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.

README.md

@@ -1,9 +1,9 @@
 # Dikte
 
-Press `Ctrl+Space`, talk, press again. The recording goes to OpenAI or OpenRouter
+Press `Ctrl+Space`, talk, press again. The recording is transcribed on this
-for transcription, a model on OpenRouter cleans it up (dropping the *uh*s, the
+machine by default, a model cleans it up (dropping the *uh*s, the restarts, the
-restarts, the missing punctuation), and the result lands in your clipboard and
+missing punctuation), and the result lands in your clipboard and is pasted into
-is pasted into whatever window you were typing in.
+whatever window you were typing in.
 
 Built for KDE Plasma 6 on Wayland. No dependencies beyond system packages:
 just the Python standard library and PyQt6.
@@ -39,10 +39,12 @@ sudo apt install pulseaudio-utils xclip xdotool ffmpeg
 `install.sh` adds the `dikte` command, a menu entry and an autostart entry. The
 settings window installs a GNOME or KDE global shortcut.
 
-Two keys go in the settings window: **OpenAI** and **OpenRouter**. Speech to text
+Speech to text and cleanup each pick a provider in the settings window. Both can
-runs on either one (`gpt-4o-transcribe` by default), cleanup always on
+run here, on whisper.cpp and llama.cpp: the program and the model are downloaded
-OpenRouter (`google/gemini-3.5-flash-lite`), so a single OpenRouter key can
+from that window (checksummed, into `~/.local/share/dikte`), so nothing has to be
-cover both. They fall back to `OPENAI_API_KEY` and `OPENROUTER_API_KEY`, and are
+installed first and nothing leaves the machine. The hosted alternatives want a
+key: **OpenAI** or **OpenRouter** for speech to text, **OpenRouter** for cleanup
+(`google/gemini-3.5-flash-lite`), so a single OpenRouter key can cover both. They fall back to `OPENAI_API_KEY` and `OPENROUTER_API_KEY`, and are
 stored in `~/.config/dikte/config.json`, mode 600. Cleanup can be switched off,
 in which case the raw transcript is pasted, and a thinking model's effort can be
 set next to it.
@@ -144,7 +146,9 @@ ipc.py            one request and one reply over the local socket
 audio.py          PCM capture: pw-record for dictation, ffmpeg for a meeting
 meeting.py        channel split, speaker labelling, cleanup, minutes
 assistant.py      running a dictation through Claude Code, Codex or OpenRouter
-api.py            transcription on either provider, OpenRouter cleanup (stdlib only)
+api.py            transcription and cleanup on any provider (stdlib only)
+ggml.py           whisper.cpp and llama.cpp here: fetch, verify, keep serving
+hub.py            what GitHub and Hugging Face have on offer today
 worker.py         transcribe → clean up → clipboard → paste
 vad.py            deciding whether a recording holds speech at all
 filetranscribe.py file transcription: ffmpeg, chunking, timestamps

README.tr.md

@@ -1,9 +1,8 @@
 # Dikte
 
-`Ctrl+Space`'e bas, konuş, tekrar bas. Ses OpenAI'ye ya da OpenRouter'a gidip
+`Ctrl+Space`'e bas, konuş, tekrar bas. Ses varsayılan olarak bu makinede yazıya
-yazıya çevrilir, OpenRouter'daki bir model transkripti temizler (ıı'lar,
+çevrilir, bir model transkripti temizler (ıı'lar, tekrarlar, eksik noktalama),
-tekrarlar, eksik noktalama), sonuç panoya kopyalanır ve o an yazdığın pencereye
+sonuç panoya kopyalanır ve o an yazdığın pencereye yapıştırılır.
-yapıştırılır.
 
 KDE Plasma 6 / Wayland için yazıldı. Sistem paketleri dışında bağımlılığı yok:
 sadece Python standart kütüphanesi ve PyQt6.
@@ -39,10 +38,14 @@ sudo apt install pulseaudio-utils xclip xdotool ffmpeg
 `install.sh` `dikte` komutunu, menü girdisini ve oturum açılışında otomatik
 başlatmayı kurar. Ayarlar penceresi GNOME veya KDE global kısayolunu kurar.
 
-Ayarlar penceresinde iki anahtar istenir: **OpenAI** ve **OpenRouter**. Sesi
+Sesi yazıya çevirme ve temizleme, ayarlar penceresinde ayrı ayrı sağlayıcı
-yazıya çevirme ikisinden birinde çalışır (varsayılan `gpt-4o-transcribe`),
+seçer. İkisi de burada çalışabilir, whisper.cpp ve llama.cpp üzerinde: program
-temizleme her zaman OpenRouter'da (`google/gemini-3.5-flash-lite`), yani tek bir
+da model de o pencereden indirilir (sha256 doğrulamasıyla,
-OpenRouter anahtarı ikisine de yeter. Boş bırakırsan `OPENAI_API_KEY` ve
+`~/.local/share/dikte` altına), yani önceden hiçbir şey kurman gerekmez ve
+makineden hiçbir şey çıkmaz. Bulut seçenekleri anahtar ister: yazıya çevirme
+için **OpenAI** ya da **OpenRouter**, temizleme için **OpenRouter**
+(`google/gemini-3.5-flash-lite`), yani tek bir OpenRouter anahtarı ikisine de
+yeter. Boş bırakırsan `OPENAI_API_KEY` ve
 `OPENROUTER_API_KEY` kullanılır; anahtarlar `~/.config/dikte/config.json`
 içinde, izinler 600. Temizlemeyi tamamen kapatabilirsin, o zaman ham transkript
 yapıştırılır; modelin yanındaki kutudan düşünme seviyesini de seçebilirsin.
@@ -142,7 +145,9 @@ ipc.py            yerel sokette bir istek, bir cevap
 audio.py          PCM kaydı: diktede pw-record, toplantıda ffmpeg
 meeting.py        kanal ayırma, konuşmacı etiketi, temizleme, tutanak
 assistant.py      dikteyi Claude Code, Codex ya da OpenRouter'dan geçirme
-api.py            iki sağlayıcıda transkript + OpenRouter temizleme (yalnız stdlib)
+api.py            her sağlayıcıda transkript ve temizleme (yalnız stdlib)
+ggml.py           whisper.cpp ve llama.cpp'yi indirip burada çalıştırma
+hub.py            GitHub ve Hugging Face'te bugün ne olduğu
 worker.py         transkript → temizleme → pano → yapıştırma
 vad.py            kayıtta gerçekten konuşma var mı kararı
 filetranscribe.py dosyadan transkript: ffmpeg, parçalama, zaman damgaları

api.py

@@ -1,9 +1,14 @@
-"""OpenAI and OpenRouter calls, stdlib only.
+"""OpenAI, OpenRouter and this machine, stdlib only.
 
-Transcription runs on either provider: OpenRouter mirrors OpenAI's
+Transcription runs on any of three providers and cleanup on two, and none of
-/audio/transcriptions endpoint field for field, so one multipart request serves
+them needs code of its own. OpenRouter mirrors OpenAI's /audio/transcriptions
-both and only the key, the base URL and the model id change. Cleanup is always
+endpoint field for field, and ggml.py starts whisper.cpp on that same path, so
-OpenRouter.
+one multipart request serves all three; llama.cpp answers /chat/completions the
+way OpenRouter does, so one JSON request serves both. What changes between them
+is the key, the base URL and the model id.
+
+The local ones have no key, and their base URL is not known until a server is
+up, which is the one thing this module has to fill in for them.
 """
 
 import collections
@@ -14,6 +19,7 @@ import secrets
 import urllib.error
 import urllib.request
 
+import ggml
 from i18n import t
 
 APP_URL = "https://github.com/yusufipk/dikte"
@@ -21,14 +27,29 @@ USER_AGENT = f"dikte/1.0 (+{APP_URL})"
 OPENAI_URL = "https://api.openai.com/v1"
 OPENROUTER_URL = "https://openrouter.ai/api/v1"
 
-# Where a transcription request goes; built by config.Config.transcribe_target().
+# The floor for a local request. The timeouts elsewhere are sized for a hosted
-# `service` is the name the user sees in an error, `provider` the one the code
+# API, where a slow answer is a bill running; here the only thing being spent is
-# branches on.
+# time, and a long recording on a machine without a graphics card takes a good
-Target = collections.namedtuple("Target", "provider service api_key base_url model")
+# deal of it. Cutting that off would throw the work away for nothing.
+LOCAL_TIMEOUT = 3600
+
+# Where a request goes; built by config.Config's *_target() methods. `service`
+# is the name the user sees in an error, `provider` the one the code branches
+# on. `reasoning` is only read by cleanup, which is the only job with a model
+# that might think about anything.
+Target = collections.namedtuple(
+    "Target", "provider service api_key base_url model reasoning", defaults=("",))
 
 
-def timestamp_model(provider):
+def timestamp_model(provider, model):
-    """Only whisper-1 returns segment times, and OpenRouter namespaces the id."""
+    """Only whisper-1 returns segment times, and OpenRouter namespaces the id.
+
+    Whisper is what the local server runs whatever the file is called, so there
+    it stays on the model that is already loaded; asking for another one would
+    name a model that server has never heard of.
+    """
+    if provider == "local":
+        return model
     return "openai/whisper-1" if provider == "openrouter" else "whisper-1"
 
 
@@ -106,7 +127,11 @@ def _multipart(fields, file_field, file_path):
 
 
 def _headers(provider, api_key, content_type=None):
-    headers = {"Authorization": f"Bearer {api_key}", "User-Agent": USER_AGENT}
+    headers = {"User-Agent": USER_AGENT}
+    # A server on this machine has nothing to authorise, and sending it a
+    # bearer token would only be a made-up one.
+    if api_key:
+        headers["Authorization"] = f"Bearer {api_key}"
     if content_type:
         headers["Content-Type"] = content_type
     if provider == "openrouter":
@@ -116,17 +141,44 @@ def _headers(provider, api_key, content_type=None):
     return headers
 
