For natural language to SQL generation, Select AI processes the natural language prompt, supplements the prompt with metadata, and then accesses the LLM to generate a query, and if requested, run that query.

• About Select AI
  Use natural language to interact with your database and LLMs through SQL to enhance user productivity and develop AI-based applications. Select AI simplifies and automates using generative AI, whether generating, running, and explaining SQL from a natural language prompt, using retrieval augmented generation with vector stores, or chatting with the LLM.
• Select AI Concepts
  Describes the concepts and terms related to Select AI.
• Select AI Use Cases
  Select AI enhances data interaction and enables developers to build AI-driven applications directly from SQL, transforming natural language prompts to SQL queries and text responses, supports chat interaction with LLMs, enhances response accuracy with current data using RAG, and generating synthetic data.
• Getting Started with Select AI
  To get started, review the prerequisites and the tasks that you need to perform to use Select AI.
• Manage AI Profiles
  You can create and manage your AI profiles through DBMS_CLOUD_AI package.
• Use AI Keyword to Enter Prompts
  Use AI as the keyword in a SELECT statement for interacting with the database using natural language prompts.
• Select AI with Retrieval Augmented Generation (RAG)
  Select AI with RAG augments your natural language prompt by retrieving content from your specified vector store using semantic similarity search. This reduces hallucinations by using your specific and up-to-date content and provides more relevant natural language responses to your prompts.
• Synthetic Data Generation
  Generate synthetic data using random generators, algorithms, statistical models, and Large Language Models (LLMs) to simulate real data for developing and testing solutions effectively.
• Examples of Using Select AI
  Explore integrating Oracle's Select AI with various supported AI providers to generate, run, and explain SQL from natural language prompts or chat with the LLM.