Reject failed Whisper GPU attempts, identify Llama devices from model buffers, and keep historical diagnostics independent of current settings. Report loaded backends without inferring build support, with regression coverage for each case.
A whisper.cpp or llama.cpp server started for one dictation stayed loaded
until Dikte quit. On this machine that is 1.3 GB of VRAM for large-v3 plus
whatever the cleanup LLM takes, held all day between dictations that last
seconds.
Each Server now carries an idle window. A watcher thread per launch stops the
server once nothing has asked it anything for that long, and the next request
loads it again through serve(), which already starts what is not running.
Settings has one checkbox and one number for both servers, on by default at ten
minutes, and it only appears for a machine that runs a model here. The tray menu
says which models are loaded and offers to unload them now.
Two things the clock alone gets wrong, both held off by a count of requests in
flight:
* A file or a meeting is one address lookup and then minutes of work, which
to a clock started at the lookup looks exactly like a model nobody wants.
api.py and cleanup.py hold the count for the length of the request.
* The count must survive the start it triggered. cleanup._local takes the
hold and only then asks for the address, so a cold start happens inside it;
neither serve() nor _stop_now() resets the count any more.
Unloading by hand runs on the interface's thread, so it asks for the start lock
rather than waiting on it: a model still being read in is refused, the way one
in the middle of a request is, instead of freezing the window for as long as
the load takes.
Three from the review of the change before this one.
sysconf answers -1 for a limit it holds to be indeterminate, and CPython
hands that back rather than raising, so the page count times the page size
came out negative. A negative is truthy, so it went past the check for a
machine nothing could be read from and floored at half a gigabyte: a 64 GB
workstation was told every model past 512 MB was too big for it, the
suggestion dropped to small-q5_1, and the machine line read "Memory:
-4096 B". Anything not positive is now the unknown machine it always was.
The memory is read once and kept. It does not change while Dikte runs, and
a thirty row list asked seventy times per draw, which on the Mac path is
seventy processes started on the interface thread every time a download
finished, a model was deleted or a publisher changed.
And "test-" is matched as a plain substring, so it was also inside
"Latest-" and dropped a publisher nothing is wrong with. Anchored the way
every other mark in that list already is.
The two local model boxes handed over a flat list sorted by size and left
every choice in it to the reader. For whisper that interleaved the models:
large-v3-turbo-q5_0 landed between the two medium quantisations, half a
screen from the turbo model it is a copy of. For cleanup it was forty
repository ids, half of which answer with nothing at all because what they
publish is split across files or larger than the cap, and an empty box read
as though the click had not registered.
Now each box says what the machine is, groups the list by model, and marks
the row to take:
- whisper rows are grouped by model, with the quantisations and the
English-only files under the model they are a copy of, and every row says
its bit depth rather than leaving q5_1 and Q4_K_M and BF16 to be decoded.
- the recommendation follows the machine. Under 4 GB it is small-q5_1;
with a graphics interface and 15 GB it is large-v3-q5_0, which is worth
about two and a half points of word error in the languages that are not
English; in between it is turbo, and a processor build where the Vulkan
one belongs is not counted as a card.
- a row larger than half the memory less a gigabyte says it is too big.
- the publisher box holds the five suggestions until the switch beside it
is turned on, and a line under it says in words what the chosen one is.
- a publisher that answers with nothing says why instead of going blank.
- the draft heads (dflash, dspark, eagle3) are no longer offered as models,
and neither are the base models that sit beside their tuned twin.
master grew _pick_asset() while this branch grew a second answer to the
same question inside install_program(). Two functions deciding which
archive this machine wants is one too many, so the managed build is
asked for at the top of the picker: Dikte's own Vulkan whisper-server
first where the machine is one it is built for, then upstream's newest,
then the nightly pointer, then the newest release that carries a build.
install_program() is back to master's three lines and reads which of the
two landed off the asset name.
"latest" for llama.cpp is a version marker carrying one file, nightly-tag.txt, and the archives it names hang off a prerelease that "latest" never points at. Reading only the latest release meant Dikte offered no llama-server for any machine, so _pick_asset now follows that pointer, and when there is none it walks the recent releases and takes the newest one that does carry a build for this machine. hub grows releases() for the listing and text() for the pointer file; the pointer is read rather than cached, because what it carries is a few bytes on the way to a download that is checksummed in full.
The extra lookups are best effort: whatever goes wrong in them leaves the caller's own message standing, but a first release that could not be fetched at all is kept and re-raised when nothing else turns up, so an unreachable GitHub still reads as an unreachable GitHub rather than as a machine nobody publishes for.
The install falls back to upstream's CPU archive whenever Dikte's own
release, the file in it, or its reviewed digest is not there, and until
the package is published by hand that is every download. It happened
without a word: the window said "Downloaded, version v1.9.3." either
way, and a graphics card sitting idle looks exactly like one being used.
The install record now carries which of the two builds landed, written
only where both were on offer, and the settings window says so on the
line that already reports the version.
Refusing the install on a Python without the extraction filters is a
change to how every archive on every platform is unpacked, and it has
nothing to do with shipping a Vulkan whisper-server. On those Pythons
the download stops working altogether, which is a worse answer than the
one that was there.
Worth doing on its own terms, in its own change, where the versions it
turns away can be argued about without a backend release riding on it.
Two things the first pass got wrong.
The card was named out of whichever listing came first, so a machine
with both a CUDA build and a Vulkan loader could have its card named
from the wrong one. Worse, whisper numbers every device it can see in
one sequence while the handle carries the backend's own index: a
processor-only build lent a Vulkan backend through GGML_BACKEND_PATH
reports "device 1: Vulkan0", and reading that listing by the handle's
digit names whatever sat in slot zero. The backend's own enumeration is
asked first now, because it is the only one indexed the way the handle
is, and whisper's listing is a fallback taken only when it names
exactly one card.