 
+def _serving(target, server, timeout):
+    """A local target with the address of a running server in it.
+
+    The server is started on demand and picks its own port, so this is the first
+    moment its address exists. serve() is idempotent: once it is up this costs
+    nothing.
+    """
+    try:
+        return target._replace(base_url=server.serve()), max(timeout, LOCAL_TIMEOUT)
+    except ggml.LocalError as exc:
+        raise ApiError(str(exc)) from None
+
+
+def _local_failure(target, server, exc):
+    """A server that died mid-request, explained by its own output.
+
+    Without this the message is that the connection dropped, when the reason for
+    it was printed by the process at the other end.
+    """
+    detail = server.error()
+    return ApiError(f"{target.service}: {exc}" + (f" ({detail})" if detail else ""),
+                    exc.status)
+
+
 def _transcribe_request(target, wav_path, language, prompt, response_format,
                         granularity=None, timeout=300):
-    if not target.api_key:
+    if target.provider == "local":
+        target, timeout = _serving(target, ggml.whisper, timeout)
+    elif not target.api_key:
         raise ApiError(t("{service} API key is empty. Add it in Settings.",
                          service=target.service))
     fields = [("model", target.model), ("response_format", response_format)]
     if language and language != "auto":
         fields.append(("language", language))
     # OpenRouter takes the hint field and throws it away, so spare it the bytes.
-    # The same words still reach the cleanup model as a glossary.
+    # The same words still reach the cleanup model as a glossary. whisper.cpp
-    if prompt and target.provider == "openai":
+    # takes it as the initial prompt, the way OpenAI does.
+    if prompt and target.provider in ("openai", "local"):
         fields.append(("prompt", prompt))
     if granularity:
         fields.append(("timestamp_granularities[]", granularity))
@@ -137,14 +189,58 @@ def _transcribe_request(target, wav_path, language, prompt, response_format,
             _headers(target.provider, target.api_key, ctype), timeout=timeout,
         )
     except ApiError as exc:
+        if target.provider == "local":
+            raise _local_failure(target, ggml.whisper, exc) from None
         raise explain(exc, target.service) from None
 
 
+# Whisper marks the start of a word with a leading space, so a piece of text
+# that does not begin with one continues the word before it rather than starting
+# a new one. Both helpers below turn on that.
+def _continues_a_word(previous, following):
+    return bool(previous) and not previous[-1:].isspace() and not following[:1].isspace()
+
+
+def _local_text(text):
+    """whisper.cpp's segments, joined back into the flowing line OpenAI returns.
+
+    Its plain text puts one segment per line, and a segment boundary falls
+    wherever the tokens fell, which in Turkish lands inside a word about as
+    often as between two. Nothing takes the line break's place: whisper's own
+    leading spaces are what separate the words, and a break inside "değ|iller"
+    has nothing on either side of it worth keeping.
+    """
+    return "".join(text.split("\n"))
+
+
+def _merge_word_splits(segments):
+    """Fold a segment that begins mid-word into the one it continues.
+
+    The hosted whisper-1 hands back segments cut on sentences; whisper.cpp cuts
+    them on tokens, and a subtitle cue reading "değ" is not a cue. The times are
+    joined along with the text, so the merged segment still covers the whole
+    word.
+    """
+    merged = []
+    for seg in segments:
+        text = seg.get("text") or ""
+        if merged and _continues_a_word(merged[-1]["text"], text):
+            merged[-1]["text"] += text
+            merged[-1]["end"] = seg.get("end") or merged[-1]["end"]
+            continue
+        merged.append({"text": text, "start": seg.get("start") or 0.0,
+                       "end": seg.get("end") or 0.0})
+    return merged
+
+
 def transcribe(target, wav_path, language="", prompt="", timeout=300):
     data = _transcribe_request(
         target, wav_path, language, prompt, "json", timeout=timeout
     )
-    text = (data.get("text") or "").strip()
+    text = data.get("text") or ""
+    if target.provider == "local":
+        text = _local_text(text)
+    text = text.strip()
     if not text:
         raise ApiError(t("Transcript came back empty."))
     return text
@@ -153,11 +249,13 @@ def transcribe(target, wav_path, language="", prompt="", timeout=300):
 def transcribe_segments(target, wav_path, language="", prompt="", timeout=300):
     """[(start_seconds, end_seconds, text)] using whisper-1's verbose response."""
     data = _transcribe_request(
-        target._replace(model=timestamp_model(target.provider)),
+        target._replace(model=timestamp_model(target.provider, target.model)),
         wav_path, language, prompt, "verbose_json",
         granularity="segment", timeout=timeout,
     )
     segments = data.get("segments") or []
+    if target.provider == "local":
+        segments = _merge_word_splits(segments)
     out = []
     for seg in segments:
         text = (seg.get("text") or "").strip()
@@ -166,45 +264,91 @@ def transcribe_segments(target, wav_path, language="", prompt="", timeout=300):
             end = float(seg.get("end") or 0.0)
             out.append((start, max(end, start), text))
     if not out:
-        text = (data.get("text") or "").strip()
+        text = data.get("text") or ""
+        if target.provider == "local":
+            text = _local_text(text)
+        text = text.strip()
         if not text:
             raise ApiError(t("Transcript came back empty."))
         out = [(0.0, 0.0, text)]
     return out
 
 
-def cleanup(text, api_key, model, system_prompt, reasoning="",
+def _thinking(target, payload):
-            base_url=OPENROUTER_URL, timeout=180):
+    """Ask for as much thinking as this provider understands, or for none.
-    if not api_key:
+
+    An empty level means "whatever the model does on its own", so nothing is
+    sent. The two providers mean opposite things by that, which is why the
+    setting is kept per provider: OpenRouter's cleanup models answer straight
+    away, while a local model that was trained to think will think, and cleanup
+    is punctuation rather than a job worth thinking about.
+    """
+    if not target.reasoning:
+        return
+    if target.provider == "local-llm":
+        # What llama.cpp passes to the chat template. The models that think
+        # read it; the ones that do not ignore it.
+        payload["chat_template_kwargs"] = {
+            "enable_thinking": target.reasoning != "none"}
+        return
+    if target.reasoning != "none":
+        # The thinking itself is never shown, so ask for it to be left out.
+        payload["reasoning"] = {"effort": target.reasoning, "exclude": True}
+
+
+def _local_ceiling(text):
+    """How much of a reply is worth waiting for from a model on this machine.
+
+    Cleanup gives back what it was given, near enough, so a reply several times
+    the length of the transcript is a model that has lost the thread rather than
+    one doing the job. A small one will happily repeat the transcript until the
+    context is full, and every one of those tokens is a second of somebody
+    waiting. A hosted model is left alone: there the same runaway is rare, and a
+    ceiling would cut the minutes short instead.
+    """
+    return max(512, len(text))
+
+
+def cleanup(target, text, system_prompt, timeout=180):
+    if target.provider == "local-llm":
+        target, timeout = _serving(target, ggml.llm, timeout)
+    elif not target.api_key:
         raise ApiError(t("{service} API key is empty. Add it in Settings.",
-                         service="OpenRouter"))
+                         service=target.service))
     payload = {
-        "model": model,
+        "model": target.model,
         "temperature": 0,
         "messages": [
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": f"<transcript>\n{text}\n</transcript>"},
         ],
     }
-    # An empty level means "whatever the model does on its own"; anything else is
+    if target.provider == "local-llm":
-    # one of OpenRouter's efforts. The thinking itself is never shown, so ask for
+        payload["max_tokens"] = _local_ceiling(text)
-    # it to be left out of the reply.
+    _thinking(target, payload)
-    if reasoning:
-        payload["reasoning"] = {"effort": reasoning, "exclude": True}
     try:
         data = _request(
-            f"{base_url.rstrip('/')}/chat/completions",
+            f"{target.base_url.rstrip('/')}/chat/completions",
             json.dumps(payload).encode("utf-8"),
-            _headers("openrouter", api_key, "application/json"),
+            _headers(target.provider, target.api_key, "application/json"),
             timeout=timeout,
         )
     except ApiError as exc:
-        raise explain(exc, "OpenRouter") from None
+        if target.provider == "local-llm":
+            raise _local_failure(target, ggml.llm, exc) from None
+        raise explain(exc, target.service) from None
     choices = data.get("choices") or []
     if not choices:
         raise ApiError(_extract_error(json.dumps(data)))
-    content = ((choices[0].get("message") or {}).get("content") or "").strip()
+    message = choices[0].get("message") or {}
+    content = (message.get("content") or "").strip()
     if not content:
+        # A thinking model can spend the whole reply on the thinking and leave
+        # nothing to paste. Worth naming, because the fix is a setting rather
+        # than a retry: cleanup is not a job that wants thinking.
+        if message.get("reasoning_content") or message.get("reasoning"):
+            raise ApiError(t("The cleanup model spent its whole reply on "
+                             "thinking. Set Thinking to “Off”."))
         raise ApiError(t("The cleanup model returned an empty reply."))
     return content
 

