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| 1 | +// This module is used in the following assemblies: |
| 2 | + |
| 3 | +// * about/ols-about-openshift-lightspeed.adoc |
| 4 | + |
| 5 | +:_mod-docs-content-type: CONCEPT |
| 6 | +[id="ols-large-language-model-overview"] |
| 7 | += Large Language Model (LLM) overview |
| 8 | +:context: ols-large-language-model-overview |
| 9 | + |
| 10 | +A large language model (LLM) is a type of machine learning model that can interpret and generate human-like language. When an LLM is used with a virtual assistant the LLM can interpret questions accurately and provide helpful answers in a conversational manner. |
| 11 | + |
| 12 | +As part of the {ols-release} release, {ols-long} can rely on the following Software as a Service (SaaS) LLM providers: |
| 13 | + |
| 14 | +* OpenAI |
| 15 | +
|
| 16 | +* {azure-openai} |
| 17 | +
|
| 18 | +* {watsonx} |
| 19 | +
|
| 20 | +[NOTE] |
| 21 | +==== |
| 22 | +Many self-hosted or self-managed model servers claim API compatibility with OpenAI. It is possible to configure the {ols-long} OpenAI provider to point to an API-compatible model server. If the model server is truly API-compatible, especially with respect to authentication, then it may work. These configurations have not been tested by Red Hat, and issues related to their use are outside the scope of {ols-release} support. |
| 23 | +==== |
| 24 | + |
| 25 | +For {ols-long} configurations with {rhoai} or {rhelai}, you must host your own LLM provider rather than use a SaaS LLM provider. |
| 26 | + |
| 27 | +[id="ibm-watsonx_{context}"] |
| 28 | +== {watsonx} |
| 29 | + |
| 30 | +To use {watsonx} with {ols-official}, you need an account with link:https://www.ibm.com/products/watsonx-ai[IBM Cloud's watsonx]. |
| 31 | + |
| 32 | +[id="open-ai_{context}"] |
| 33 | +== Open AI |
| 34 | + |
| 35 | +To use {openai} with {ols-official}, you need access to the {openai} link:https://openai.com/api/[API platform]. |
| 36 | + |
| 37 | +[id="azure-open-ai_{context}"] |
| 38 | +== {azure-openai} |
| 39 | + |
| 40 | +To use {azure-official} with {ols-official}, you need access to {azure-openai}. |
| 41 | + |
| 42 | +[id="rhelai_{context}"] |
| 43 | +== {rhelai} |
| 44 | + |
| 45 | +{rhelai} is OpenAI API-compatible, and is configured in a similar manner as the OpenAI provider. |
| 46 | + |
| 47 | +You can configure {rhelai} as the (Large Language Model) LLM provider. |
| 48 | + |
| 49 | +Because the {rhel} is in a different environment than the {ols-long} deployment, the model deployment must allow access using a secure connection. For more information, see link:https://docs.redhat.com/en/documentation/red_hat_enterprise_linux_ai/1.2/html-single/building_your_rhel_ai_environment/index#creating_secure_endpoint[Optional: Allowing access to a model from a secure endpoint]. |
| 50 | + |
| 51 | + |
| 52 | +[id="rhoai_{context}"] |
| 53 | +== {rhoai} |
| 54 | + |
| 55 | +{rhoai} is OpenAI API-compatible, and is configured largely the same as the OpenAI provider. |
| 56 | + |
| 57 | +You need a Large Language Model (LLM) deployed on the single model-serving platform of {rhoai} using the Virtual Large Language Model (vLLM) runtime. If the model deployment is in a different {ocp-short-name} environment than the {ols-long} deployment, the model deployment must include a route to expose it outside the cluster. For more information, see link:https://docs.redhat.com/en/documentation/red_hat_openshift_ai_self-managed/2-latest/html/serving_models/serving-large-models_serving-large-models#about-the-single-model-serving-platform_serving-large-models[About the single-model serving platform]. |
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