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 streams into its own collapsible block
  (closed by default), labelled with how long it took, and is never replayed as
  context
- **Live Markdown** — formatting appears as the model writes, not at the end
- **Stop and rewind** — cut a reply short and keep what arrived, or edit an
  earlier message and run the conversation on from there
- **Replies keep running in the background** — navigate away, open another
  chat, close the tab; a green dot and a notification tell you when it lands
- **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
- **Web search** — offered to the model as a tool it calls when a question needs
  it. DuckDuckGo out of the box (no account, no key), or point it at your own
  SearXNG, or Firecrawl. The sources stay in the transcript
- **Your own tools** — describe an HTTP call in the admin area (a schema, a URL
  template, a secret) and a model can make it. Or add an **MCP server** by URL
  and its tools appear beside the built-in ones. Both restrictable to groups,
  and neither can be pointed at your own network unless you say so
- **Agent chats** — start a chat as an *Agent* instead, pointed at one of your
  own SSH connections and a directory on it, and a model can read files, write
  files and run commands **there**. Nothing ever runs on the machine LLeMbas
  itself is on. What it may do without asking is a mode you set and can change
  mid-conversation: *Manual* shows you everything first, *Edit* writes freely
  but asks before commands, *Auto* asks about nothing, and *Plan* reads freely,
  changes nothing, and finishes by proposing steps you can carry out with one
  button. Adding a host shows you its fingerprint before anything is sent to it
- **A terminal beside the chat** — the same connection, a real shell, opened and
  closed like any panel. It survives closing the panel and reloading the page,
  so a build keeps running; the model cannot see it, and a button hands it the
  output you choose
- **It can ask you things** — a model that needs a decision can stop and put a
  few questions on one card, with answers to pick from and a box to write your
  own. In any chat, not only an agent one
- **Speech in and out** — dictate a message and have replies read aloud, against
  any OpenAI-compatible audio endpoint (whisper.cpp, Speaches, Kokoro…). Each
  person picks their own voice
- **A library** — four places a model can reach for. **Knowledge**: documents,
  images and web pages you collect, grouped into named bases so a chat can be
  pointed at just the right one, searched before the web. **Notes**: longer
  things it writes down and finds again later. **Memory**: short facts about you,
  in front of it on every turn. **Skills**: saved procedures it can follow, and
  write. All of it visible and editable by you, and shareable with a group or a
  person, read-only
- **Installable** — add it to a phone home screen or a desktop launcher and it
  runs in its own window
- **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**

Image generation · OCR for scanned PDFs · semantic search in the library.

See [PLAN.md](PLAN.md) for what is built, what is not, and why.

## 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,search,ssh]"   # search: DuckDuckGo. ssh: agent chats.
                                     # Drop either if you do not want it

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`.

### Web search

**Admin → Web search.** DuckDuckGo needs nothing beyond the `search` extra
above. SearXNG needs its JSON format enabled — add `- json` under
`search.formats` in its `settings.yml`, or every search fails. Firecrawl needs
an API key.

Search is offered to the model as a *tool*, so it decides when a question needs
looking up. It is only offered to models marked **tools** under
**Admin → Models**: an endpoint without tool support rejects the whole request
rather than ignoring the extra field, so the flag is a real switch and not a
hint.

### Audio

**Admin → Audio.** Two endpoints, because they are usually two servers:

| | Speaks | Example |
|---|---|---|
| Dictation | `POST /v1/audio/transcriptions` | whisper.cpp's `whisper-server`, Speaches, faster-whisper-server |
| Read aloud | `POST /v1/audio/speech` | Kokoro-FastAPI, OpenAI |

If the speech endpoint also answers `GET /v1/audio/voices` the voice list is
read from it, and each person can pick their own under **Settings → Audio**.
Recorded audio is passed straight through and never written to disk.

> The microphone needs HTTPS or localhost. Browsers do not grant it over plain
> HTTP, so a LAN install without TLS will not offer dictation.