config.py

@@ -6,7 +6,9 @@ import os
 import pathlib
 
 import api
+import ggml
 import i18n
+from i18n import t
 
 
 def _xdg(var, default):
@@ -365,14 +367,46 @@ DEFAULTS = {
     "openai_base_url": "https://api.openai.com/v1",
     "openrouter_api_key": "",
     "openrouter_base_url": "https://openrouter.ai/api/v1",
-    "transcribe_provider": "openai",  # openai | openrouter
+    "transcribe_provider": "local",  # local | openai | openrouter
     "transcribe_model": "gpt-4o-transcribe",           # used when provider is openai
     "openrouter_transcribe_model": "openai/gpt-4o-transcribe",
     "language": "tr",
     "transcribe_prompt": "",
+
+    # --- whisper.cpp, on this machine ---------------------------------------
+    # The program and the model are both fetched from Settings; empty means
+    # nothing has been downloaded yet, which is what opens Settings on a first
+    # run.
+    # Pointed at the suggestion rather than at nothing, so the settings window
+    # opens with the Download button already on the right model.
+    "local_model": ggml.SUGGESTED_WHISPER,
+    "local_threads": 0,             # 0 -> whisper.cpp picks
+    "local_gpu": True,
+    "local_preload": True,          # load the model while Dikte starts, rather
+                                    # than on the first dictation
+    "local_binary": "",             # empty -> whichever copy ggml.py finds
+
     "cleanup_enabled": True,
+    "cleanup_provider": "openrouter",   # openrouter | local
     "cleanup_model": "google/gemini-3.5-flash-lite",
     "cleanup_reasoning": "",        # empty -> whatever the model does by default
+
+    # --- llama.cpp, on this machine -----------------------------------------
+    # Kept apart from the meeting settings on purpose. Cleanup is punctuation
+    # and filler words, which a small model does in a moment; the minutes are a
+    # summary of an hour, which it does not.
+    "local_llm_model": "",          # a file name, e.g. gemma-3-4b-it-Q4_K_M.gguf
+    # Where the model list is read from; the settings window offers the
+    # publishers ggml.py knows of and takes any other one that is typed in.
+    "local_llm_repo": ggml.SUGGESTED_LLM[0],
+    "local_llm_threads": 0,
+    "local_llm_gpu": True,
+    "local_llm_context": 8192,
+    "local_llm_binary": "",
+    "local_llm_preload": False,     # heavier than whisper, so only when asked
+    # Off rather than empty: a model trained to think will, and 300 tokens of
+    # reasoning about a comma is 300 tokens of waiting.
+    "local_llm_reasoning": "none",
     "cleanup_prompt": "",           # empty -> language-specific default
     "auto_paste": True,
     "paste_shortcut": "ctrl+v",
@@ -400,6 +434,7 @@ DEFAULTS = {
     "meeting_language": "",         # empty -> the dictation speech language
     "meeting_max_seconds": 14400,   # 4 hours
     "meeting_cleanup": True,
+    "meeting_provider": "openrouter",   # openrouter | local
     "meeting_model": "google/gemini-3.5-flash",
     "meeting_reasoning": "",
     "meeting_prompt": "",           # empty -> language-specific default
@@ -495,14 +530,84 @@ class Config:
         return self["openrouter_api_key"].strip() or os.environ.get("OPENROUTER_API_KEY", "").strip()
 
     def transcribe_target(self):
-        """Key, endpoint and model for whichever provider does speech to text."""
+        """Key, endpoint and model for whichever provider does speech to text.
-        if self["transcribe_provider"] == "openrouter":
+
+        The local one leaves its base URL empty on purpose: the server picks a
+        port when it starts, and starting it here would make reading a setting
+        launch a process. api.py fills the address in when it is about to send
+        the request, which is the moment the server is needed anyway.
+        """
+        provider = self["transcribe_provider"]
+        if provider == "local":
+            return api.Target("local", t("Local whisper"), "", "",
+                              self["local_model"])
+        if provider == "openrouter":
             return api.Target("openrouter", "OpenRouter", self.openrouter_key(),
                               self["openrouter_base_url"],
                               self["openrouter_transcribe_model"])
         return api.Target("openai", "OpenAI", self.openai_key(),
                           self["openai_base_url"], self["transcribe_model"])
 
+    def cleanup_target(self):
+        """The same, for the model that tidies a transcript up."""
+        if self["cleanup_provider"] == "local":
+            return api.Target("local-llm", t("Local model"), "", "",
+                              self["local_llm_model"], self["local_llm_reasoning"])
+        return api.Target("openrouter", "OpenRouter", self.openrouter_key(),
+                          self["openrouter_base_url"], self["cleanup_model"],
+                          self["cleanup_reasoning"])
+
+    def minutes_target(self):
+        """The same again, for the minutes.
+
+        Its own provider rather than the cleanup one. The two jobs are not the
+        same size: a 4B model on this machine will strip the filler words out of
+        a dictation perfectly well and will not write up an hour long meeting,
+        so choosing it for the first must not quietly choose it for the second.
+        """
+        if self["meeting_provider"] == "local":
+            return api.Target("local-llm", t("Local model"), "", "",
+                              self["local_llm_model"], self["local_llm_reasoning"])
+        return api.Target("openrouter", "OpenRouter", self.openrouter_key(),
+                          self["openrouter_base_url"], self["meeting_model"],
+                          self["meeting_reasoning"])
+
+    def transcribe_ready(self):
+        """Whether speech to text could run right now, without opening Settings."""
+        if self["transcribe_provider"] == "local":
+            return self.local_whisper_ready()
+        return bool(self.transcribe_target().api_key)
+
+    def local_whisper_ready(self):
+        return bool(ggml.program_path(ggml.WHISPER, self["local_binary"])
+                    and self["local_model"]
+                    and ggml.have_model(ggml.whisper_model_path(self["local_model"])))
+
+    def local_llm_ready(self):
+        return bool(ggml.program_path(ggml.LLAMA, self["local_llm_binary"])
+                    and self["local_llm_model"]
+                    and ggml.have_model(ggml.llm_model_path(self["local_llm_model"])))
+
+    def apply_local(self):
+        """Hand the local settings to the servers, restarting what they change."""
+        ggml.whisper.configure(
+            model=self["local_model"],
+            threads=int(self["local_threads"]),
+            gpu=bool(self["local_gpu"]),
+            binary=self["local_binary"],
+        )
+        ggml.llm.configure(
+            model=self["local_llm_model"],
+            threads=int(self["local_llm_threads"]),
+            gpu=bool(self["local_llm_gpu"]),
+            binary=self["local_llm_binary"],
+            context=int(self["local_llm_context"]),
+        )
+
+    def uses_local_llm(self):
+        """Whether anything is set to run the local cleanup model."""
+        return "local" in (self["cleanup_provider"], self["meeting_provider"])
+
     def cleanup_prompt(self, with_timestamps=False, with_speakers=False,
                        subtitles=False):
         turkish = i18n.language() == "tr"

dikte.py

@@ -7,16 +7,20 @@ terminal talks to. Every verb it answers is in cli.py, which is also what runs
 command line says "there is no instance to talk to, so be one".
 """
 
+import contextlib
 import json
 import os
+import signal
+import socket
 import sys
+import threading
 
 # A Wayland client cannot place a window in a screen corner, so the indicator
 # is drawn through XWayland.
 if os.environ.get("XDG_SESSION_TYPE") == "wayland" and os.environ.get("DISPLAY"):
     os.environ.setdefault("QT_QPA_PLATFORM", "xcb")
 
-from PyQt6.QtCore import QTimer, QElapsedTimer  # noqa: E402
+from PyQt6.QtCore import QTimer, QElapsedTimer, QSocketNotifier  # noqa: E402
 from PyQt6.QtGui import QAction, QIcon  # noqa: E402
 from PyQt6.QtNetwork import QLocalServer, QLocalSocket  # noqa: E402
 from PyQt6.QtWidgets import QApplication, QMenu, QSystemTrayIcon  # noqa: E402
@@ -25,6 +29,7 @@ import assistant  # noqa: E402
 import audio  # noqa: E402
 import cli  # noqa: E402
 import config as cfg  # noqa: E402
+import ggml  # noqa: E402
 import hotkey  # noqa: E402
 import i18n  # noqa: E402
 import ipc  # noqa: E402
@@ -92,6 +97,9 @@ class Dikte:
         self.meeting_recorder = audio.MeetingRecorder()
         self.meetings = MeetingPipeline(self.conf)
         self.evdev = hotkey.EvdevHotkey()
+        # Before anything of ours is started: a server from a Dikte that was
+        # killed outright is still holding a model in memory.
+        ggml.sweep()
 
         self.recorder.level.connect(self._on_level)
         self.recorder.stopped.connect(self._on_recorded)
@@ -802,9 +810,44 @@ class Dikte:
         # Don't drop the object while its own signal is still being delivered.
         QTimer.singleShot(0, lambda: setattr(self, "settings_window", None))
 
+    def _apply_local(self):
+        """Pass the local settings on, and hold the models ready if asked to.
+
+        Loading a model takes a second or two for whisper and longer for an LLM.
+        Doing it while Dikte starts rather than on the first dictation is the
+        whole reason a server is kept alive instead of running the program once
+        per recording; the checkboxes are there for the machine whose memory is
+        wanted elsewhere.
+        """
+        self.conf.apply_local()
+        wanted = []
+        if self.conf["transcribe_provider"] == "local":
+            if self.conf["local_preload"] and self.conf.local_whisper_ready():
+                wanted.append((ggml.whisper, "whisper"))
+        else:
+            ggml.whisper.stop()      # give the memory back when it is not in use
+        if self.conf.uses_local_llm():
+            if self.conf["local_llm_preload"] and self.conf.local_llm_ready():
+                wanted.append((ggml.llm, "llama"))
+        else:
+            ggml.llm.stop()
+
+        def warm():
+            for server, name in wanted:
+                try:
+                    server.serve()
+                except ggml.LocalError as exc:
+                    # Not worth an indicator: the first dictation raises the
+                    # same thing where the user can act on it.
+                    print(f"dikte: {name}: {exc}", file=sys.stderr)
+
+        if wanted:
+            threading.Thread(target=warm, daemon=True).start()
+
     def _apply_settings(self):
         self.overlay.corner = self.conf["overlay_corner"]
         self.ask_overlay.corner = self.conf["overlay_corner"]
+        self._apply_local()
         self._build_tray()
         self._refresh_tray()
         if self.conf["evdev_hotkey"]:
@@ -834,6 +877,9 @@ class Dikte:
             self.meeting_recorder.stop()
         self.overlay.dismiss()
         self.ask_overlay.dismiss()
+        # Also on the restart path, which replaces the process without ever
+        # reaching atexit and would otherwise leave the models in memory.
+        ggml.stop_all()
         self.tray.hide()
 
