LazyDigest: Zero-Effort Note Digests Powered by Local Gemma

A developer built LazyDigest, an open-source, local-first background utility that reads raw Markdown notes dropped into a folder and generates a daily digest with a category, one-line takeaway and optional action item for each note. The tool runs Google's Gemma 3 1B open-weight model locally through Ollama, avoiding external API calls, and can run as a daemon that processes notes nightly at 03:00 and archives them so they are never read twice.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady https://dev.to/challenges/hacktoberfest-week3-2026-10-19 I built LazyDigest , a small background utility that takes the raw, unorganized Markdown notes I drop into a folder and turns them into a short daily digest: a category, a one-line takeaway and an optional action item for each note. Instead of organizing folders, adding tags or re-reading messy scratchpads, LazyDigest runs quietly every night at 03:00 using our Faithful Servant, Google's Gemma 3 1B open-weight model, through Ollama. I dump files into a folder, go to sleep, and wake up to a summary. The video shows LazyDigest reading a folder of raw Markdown notes, writing a digest file offline, and moving the processed notes into the archive folder. LazyDigest is an open-source, local-first background utility that reads the scattered Markdown notes you drop into a folder and turns them into one short daily digest — a category, a one-line takeaway, and an optional action item per note — using Google's Gemma model running locally through Ollama. Built for the Hacktoberfest Open-Source AI Challenge 2026 Week 3: Slow and Steady . .md file in data/input notes/ . gemma3:1b via Ollama, without sending data to external APIs. data/output digests/digest output.md , then moves processed notes into data/processed/ so they are never read twice. --daemon and it digests your notes every night at 03:00 while you sleep. ollama-python with schedule library runs it daily at 03:00 and moves processed files into