Initial commit: NovaPhonic Tauri App

This commit is contained in:
Jürgen Zwiener 2026-08-19 08:40:26 +02:00
commit dac55b40e3
30 changed files with 2868 additions and 0 deletions

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tauri-app/node_modules/
tauri-app/src-tauri/target/
tauri-app/src-tauri/gen/
tauri-app/src-tauri/binaries/
.DS_Store
Thumbs.db

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# NovaPhonic auf GitHub einrichten
Ich habe hier keinen GitHub Zugriff (keine Zugangsdaten, kein verbundenes GitHub Konto),
das Repository muss deshalb einmalig von dir selbst angelegt und gepusht werden, genau
wie bei NovaImage. Der GitHub Actions Workflow, der danach automatisch den Windows
Installer baut (inklusive Download der drei Sidecar Werkzeuge), liegt bereits fertig
unter `.github/workflows/build.yml`.
## Schritte
1. Auf GitHub ein neues, leeres Repository anlegen, zum Beispiel
`https://github.com/kiwerkepro-org/novaphonic` (passend zum Namensmuster von
NovaImage).
2. Eingabeaufforderung oder PowerShell öffnen und in den Ordner wechseln, in dem
dieses NOVA-PHONIC Verzeichnis liegt, dann:
```
cd "C:\KIW-SCHMIEDE\NOVA-PHONIC" && git init && git add . && git commit -m "Initial commit: NovaPhonic Tauri App" && git branch -M main && git remote add origin https://github.com/kiwerkepro-org/novaphonic.git && git push -u origin main
```
Falls das Repository bereits eine README oder Lizenz enthält und der Push deswegen
abgelehnt wird, hilft `git push -u origin main --force` (nur beim allerersten Push
unbedenklich, da das Repo sonst leer ist), oder vorher
`git pull origin main --allow-unrelated-histories`.
3. Danach im Repository auf GitHub den Reiter **Actions** öffnen. Der Workflow
"Windows Installer bauen" startet automatisch nach dem Push (weil Dateien unter
`tauri-app/` enthalten sind) und kann zusätzlich jederzeit manuell über den Button
**Run workflow** gestartet werden.
4. Nach erfolgreichem Lauf (dauert etwas länger als bei NovaImage, weil zusätzlich
auto-editor, FFmpeg und DeepFilterNet heruntergeladen werden) findest du im
jeweiligen Workflow Lauf unter **Artifacts** die Datei
`novaphonic-windows-installer` zum Herunterladen, darin enthalten der fertige
`.exe` (NSIS) Installer.
## Falls der erste Cloud Build fehlschlägt
Am wahrscheinlichsten ist ein Problem beim automatischen Herunterladen der
DeepFilterNet Windows Datei, weil sich deren genauer Dateiname von Version zu Version
ändern kann. Die Fehlermeldung im Actions Log zeigt das klar an, im Zweifel kurz die
Log-Ausgabe hierher kopieren, dann wird der entsprechende Schritt im Workflow
angepasst.
## Später: eigenes Signierschlüsselpaar für automatische Updates
Siehe dazu den Abschnitt "Wie Updates beim Nutzer ankommen" in
`tauri-app/BAUANLEITUNG.md`.

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GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
NovaImage, ein Tool von KI-WERKE zur Kennzeichnung KI generierter Bilder.
Copyright (C) 2026 KI-WERKE
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
NovaImage Copyright (C) 2026 KI-WERKE
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<https://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<https://www.gnu.org/licenses/why-not-lgpl.html>.
---
Hinweis zu Marken (kein Bestandteil der GPL, gilt zusätzlich):
Die Namen "NovaImage", "NovaFlow", "KI-WERKE" und "KIW Schmiede" sowie die
zugehörigen Logos sind Kennzeichen von KI-WERKE und nicht Teil der oben
gewährten Software-Lizenz. Das Recht, den Quellcode zu nutzen, zu
verändern und weiterzugeben, umfasst nicht das Recht, diese Namen oder
Logos für eigene, insbesondere abgewandelte oder umbenannte Versionen zu
verwenden.

