AI-Powered SQL Assistant
Enables natural language querying of Oracle Autonomous Databases by generating SQL and performing vector searches.
About
The AI-Powered SQL Assistant is a proof-of-concept system designed to bridge the gap between natural language and database queries, specifically for Oracle Autonomous Database (23ai). It allows users to ask questions in plain English, which are then intelligently translated into SQL or semantic vector searches. The system leverages a locally running Large Language Model (LLaMA 3.2 via Ollama) for query interpretation and SQL generation, a FastAPI-based backend (MCP Server) for execution on Oracle ADBS, and native Oracle Vector Search capabilities, eliminating the need for external vector databases. Its modular architecture ensures flexible query routing and an optional LLM-driven interpretation of results for more human-readable answers.
Key Features
- Optional LLM-based interpretation of SQL results for natural language answers.
- Native Oracle ADBS vector embedding and querying, no external vector database required.
- Fully local LLM for intelligent SQL generation via Ollama.
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- Modular architecture facilitating easy expansion and integration.
- Smart switching between structured SQL and semantic vector search.
Use Cases
- Natural language querying of Oracle 23ai databases.
- Performing semantic searches on unstructured data stored within Oracle Autonomous Database.
- Generating SQL statements from plain English descriptions.
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