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LLeMbas/README.md
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Jaroslav Beneš 1d3f6c450b Users, groups, permissions, model settings and reasoning display
Four features, plus the schema machinery they needed.

**Schema sync.** The first live instance had data in it, and create_all
only creates missing *tables* -- a new column silently never appeared.
db/migrations.py now diffs the declared models against the database and
ALTER TABLE ... ADD COLUMN for what is missing, deriving a backfill
default from the column type (SQLite refuses a NOT NULL column without
one, and a Python-side `default=dict` cannot be expressed in DDL).
Verified against a copy of the live database: eight changes applied, all
rows preserved, second run a no-op. Renames, drops and retypes are still
manual and say so.

**Permissions.** A flat set of named booleans: an instance baseline
widened by each group the user belongs to. A group grants and never
denies -- with denies, "why can this user not do X" cannot be answered
without simulating every group. Admins bypass entirely, because an admin
can grant it back to themselves in two clicks and pretending otherwise
is theatre. Model *access* is separate: public, or granted to groups.
The picker is not the boundary -- switching a chat to a model you cannot
reach is a 403.

**Model settings.** Ordering, pinned-first, an instance default and a
per-user default, display names, descriptions, capability flags, and
uploaded images. Images are stored and served locally rather than by
URL: a remote URL makes every page render a request to a third party.
Uploads are validated by magic number, not the declared content type,
and stored under a random name. Models with no image get a generated
initial whose hue is derived from the model id, so it is stable.

**Reasoning display.** Streams into its own collapsible block above the
answer, labelled "Thought for 14 seconds", collapsed once finished, and
never replayed as context on the next turn. Two sources: the
reasoning_content delta field, and <think> tags inline in content -- the
latter needs a streaming splitter because the tags arrive split across
chunks. Models emitting no reasoning show nothing, via a :has() rule
rather than JavaScript. Verified against qwen35-9b on llama-swap: 694
reasoning events, 52 answer tokens, cleanly separated.

Two bugs found and fixed while testing:

- A bare `Mapped[list]` relationship is treated by SQLAlchemy as a scalar
  and returns None instead of []. It needs the element type.
- FastAPI substitutes the default for an empty form value, so with
  `x: str | None = Form(None)` a submitted `x=` is indistinguishable from
  an absent field. That silently broke clearing a system prompt or a
  temperature. update_chat now reads the raw form and checks key presence.

143 tests, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-21 11:49:32 +02:00

167 lines
6.8 KiB
Markdown

<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, per-chat system prompt and
sampling settings
- **Reasoning display** — thinking from reasoning models streams into its own
collapsible block, labelled with how long it took, and is never replayed as
context
- **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** — ordering, pinned models, an instance default and a
per-user default, custom names and descriptions, uploaded model images
- **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**
File upload, vision and PDFs · built-in tools with admin settings · custom tools
and MCP servers · agentic execution (local and over SSH) · image generation.
## 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.