LlamaIndex + Text-to-SQL: What I Learned

Mon, 27 Oct 2025 00:00:00 +0000

What I Was Trying to Do

I had structured data in SQLite and didn’t want to write SQL for every question. LlamaIndex let me ask things like “which city has the most people?” in plain English — it figures out the query, runs it, and returns the answer.

Key capabilities include:

Translating natural language into SQL queries.
Converting unstructured context into structured insights.
Dynamically retrieving relevant schemas or tables for complex databases.

Note: Never expose full write-access databases to LLMs. Always use read-only credentials or sandboxed environments for safety.

RAG Text-to-SQL: Asking My Database Questions in Plain English

Sat, 25 Oct 2025 00:00:00 +0000

What I Built

I hate writing SQL for simple questions. This project lets me ask things like “how many customers are from Brazil?” in plain English — it generates the SQL, runs it, and gives me a readable answer. All local, using Ollama and ChromaDB.

Easy to use — ask questions in everyday language
Private — everything runs locally on your machine
Fast feedback — generates and runs SQL in seconds
Schema-aware — understands table names and relationships
Interactive — ask follow-up questions in a chat-style flow
Error handling — catches common issues like wrong table name casing

System Architecture

My RAG Text-to-SQL system consists of five core components:

Sql on ayyzenn

LlamaIndex + Text-to-SQL: What I Learned

What I Was Trying to Do

RAG Text-to-SQL: Asking My Database Questions in Plain English

What I Built

System Architecture