And "this build carries no graphics backend" left the reader with
nowhere to go. It is the one case with a fix worth naming: whisper.cpp
publishes no build that reaches a card on Linux, and program_path runs
a copy from the system ahead of the downloaded one, so installing one
is the whole remedy. Server.state() now says which copy is running,
and the line says so only when it is Dikte's own download; a system
build that cannot reach the card gets the shorter sentence, since
installing it again would change nothing.
Co-Authored-By: Claude Opus 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_019zqCqhmeaNT6m1GPp8ZWPp
"Use the graphics card" was a flag and nothing else: whisper got -ng
when it was off, llama got -ngl 99 or 0, and nobody looked at what
happened next. A build without a GPU backend runs on the processor
while the box stays ticked, which is what the release archives for
Linux do, every time. Nothing anywhere reported whether the local
server was even up.
Both servers already say where the model went, in the log Dikte
captures. It is read back once the server reports ready and turned
into a backend, a card and, for llama, the layers it offloaded. The
verdict comes from what whisper committed to -- "using X backend" and
the model buffer -- rather than from the devices it merely listed: a
card that is found and then fails to initialise sends it back to the
processor, and the listing alone would have called that a graphics
card. A log that says nothing stays "could not tell" instead of being
guessed at; a hand-built macOS whisper has Metal compiled in and
prints no backend line at all.
The state is then somewhere to be seen. Server.state() is a snapshot
of the process and what it settled on, and it reaches `dikte status`,
`dikte doctor` and a line under each local model box in the settings
window. doctor reads the log from disk when no instance is running, so
it still answers on a machine where Dikte is closed, and it says which
of the three it is: what the last run used, that the last run said
nothing, or that none ever ran here. Where the card was asked for and
not obtained, the line says which of the two it is -- none was found,
or this build carries none -- because only the second is worth
replacing a download over.
The tests grew a second isolation. They read ggml's own data
directory, which is the real one on the machine running them, and
program_path prefers a whisper-server on the PATH, so the suite
answered from whatever the developer happened to have installed. Both
are now the test's own.
Co-Authored-By: Claude Opus 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_019zqCqhmeaNT6m1GPp8ZWPp
New installs start detecting instead of being locked to one language; a stored
value from before this default still wins. The dictation chain asks
transcribe_detected() in auto mode, records the detected code in history as
speech_language, hands it to the cleanup prompt (a detected Turkish recording
gets the Turkish prompt and glossary rule), and reports it on the socket reply.
The stale comment claiming whisper.cpp's -l auto does not detect is corrected.
install_program deleted the working install before the download had even
started, so a network failure, or the running server's own locked DLLs,
left "whisper.cpp is not installed" behind on a machine where it had
been. The order is now: download, unpack beside, stop the server whose
binary lives there, swap, so the outage is the swap and not the whole
transfer, and a download that fails never takes the server down at all.
A re-downloaded model the server still holds open no longer costs the
finished download; the .part survives and the message says who is holding
the file.
sweep() forgot the pid file before verifying or killing, so one transient
error orphaned a loaded model forever; it verifies, kills, then forgets,
and a verification that could not run leaves the file for the next start.
On Windows the ownership check was the executable's basename, which a
recycled pid could satisfy with somebody else's server; it is the full
image path now, read into a buffer that grows past 260 characters.
stop() takes the launch lock, so stopping during a start kills the server
the start was making rather than missing it, and _forget only removes a
record that is still its own. The relaunch retry stopped reading English
out of the log tail: the retryable failure is a child that exited without
ever listening, and that is what is tested, along with the child still
being alive once its port answers.
Co-Authored-By: Claude Fable 5 <[email protected]>
Every file this branch touches moved into dikte/, so the merge is mostly the
rename following the edits. What needed a hand:
hotkey.py: master replaced the _macos()/_gnome() pair with one backend()
chooser, and this branch had added _windows() to the pair. Windows is a fifth
value of the chooser now, and everything that used to ask "macOS or Windows?"
asks backend() instead. The key is held by the running process there, so
installs_shortcuts() and shortcut_needs_restart() are both false for it, and
desktop_name() says Windows.
install.ps1 and the Windows README name dikte/__main__.py, the entry point the
Linux and macOS installers were pointed at in the same commit. The Start Menu
entry, the autostart entry and the dikte.cmd shim all come off one $entry
variable.
settings_ui.py: the shortcut tab now has a Windows sentence of its own, with
the Turkish for it. Falling through to the branch master wrote for a desktop
with no registry would have told a Windows user to check /dev/input. Nothing
covers that branch: there is no Windows Settings test class, the way there is
one for macOS.
CONTRIBUTING: the chooser it names is backend() now, and the test count is the
merged one, 1067 of 1110 running anywhere.
Twenty-two files at the top of the tree was the first thing anybody saw of
this repository. They are one package now, imported relatively, and the three
scripts that are not the front door moved under scripts/. install.sh stays
where the README has always said it is.
What starts the application is dikte/__main__.py: python3 -m dikte runs it,
and so does naming the file, which is what the launcher symlink, both .desktop
files, the macOS bundle and every registered shortcut do. Run by path there is
no package around it, so it puts the checkout on sys.path itself.
The installers now keep the keys you chose when they are given none, which is
what an update is: update.sh no longer has to read them out and pass them back.
An updater from before this commit cannot read them at all, so the one thing it
can say, the default key with an empty discard key, is read as "nothing was
asked for" rather than obeyed. That guard can go once nobody is updating across
this commit.
yusufipek
nomoreshow