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default OpenSearch Assistant Toolkit false false 28

OpenSearch Assistant Toolkit

Introduced 2.12 {: .label .label-purple }

This is an experimental feature and is not recommended for use in a production environment. For updates on the progress of the feature or if you want to leave feedback, see the associated OpenSearch forum thread.
{: .warning}

The OpenSearch Assistant Toolkit helps you create AI-powered assistants for OpenSearch Dashboards. The toolkit includes the following elements:

  • Agents and tools: Agents interface with a large language model (LLM) and execute high-level tasks, such as summarization or generating Piped Processing Language (PPL) queries from natural language. The agent's high-level tasks consist of low-level tasks called tools, which can be reused by multiple agents.
  • Configuration automation: Uses templates to set up infrastructure for artificial intelligence and machine learning (AI/ML) applications. For example, you can automate configuring agents to be used for chat or generating PPL queries from natural language.
  • OpenSearch Assistant for OpenSearch Dashboards: This is the OpenSearch Dashboards UI for the AI-powered assistant. The assistant's workflow is configured with various agents and tools.

Enabling OpenSearch Assistant

To enable OpenSearch Assistant, perform the following steps:

  • Enable the agent framework and retrieval-augmented generation (RAG) by configuring the following settings: 
    plugins.ml_commons.agent_framework_enabled: true
plugins.ml_commons.rag_pipeline_feature_enabled: true
    {% include copy.html %}
  • Enable the assistant by configuring the following settings: 
    assistant.chat.enabled: true
observability.query_assist.enabled: true
    {% include copy.html %}

For more information about ways to enable experimental features, see Experimental feature flags.

Next steps