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Spendify — Deployment Guide

This document describes how to install, configure and update Spendify. For backup, restore and database management → database.en.md. For installation on native Mac, Linux with Ollama and Windows with llama.cpp → installazione.en.md.

Table of contents

  1. Quick installation (one-liner Docker)
  2. Docker Compose installation from repository
  3. Native installation (development / Mac)
  4. Updating the application
  5. Docker operational commands
  6. Troubleshooting
  7. Uninstall

Docker concepts for beginners

Concept Analogy What it means in practice
Image Cooking recipe The package containing all the code and dependencies
Container Cooked dish The running app, created from the image
Volume External notebook The persistent folder where the database lives — survives even if the container is deleted

What does NOT delete your data:

  • docker compose down ✅ safe
  • docker compose up -d --build ✅ safe (rebuilds the image, data intact)

What DELETES data:

  • docker compose down -v ⚠️ deletes the volumes — use only for a full reset

1 — Quick installation (one-liner Docker)

The only prerequisite is Docker Desktop installed and running.

Mac / Linux:

curl -fsSL https://raw.githubusercontent.com/drake69/spendify/main/installer/install.sh | bash

Windows (PowerShell):

irm https://raw.githubusercontent.com/drake69/spendify/main/installer/install.ps1 | iex

The script creates the ~/spendify/ folder, downloads the image from GitHub Container Registry, starts the container and opens the browser at http://localhost:8501 automatically.

Local AI included (optional): the script asks whether to install Ollama with the gemma3:12b model — downloaded automatically in the background on first start (~8 GB, ~10–15 minutes). Alternatively you can configure an external API key (OpenAI/Anthropic) from the ⚙️ Settings page.

Update: docker compose --project-directory ~/spendify pull && docker compose --project-directory ~/spendify up -d

Uninstall: curl -fsSL https://raw.githubusercontent.com/drake69/spendify/main/installer/uninstall.sh | bash

2 — Docker Compose installation from repository

Suitable for those who want to modify the code or configure LLM profiles (Ollama, llama.cpp).

2.1 — Clone the repository

git clone https://github.com/drake69/spendify.git spendify
cd spendify

2.2 — Configure the environment

cp .env.example .env

2.3 — Build and start

docker compose up -d --build
  • --build forces the image to be rebuilt (required on first launch or after code updates)
  • -d starts in the background

The app is available at http://localhost:8501

The REST API is available at http://localhost:8000 · Interactive docs: http://localhost:8000/docs

2.4 — With local LLM (optional)

# Ollama (Linux / server with GPU)
docker compose --profile ollama up -d

# llama.cpp (Windows / CPU)
docker compose --profile llama-cpp up -d

For complete LLM backend configuration → installazione.en.md.

3 — Native installation (development / Mac)

Prerequisites

Tool Minimum version
Python 3.13
uv any — curl -Ls https://astral.sh/uv/install.sh | sh

Steps

git clone https://github.com/drake69/spendify.git spendify
cd spendify
uv sync
cp .env.example .env
uv run streamlit run app.py

The app is available at http://localhost:8501

To also start the REST API in development:

uv run uvicorn api.main:app --host 0.0.0.0 --port 8000

The ledger.db database is created automatically in the project folder on first launch.

4 — Updating the application

One-liner Docker

docker compose --project-directory ~/spendify pull
docker compose --project-directory ~/spendify up -d

Docker Compose from repository

git pull origin main
docker compose down
docker compose up -d --build

Native

git pull origin main
uv sync
pkill -f "streamlit run app.py"
uv run streamlit run app.py

Database migrations are applied automatically on startup — no manual intervention is required.

5 — Docker operational commands

# Container status
docker compose ps

# Real-time logs
docker compose logs -f spendify

# Healthcheck
docker inspect spendify_app --format='{{.State.Health.Status}}'

# Stop (data intact)
docker compose down

# Stop + remove orphan containers (data intact)
docker compose down --remove-orphans

# ⚠️  Full reset including volumes (DATA LOSS)
docker compose down -v

For the one-liner installation, add --project-directory ~/spendify to every command, e.g. docker compose --project-directory ~/spendify logs -f.

6 — Troubleshooting

The app does not start / port 8501 is busy

# Check what is using the port
lsof -i :8501

# Native
pkill -f "streamlit run app.py"

# Docker
docker compose down && docker compose up -d

The Docker container keeps restarting

docker compose logs --tail=50 spendify

Common causes:

  • .env missing or incorrect values
  • Volume not mounted correctly
  • Port 8501 already in use

Insufficient memory for Ollama

The gemma3:12b model requires ~8 GB of RAM. Change the model from the ⚙️ Settings page:

Model Required RAM
gemma3:12b ~8 GB
qwen2.5:7b ~5 GB
llama3.2:3b ~3 GB

Database issues

Errors such as database is locked, file corruption, restore from backup → database.en.md.

7 — Uninstall

The uninstall scripts interactively remove all Spendify components. No data is deleted without explicit confirmation.

Mac / Linux:

curl -fsSL https://raw.githubusercontent.com/drake69/spendify/main/installer/uninstall.sh | bash

Windows (PowerShell):

irm https://raw.githubusercontent.com/drake69/spendify/main/installer/uninstall.ps1 | iex

The script asks separately for each component:

What Detail
Transaction database Volumes spendify_data and spendify_logs
Ollama models Volume ollama_models (~8 GB)
llama.cpp + models/ folder llama.cpp:server image + GGUF files
Docker images ghcr.io/drake69/spendify + ollama/ollama (~500 MB–1 GB)
Installation folder ~/spendify/ (or SPENDIFY_INSTALL_DIR)
Docker Desktop removal guide Step-by-step guide for macOS / Linux / Windows

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