 
@@ -872,6 +918,41 @@ def main():
     return run_app([arg for arg in argv if arg != "--gui"])
 
 
+def install_signal_handlers(app):
+    """Quit properly on the signals a session sends, rather than dying where we stand.
+
+    Qt spends its time blocked inside C, and a Python signal handler only runs
+    between bytecodes, so on its own it would not run until the next event
+    arrived, which for an idle tray icon may be never. set_wakeup_fd writes the
+    signal number to a socket instead, and a notifier turns that into an event
+    Qt does deliver.
+
+    Worth the trouble because of what shutdown() does: a logout sends SIGTERM,
+    and without this a whisper.cpp or llama.cpp server outlives the session
+    holding its model in memory. SIGKILL cannot be caught at all, which is what
+    ggml.sweep() is for.
+
+    Returns the objects it made; they have to stay alive to keep working.
+    """
+    reader, writer = socket.socketpair()
+    reader.setblocking(False)
+    writer.setblocking(False)
+    signal.set_wakeup_fd(writer.fileno())
+    notifier = QSocketNotifier(reader.fileno(), QSocketNotifier.Type.Read)
+
+    def woken():
+        with contextlib.suppress(OSError):
+            reader.recv(64)
+        app.quit()          # aboutToQuit runs shutdown()
+
+    notifier.activated.connect(woken)
+    for sig in (signal.SIGINT, signal.SIGTERM, signal.SIGHUP):
+        # A handler that does nothing, so that the default action, stopping the
+        # process where it stands, is replaced by the wakeup above.
+        signal.signal(sig, lambda *_: None)
+    return reader, writer, notifier
+
+
 def run_app(args):
     command = args[0] if args else ""
 
@@ -879,6 +960,12 @@ def run_app(args):
     app.setApplicationName("Dikte")
     app.setDesktopFileName("dikte")
     app.setQuitOnLastWindowClosed(False)
+    # Before Dikte is built, because building it is what may start a server, and
+    # a signal arriving in the middle of that would otherwise take the default
+    # action and leave the server behind. A signal this early lands in the
+    # socket and is delivered as soon as the event loop starts. Held in a name
+    # so that the notifier and its socket outlive this function.
+    signal_plumbing = install_signal_handlers(app)  # noqa: F841
 
     if not QSystemTrayIcon.isSystemTrayAvailable():
         print("dikte: no system tray found, running anyway")
@@ -927,7 +1014,10 @@ def run_app(args):
 
     # No key for the chosen transcription provider means nothing can work yet,
     # so the settings window is the only useful thing to open.
-    if command == "settings" or not dikte.conf.transcribe_target().api_key:
+    # A transcription provider that cannot run yet, whether that is a missing
+    # API key or a model nobody has downloaded, means nothing can work, so the
+    # settings window is the only useful thing to open.
+    if command == "settings" or not dikte.conf.transcribe_ready():
         dikte.open_settings()
     elif command == "toggle":
         QTimer.singleShot(0, dikte.toggle)

filetranscribe.py

@@ -127,17 +127,11 @@ class FileTranscriber(QObject):
     def _cleanup(self, text, timestamps):
         conf = self.conf
         prompt = conf.cleanup_prompt(with_timestamps=timestamps, subtitles=True)
+        target = conf.cleanup_target()
         out = []
         for block in split_text(text, timestamps):
             self._check()
-            out.append(api.cleanup(
+            out.append(api.cleanup(target, block, prompt))
-                block,
-                conf.openrouter_key(),
-                conf["cleanup_model"],
-                prompt,
-                reasoning=conf["cleanup_reasoning"],
-                base_url=conf["openrouter_base_url"],
-            ))
         return ("\n" if timestamps else "\n\n").join(out)
 
 

install.sh

@@ -116,5 +116,6 @@ fi
 
 echo
 ok "Done. Start it with:  dikte"
-say "The settings window opens on first run; add an OpenAI, Groq or OpenRouter key."
+say "The settings window opens on first run: download a speech model, or add"
+say "an OpenAI or OpenRouter key instead."
 echo

meeting.py

@@ -118,18 +118,12 @@ class MeetingPipeline(QObject):
 
             self._check()
             self._say(t("Writing the minutes…"))
-            minutes = api.cleanup(
+            writer = self.conf.minutes_target()
-                transcript,
+            minutes = api.cleanup(writer, transcript, self.conf.meeting_prompt(),
-                self.conf.openrouter_key(),
+                                  timeout=600)
-                self.conf["meeting_model"],
-                self.conf.meeting_prompt(),
-                reasoning=self.conf["meeting_reasoning"],
-                base_url=self.conf["openrouter_base_url"],
-                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(
+            out.append(api.cleanup(target, block, prompt))
-                block,
-                conf.openrouter_key(),
-                conf["cleanup_model"],
-                prompt,
-                reasoning=conf["cleanup_reasoning"],
-                base_url=conf["openrouter_base_url"],
-            ))
         return "\n".join(out)
 
     def _write(self, doc_path, minutes, transcript, entry):

settings_ui.py

@@ -18,6 +18,7 @@ import assistant
 import audio
 import config as cfg
 import filetranscribe
+import ggml
 import hotkey
 import meeting
 from filetranscribe import FileTranscriber
@@ -29,7 +30,10 @@ LANGUAGES = [
     ("German", "de"), ("French", "fr"), ("Spanish", "es"), ("Arabic", "ar"),
 ]
 CORNERS = ["bottom-left", "bottom-right", "top-left", "top-right"]
-TRANSCRIBE_PROVIDERS = [("OpenAI", "openai"), ("OpenRouter", "openrouter")]
+TRANSCRIBE_PROVIDERS = [("This machine (whisper.cpp)", "local"),
+                        ("OpenAI", "openai"), ("OpenRouter", "openrouter")]
+CLEANUP_PROVIDERS = [("OpenRouter", "openrouter"),
+                     ("This machine (llama.cpp)", "local")]
 # Starting points for the model box; "Fetch model list" replaces them with
 # whatever the provider offers today.
 TRANSCRIBE_MODELS = {
@@ -103,6 +107,316 @@ AUDIO_FILTER = ("*.mp3 *.wav *.m4a *.ogg *.opus *.flac *.aac *.wma "
                 "*.mp4 *.mkv *.webm *.mov *.avi")
 
