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Clean the transcript up on the subscription you already have
Cleanup was the one step with only one place to run. Speech to text has three providers behind a setting and the agent has three behind another, but the model that drops the "eee"s out of a sentence was always a request to OpenRouter, which meant a second key on a machine that already pays for a model and already hands whole dictations to it as commands. Claude Code and Codex can rewrite a sentence as easily as they can put something in your calendar, and now they may. cleanup.py is where that choice lives, so worker, the file transcriber and the meeting all ask the same question rather than each building the same OpenRouter request. What comes out of a CLI that failed is a CleanupError, which is an ApiError, because to the chain a cleanup that failed is a cleanup that failed however it was run: the raw transcript is still pasted and the reason still shows in the corner, unchanged. Neither CLI is given anything it does not need for the job. No tools, no MCP servers, no session to resume, and the home directory rather than wherever the agent is pointed, since a project's instructions have opinions about how text should be written and none of them are about this transcript. The transcript goes in fenced the same way the OpenRouter call fences it, because it is material rather than an instruction however much of it reads like one. Claude takes the cleanup rules as its whole system prompt; Codex has no system prompt of its own, so they ride in front of the text, and its answer is read from the file it writes on the way out rather than from a stdout that also carries a header, its thinking and a token count. The cost is seconds. OpenRouter answers in about one, a CLI in six or seven, because each one opens a whole session to do it. That is the trade the box says out loud, and the default has not moved: OpenRouter cleans up until you say otherwise. Codex's two lowest thinking levels now ask for "low". "minimal" was its bottom rung until the newer models replaced it with "none", and each of them answers the other's word with a 400, which the agent has been quietly hitting too. In the settings window the model box belongs to whoever is chosen rather than meaning three different things in turn, since an OpenRouter id and a Claude alias do not belong in the same field, and under it is the same "found it or not" line the agent tab has. dikte doctor asks about the program instead of the key when a CLI does the cleaning, and the history records which model actually did it.
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@@ -1,7 +1,7 @@
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# Dikte
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Press `Ctrl+Space`, talk, press again. The recording goes to OpenAI or OpenRouter
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for transcription, a model on OpenRouter cleans it up (dropping the *uh*s, the
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for transcription, a model cleans it up (dropping the *uh*s, the
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restarts, the missing punctuation), and the result lands in your clipboard and
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is pasted into whatever window you were typing in.
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@@ -43,8 +43,8 @@ again and leaves your settings and dictations alone unless you pass `--purge`.
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Three keys go in the settings window: **OpenAI**, **Groq** and **OpenRouter**.
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Speech to text runs on any of them (`gpt-4o-transcribe` by default), cleanup
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always on OpenRouter (`google/gemini-3.5-flash-lite`), so a single OpenRouter key
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can cover both. They fall back to `OPENAI_API_KEY`, `GROQ_API_KEY` and
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on OpenRouter (`google/gemini-3.5-flash-lite`) or, when either is installed, on
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Claude Code or Codex instead, so a single OpenRouter key can cover both. They fall back to `OPENAI_API_KEY`, `GROQ_API_KEY` and
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`OPENROUTER_API_KEY`, and are
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stored in `~/.config/dikte/config.json`, mode 600. Cleanup can be switched off,
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in which case the raw transcript is pasted, and a thinking model's effort can be
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@@ -148,6 +148,7 @@ audio.py PCM capture: pw-record for dictation, ffmpeg for a meeting
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meeting.py channel split, speaker labelling, cleanup, minutes
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assistant.py running a dictation through Claude Code, Codex or OpenRouter
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api.py transcription on either provider, OpenRouter cleanup (stdlib only)
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cleanup.py who rewrites the transcript: OpenRouter, Claude Code or Codex
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worker.py transcribe → clean up → clipboard → paste
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vad.py deciding whether a recording holds speech at all
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filetranscribe.py file transcription: ffmpeg, chunking, timestamps
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