Jaroslav Beneš
d90195015c
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>
170 lines
7.0 KiB
Markdown
170 lines
7.0 KiB
Markdown
<p align="center">
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<img src="assets/banner.svg" alt="LLeMbas — waybread for the long road of thought" width="100%">
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</p>
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<p align="center">
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<strong>A self-hosted web UI for your language models, written in Python.</strong><br>
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Talks to anything that speaks the OpenAI API. Themed after Middle-earth.
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</p>
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<p align="center">
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<img alt="Python 3.11+" src="https://img.shields.io/badge/python-3.11%2B-3E6B7A?style=flat-square">
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<img alt="License GPL-3.0" src="https://img.shields.io/badge/license-GPL--3.0-C9A227?style=flat-square">
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<img alt="No Node required" src="https://img.shields.io/badge/build%20step-none-6B8E4E?style=flat-square">
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</p>
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---
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*Lembas* is the Elvish waybread — one bite sustains a traveller for a day's
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march. The capitals hide what it runs on: **LLeM**bas.
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## Why this exists
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Most self-hosted LLM front-ends are large JavaScript applications with a Python
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API bolted underneath. LLeMbas is the other way round: **server-rendered
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Python**, with htmx and a little Alpine for interactivity. There is no
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`package.json`, no bundler, no build step, and nothing is fetched from a CDN at
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runtime. Clone it, `pip install -e .`, run it.
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## Features
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**Working now**
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- **Chats** — streaming replies, Markdown with server-side syntax highlighting,
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copy and regenerate, automatic chat titles, per-chat system prompt and
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sampling settings
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- **Reasoning display** — thinking from reasoning models streams into its own
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collapsible block, labelled with how long it took, and is never replayed as
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context
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- **Attachments** — drag, paste or pick images, PDFs and text files. Images are
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downscaled and sent to vision models; PDF and text content is extracted and
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put in the prompt
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- **Folders** — arbitrarily nested, delete a folder without losing the chats
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inside it
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- **OpenAI connections** — point at OpenAI, LM Studio, vLLM, llama.cpp,
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llama-swap, Ollama or OpenRouter; models are discovered and cached
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- **Model settings** — ordering, pinned models, an instance default and a
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per-user default, custom names and descriptions, uploaded model images
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- **Users, groups & permissions** — per-group grants that union rather than
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override, and model access restricted to chosen groups
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- **Accounts** — first account becomes the administrator, argon2 password
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hashing, revocable server-side sessions, self-service password change,
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admin-managed accounts
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- **Admin settings** — open or close registration from the UI, stored in the
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database and effective immediately
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- **Two themes** — *Moria* (dark) and *Shire* (light), switchable per user
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**Planned**
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Built-in tools with admin settings · custom tools and MCP servers · agentic
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execution (local and over SSH) · image generation · OCR for scanned PDFs.
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## Quick start
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```bash
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git clone https://git.houmeres.sk/Houmeres/LLeMbas.git
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cd LLeMbas
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python -m venv .venv && . .venv/bin/activate
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pip install -e ".[dev]"
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cp .env.example .env
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lembas secret-key # paste the result into LEMBAS_SECRET_KEY
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lembas serve # http://127.0.0.1:8080
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```
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Open the address and create the first account — it becomes the administrator.
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Then go to **Admin → Connections** and add an endpoint. For a local runner that
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is usually `http://localhost:1234/v1` with no API key. Press **Test & refresh**
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and its models appear in the chat model picker.
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> The vendored browser libraries (htmx, Alpine) are committed, so no network
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> access is needed to run. To re-fetch or bump them:
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> `python scripts/fetch_vendor.py --update`.
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## Configuration
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All variables are prefixed `LEMBAS_` and can live in `.env`. See
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[`.env.example`](.env.example) for the annotated list.
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| Variable | Default | Purpose |
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|---|---|---|
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| `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. |
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| `LEMBAS_DATA_DIR` | `./data` | SQLite database and uploads. |
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| `LEMBAS_HOST` / `LEMBAS_PORT` | `127.0.0.1` / `8080` | Bind address. |
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| `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. |
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| `LEMBAS_DEFAULT_THEME` | `moria` | `moria` (dark) or `shire` (light). |
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| `LEMBAS_SESSION_TTL` | `2592000` | Session lifetime in seconds. |
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| `LEMBAS_REQUEST_TIMEOUT` | `300` | Seconds to wait on an upstream model. |
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### Commands
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```bash
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lembas serve # run the server
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lembas info # where data lives, what is configured
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lembas secret-key # generate a value for LEMBAS_SECRET_KEY
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lembas create-admin # create or promote an administrator
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```
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## How it fits together
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```
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Browser ──form POST──▶ FastAPI ──▶ SQLite
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▲ │
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│ └──httpx──▶ any OpenAI-compatible endpoint
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└──── server-sent events ◀───────────────┘ (streamed reply)
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```
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Sending a message stores the turn and returns two HTML fragments: the user's
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bubble and an empty assistant bubble carrying an `sse-connect`. That opens a
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server-sent event stream which appends tokens as they arrive, then replaces the
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whole bubble with the finished, Markdown-rendered version. Rendering and
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highlighting happen in Python, so the streamed and final views cannot disagree.
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```
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src/lembas/
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api/ routes: auth, chats, folders, admin, pages
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db/models/ SQLAlchemy schema
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security/ password hashing, sessions
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services/ llm client, chat orchestration, markdown, crypto, sse
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web/ Jinja templates and static assets
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assets/ SVG artwork masters
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scripts/ artwork generator, vendored-JS fetcher
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deploy/ systemd unit and nginx vhost for a real install
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```
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## Development
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```bash
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pytest # test suite
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ruff check . # lint
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python scripts/build_artwork.py # regenerate the SVG artwork
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python scripts/fetch_vendor.py # verify vendored JS against the lockfile
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```
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There is no Alembic. The schema is SQLite-only and synchronised at startup:
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missing tables and missing columns are added automatically, so adding a field to
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a model needs nothing but a restart. Renames, drops and retypes are still manual
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— see `CLAUDE.md`.
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## Artwork
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The logo, favicon and banner are original vector work, generated by
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[`scripts/build_artwork.py`](scripts/build_artwork.py) so the mallorn leaf stays
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identical across every size it appears at. The wordmark is
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[Source Serif 4](https://github.com/adobe-fonts/source-serif) (SIL OFL 1.1)
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converted to outlines — a README banner cannot load a webfont, and `<text>`
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would render in whatever serif the reader happens to have.
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## Licence
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[GPL-3.0](LICENSE).
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## A note on the theme
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This is an independent hobby project, themed as an affectionate nod to
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J.R.R. Tolkien's world. It is **not affiliated with, endorsed by, or connected
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to** the Tolkien Estate, Middle-earth Enterprises, or any related rights
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holder. All artwork here is original.
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