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# Automatisierte Video Schnitt Pipeline mit WhisperX, Pyannote und ROCm
Vollständige Übersicht aller benötigten Werkzeuge sowie ein praxisnaher, schrittweiser Ablaufplan für einen Ubuntu Server mit AMD ROCm GPU und Docker.
## 1. Benötigte Werkzeuge und Komponenten
**WhisperX (KI Transkription und Wort Alignment)**
Nutzt intern CTranslate2 und faster whisper und erzeugt exakte Zeitstempel für jedes einzelne Wort.
GitHub: https://github.com/m-bain/whisperX
**pyannote.audio (Sprecher Diarisierung)**
Trennt automatisch beliebig viele Stimmen im Raum und weist jedes Wort dem jeweiligen Sprecher zu.
GitHub: https://github.com/pyannote/pyannote-audio
Hugging Face Modell: https://huggingface.co/pyannote/speaker-diarization-3.1
**FFmpeg (Video und Audio Engine)**
Extrahiert die Audiospur und schneidet das UHD Videomaterial verlustfrei ohne Neukodierung zusammen.
Webseite: https://ffmpeg.org
**ROCm PyTorch Docker Basis**
Stellt die GPU Treiberanbindung für AMD Grafikkarten im Container bereit.
Dokumentation: https://rocm.docs.amd.com
PyTorch: https://pytorch.org
**Docker Engine**
Webseite: https://docs.docker.com/engine/install/ubuntu/
## 2. Speicher und Verzeichnisstruktur auf dem Server
Passend zur Partitionierung werden feste Einhängepunkte (Mounts) eingerichtet:
```
/ (500 GB: Ubuntu System und Root)
/srv/ai-tools (100 GB: Docker Images, Skripte, Hugging Face / Whisper Modell-Caches)
/srv/backups (300 GB: Datensicherungen und Skript Backups)
/data/media (ca. 3.6 TB: Rohvideos, Arbeitsverzeichnis, finale Schnitte)
```
Benötigte Ordner im Terminal erstellen:
```bash
sudo mkdir -p /srv/ai-tools/models /srv/ai-tools/pipeline /data/media/input /data/media/output /data/media/temp
sudo chown -R $USER:$USER /srv/ai-tools /data/media
```
## 3. Vorbereitung: Hugging Face Token für Diarisierung
Das Diarisierungsmodell pyannote/speaker-diarization-3.1 ist kostenfrei auf Hugging Face verfügbar, erfordert jedoch eine einmalige Nutzungsbestätigung:
1. Kostenlosen Account erstellen auf https://huggingface.co
2. Die Modellseite https://huggingface.co/pyannote/speaker-diarization-3.1 aufrufen und die Lizenzbedingungen akzeptieren.
3. Die Segmentierungsseite https://huggingface.co/pyannote/segmentation-3.0 aufrufen und ebenfalls akzeptieren.
4. Unter Settings, Access Tokens einen Lese Token (Read Token) erstellen.
## 4. Docker Setup für AMD ROCm
Im Ordner `/srv/ai-tools/pipeline` werden die folgenden zwei Dateien erstellt.
### Datei 1: Dockerfile
```dockerfile
FROM rocm/pytorch:rocm6.2_ubuntu22.04_py3.10_pytorch_2.3.0
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1
RUN apt-get update && apt-get install -y \
ffmpeg \
git \
libsndfile1 \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /app
RUN pip install --no-cache-dir \
whisperx \
pyannote.audio \
torchaudio \
pandas
COPY cut_engine.py /app/cut_engine.py
ENTRYPOINT ["python3", "/app/cut_engine.py"]
```
### Datei 2: cut_engine.py
Dieses Skript steuert die gesamte Logik: Audio extrahieren, WhisperX mit Diarisierung ausführen, Füllwörter filtern, Dialogpausen schützen und das Video verlustfrei per FFmpeg schneiden.
