Transcribe and clean up on this machine, without installing anything first

whisper-server is started on --inference-path /v1/audio/transcriptions,
which is exactly the path api.py already builds for the hosted providers,
and llama-server answers /chat/completions the way OpenRouter does. So the
local half is one more base URL rather than a second code path: worker.py,
filetranscribe.py and meeting.py are untouched, and dictation, subtitles
and meetings all work here on the first try.

Three findings worth naming, none of them in the new code:

whisper.cpp cuts segments on tokens, which in Turkish lands inside a word
about as often as between two. Pasted raw that gives "akraba değ\niller.";
in a subtitle it gives a cue reading "değ". Whisper marks the start of a
word with a leading space, so a piece that does not begin with one
continues the word above it.

A small model will repeat the transcript until the context is full, and
every one of those tokens is a second of somebody waiting: measured at 206
seconds, and 25 with a ceiling on the reply. Hosted models are left alone,
where the same runaway is rare and a ceiling would cut the minutes short.

A server outlives SIGTERM and SIGKILL holding its model in memory. Signals
are now turned into an event Qt delivers, since Qt blocks in C where a
Python handler never runs, and a pid file lets the next start sweep up
what a SIGKILL left behind.

The minutes keep their own provider rather than following cleanup's. The
two jobs are not the same size: a 4B model here will strip the filler words
out of a dictation and will not write up an hour long meeting.

The suite runs offline now: a test that reaches the network says so instead
of quietly going there.
This commit is contained in:
yusufipk
2026-08-01 20:00:35 +03:00
parent c0b892f53c
commit 2cfbbb2d99
16 changed files with 1194 additions and 120 deletions
+84 -3
View File
@@ -13,6 +13,7 @@ from unittest import mock
import api
import config as cfg
import ggml
import i18n
from tests.support import DikteTest
@@ -127,8 +128,17 @@ class Keys(DikteTest):
class TranscribeTarget(DikteTest):
def test_openai_by_default(self):
target = self.config(openai_api_key="sk-test").transcribe_target()
def test_this_machine_by_default(self):
target = cfg.Config().transcribe_target()
self.assertEqual(target.provider, "local")
self.assertEqual(target.api_key, "")
# Empty on purpose: the server picks a port when it starts, and reading
# a setting must not be what starts it.
self.assertEqual(target.base_url, "")
def test_openai_when_it_is_picked(self):
target = self.config(transcribe_provider="openai",
openai_api_key="sk-test").transcribe_target()
self.assertEqual(target.provider, "openai")
self.assertEqual(target.service, "OpenAI")
self.assertEqual(target.api_key, "sk-test")
@@ -146,7 +156,8 @@ class TranscribeTarget(DikteTest):
self.assertEqual(target.model, "openai/whisper-1")
def test_a_self_hosted_endpoint(self):
conf = self.config(openai_base_url="http://localhost:8080/v1")
conf = self.config(transcribe_provider="openai",
openai_base_url="http://localhost:8080/v1")
self.assertEqual(conf.transcribe_target().base_url, "http://localhost:8080/v1")
@@ -425,3 +436,73 @@ class Defaults(unittest.TestCase):
if __name__ == "__main__":
unittest.main()
class LocalTargets(DikteTest):
def test_cleanup_can_run_here_while_the_minutes_do_not(self):
# The two jobs are not the same size: a small model on this machine
# strips filler words perfectly well and will not write up an hour.
conf = self.config(cleanup_provider="local", local_llm_model="gemma.gguf")
self.assertEqual(conf.cleanup_target().provider, "local-llm")
self.assertEqual(conf.minutes_target().provider, "openrouter")
self.assertEqual(conf.minutes_target().model, cfg.DEFAULTS["meeting_model"])
def test_the_minutes_can_run_here_on_their_own(self):
conf = self.config(meeting_provider="local", local_llm_model="gemma.gguf")
self.assertEqual(conf.minutes_target().model, "gemma.gguf")
self.assertEqual(conf.cleanup_target().provider, "openrouter")
def test_the_local_cleanup_target_carries_the_thinking_level(self):
conf = self.config(cleanup_provider="local", local_llm_model="gemma.gguf",
local_llm_reasoning="none")
target = conf.cleanup_target()
self.assertEqual(target.reasoning, "none")
self.assertEqual(target.api_key, "")
def test_either_of_them_counts_as_using_the_local_model(self):
self.assertFalse(cfg.Config().uses_local_llm())
self.assertTrue(self.config(cleanup_provider="local").uses_local_llm())
self.assertTrue(self.config(meeting_provider="local").uses_local_llm())
class ReadyToRun(DikteTest):
def setUp(self):
super().setUp()
self.patch_attr(ggml, "MODELS_DIR", self.path("models"))
def install(self, name):
path = ggml.whisper_model_path(name)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_bytes(b"model")
def test_a_missing_program_is_not_ready(self):
with mock.patch("shutil.which", return_value=None):
self.install("ggml-base.bin")
conf = self.config(local_model="ggml-base.bin")
self.assertFalse(conf.transcribe_ready())
def test_a_missing_model_is_not_ready_either(self):
with mock.patch("shutil.which", return_value="/usr/bin/whisper-server"):
conf = self.config(local_model="ggml-base.bin")
self.assertFalse(conf.transcribe_ready())
def test_both_halves_in_place(self):
with mock.patch("shutil.which", return_value="/usr/bin/whisper-server"):
self.install("ggml-base.bin")
conf = self.config(local_model="ggml-base.bin")
self.assertTrue(conf.transcribe_ready())
def test_a_hosted_provider_is_ready_when_it_has_a_key(self):
conf = self.config(transcribe_provider="openai", openai_api_key="sk-test")
self.assertTrue(conf.transcribe_ready())
def test_the_settings_reach_the_servers(self):
conf = self.config(local_model="ggml-base.bin", local_threads=4,
local_gpu=False, local_llm_model="gemma.gguf",
local_llm_context=4096)
conf.apply_local()
self.addCleanup(ggml.whisper.configure, model="", threads=0, gpu=True)
self.assertEqual(ggml.whisper.settings()["model"], "ggml-base.bin")
self.assertEqual(ggml.whisper.settings()["threads"], 4)
self.assertFalse(ggml.whisper.settings()["gpu"])
self.assertEqual(ggml.llm.settings()["context"], 4096)