Use Select AI for Natural Language Interaction with your Database
Select AI enables SQL access to generative AI using Large Language
Models (LLMs) and embedding models. This includes support for natural language to SQL
query generation and retrieval augmented generation, among other features.
- 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, generating synthetic data, or chatting with the LLM. - Select AI Concepts
Explores 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, supporting chat interaction with LLMs, enhancing 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 throughDBMS_CLOUD_AI
package. - Use AI Keyword to Enter Prompts
UseAI
as the keyword in aSELECT
statement for interacting with the database using natural language prompts. - Enable Conversations to Enhance User Interaction
Conversations in Select AI refer to the interactive dialogue between the user and the system, where a sequence of user-provided natural language prompts are used to query or interact with the database. - 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.
Related Topics
Parent topic: Features