```python
import os
import sys
import json
import subprocess
import torch
import whisperx
import gc
FILLER_WORDS = {
"äh", "ähm", "ahm", "uhm", "uh", "er", "ah", "mh", "mhm", "öhm", "öh"
}
def run_cmd(cmd):
subprocess.run(cmd, shell=True, check=True)
def process_video(video_path, output_path, hf_token, device="cuda"):
base_name = os.path.splitext(os.path.basename(video_path))[0]
temp_audio = f"/data/media/temp/{base_name}_temp.wav"
print(f"[1/4] Extrahiere 16kHz Audio aus {video_path}...")
run_cmd(f'ffmpeg -y -i "{video_path}" -vn -acodec pcm_s16le -ar 16000 -ac 1 "{temp_audio}"')
print("[2/4] Starte WhisperX Transkription...")
# 8GB VRAM Optimierung: float16 und moderate Batch-Size
compute_type = "float16" if torch.cuda.is_available() else "int8"
model = whisperx.load_model("large-v3", device, compute_type=compute_type, download_root="/srv/ai-tools/models")
audio = whisperx.load_audio(temp_audio)
result = model.transcribe(audio, batch_size=4)
# Alignment für wortgenaue Zeitstempel
model_a, metadata = whisperx.load_align_model(language_code=result["language"], device=device)
result = whisperx.align(result["segments"], model_a, metadata, audio, device, return_char_alignments=False)
# Speicher freigeben für Diarisierung
del model
del model_a
gc.collect()
torch.cuda.empty_cache()
print("[3/4] Starte Sprecher-Diarisierung (Pyannote)...")
diarize_model = whisperx.DiarizationPipeline(use_auth_token=hf_token, device=device)
diarize_segments = diarize_model(audio)
result = whisperx.assign_word_speakers(diarize_segments, result)
del diarize_model
gc.collect()
torch.cuda.empty_cache()
# Schnitte berechnen
print("[4/4] Analysiere Füllwörter und erstelle Schnittliste...")
cut_intervals = []
for segment in result["segments"]:
speaker = segment.get("speaker", "UNKNOWN")
words = segment.get("words", [])
for w in words:
word_clean = w.get("word", "").strip().lower().strip(".,!?:;\"'")
if word_clean in FILLER_WORDS:
if "start" in w and "end" in w:
# Füllwort gefunden: Intervall zum Herausschneiden markieren
cut_intervals.append((w["start"], w["end"], speaker, word_clean))
print(f" -> Entferne Füllwort '{word_clean}' von {speaker} ({w['start']:.2f}s bis {w['end']:.2f}s)")
# Audio-Länge ermitteln
probe_cmd = f'ffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1 "{temp_audio}"'
total_duration = float(subprocess.check_output(probe_cmd, shell=True).decode().strip())
# Zeitbereiche berechnen, die BEHALTEN werden sollen
keep_segments = []
current_pos = 0.0
for start, end, _, _ in sorted(cut_intervals, key=lambda x: x[0]):
if start > current_pos:
keep_segments.append((current_pos, start))
current_pos = max(current_pos, end)
if current_pos < total_duration:
keep_segments.append((current_pos, total_duration))
# Verlustfreier Schnitt via FFmpeg Concat Demuxer
concat_list_file = f"/data/media/temp/{base_name}_concat.txt"
segment_files = []
with open(concat_list_file, "w") as f:
for idx, (k_start, k_end) in enumerate(keep_segments):
dur = k_end - k_start
if dur < 0.1: # Sehr kurze Fragmente überspringen
continue
seg_file = f"/data/media/temp/seg_{idx}_{base_name}.mp4"
# Stream Copy (-c copy) für 100% verlustfreie UHD-Qualität
run_cmd(f'ffmpeg -y -ss {k_start} -i "{video_path}" -t {dur} -c copy -avoid_negative_ts make_zero "{seg_file}"')
f.write(f"file '{seg_file}'\n")
segment_files.append(seg_file)
print(f"Füge fertiges Video zusammen -> {output_path}")
run_cmd(f'ffmpeg -y -f concat -safe 0 -i "{concat_list_file}" -c copy "{output_path}"')
# Aufräumen
os.remove(temp_audio)
os.remove(concat_list_file)
for sf in segment_files:
if os.path.exists(sf):
os.remove(sf)
print("Fertiggestellt!")
