diff --git a/solutions/observability/observability-ai-assistant.md b/solutions/observability/observability-ai-assistant.md index 48ecea825e..b04eac607e 100644 --- a/solutions/observability/observability-ai-assistant.md +++ b/solutions/observability/observability-ai-assistant.md @@ -18,17 +18,17 @@ You can [interact with the AI Assistant](#obs-ai-interact) in two ways: * **Contextual insights**: Embedded assistance throughout Elastic UIs that explains errors and messages with suggested remediation steps. * **Chat interface**: A conversational experience where you can ask questions and receive answers about your data. The assistant uses function calling to request, analyze, and visualize information based on your needs. -The AI Assistant integrates with your large language model (LLM) provider through our supported {{stack}} connectors: +The AI Assistant integrates with your large language model (LLM) provider through our [supported {{stack}} connectors](kibana://reference/connectors-kibana/gen-ai-connectors.md). Refer to the [{{obs-ai-assistant}} LLM performance matrix](./llm-performance-matrix.md) for supported third-party LLM providers and their performance ratings. ## Use cases The {{obs-ai-assistant}} helps you: -* **Decode error messages**: Interpret stack traces and error logs to pinpoint root causes -* **Identify performance bottlenecks**: Find resource-intensive operations and slow queries in Elasticsearch -* **Generate reports**: Create alert summaries and incident timelines with key metrics -* **Build and execute queries**: Build Elasticsearch queries from natural language, convert Query DSL to ES|QL syntax, and execute queries directly from the chat interface -* **Visualize data**: Create time-series charts and distribution graphs from your Elasticsearch data +* **Decode error messages**: Interpret stack traces and error logs to pinpoint root causes. +* **Identify performance bottlenecks**: Find resource-intensive operations and slow queries in {{es}}. +* **Generate reports**: Create alert summaries and incident timelines with key metrics. +* **Build and execute queries**: Build {{es}} queries from natural language, convert Query DSL to {{esql}} syntax, and execute queries directly from the chat interface. +* **Visualize data**: Create time-series charts and distribution graphs from your {{es}} data. ## Requirements [obs-ai-requirements] @@ -36,7 +36,7 @@ The AI assistant requires the following: - An **Elastic deployment**: - - For **Observability**: {{stack}} version **8.9** or later, or an **{{observability}} serverless project**. + - For **{{observability}}**: {{stack}} version **8.9** or later, or an **{{observability}} serverless project**. - For **Search**: {{stack}} version **8.16.0** or later, or **{{serverless-short}} {{es}} project**. @@ -46,12 +46,12 @@ The AI assistant requires the following: - The free tier offered by third-party generative AI provider may not be sufficient for the proper functioning of the AI assistant. In most cases, a paid subscription to one of the supported providers is required. - Refer to the [documentation](/deploy-manage/manage-connectors.md) for your provider to learn about supported and default models. + Refer to the [documentation](kibana://reference/connectors-kibana/gen-ai-connectors.md) for your provider to learn about supported and default models. * The knowledge base requires a 4 GB {{ml}} node. - In {{ecloud}} or {{ece}}, if you have Machine Learning autoscaling enabled, Machine Learning nodes will be started when using the knowledge base and AI Assistant. Therefore using these features will incur additional costs. -* A self-deployed connector service if [content connectors](elasticsearch://reference/search-connectors/index.md) are used to populate external data into the knowledge base. +* A self-deployed connector service if you're using [content connectors](elasticsearch://reference/search-connectors/index.md) to populate external data into the knowledge base. ## Manage access to AI Assistant @@ -62,9 +62,9 @@ serverless: ga The [**GenAI settings**](/explore-analyze/manage-access-to-ai-assistant.md) page allows you to: -- Manage which AI connectors are available in your environment. +- Manage which AI connectors are available in your environment. - Enable or disable AI Assistant and other AI-powered features in your environment. -- {applies_to}`stack: ga 9.2` {applies_to}`serverless: unavailable` Specify in which Elastic solutions the `AI Assistant for Observability and Search` and the `AI Assistant for Security` appear. +- {applies_to}`stack: ga 9.2` {applies_to}`serverless: unavailable` Specify in which Elastic solutions the `AI Assistant for {{observability}} and Search` and the `AI Assistant for Security` appear. ## Your data and the AI Assistant [data-information] @@ -98,11 +98,11 @@ The AI Assistant connects to one of these supported LLM providers: **Setup steps**: -1. **Create authentication credentials** with your chosen provider using the links above. +1. **Create authentication credentials** with your chosen provider using the links in the previous table. 2. **Create an LLM connector** for your chosen provider by going to the **Connectors** management page in the navigation menu or by using the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md). 3. **Authenticate the connection** by entering: - - The provider's API endpoint URL - - Your authentication key or secret + - The provider's API endpoint URL. + - Your authentication key or secret. ::::{admonition} Recommended models While the {{obs-ai-assistant}} is compatible with many different models, refer to the [Large language model performance matrix](/solutions/observability/llm-performance-matrix.md) to select models that perform well with your desired use cases.