 
+class LocalModelBox(QGroupBox):
+    """The program, the model, and the two downloads that put them there.
+
+    One class for whisper.cpp and llama.cpp, because the job is the same one
+    twice: say whether the program is here, offer the models somebody publishes,
+    fetch the chosen one, and stay usable while a gigabyte arrives. Nothing is
+    listed in the source; `repos` and `models` are asked at the moment the box is
+    opened, so a model published this morning is in the list this afternoon.
+    """
+
+    _listed = pyqtSignal(list, str)
+    _quants = pyqtSignal(list, str)
+    _progress = pyqtSignal(int, int)
+    _finished = pyqtSignal(str, str)
+    _installed = pyqtSignal(str, str)
+
+    changed = pyqtSignal()
+
+    def __init__(self, program, title, models, model_path, repos=None, parent=None):
+        super().__init__(title, parent)
+        self.program = program
+        self._models = models          # () -> [hub.Item], or (repo) -> [hub.Item]
+        self._model_path = model_path  # (name) -> Path
+        self._repos = repos            # None, or () -> [repo id]
+        self._downloading = False
+        self._pending = False
+        self._stop = False
+        self._wanted = ""              # the model to select once a list arrives
+
+        form = QFormLayout(self)
+
+        self.program_label = QLabel("")
+        self.program_label.setWordWrap(True)
+        self.install_button = QPushButton(t("Download"))
+        self.install_button.clicked.connect(self._install_program)
+        form.addRow(t("Program"), self._side_by_side(self.program_label,
+                                                     self.install_button))
+
+        if self._repos is not None:
+            self.repo = QComboBox()
+            self.repo.setEditable(True)
+            self.repo.setToolTip(t("A Hugging Face repository of GGUF files. The "
+                                   "list is fetched; any other one can be typed in."))
+            self.repo.currentTextChanged.connect(self._repo_changed)
+            form.addRow(t("Publisher"), self.repo)
+
+        self.model = QComboBox()
+        self.download_button = QPushButton(t("Download"))
+        self.download_button.clicked.connect(self._download)
+        self.delete_button = QPushButton(t("Delete"))
+        self.delete_button.clicked.connect(self._delete)
+        form.addRow(t("Model"), self._side_by_side(self.model,
+                                                   self.download_button,
+                                                   self.delete_button))
+        self.model.currentIndexChanged.connect(self._model_changed)
+
+        self.status = QLabel("")
+        self.status.setWordWrap(True)
+        form.addRow(self.status)
+
+        self._listed.connect(self._on_listed)
+        self._quants.connect(self._on_listed)
+        self._progress.connect(self._on_progress)
+        self._finished.connect(self._on_finished)
+        self._installed.connect(self._on_installed)
+
+    @staticmethod
+    def _side_by_side(*widgets):
+        layout = QHBoxLayout()
+        layout.setContentsMargins(0, 0, 0, 0)
+        for index, widget in enumerate(widgets):
+            layout.addWidget(widget, 1 if index == 0 else 0)
+        holder = QWidget()
+        holder.setLayout(layout)
+        return holder
+
+    # ---- what is here ----------------------------------------------------
+
+    def selected(self):
+        return self.model.currentData() or ""
+
+    def repository(self):
+        return self.repo.currentText().strip() if self._repos is not None else ""
+
+    def load(self, model, repo=""):
+        """Show what is stored. What else is on offer is asked for on the way up.
+
+        Nothing is fetched here: building the settings window is not the same as
+        opening it, and a list nobody is looking at is not worth a request. What
+        is already on this disk is shown straight away either way.
+        """
+        self._wanted = model
+        self._pending = True
+        self._show_program()
+        if self._repos is not None:
+            self.repo.blockSignals(True)
+            self.repo.clear()
+            self.repo.addItems(list(ggml.SUGGESTED_LLM))
+            self.repo.setCurrentText(repo or ggml.SUGGESTED_LLM[0])
+            self.repo.blockSignals(False)
+        self._fill_models([])
+
+    def showEvent(self, event):
+        super().showEvent(event)
+        if self._pending:
+            self._pending = False
+            if self._repos is not None:
+                self._fill_repos(self.repository())
+            self._fetch_models(self.repository())
+
+    def _show_program(self):
+        path = ggml.program_path(self.program)
+        if not path:
+            self.program_label.setText(t("Not installed."))
+            self.install_button.setVisible(True)
+            return
+        self.install_button.setVisible(not ggml.installed_program(self.program)
+                                       and not ggml.system_program(self.program))
+        if ggml.system_program(self.program):
+            # Worth saying which one is running: a distribution package is built
+            # for this machine and may reach the graphics card, while the
+            # released binaries carry processor backends only.
+            self.program_label.setText(t("Installed on the system: {path}", path=path))
+        else:
+            self.program_label.setText(
+                t("Downloaded, version {version}.",
+                  version=ggml.installed_version(self.program) or "?"))
+
+    # ---- the lists -------------------------------------------------------
+
+    def _fill_repos(self, current):
+        def work():
+            self._listed.emit([("repos", ggml.llm_repos())], "")
+
+        threading.Thread(target=work, daemon=True).start()
+
+    def _repo_changed(self):
+        if not self._downloading:
+            self._fetch_models(self.repository())
+
+    def _fetch_models(self, repo=""):
+        self.status.setText(t("Fetching the model list…"))
+
+        def work():
+            try:
+                found = self._models(repo) if self._repos is not None else self._models()
+                self._quants.emit([("models", found)], "")
+            except ggml.LocalError as exc:
+                self._quants.emit([], str(exc))
+
+        threading.Thread(target=work, daemon=True).start()
+
+    def _on_listed(self, payload, error):
+        if error:
+            self.status.setText(error)
+            self._refresh_buttons()
+            return
+        kind, found = payload[0]
+        if kind == "repos":
+            current = self.repo.currentText()
+            self.repo.blockSignals(True)
+            self.repo.clear()
+            self.repo.addItems(found)
+            self.repo.setCurrentText(current)
+            self.repo.blockSignals(False)
+            return
+        self._fill_models(found)
+
+    def _fill_models(self, items):
+        """One row per model, saying what it weighs and whether it is here."""
+        wanted = self._wanted or self.selected()
+        here = [name for name in (self._model_path(i.name).name for i in items)]
+        self.model.blockSignals(True)
+        self.model.clear()
+        for item, name in zip(items, here):
+            mark = (t("downloaded") if ggml.have_model(self._model_path(item.name))
+                    else ggml.human_size(item.size))
+            self.model.addItem(f"{name}  ({mark})", name)
+            self.model.setItemData(self.model.count() - 1, item, Qt.ItemDataRole.UserRole + 1)
+        # A model that was downloaded and then dropped from the list upstream is
+        # still on this disk and still works, so it stays on offer.
+        for name in self._on_disk():
+            if self.model.findData(name) < 0:
+                self.model.addItem(f"{name}  ({t('downloaded')})", name)
+        # And one that is chosen but not here, because the file was deleted from
+        # underneath or the settings came from another machine, stays chosen:
+        # Save reads this box, and a row missing here would quietly empty the
+        # setting rather than showing that the model needs downloading again.
+        if wanted and self.model.findData(wanted) < 0:
+            self.model.addItem(f"{wanted}  ({t('not downloaded')})", wanted)
+        index = self.model.findData(wanted)
+        self.model.setCurrentIndex(max(index, 0))
+        self.model.blockSignals(False)
+        self._wanted = ""
+        self._model_changed()
+
+    def _on_disk(self):
+        return (ggml.installed_whisper_models() if self.program is ggml.WHISPER
+                else ggml.installed_llm_models())
+
+    # ---- fetching --------------------------------------------------------
+
+    def _install_program(self):
+        self.install_button.setEnabled(False)
+        self.program_label.setText(t("Downloading…"))
+
+        def work():
+            try:
+                ggml.install_program(self.program, on_progress=self._report)
+                self._installed.emit("", "")
+            except ggml.LocalError as exc:
+                self._installed.emit("", str(exc))
+
+        threading.Thread(target=work, daemon=True).start()
+
+    def _on_installed(self, _, error):
+        self.install_button.setEnabled(True)
+        self._show_program()
+        if error:
+            self.program_label.setText(error)
+        self.changed.emit()
+
+    def _current_item(self):
+        return self.model.currentData(Qt.ItemDataRole.UserRole + 1)
+
+    def _download(self):
+        if self._downloading:
+            self._stop = True
+            return
+        item = self._current_item()
+        if item is None:
+            return
+        self._downloading, self._stop = True, False
+        self._refresh_buttons()
+
+        def work():
+            try:
+                landed = ggml.download(item, self._model_path(item.name),
+                                       on_progress=self._report,
+                                       should_stop=lambda: self._stop)
+                self._finished.emit(item.name if landed else "", "")
+            except ggml.LocalError as exc:
+                self._finished.emit("", str(exc))
+
+        threading.Thread(target=work, daemon=True).start()
+
+    def _report(self, done, total):
+        self._progress.emit(done, total)
+
+    def _on_progress(self, done, total):
+        share = f" ({done * 100 // total}%)" if total else ""
+        text = t("Downloading: {done} of {total}{share}",
+                 done=ggml.human_size(done), total=ggml.human_size(total or done),
+                 share=share)
+        if self._downloading:
+            self.status.setText(text)
+        else:
+            self.program_label.setText(text)
+
+    def _on_finished(self, name, error):
+        self._downloading = False
+        if error:
+            self.status.setText(error)
+        elif not name:
+            self.status.setText(t("Download stopped."))
+        self._fill_models_from_current()
+        self.changed.emit()
+
+    def _fill_models_from_current(self):
+        """Redraw the rows without asking anybody anything again."""
+        items = [self.model.itemData(i, Qt.ItemDataRole.UserRole + 1)
+                 for i in range(self.model.count())]
+        self._wanted = self.selected()
+        self._fill_models([i for i in items if i is not None])
+
+    def _delete(self):
+        name = self.selected()
+        if not name or not ggml.have_model(self._model_path(name)):
+            return
+        if QMessageBox.question(self, t("Delete model"),
+                                t("Delete {name} from this machine?", name=name)) \
+                != QMessageBox.StandardButton.Yes:
+            return
+        try:
+            ggml.delete_model(self._model_path(name))
+        except ggml.LocalError as exc:
+            self.status.setText(str(exc))
+        self._fill_models_from_current()
+        self.changed.emit()
+
+    def _model_changed(self):
+        self._refresh_buttons()
+        self.changed.emit()
+
+    def _refresh_buttons(self):
+        name = self.selected()
+        here = bool(name) and ggml.have_model(self._model_path(name))
+        self.delete_button.setEnabled(here and not self._downloading)
+        self.download_button.setText(t("Stop") if self._downloading else t("Download"))
+        self.download_button.setEnabled(self._downloading or (bool(name) and not here))
+        if self._downloading:
+            return
+        if not name:
+            self.status.setText(t("Nothing downloaded yet."))
+        elif here:
+            self.status.setText(t("Ready: {name}.", name=name))
+        else:
+            self.status.setText(t("{name} has not been downloaded yet.", name=name))
+
+
 class SettingsWindow(QDialog):
     applied = pyqtSignal()
 
@@ -127,9 +441,9 @@ class SettingsWindow(QDialog):
         self.setWindowTitle(t("Dikte Settings"))
         self.resize(680, 640)
 
-        tabs = QTabWidget(self)
+        tabs = self.tabs = QTabWidget(self)
         tabs.addTab(self._general_tab(), t("General"))
-        tabs.addTab(self._api_tab(), t("API and models"))
+        self.api_tab_index = tabs.addTab(self._api_tab(), t("API and models"))
         tabs.addTab(self._prompt_tab(), t("Cleanup rules"))
         tabs.addTab(self._assistant_tab(), t("Agent"))
         tabs.addTab(self._meeting_tab(), t("Meeting"))
@@ -161,6 +475,10 @@ class SettingsWindow(QDialog):
             self.meetings.finished.connect(self._on_minutes_finished)
             self.meetings.failed.connect(self._on_minutes_failed)
         self._load()
+        # On a machine where nothing can transcribe yet, this window was opened
+        # because of that, so open it on the tab that fixes it.
+        if not conf.transcribe_ready():
+            self.tabs.setCurrentIndex(self.api_tab_index)
 
     # ---- tabs ----------------------------------------------------------
 
@@ -269,20 +587,55 @@ class SettingsWindow(QDialog):
         stt_form = QFormLayout(stt)
         self.transcribe_provider = QComboBox()
         for label, value in TRANSCRIBE_PROVIDERS:
-            self.transcribe_provider.addItem(label, value)
+            self.transcribe_provider.addItem(t(label), value)
         stt_form.addRow(t("Provider"), self.transcribe_provider)
 
