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.

meeting.py

@@ -118,18 +118,12 @@ class MeetingPipeline(QObject):
 
             self._check()
             self._say(t("Writing the minutes…"))
-            minutes = api.cleanup(
-                transcript,
-                self.conf.openrouter_key(),
-                self.conf["meeting_model"],
-                self.conf.meeting_prompt(),
-                reasoning=self.conf["meeting_reasoning"],
-                base_url=self.conf["openrouter_base_url"],
-                timeout=600,
-            )
+            writer = self.conf.minutes_target()
+            minutes = api.cleanup(writer, transcript, self.conf.meeting_prompt(),
+                                  timeout=600)
             title = self._write(doc_path, minutes, transcript, entry)
             cfg.update_meeting(base, status="done", error="", title=title,
-                               model=self.conf["meeting_model"])
+                               model=writer.model)
             self._discard_audio(wav_path)
             self.finished.emit(base, title)
 
@@ -201,6 +195,7 @@ class MeetingPipeline(QObject):
     def _cleanup(self, transcript):
         conf = self.conf
         prompt = conf.cleanup_prompt(with_timestamps=True, with_speakers=True)
+        target = conf.cleanup_target()
         out = []
         blocks = filetranscribe.split_text(transcript, True)
         for index, block in enumerate(blocks, start=1):
@@ -208,14 +203,7 @@ class MeetingPipeline(QObject):
             if len(blocks) > 1:
                 self._say(t("Cleaning up {index}/{count}…",
                             index=index, count=len(blocks)))
-            out.append(api.cleanup(
-                block,
-                conf.openrouter_key(),
-                conf["cleanup_model"],
-                prompt,
-                reasoning=conf["cleanup_reasoning"],
-                base_url=conf["openrouter_base_url"],
-            ))
+            out.append(api.cleanup(target, block, prompt))
         return "\n".join(out)
 
     def _write(self, doc_path, minutes, transcript, entry):