LLeMbas/README.md

<p align="center">
  <img src="assets/banner.svg" alt="LLeMbas — waybread for the long road of thought" width="100%">
</p>

<p align="center">
  <strong>A self-hosted web UI for your language models, written in Python.</strong><br>
  Talks to anything that speaks the OpenAI API. Themed after Middle-earth.
</p>

<p align="center">
  <img alt="Python 3.11+" src="https://img.shields.io/badge/python-3.11%2B-3E6B7A?style=flat-square">
  <img alt="License GPL-3.0" src="https://img.shields.io/badge/license-GPL--3.0-C9A227?style=flat-square">
  <img alt="No Node required" src="https://img.shields.io/badge/build%20step-none-6B8E4E?style=flat-square">
</p>

---

*Lembas* is the Elvish waybread — one bite sustains a traveller for a day's
march. The capitals hide what it runs on: **LLeM**bas.

## Why this exists

Most self-hosted LLM front-ends are large JavaScript applications with a Python
API bolted underneath. LLeMbas is the other way round: **server-rendered
Python**, with htmx and a little Alpine for interactivity. There is no
`package.json`, no bundler, no build step, and nothing is fetched from a CDN at
runtime. Clone it, `pip install -e .`, run it.

## Features

**Working now**

- **Chats** — streaming replies, Markdown with server-side syntax highlighting,
  copy and regenerate, automatic chat titles. Chats are created when you send
  the first message, so an abandoned one never clutters the sidebar
- **System prompts** — instance-wide, per-model and per-chat, with the most
  specific winning outright
- **Reasoning display** — thinking from reasoning models streams into its own
  collapsible block, labelled with how long it took, and is never replayed as
  context
- **Attachments** — drag, paste or pick images, PDFs and text files. Images are
  downscaled and sent to vision models; PDF and text content is extracted and
  put in the prompt
- **Folders** — arbitrarily nested, delete a folder without losing the chats
  inside it
- **OpenAI connections** — point at OpenAI, LM Studio, vLLM, llama.cpp,
  llama-swap, Ollama or OpenRouter; models are discovered and cached
- **Model settings** — searchable, filterable list with a page per model:
  ordering, pinned models, an instance default and a per-user default, custom
  names, descriptions and images. Scales to hundreds of models
- **Users, groups & permissions** — per-group grants that union rather than
  override, and model access restricted to chosen groups
- **Accounts** — first account becomes the administrator, argon2 password
  hashing, revocable server-side sessions, self-service password change,
  admin-managed accounts
- **Admin settings** — open or close registration from the UI, stored in the
  database and effective immediately
- **Two themes** — *Moria* (dark) and *Shire* (light), switchable per user

**Planned**

Built-in tools with admin settings · custom tools and MCP servers · agentic
execution (local and over SSH) · image generation · OCR for scanned PDFs.

## Quick start

```bash
git clone https://git.houmeres.sk/Houmeres/LLeMbas.git
cd LLeMbas

python -m venv .venv && . .venv/bin/activate
pip install -e ".[dev]"

cp .env.example .env
lembas secret-key           # paste the result into LEMBAS_SECRET_KEY

lembas serve                # http://127.0.0.1:8080
```

Open the address and create the first account — it becomes the administrator.
Then go to **Admin → Connections** and add an endpoint. For a local runner that
is usually `http://localhost:1234/v1` with no API key. Press **Test & refresh**
and its models appear in the chat model picker.

> The vendored browser libraries (htmx, Alpine) are committed, so no network
> access is needed to run. To re-fetch or bump them:
> `python scripts/fetch_vendor.py --update`.

## Configuration

All variables are prefixed `LEMBAS_` and can live in `.env`. See
[`.env.example`](.env.example) for the annotated list.

| Variable | Default | Purpose |
|---|---|---|
| `LEMBAS_SECRET_KEY` | *generated* | Signs sessions and encrypts stored API keys. **Set this.** A generated key changes every restart, signing everyone out and making stored API keys unreadable. |
| `LEMBAS_DATA_DIR` | `./data` | SQLite database and uploads. |
| `LEMBAS_HOST` / `LEMBAS_PORT` | `127.0.0.1` / `8080` | Bind address. |
| `LEMBAS_ALLOW_SIGNUP` | `true` | Whether new users may register themselves — the *initial* value only. Once set under **Admin → General** the stored setting wins. The first account is always an admin regardless. |
| `LEMBAS_DEFAULT_THEME` | `moria` | `moria` (dark) or `shire` (light). |
| `LEMBAS_SESSION_TTL` | `2592000` | Session lifetime in seconds. |
| `LEMBAS_REQUEST_TIMEOUT` | `300` | Seconds to wait on an upstream model. |

### Commands

```bash
lembas serve          # run the server
lembas info           # where data lives, what is configured
lembas secret-key     # generate a value for LEMBAS_SECRET_KEY
lembas create-admin   # create or promote an administrator
```

## How it fits together

```
Browser  ──form POST──▶  FastAPI  ──▶  SQLite
   ▲                        │
   │                        └──httpx──▶  any OpenAI-compatible endpoint
   └──── server-sent events ◀───────────────┘   (streamed reply)
```

Sending a message stores the turn and returns two HTML fragments: the user's
bubble and an empty assistant bubble carrying an `sse-connect`. That opens a
server-sent event stream which appends tokens as they arrive, then replaces the
whole bubble with the finished, Markdown-rendered version. Rendering and
highlighting happen in Python, so the streamed and final views cannot disagree.

```
src/lembas/
  api/         routes: auth, chats, folders, admin, pages
  db/models/   SQLAlchemy schema
  security/    password hashing, sessions
  services/    llm client, chat orchestration, markdown, crypto, sse
  web/         Jinja templates and static assets
assets/        SVG artwork masters
scripts/       artwork generator, vendored-JS fetcher
deploy/        systemd unit and nginx vhost for a real install
```

## Development

```bash
pytest                              # test suite
ruff check .                        # lint
python scripts/build_artwork.py     # regenerate the SVG artwork
python scripts/fetch_vendor.py      # verify vendored JS against the lockfile
```

There is no Alembic. The schema is SQLite-only and synchronised at startup:
missing tables and missing columns are added automatically, so adding a field to
a model needs nothing but a restart. Renames, drops and retypes are still manual
— see `CLAUDE.md`.

## Artwork

The logo, favicon and banner are original vector work, generated by
[`scripts/build_artwork.py`](scripts/build_artwork.py) so the mallorn leaf stays
identical across every size it appears at. The wordmark is
[Source Serif 4](https://github.com/adobe-fonts/source-serif) (SIL OFL 1.1)
converted to outlines — a README banner cannot load a webfont, and `<text>`
would render in whatever serif the reader happens to have.

## Licence

[GPL-3.0](LICENSE).

## A note on the theme

This is an independent hobby project, themed as an affectionate nod to
J.R.R. Tolkien's world. It is **not affiliated with, endorsed by, or connected
to** the Tolkien Estate, Middle-earth Enterprises, or any related rights
holder. All artwork here is original.