+        # The hosted providers take any model id that is typed at them; the
+        # local one offers what has been published, so the two are separate
+        # blocks and only one of them is ever visible.
+        self.hosted_stt = QWidget()
+        hosted_form = QFormLayout(self.hosted_stt)
+        hosted_form.setContentsMargins(0, 0, 0, 0)
         self.transcribe_model = QComboBox()
         self.transcribe_model.setEditable(True)
         self.refresh_transcribe_models = QPushButton(t("Fetch model list"))
         self.refresh_transcribe_models.clicked.connect(self._load_transcribe_models)
-        stt_form.addRow(t("Model"),
+        hosted_form.addRow(t("Model"),
-                        self._row(self.transcribe_model, self.refresh_transcribe_models))
+                           self._row(self.transcribe_model,
+                                     self.refresh_transcribe_models))
         # A spanning row: in the narrow field column a wrapped label gets a
         # height that fits one line, and the rest of the text is cut off.
         self.transcribe_status = QLabel("")
         self.transcribe_status.setWordWrap(True)
-        stt_form.addRow(self.transcribe_status)
+        hosted_form.addRow(self.transcribe_status)
+        stt_form.addRow(self.hosted_stt)
+
+        self.local_whisper = LocalModelBox(
+            ggml.WHISPER, t("On this machine"),
+            ggml.whisper_models, ggml.whisper_model_path)
+        stt_form.addRow(self.local_whisper)
+
+        self.local_gpu = QCheckBox(t("Use the graphics card"))
+        self.local_gpu.setToolTip(
+            t("whisper.cpp reaches the card through CUDA, ROCm or Vulkan when the "
+              "build it is running was made with one. A build without any of them "
+              "runs on the processor whatever this says."))
+        self.local_preload = QCheckBox(t("Load the model when Dikte starts"))
+        self.local_preload.setToolTip(
+            t("A large model takes a second or two to load. Loading it up front "
+              "spends that once instead of on the first dictation, at the cost of "
+              "the memory it sits in."))
+        self.local_threads = QSpinBox()
+        self.local_threads.setRange(0, 64)
+        self.local_threads.setSpecialValueText(t("Automatic"))
+        self.local_options = QWidget()
+        options_form = QFormLayout(self.local_options)
+        options_form.setContentsMargins(0, 0, 0, 0)
+        options_form.addRow("", self.local_gpu)
+        options_form.addRow("", self.local_preload)
+        options_form.addRow(t("Threads"), self.local_threads)
+        stt_form.addRow(self.local_options)
+
         self.transcribe_provider.currentIndexChanged.connect(self._provider_changed)
         outer.addWidget(stt)
 
@@ -291,12 +644,22 @@ class SettingsWindow(QDialog):
         self.cleanup_enabled = QCheckBox(t("Clean the transcript with a model"))
         orr_form.addRow("", self.cleanup_enabled)
 
+        self.cleanup_provider = QComboBox()
+        for label, value in CLEANUP_PROVIDERS:
+            self.cleanup_provider.addItem(t(label), value)
+        self.cleanup_provider.currentIndexChanged.connect(self._cleanup_provider_changed)
+        orr_form.addRow(t("Provider"), self.cleanup_provider)
+
+        self.hosted_cleanup = QWidget()
+        cleanup_form = QFormLayout(self.hosted_cleanup)
+        cleanup_form.setContentsMargins(0, 0, 0, 0)
         self.cleanup_model = QComboBox()
         self.cleanup_model.setEditable(True)
         self.cleanup_model.addItems(CLEANUP_MODELS)
         self.refresh_models = QPushButton(t("Fetch model list"))
         self.refresh_models.clicked.connect(self._load_models)
-        orr_form.addRow(t("Model"), self._row(self.cleanup_model, self.refresh_models))
+        cleanup_form.addRow(t("Model"), self._row(self.cleanup_model,
+                                                  self.refresh_models))
 
         self.cleanup_reasoning = QComboBox()
         for label, value in REASONING_LEVELS:
@@ -306,11 +669,38 @@ class SettingsWindow(QDialog):
               "a light job, so more thinking mostly costs time and tokens. Models "
               "that cannot think ignore this.")
         )
-        orr_form.addRow(t("Thinking"), self.cleanup_reasoning)
+        cleanup_form.addRow(t("Thinking"), self.cleanup_reasoning)
 
         self.models_label = QLabel(t("Runs on OpenRouter."))
         self.models_label.setWordWrap(True)
-        orr_form.addRow(self.models_label)
+        cleanup_form.addRow(self.models_label)
+        orr_form.addRow(self.hosted_cleanup)
+
+        self.local_llm = LocalModelBox(
+            ggml.LLAMA, t("On this machine"),
+            ggml.llm_quants, ggml.llm_model_path, repos=ggml.llm_repos)
+        orr_form.addRow(self.local_llm)
+
+        self.local_llm_gpu = QCheckBox(t("Use the graphics card"))
+        self.local_llm_preload = QCheckBox(t("Load the model when Dikte starts"))
+        self.local_llm_preload.setToolTip(
+            t("An LLM is slower to load than a whisper model and sits in more "
+              "memory. Off means it is loaded on the first cleanup instead."))
+        self.local_llm_reasoning = QComboBox()
+        for label, value in REASONING_LEVELS:
+            self.local_llm_reasoning.addItem(t(label), value)
+        self.local_llm_reasoning.setToolTip(
+            t("A model trained to think will think unless it is told not to, and "
+              "spending 300 tokens of reasoning on a comma is 300 tokens of "
+              "waiting. Off is what cleanup wants."))
+        self.local_llm_options = QWidget()
+        llm_form = QFormLayout(self.local_llm_options)
+        llm_form.setContentsMargins(0, 0, 0, 0)
+        llm_form.addRow("", self.local_llm_gpu)
+        llm_form.addRow("", self.local_llm_preload)
+        llm_form.addRow(t("Thinking"), self.local_llm_reasoning)
+        orr_form.addRow(self.local_llm_options)
+
         outer.addWidget(orr)
         outer.addStretch(1)
         return page
@@ -926,9 +1316,20 @@ class SettingsWindow(QDialog):
         self._shown_provider = ""
         self._select_data(self.transcribe_provider, conf["transcribe_provider"])
         self._provider_changed()  # selecting index 0 fires no signal
+        self.local_gpu.setChecked(conf["local_gpu"])
+        self.local_preload.setChecked(conf["local_preload"])
+        self.local_threads.setValue(int(conf["local_threads"]))
+        self.local_whisper.load(conf["local_model"])
+
         self.cleanup_enabled.setChecked(conf["cleanup_enabled"])
+        self._select_data(self.cleanup_provider, conf["cleanup_provider"])
+        self._cleanup_provider_changed()
         self.cleanup_model.setCurrentText(conf["cleanup_model"])
         self._select_data(self.cleanup_reasoning, conf["cleanup_reasoning"])
+        self.local_llm_gpu.setChecked(conf["local_llm_gpu"])
+        self.local_llm_preload.setChecked(conf["local_llm_preload"])
+        self._select_data(self.local_llm_reasoning, conf["local_llm_reasoning"])
+        self.local_llm.load(conf["local_llm_model"], conf["local_llm_repo"])
         self.cleanup_prompt.setPlainText(conf["cleanup_prompt"] or cfg.default_cleanup_prompt())
         self.file_cleanup_prompt.setPlainText(
             conf["file_cleanup_prompt"] or cfg.default_file_cleanup_prompt()
@@ -1003,16 +1404,27 @@ class SettingsWindow(QDialog):
         conf["openai_api_key"] = self.openai_key.text().strip()
         conf["openrouter_api_key"] = self.openrouter_key.text().strip()
 
-        provider = self.transcribe_provider.currentData() or "openai"
+        provider = self.transcribe_provider.currentData() or "local"
+        if provider in TRANSCRIBE_MODELS:
             self._models[provider] = self.transcribe_model.currentText().strip()
         conf["transcribe_provider"] = provider
         for key, name in (("openai", "transcribe_model"),
                           ("openrouter", "openrouter_transcribe_model")):
             conf[name] = self._models[key].strip() or cfg.DEFAULTS[name]
+        conf["local_model"] = self.local_whisper.selected()
+        conf["local_gpu"] = self.local_gpu.isChecked()
+        conf["local_preload"] = self.local_preload.isChecked()
+        conf["local_threads"] = self.local_threads.value()
 
         conf["cleanup_enabled"] = self.cleanup_enabled.isChecked()
+        conf["cleanup_provider"] = self.cleanup_provider.currentData() or "openrouter"
         conf["cleanup_model"] = self.cleanup_model.currentText().strip()
         conf["cleanup_reasoning"] = self.cleanup_reasoning.currentData() or ""
+        conf["local_llm_model"] = self.local_llm.selected()
+        conf["local_llm_repo"] = self.local_llm.repository()
+        conf["local_llm_gpu"] = self.local_llm_gpu.isChecked()
+        conf["local_llm_preload"] = self.local_llm_preload.isChecked()
+        conf["local_llm_reasoning"] = self.local_llm_reasoning.currentData() or ""
 
         # Store an empty prompt when it matches the default, so switching the
         # interface language also switches the prompt language.
@@ -1093,15 +1505,27 @@ class SettingsWindow(QDialog):
 
     def _provider_changed(self):
         """Swap the model box over to the newly chosen provider's own model."""
-        if self._shown_provider:
+        if self._shown_provider in TRANSCRIBE_MODELS:
             self._models[self._shown_provider] = self.transcribe_model.currentText().strip()
-        provider = self.transcribe_provider.currentData() or "openai"
+        provider = self.transcribe_provider.currentData() or "local"
         self._shown_provider = provider
+        local = provider == "local"
+        self.hosted_stt.setVisible(not local)
+        self.local_whisper.setVisible(local)
+        self.local_options.setVisible(local)
+        if local:
+            return
         self.transcribe_model.clear()
         self.transcribe_model.addItems(TRANSCRIBE_MODELS[provider])
         self.transcribe_model.setCurrentText(self._models[provider])
         self.transcribe_status.setText("")
 
