Ollama on ayyzenn

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:

Local RAG with Ollama and ChromaDB: Running AI Offline

Sun, 29 Jun 2025 00:00:00 +0000

Why I Built This

I wanted a chatbot that answers questions from my own documents — without sending data to a cloud API. This RAG setup runs fully offline with Ollama and ChromaDB on my machine.

Privacy — your data stays on your machine
No API costs — no usage fees or rate limits
Speed — no network delay for each query
Control — you choose what goes into the knowledge base
Offline use — works without internet after setup

Architecture Overview

My local RAG system consists of four main components:

Ollama + DeepSeek: How I Run LLMs Locally

Mon, 03 Feb 2025 00:00:00 +0000

Why I Use Ollama

I wanted to run LLMs on my own hardware without paying for API calls or sending data to the cloud. Ollama made that straightforward — install, pull a model, start chatting.

Install Ollama

Arch Linux

Update your system, then install Ollama:

sudo pacman -Syu
sudo pacman -S ollama

Enable and start the service:

sudo systemctl enable ollama
sudo systemctl start ollama
sudo systemctl status ollama

You should see active (running).