokens": 300
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}
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}
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```
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The request returns the following response:
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```json
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(...)
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{
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"role" : "assistant",
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"content": "Yes",
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"model" : "rainbow-sprinkles",
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"object" : "chat.completion.chunk",
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"usage" : {
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"completion_tokens" : 4,
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"prompt_tokens" : 13,
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"total_tokens" : 17
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}
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}
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(...)
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```

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