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In the context of Profound AI's Knowledge Documents, semantic search enables the AI agents to sift through extensive documentation and find the most relevant sections that answer or relate to the user's query. The approach is used is typically referred to as RAG, or Retrieval-Augmented Generation. This approach ensures more accurate, context-aware responses and a better understanding of user needs, compared to traditional keyword-based search methods.
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A model can optionally be configured to use specific RAG, or Retrieval-Augmented Generation, options (see . See Model Configuration) for additional details. When no RAG configuration is provided, defaults default settings are used.
A RAG configuration consists of the following:
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