### Agent chats

**Admin → Agents** to turn the feature on, then **Connections** in the sidebar
to add a machine. Three things have to line up before an agent chat can start:
the feature enabled, the *Run commands* permission, and a model flagged **Agent
execution**. All three are off by default, on purpose.

Nothing an agent does runs on the machine LLeMbas is on. Commands go to a host
you name over SSH, which means **the containment is that host** — a container
built for the job is a very different thing from a key to a server you care
about, and LLeMbas cannot tell them apart. A throwaway container is the intended
shape:

```bash
docker run -d --name agent-box -p 127.0.0.1:2222:22 <an sshd image>
```

Adding a connection does not connect to it. **Check** shows you the host's
fingerprint with nothing sent — not your username, not your key — and only
accepting pins it. If that host later answers with a different key, it is
refused rather than quietly trusted.

Then start a chat with the **Agent** toggle, pick the connection and a
directory, and choose a mode. The mode is in the chat header and changes at any
time:

| | Reads | Writes files | Runs commands |
|---|---|---|---|
| **Manual** | asks | asks | asks |
| **Edit** | free | free | asks |
| **Auto** | free | free | free |
| **Plan** | free | asks | asks |

The mode is enforced in the reply loop, not written into the prompt: everything
a model reads — a web page, a README, the last command's output — is untrusted,
and a rule that lives only in a system message is one a poisoned file can argue
with. In **Auto**, nothing stands between that and a command running.

*Plan* finishes by proposing steps, with a button that carries them out — which
switches to *Edit*, never *Auto*, because the plan was written under a mode
where every command still asked.

#### The terminal

An agent chat has a **Terminal** button in its header, which opens a real shell
on that chat's connection, in its directory, beside the conversation. It needs
the *Open a terminal* permission, which is off by default.

The modes above do not apply to it. They exist because a model reads pages,
files and command output it did not write; you hold the credential and could
open the same shell with an ssh client, so nothing you type is queued for your
own approval. The model cannot see the panel either — the button in its header
puts the selection, or the last of the output, into the message box, where you
read it before it goes anywhere.

The shell is not tied to the panel. Close it and a build carries on; come back,
or reload, and you reattach with the scrollback. Two tabs share one shell, and
the smaller window decides the size. It ends when nobody has watched it and
nothing has been typed for a while, when the chat is deleted, when the
connection is disabled or deleted, or when LLeMbas restarts — a deploy cuts off
whatever was running, and the panel says so rather than quietly opening a fresh
shell that has lost your working directory.

> Nothing typed here is in the transcript and nothing is logged but the opening
> and the closing. If you are running this over plain http, note that the
> session cookie is not marked `secure` so a LAN install works at all — with a
> terminal switched on, that is worth a certificate.

### The library

**Sidebar → Library**, and **Settings → Memory**. Nothing is on by default for a
model: give it the tools it should have under **Admin → Models**, where
`tools` decides whether a tool list may be sent at all and the built-in tools are
chosen one by one.

Knowledge is organised into **bases** — one per subject, project or client. A
chat with no base attached searches everything you have; tick some in the chat's
settings panel and it searches only those. Sharing happens at the base: share it
and everything in it comes too, read-only.

Search is SQLite's FTS5 — keyword matching with BM25 ranking, no embedding
service to run and nothing that stops working offline. It will not match a
paraphrase, so a line of description on a document is worth writing.

> Saving a **link** makes your server fetch a URL. Addresses on your own machine
> and network are refused unless an administrator opts in under
> **Admin → Web search**, because the address can come from a model and the
> server can reach things your browser cannot.

### Installing as an app

Open it in a browser and use *Install* (Chromium) or *Share → Add to Home
Screen* (iOS). This also needs HTTPS or localhost — service workers are
unavailable over plain HTTP, and without one there is nothing to install.

There is no offline mode beyond a page saying so. Everything is rendered by your
server, so a cached conversation would be a snapshot that silently went stale.

## 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.