thomas.kopp 11dee75ab3 fix: record at 48000 Hz — PipeWire virtual sinks reject 16 kHz resampling ...

Whisper and faster-whisper both handle arbitrary sample rates internally.

2026-04-02 09:14:34 +02:00

api

fix: use sounddevice names for audio device list and combined source

2026-04-02 07:51:42 +02:00

docs

feat: add whisper.cpp ROCm backend support for AMD GPU acceleration

2026-04-02 01:33:32 +02:00

frontend

feat: add whisper.cpp ROCm backend support for AMD GPU acceleration

2026-04-02 01:33:32 +02:00

tests

fix: update audio devices test to mock sounddevice instead of pactl

2026-04-02 07:52:34 +02:00

.gitignore

chore: project scaffold

2026-04-01 02:12:41 +02:00

alignment.py

feat: align_segments() — map Whisper timestamps to pyannote speakers

2026-04-02 01:00:58 +02:00

audio.py

fix: record at 48000 Hz — PipeWire virtual sinks reject 16 kHz resampling

2026-04-02 09:14:34 +02:00

auth.py

feat: multi-user auth — per-user spaces, pbkdf2 passwords, session tokens, login page

2026-04-01 08:39:16 +02:00

CLAUDE.md

chore: project scaffold

2026-04-01 02:12:41 +02:00

config.py

feat: add whisper.cpp ROCm backend support for AMD GPU acceleration

2026-04-02 01:33:32 +02:00

diarization.py

feat: Diarizer class wrapping pyannote/speaker-diarization-3.1

2026-04-02 00:59:50 +02:00

install.sh

fix: use ip route instead of hostname -I for Arch compatibility

2026-04-01 12:23:41 +02:00

llm.py

feat: OllamaClient.identify_speakers() and summarize() for diarization pipeline

2026-04-02 01:03:40 +02:00

main.py

fix: use sounddevice names for audio device list and combined source

2026-04-02 07:51:42 +02:00

output.py

feat: write_meeting_docs() — creates index, transkript, zusammenfassung

2026-04-02 01:05:07 +02:00

pytest.ini

chore: project scaffold

2026-04-01 02:12:41 +02:00

requirements.txt

feat: Diarizer class wrapping pyannote/speaker-diarization-3.1

2026-04-02 00:59:50 +02:00

transcription.py

feat: add whisper.cpp ROCm backend support for AMD GPU acceleration

2026-04-02 01:33:32 +02:00

S

Description

Lokales KI-Transkriptionstool — Whisper + Ollama + Browser-UI

203 KiB

Languages

Python 66.1%

HTML 20.3%

JavaScript 11.5%

Shell 2.1%