Use OpenSearch LLM-Based Conversational Search Edition to provide RAG capabilities for other editions of OpenSearch
For more information about the retrieval-augmented generation (RAG) capabilities of OpenSearch Vector Search Edition, see Implement RAG for OpenSearch Vector Search Edition.
For more information about the RAG capabilities of OpenSearch Retrieval Engine Edition, see Implement RAG for OpenSearch Retrieval Engine Edition.
OpenSearch LLM-Based Conversational Search Edition provides a variety of built-in models such as large language models (LLMs), vectorization models, and segmentation models. You can use these models to build an enterprise-dedicated conversational search system. Due to the limited customization features provided by OpenSearch LLM-Based Conversational Search Edition, you cannot add custom fields or use custom fields to create filtering and sorting rules when you customize a data structure, create search indexes, and retrieve data. In this case, you can use OpenSearch Retrieval Engine Edition as the retrieval engine to add custom fields.