# Memory Lantern: a private remembrance writer with local open AI

> Source: <https://dev.to/eliahwafula/memory-lantern-a-private-remembrance-writer-with-local-open-ai-1je5>
> Published: 2026-10-31 15:47:06+00:00

*This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine](https://dev.to/challenges/hacktoberfest-week4-2026-10-26)*

Memory Lantern is a local-first remembrance writer for Día de los Muertos. Add a name, a memory, and a few things they loved; a model on your own computer helps shape those notes into a gentle letter, short poem, or words to read aloud. The keepsake stays editable and printable.

I wanted a tool for keeping someone's stories close without pretending software can speak for the person who died. The model is instructed to use only details the writer supplied, and the result is presented as a draft to review.

**Hosted UI preview:** [https://wafulaeliah373-jpg.github.io/memory-lantern/](https://wafulaeliah373-jpg.github.io/memory-lantern/) — this is a static fictional sample, clearly labeled in the app; the hosted preview does not run a model.

To try local generation: install Ollama, run `ollama pull gemma3:4b`, start Ollama, then run `python server.py` from the project folder and open `http://127.0.0.1:8000`. Notes are sent only to Ollama on the same computer.

The interface is plain HTML, CSS, and JavaScript. A small Python standard-library server serves the page and forwards prompts to Ollama's local chat endpoint. The app is designed around Gemma 3 (`gemma3:4b`), an open-weight model that can run on the user's machine. Drafts are stored in browser local storage; there is no cloud account or analytics.

These notes can be deeply personal. Running an open-weight model locally means family stories do not need to be sent to a hosted AI provider. After downloading the model, the writing flow can work without internet, and the writer can swap models. Here, control over where memories go matters more than the convenience of a closed API.

The project takes “Ghost in the Machine” as a prompt to remember, not simulate a dead person. The person supplies the memories; the model helps arrange them. The writer can edit the result until it sounds like their own.