Four pieces of work.
**Installable.** A manifest carrying the instance name, PWA icons rasterised
from the existing mark at design time, a service worker and a themed offline
page. The worker caches the shell only and bails out on /api/, /auth/, /admin/
and anything accepting text/event-stream -- passing a reply stream through a
worker turns it into one delivery at the end, or nothing. It is served from
GET /sw.js rather than the static mount because a worker's scope is the path it
came from.
**Send and Stop are one button.** They were two, and the hidden one was never
hidden: `.btn` is display: inline-flex, which outranks the browser's own
`[hidden] { display: none }`, so Stop sat permanently beside Send. app.css now
forces the attribute to win -- every control toggled with `hidden` depended on
that -- and the composer renders one button carrying both icons, with ui.js
flipping data-composer-action and the type with it.
**Audio.** Speech to text and text to speech against any OpenAI-shaped
/v1/audio/* endpoint: dictate into the composer, have a reply read out.
Instance settings in Admin, per-reader overrides in Settings, with the voice
list discovered from the server where it offers one. Recorded audio is capped
and never written to disk -- it is not an attachment, it has no owner, and
nothing would ever sweep it.
**Web search, as a tool.** This is the tool loop PLAN.md described as the real
work: one reply is now a bounded sequence of requests rather than one. The model
asks, the tool runs, the result goes back and it is asked again, up to three
rounds. Providers are DuckDuckGo (no setup), SearXNG and Firecrawl.
Two decisions worth stating. Tools are only offered to models flagged `tools`,
because an endpoint without support rejects the whole request rather than
ignoring the array -- the same reason images only reach models flagged
`vision`. And tool results are not replayed as context on the next turn, for the
same reasons reasoning is not: the answer already contains what the model made
of them, and replaying stale results into every later request wastes the window
and reliably sends a small model into a search loop. The sources stay visible in
the transcript instead.
Search results are untrusted third-party text and are treated as such: escaped,
and only http/https URLs rendered as links.
338 tests, ruff clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
LLeMbas now runs end to end. Register, add an OpenAI-compatible
connection, and hold a real streaming conversation organised into
folders. Verified against the local llama-swap instance.
Streaming is the one genuinely tricky part. Sending a message returns
two HTML fragments -- the user bubble and an empty assistant bubble
carrying an sse-connect -- and that attribute is the ONLY thing that
starts a generation. Rendering an incomplete assistant message as a
streaming shell falls out of the same template, which means loading a
page whose last reply never finished simply picks it up again.
Details worth knowing about, each commented where it matters:
- SSE payloads are split across several data: lines. A raw newline in
one data: line truncates the event, which shows up the first time a
model emits a code block.
- Markdown is rendered server-side by the same helper for both the page
and the final streamed frame, so the two cannot disagree. The fence
renderer is replaced outright rather than using markdown-it's
highlight option, which re-wraps output in a second <pre>.
- escape_text is html.escape, not nh3.clean_text: it escapes character
by character, so escaping stream chunks separately equals escaping
the whole string.
- The stream opens its own session via session_scope(); it outlives the
request handler and the dependency-scoped session may be closed.
- Deleting a folder keeps the chats inside it (FK is SET NULL). Losing
a conversation to a mis-clicked folder delete is unforgivable.
- Login failures use one message for "no such account" and "wrong
password" so the form cannot enumerate registered addresses.
Also adds deploy/ for the gamebox install at https://chat.lan: system
unit, nginx vhost with buffering off (buffering on turns streaming into
one lump at the end), and install/update scripts following the same
service-user and /srv bind-mount conventions as llama-swap and comfyui.
70 tests, ruff clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Establish the LLeMbas foundation: FastAPI/Jinja/SQLite layout, the ORM
schema, and the original SVG identity.
Notable decisions, all recorded in comments at the point they matter:
- No Alembic. SQLite only, schema created at startup, so models carry a
few columns nothing reads yet (Message.parent_id for branching,
content_parts_json for multimodal turns). Adding them later to a live
database without migrations is the painful path.
- Sessions are server-side rows keyed by a SHA-256 of the cookie value,
not JWTs, so logout and bans revoke access immediately.
- Upstream API keys are Fernet-encrypted with a key derived from
LEMBAS_SECRET_KEY. decrypt() fails soft to "" so rotating the secret
degrades to re-entering keys rather than crashing the admin UI.
- Artwork is generated by scripts/build_artwork.py rather than hand-drawn
per file: the mallorn leaf appears in the icon, favicon, lockup and
banner, and one source is the only way those stay in sync. The wordmark
is Source Serif 4 (OFL) converted to outlines, because a README banner
cannot load a webfont and <text> would render in whatever serif the
viewer happens to have.
- Icons live in a template partial, not assets/, because same-document
<use href="#id"> is universally supported and the cross-document form
is not.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Jaroslav Beneš