if __name__ == "__main__":
if len(sys.argv) < 3:
print("Verwendung: python3 cut_engine.py <Eingabedatei> <Ausgabedatei> <HF_TOKEN>")
sys.exit(1)
in_video = sys.argv[1]
out_video = sys.argv[2]
token = sys.argv[3]
process_video(in_video, out_video, token)
```
## 5. Image bauen und ausführen
### Schritt A: Docker Image erstellen
Navigiere in den Ordner und baue das Image:
```bash
cd /srv/ai-tools/pipeline
docker build -t rocm-video-cut .
```
### Schritt B: Video verarbeiten
Platziere deine UHD Aufnahme (zum Beispiel interview_uhd.mp4) im Ordner `/data/media/input/`.
Starte die Verarbeitung mit Zugriff auf die AMD GPU:
```bash
docker run --rm \
--device=/dev/kfd \
--device=/dev/dri \
--group-add video \
--group-add render \
--security-opt seccomp=unconfined \
-v /srv/ai-tools/models:/srv/ai-tools/models \
-v /data/media:/data/media \
rocm-video-cut \
"/data/media/input/interview_uhd.mp4" \
"/data/media/output/interview_geschnitten.mp4" \
"DEIN_HUGGINGFACE_TOKEN"
```
## 6. Wichtige Details für 8 GB VRAM und saubere Dialoge
**VRAM Schutz bei 8 GB**
Im Skript wird nach der WhisperX Transkription der Speicher explizit mit `del model`, `gc.collect()` und `torch.cuda.empty_cache()` freigegeben, bevor das Diarisierungsmodell geladen wird. Dadurch passen selbst große 4K Dateien problemlos durch die 8 GB GPU.
**100% Erhalt der UHD Qualität**
Da FFmpeg mit `-c copy` arbeitet, werden die Videoframes nicht neu gerendert oder komprimiert. Die Bildschärfe und die Farben der Kameraaufnahme bleiben bitgenau erhalten.
**Natürliche Sprecherpausen**
Weil gezielt nur Füllwörter und keine regulären Sprechpausen zwischen verschiedenen Personen weggeschnitten werden, bleibt der natürliche Gesprächsrhythmus zwischen zwei oder mehr Personen vollkommen intakt.
## 7. Fachliche Prüfung des Entwurfs (Stand 2026-08-18)
Der ursprüngliche Entwurf wurde vor dem Bau kritisch geprüft. Dabei wurden fünf Kernprobleme identifiziert, die vor der Umsetzung berücksichtigt werden müssen.
**CTranslate2 und ROCm**
WhisperX baut auf CTranslate2 (faster whisper) auf. CTranslate2 hat keinen nativen ROCm/HIP Support, sondern unterstützt primär Nvidia CUDA und x86 CPUs. Der Aufruf von `whisperx.load_model(..., device="cuda")` wird auf dem ROCm Server vermutlich mit einem Initialisierungsfehler abbrechen, nicht nur langsamer laufen. Alignment (wav2vec2 über Hugging Face Transformers) und Diarisierung (Pyannote) laufen dagegen auf reinem PyTorch und sollten auf ROCm funktionieren. Empfohlene Architektur Alternative: nur den Transkriptionsschritt ersetzen, zum Beispiel durch die Hugging Face Transformers Whisper Pipeline oder OpenAI Whisper, und das Ergebnis in das von `whisperx.align` erwartete Segmentformat überführen. Der Rest der WhisperX Pipeline (Alignment, Diarisierung) bleibt dabei erhalten. Alternativ Transkription auf der CPU laufen lassen, während Alignment und Diarisierung auf der ROCm GPU laufen.
