Jaroslav Beneš
bdce2764b1
Drag, paste or pick a file in the composer. Images go to vision models as multimodal content parts; PDFs and text files have their content extracted and placed in the prompt. Verified end to end against gemma4-e4b-q8 on llama-swap: given a drawing and a text file, it named the red square and blue circle and read the number out of the document. Type is decided by inspecting the bytes, never the filename or the browser's Content-Type -- a .png full of text is stored as text. Images are downscaled to 1400px and re-encoded: a phone photo is several megabytes of base64, which is slow and a large slice of the context window. PDF text is extracted once, at upload, and stored; re-extracting per request would let a reply change because a parser was upgraded. Design points worth keeping: - Images are only sent to models an administrator has marked `vision`. This is not graceful degradation -- most endpoints reject the entire request rather than ignoring an image part. A plain text turn stays a plain string for the same reason: the list form 400s on endpoints that do not implement it. - Images reach the model as base64 data URIs, not links. A local endpoint has no route back to LLeMbas, and a hosted one has no credentials for it. - Non-images are served Content-Disposition: attachment with nosniff, so an uploaded .html can never execute in this origin. Stored names are random; the uploader's name is a label and never a path. - Uploads are unbound until the message is sent, which is what lets a file be removed beforehand. claim() only takes unclaimed rows owned by the sender, so a forged id cannot pull in someone else's file. Abandoned uploads are swept at startup. - A scanned PDF says so rather than silently contributing nothing, and truncation is declared to the model in the document tag so it can admit it did not see page 400. - "Here, look at this" with no words is a legitimate turn, so a message is only empty when it carries neither text nor files. Also fixes auto-titling, which read message["content"] as a string and would have broken on the first multimodal turn. 186 tests, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A self-hosted web UI for your language models, written in Python.
Talks to anything that speaks the OpenAI API. Themed after Middle-earth.
Lembas is the Elvish waybread — one bite sustains a traveller for a day's march. The capitals hide what it runs on: LLeMbas.
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
- 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 — 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
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
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 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
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
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 so the mallorn leaf stays
identical across every size it appears at. The wordmark is
Source Serif 4 (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
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.