Skip to main content

Retrieval-Augmented Generation

Connect RAG Vector Database​

Integrating a Retrieval Augmented Generation (RAG) system improves LLM responses by grounding them in proprietary data, resulting in more accurate and contextually relevant answers.

The assistant can use an Elasticsearch vector database to perform Retrieval Augmented Generation (RAG).

  • Add the following settings to the configuration to enable RAG using Elasticsearch as a vector database:
{
    "rag_es_server": "RAG_ELASTICSEARCH_SERVER",
    "rag_vector_es_index": "RAG_VECTOR_ELASTICSEARCH_INDEX",
    "rag_embeddings_model": "RAG_EMBEDDINGS_MODEL"
}