**Keyframe Problem bei Stream Copy**
Ein Schnitt per `-c copy` trifft bei UHD MP4 mit größeren GOP Abständen nur Keyframes, keine frame genauen Positionen. Kurze Füllwörter von einigen hundert Millisekunden lassen sich so nicht sauber isolieren, es kann zu eingefrorenem Bild oder Ton/Bild Versatz kommen. Lösung: Smart Cut Ansatz, bei dem nur kurze Übergangsfenster um die tatsächlichen Schnittkanten neu kodiert werden (CPU mit libx264, CRF 17 für optisch verlustfreie Qualität, oder AMD GPU beschleunigt über VAAPI mit hevc_vaapi/h264_vaapi), während der Großteil des Videos weiterhin per Stream Copy erhalten bleibt. Zusätzlich sollten Schnitte in der Tonspur minimale Überblendungen von 5 bis 10 Millisekunden erhalten, um Knackgeräusche zu vermeiden. Für VAAPI müssen im Docker Image zusätzlich Mesa VAAPI Treiber installiert werden, die im ROCm PyTorch Basisimage nicht automatisch enthalten sind.
**Consumer GPU Workaround**
Consumer Karten wie RX 6600, 6700 oder 7600 werden von ROCm standardmäßig nicht offiziell zertifiziert. Ohne Überschreibung der Architekturversion verweigert der Treiber den Start. Im Docker Setup muss die Umgebungsvariable `HSA_OVERRIDE_GFX_VERSION` gesetzt werden, für RDNA2 Karten (RX 6000 Serie) auf `10.3.0`, für RDNA3 Karten (RX 7000 Serie) auf `11.0.0`. Das genaue GPU Modell im Server steht noch aus und sollte vor dem Bau bestätigt werden. Vor dem Docker Test empfiehlt sich außerdem, auf dem Host selbst (außerhalb jedes Containers) einmal `rocminfo` beziehungsweise `rocm-smi` laufen zu lassen, um sicherzustellen, dass der Kernel Treiber (amdgpu/KFD) die Karte korrekt erkennt.
**Jump Cuts bei Einzelkamera Material**
Bei Aufnahmen von einer einzelnen, fest stehenden Kamera erzeugt automatisches Herausschneiden von Füllwörtern unvermeidbar sichtbare Bildsprünge (Kopf oder Handposition ändert sich zwischen den beiden Enden des Schnitts). Das ist eine redaktionelle Entscheidung, keine rein technische. Siehe Testergebnis unten für die Bewertung bei JJs eigenem Material sowie konkrete Lösungsansätze.
**Wartungsrisiko ROCm**
ROCm auf Consumer Grafikkarten läuft nicht dauerhaft geräuschlos. Updates von Ubuntu, Kernel, PyTorch oder Docker können GPU Passthrough oder die Architektur Overrides erneut anpassungsbedürftig machen. Das sollte als wiederkehrender Wartungsaufwand eingeplant werden, nicht als einmalige Einrichtung.
Zusätzlich empfohlen: Versionen von whisperx und pyannote.audio im Dockerfile fest pinnen statt ungepinnt zu installieren, da beide Projekte ihre Abhängigkeiten häufig ändern und ein ungepinntes `pip install` beim nächsten Build brechen kann.
## 8. Praxistest mit auto-editor als Zwischenschritt
Bevor Zeit in den vollständigen ROCm Aufbau fließt, wurde als pragmatischer Zwischenschritt das schlanke Open Source Tool auto-editor (https://auto-editor.com, https://github.com/WyattBlue/auto-editor) genutzt, um am echten Bildmaterial zu prüfen, wie sich automatischer Schnitt grundsätzlich anfühlt, ohne bereits in die komplexe WhisperX/Pyannote/ROCm Pipeline zu investieren.