+    def _cleanup_provider_changed(self):
+        local = (self.cleanup_provider.currentData() or "openrouter") == "local"
+        self.hosted_cleanup.setVisible(not local)
+        self.local_llm.setVisible(local)
+        self.local_llm_options.setVisible(local)
+
     def _load_transcribe_models(self):
         """The model list of whichever provider is selected."""
         provider = self.transcribe_provider.currentData() or "openai"

tests/support.py

@@ -18,6 +18,7 @@ import sys
 import tempfile
 import unittest
 import urllib.error
+import urllib.request
 import wave
 from unittest import mock
 
@@ -40,6 +41,12 @@ linux_only = unittest.skipUnless(
 )
 
 
+def _no_network(*args, **kwargs):
+    raise AssertionError(
+        "a test reached the network; wrap the call in support.fake_urlopen"
+    )
+
+
 def _no_exec(*args, **kwargs):
     raise AssertionError(
         "a test reached os.execv, which would replace the test process with the "
@@ -78,6 +85,11 @@ class DikteTest(unittest.TestCase):
         # with it and hang, so it fails loudly here instead.
         self.patch_attr(os, "execv", _no_exec)
 
+        # Every way out of here goes through urllib, so closing it is enough to
+        # keep the suite offline. A test that means to answer a request patches
+        # this again through fake_urlopen.
+        self.patch_attr(urllib.request, "urlopen", _no_network)
+
     # ---- helpers ---------------------------------------------------------
 
     def path(self, *parts):

tests/test_api.py

@@ -10,6 +10,7 @@ import os
 import unittest
 
 import api
+import ggml
 from tests.support import (
     DikteTest,
     fake_urlopen,
@@ -27,10 +28,18 @@ OPENROUTER = api.Target("openrouter", "OpenRouter", "sk-or-test",
 
 class TimestampModel(unittest.TestCase):
     def test_only_whisper_returns_segment_times(self):
-        self.assertEqual(api.timestamp_model("openai"), "whisper-1")
+        self.assertEqual(api.timestamp_model("openai", "gpt-4o-transcribe"),
+                         "whisper-1")
 
     def test_openrouter_namespaces_the_id(self):
-        self.assertEqual(api.timestamp_model("openrouter"), "openai/whisper-1")
+        self.assertEqual(api.timestamp_model("openrouter", "openai/gpt-4o-transcribe"),
+                         "openai/whisper-1")
+
+    def test_the_local_server_stays_on_the_model_it_loaded(self):
+        # Asking it for whisper-1 would name a model it has never heard of, and
+        # it is running whisper whatever the file is called.
+        self.assertEqual(api.timestamp_model("local", "ggml-base.bin"),
+                         "ggml-base.bin")
 
 
 class Explain(DikteTest):
@@ -278,10 +287,15 @@ def chat_reply(content):
     return {"choices": [{"message": {"content": content}}]}
 
 
+def openrouter(model="some/model", key="sk-or-test", reasoning="",
+               base_url="https://openrouter.ai/api/v1"):
+    return api.Target("openrouter", "OpenRouter", key, base_url, model, reasoning)
+
+
 class Cleanup(DikteTest):
-    def call(self, replies, **kwargs):
+    def call(self, replies, target=None, **kwargs):
         with fake_urlopen(replies) as calls:
-            result = api.cleanup("uh, hello", "sk-or-test", "some/model",
+            result = api.cleanup(target or openrouter(), "uh, hello",
                                  "you clean up text", **kwargs)
         return result, calls
 
@@ -311,32 +325,34 @@ class Cleanup(DikteTest):
         self.assertNotIn("reasoning", sent_json(calls[0]))
 
     def test_an_effort_is_passed_on_and_the_thinking_left_out(self):
-        _, calls = self.call(chat_reply("Hello."), reasoning="high")
+        _, calls = self.call(chat_reply("Hello."),
+                             target=openrouter(reasoning="high"))
         self.assertEqual(sent_json(calls[0])["reasoning"],
                          {"effort": "high", "exclude": True})
 
     def test_a_local_base_url(self):
-        _, calls = self.call(chat_reply("Hello."), base_url="http://localhost:1234/v1")
+        _, calls = self.call(chat_reply("Hello."),
+                             target=openrouter(base_url="http://localhost:1234/v1"))
         self.assertEqual(calls[0].full_url, "http://localhost:1234/v1/chat/completions")
 
     def test_no_key(self):
         with self.assertRaises(api.ApiError):
-            api.cleanup("hello", "", "some/model", "prompt")
+            api.cleanup(openrouter(key=""), "hello", "prompt")
 
     def test_a_reply_with_no_choices_says_why(self):
         with fake_urlopen({"error": {"message": "model is offline"}}), \
                 self.assertRaises(api.ApiError) as caught:
-            api.cleanup("hello", "k", "m", "p")
+            api.cleanup(openrouter(), "hello", "p")
         self.assertIn("model is offline", str(caught.exception))
 
     def test_an_empty_answer(self):
         with fake_urlopen(chat_reply("   ")), self.assertRaises(api.ApiError):
-            api.cleanup("hello", "k", "m", "p")
+            api.cleanup(openrouter(), "hello", "p")
 
     def test_a_rate_limit_is_explained(self):
         with fake_urlopen(http_error(429)), \
                 self.assertRaises(api.ApiError) as caught:
-            api.cleanup("hello", "k", "m", "p")
+            api.cleanup(openrouter(), "hello", "p")
         self.assertIn("OpenRouter", str(caught.exception))
 
 
@@ -435,3 +451,159 @@ class ModelLists(DikteTest):
 
 if __name__ == "__main__":
     unittest.main()
+
+
+class FakeServer:
+    """A ggml.Server as far as api.py is concerned."""
+
+    def __init__(self, url="http://127.0.0.1:9999/v1", fails="", log=""):
+        self.url = url
+        self.fails = fails
+        self.log = log
+        self.starts = 0
+
+    def serve(self):
+        self.starts += 1
+        if self.fails:
+            raise ggml.LocalError(self.fails)
+        return self.url
+
+    def error(self):
+        return self.log
+
+
+LOCAL = api.Target("local", "Local whisper", "", "", "ggml-base.bin")
+LOCAL_LLM = api.Target("local-llm", "Local model", "", "", "gemma.gguf", "none")
+
+
+class TranscribeHere(DikteTest):
+    def setUp(self):
+        super().setUp()
+        self.wav = str(self.path("clip.wav"))
+        os.makedirs(self.root, exist_ok=True)
+        with open(self.wav, "wb") as fh:
+            fh.write(b"RIFFfake")
+        self.server = FakeServer()
+        self.patch_attr(ggml, "whisper", self.server)
+
+    def test_the_address_comes_from_the_server_it_starts(self):
+        with fake_urlopen({"text": "hello"}) as calls:
+            api.transcribe(LOCAL, self.wav)
+        self.assertEqual(self.server.starts, 1)
+        self.assertEqual(calls[0].full_url,
+                         "http://127.0.0.1:9999/v1/audio/transcriptions")
+
+    def test_nothing_local_is_authorised(self):
+        with fake_urlopen({"text": "hello"}) as calls:
+            api.transcribe(LOCAL, self.wav)
+        self.assertNotIn("Authorization", calls[0].headers)
+
+    def test_a_server_that_will_not_start_is_the_error_shown(self):
+        self.patch_attr(ggml, "whisper", FakeServer(fails="no model downloaded"))
+        with self.assertRaises(api.ApiError) as caught:
+            api.transcribe(LOCAL, self.wav)
+        self.assertIn("no model downloaded", str(caught.exception))
+
+    def test_a_server_that_dies_mid_request_says_what_it_printed(self):
+        self.patch_attr(ggml, "whisper", FakeServer(log="out of memory"))
+        with fake_urlopen(url_error("connection reset")):
+            with self.assertRaises(api.ApiError) as caught:
+                api.transcribe(LOCAL, self.wav)
+        self.assertIn("out of memory", str(caught.exception))
+
+    def test_the_hint_reaches_whisper_as_its_initial_prompt(self):
+        with fake_urlopen({"text": "hi"}) as calls:
+            api.transcribe(LOCAL, self.wav, prompt="Dikte, Paraşüt")
+        self.assertEqual(multipart_fields(calls[0])["prompt"], "Dikte, Paraşüt")
+
+    def test_a_word_broken_over_two_lines_is_put_back_together(self):
+        # whisper.cpp cuts on tokens and writes one segment per line, which in
+        # Turkish lands inside a word about as often as between two.
+        with fake_urlopen({"text": "Onlar akraba değ\niller. Ve\n devamı."}):
+            # The line break inside a word leaves nothing in its place; the
+            # one between two words is where whisper's own leading space is.
+            self.assertEqual(api.transcribe(LOCAL, self.wav),
+                             "Onlar akraba değiller. Ve devamı.")
+
+    def test_a_local_timeout_is_not_a_hosted_one(self):
+        # Nothing is being spent but time, and a long file on a machine without
+        # a graphics card takes a good deal of it.
+        with fake_urlopen({"text": "hi"}):
+            api.transcribe(LOCAL, self.wav, timeout=300)
+        self.assertGreaterEqual(api.LOCAL_TIMEOUT, 600)
+
+    def test_segments_that_continue_a_word_are_merged(self):
+        reply = {"segments": [
+            {"start": 0.0, "end": 1.0, "text": " Onlar akraba değ"},
+            {"start": 1.0, "end": 1.4, "text": "iller."},
+            {"start": 2.0, "end": 3.0, "text": " Başka bir cümle."},
+        ]}
+        with fake_urlopen(reply):
+            out = api.transcribe_segments(LOCAL, self.wav)
+        self.assertEqual([text for _, _, text in out],
+                         ["Onlar akraba değiller.", "Başka bir cümle."])
+        self.assertEqual(out[0][1], 1.4)     # the merged cue covers the whole word
+
+    def test_the_loaded_model_is_the_one_asked_for_again(self):
+        with fake_urlopen({"segments": [{"start": 0, "end": 1, "text": " hi"}]}) as calls:
+            api.transcribe_segments(LOCAL, self.wav)
+        self.assertEqual(multipart_fields(calls[0])["model"], "ggml-base.bin")
+
+
+class CleanupHere(DikteTest):
+    def setUp(self):
+        super().setUp()
+        self.server = FakeServer("http://127.0.0.1:8888/v1")
+        self.patch_attr(ggml, "llm", self.server)
+
+    def test_it_goes_to_the_server_it_starts(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            result = api.cleanup(LOCAL_LLM, "uh, hello", "clean it up")
+        self.assertEqual(result, "Hello.")
+        self.assertEqual(calls[0].full_url,
+                         "http://127.0.0.1:8888/v1/chat/completions")
+
+    def test_no_key_is_wanted_and_none_is_sent(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(LOCAL_LLM, "hello", "prompt")
+        self.assertNotIn("Authorization", calls[0].headers)
+
+    def test_thinking_is_turned_off_in_the_words_llama_cpp_uses(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(LOCAL_LLM, "hello", "prompt")
+        self.assertEqual(sent_json(calls[0])["chat_template_kwargs"],
+                         {"enable_thinking": False})
+
+    def test_the_models_own_default_asks_for_nothing(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(LOCAL_LLM._replace(reasoning=""), "hello", "prompt")
+        self.assertNotIn("chat_template_kwargs", sent_json(calls[0]))
+
+    def test_a_reply_that_was_all_thinking_names_the_setting_that_fixes_it(self):
+        reply = {"choices": [{"message": {"content": "", "reasoning": "hmm"}}]}
+        with fake_urlopen(reply), self.assertRaises(api.ApiError) as caught:
+            api.cleanup(LOCAL_LLM, "hello", "prompt")
+        self.assertIn("Thinking", str(caught.exception))
+
+    def test_a_reply_longer_than_the_transcript_is_cut_off(self):
+        # A small model will repeat the transcript until the context is full,
+        # and every one of those tokens is a second of somebody waiting.
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(LOCAL_LLM, "x" * 4000, "prompt")
+        self.assertEqual(sent_json(calls[0])["max_tokens"], 4000)
+
+    def test_a_short_dictation_still_gets_room_to_answer(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(LOCAL_LLM, "uh, hi", "prompt")
+        self.assertEqual(sent_json(calls[0])["max_tokens"], 512)
+
+    def test_a_hosted_model_is_left_to_answer_at_length(self):
+        with fake_urlopen(chat_reply("Hello.")) as calls:
+            api.cleanup(openrouter(), "uh, hi", "prompt")
+        self.assertNotIn("max_tokens", sent_json(calls[0]))
+
+    def test_a_server_that_will_not_start_is_the_error_shown(self):
+        self.patch_attr(ggml, "llm", FakeServer(fails="llama.cpp is not installed"))
+        with self.assertRaises(api.ApiError) as caught:
+            api.cleanup(LOCAL_LLM, "hello", "prompt")
+        self.assertIn("llama.cpp", str(caught.exception))

tests/test_config.py

@@ -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):
+    def test_this_machine_by_default(self):
-        target = self.config(openai_api_key="sk-test").transcribe_target()
+        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)

tests/test_filetranscribe.py

@@ -197,7 +197,7 @@ class Transcriber(DikteTest):
 
     def test_cleanup_is_told_it_is_writing_subtitles(self):
         _, _, _, cleanup_call = self.run_chain(cleanup=True)
-        prompt = cleanup_call.call_args.args[3]
+        prompt = cleanup_call.call_args.args[2]
         self.assertEqual(prompt, self.conf.cleanup_prompt(subtitles=True))
 
     def test_timestamps_come_back_as_segments_and_as_stamped_lines(self):

tests/test_ui.py

@@ -41,8 +41,18 @@ CHANGED = {
     "transcribe_model": "whisper-1",
     "openrouter_transcribe_model": "openai/whisper-1",
     "cleanup_enabled": False,
+    "cleanup_provider": "local",
     "cleanup_model": "some/other-model",
     "cleanup_reasoning": "high",
+    "local_model": "ggml-small.bin",
+    "local_gpu": False,
+    "local_preload": False,
+    "local_threads": 6,
+    "local_llm_model": "gemma-3-4b-it-Q4_K_M.gguf",
+    "local_llm_repo": "ggml-org/gemma-4-E2B-it-GGUF",
+    "local_llm_gpu": False,
+    "local_llm_preload": True,
+    "local_llm_reasoning": "low",
     "cleanup_prompt": "Only fix the punctuation.",
     "file_cleanup_prompt": "Keep the stamps where they are.",
     "transcribe_prompt": "Paraşüt, OpenFrame",
@@ -259,3 +269,53 @@ class Overlay(DikteTest):
 
 if __name__ == "__main__":
     unittest.main()
+
+
+class LocalModels(DikteTest):
+    """The download boxes, without a network and without either program."""
+
+    def window(self, conf):
+        window = settings_ui.SettingsWindow(conf, "dikte toggle")
+        self.addCleanup(window.deleteLater)
+        self.addCleanup(window.close)
+        return window
+
+    def test_it_opens_where_the_missing_model_is_fixed(self):
+        # Nothing can transcribe on a fresh install, which is why this window
+        # was opened at all.
+        window = self.window(cfg.Config())
+        self.assertEqual(window.tabs.currentIndex(), window.api_tab_index)
+
+    def test_it_opens_where_it_was_left_when_everything_works(self):
+        conf = self.config(transcribe_provider="openai", openai_api_key="sk-test")
+        self.assertEqual(self.window(conf).tabs.currentIndex(), 0)
+
+    def test_a_model_that_is_not_here_yet_survives_a_save(self):
+        # The box is filled from what is on this disk, so a model that was
+        # deleted from underneath is not in the list. Dropping it on save would
+        # quietly empty the setting instead of asking for the download again.
+        conf = self.config(local_model="ggml-large-v3-turbo-q5_0.bin")
+        with mock.patch.object(QMessageBox, "information"):
+            self.window(conf)._save()
+        self.assertEqual(conf["local_model"], "ggml-large-v3-turbo-q5_0.bin")
+
+    def test_nothing_is_fetched_for_a_window_nobody_opened(self):
+        # DikteTest closes the network, so a request would fail the test. The
+        # lists are asked for when the box is shown, not when it is built.
+        window = self.window(cfg.Config())
+        self.assertTrue(window.local_whisper._pending)
+
+    def test_the_hosted_boxes_go_away_when_the_work_happens_here(self):
+        window = self.window(self.config(transcribe_provider="openai"))
+        self.assertTrue(window.hosted_stt.isVisibleTo(window))
+        self.assertFalse(window.local_whisper.isVisibleTo(window))
+        window._select_data(window.transcribe_provider, "local")
+        self.assertFalse(window.hosted_stt.isVisibleTo(window))
+        self.assertTrue(window.local_whisper.isVisibleTo(window))
+
+    def test_the_same_for_cleanup(self):
+        window = self.window(cfg.Config())
+        self.assertTrue(window.hosted_cleanup.isVisibleTo(window))
+        window._select_data(window.cleanup_provider, "local")
+        self.assertTrue(window.local_llm.isVisibleTo(window))
+        self.assertFalse(window.hosted_cleanup.isVisibleTo(window))

tests/test_worker.py

@@ -234,7 +234,7 @@ class Chain(DikteTest):
         self.assertEqual(row["raw"], "uh, book it for Thursday")
         self.assertEqual(row["text"], "Book it for Thursday.")
         self.assertEqual(row["duration"], 2.0)
-        self.assertEqual(row["model"], self.conf["transcribe_model"])
+        self.assertEqual(row["model"], self.conf.transcribe_target().model)
         self.assertEqual(row["mode"], "")
 
     def test_a_command_is_recorded_as_one(self):

worker.py

@@ -106,20 +106,14 @@ class Pipeline(QObject):
 
             text = raw
             warning = ""
+            cleaner = conf.cleanup_target()
             # Claude reads through “eee” and “hani” without help, so a dictation
             # on its way there is normally sent as it was heard, one API call and
             # a second or two lighter.
             if (conf["assistant_cleanup"] if ask else conf["cleanup_enabled"]):
                 self.stage.emit(t("Cleaning up…"))
                 try:
-                    text = api.cleanup(
+                    text = api.cleanup(cleaner, raw, conf.cleanup_prompt())
-                        raw,
-                        conf.openrouter_key(),
-                        conf["cleanup_model"],
-                        conf.cleanup_prompt(),
-                        reasoning=conf["cleanup_reasoning"],
-                        base_url=conf["openrouter_base_url"],
-                    )
                 except api.ApiError as exc:
                     # Keep the transcript, but never let the failure pass unseen:
                     # a rejected key would otherwise look like working dictation.
@@ -159,7 +153,7 @@ class Pipeline(QObject):
                 "duration": round(duration, 1),
                 "elapsed": round(time.monotonic() - started, 1),
                 "model": target.model,
-                "cleanup_model": conf["cleanup_model"] if conf["cleanup_enabled"] else "",
+                "cleanup_model": cleaner.model if conf["cleanup_enabled"] else "",
                 "cleanup_error": warning,
                 "mode": "ask" if ask else "",
                 "question": question,