**Installation unter Windows**
Die Installation per `pip install auto-editor` schlug lokal fehl. Funktioniert hat stattdessen der Download der vorkompilierten Windows Binärdatei `auto-editor-windows-x86_64.exe` von der GitHub Releases Seite (aktuell Version 31.5.0), ohne dass dafür Python benötigt wird.
**Lizenzhinweis**
Der Quellcode von auto-editor steht unter der Unlicense (public domain, keine Einschränkungen). Die kompilierte Windows exe von der Releases Seite hat aber offenbar eine eigene, kommerzielle Beschränkung: Bei UHD Auflösung ohne Lizenz wird automatisch auf 75 Prozent herunterskaliert (3840x2160 zu 2880x1620). Für Testzwecke unkritisch. Für eine spätere Produktivnutzung mit genau diesem Tool müsste entweder eine Lizenz erworben werden (siehe app.auto-editor.com) oder selbst aus dem Quellcode kompiliert werden, was laut Dokumentation ein WSL Umfeld mit Nim, Cmake, Meson und Ninja voraussetzt.
**Testergebnis**
Getestet an einem echten UHD Testvideo, Verarbeitungszeit rund 80 Sekunden. Füllwörter beziehungsweise Grundlaute wurden zuverlässig herausgeschnitten. Eine klangliche Verbesserung gab es erwartungsgemäß nicht, auto-editor schneidet nur, bearbeitet den Ton nicht (dafür wäre zum Beispiel Auphonic zuständig). Die Jump Cuts an den Schnittstellen sind spürbar, wurden von JJ aber nur als "eine Spur" störend eingestuft, kein Dealbreaker.
**Bewertung**
Automatischer Schnitt funktioniert grundsätzlich für JJs Content. Feinschliff bei den Übergängen ist sinnvoll. Zwei Lösungsansätze für weichere Schnitte, unabhängig davon ob mit auto-editor oder der eigenen Pipeline umgesetzt:
1. Kurzer Zoom Punch In direkt am Schnittpunkt (minimaler Zoom von wenigen Prozent), lässt den Schnitt wie eine bewusste redaktionelle Entscheidung wirken statt wie einen Fehler.
2. Sehr kurze Bildüberblendung (wenige Frames) an der Schnittstelle, zusätzlich zu den ohnehin geplanten Audio Crossfades.
## 9. Fazit und weiteres Vorgehen
Die Grundsatzfrage, ob automatischer Schnitt für JJs Material funktioniert, ist positiv beantwortet. Als Nächstes steht der gezielte Aufbau der lokalen WhisperX/Pyannote/ROCm Pipeline an, unter Berücksichtigung der in Abschnitt 7 genannten Kernprobleme (Transkriptions-Backend Wechsel weg von CTranslate2, Smart Cut statt reinem Stream Copy, korrekter HSA Override, Versions-Pinning) sowie der beiden Lösungsansätze gegen harte Jump Cuts aus Abschnitt 8.
Noch offen: genaues GPU Modell (für den korrekten HSA_OVERRIDE_GFX_VERSION Wert), tatsächliche CPU Realtime Faktor Messung für die Transkription.

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# NovaPhonic
Ein Tool von KI-WERKE. Schneidet Füllwörter und Stille automatisch aus Videos mit
einer sprechenden Person, entfernt Hintergrundgeräusche und gleicht Lautstärke sowie
Klangbalance an, ein selbstgebautes, lokales Gegenstück zu einfachen Auphonic
Funktionen.
## Status
Stufe 1 (diese App): dauerhaft kostenlos, komplett lokal, keine Internetverbindung
nötig, kein Server, für Aufnahmen mit einer Person. Näheres zur größeren
Produktvision (Stufe 2 mit Mehrsprechererkennung, Server, Abo Modell) liegt im
Projektgedächtnis, nicht in diesem Repository.
## Wie es technisch funktioniert
NovaPhonic ist eine schlanke Tauri Oberfläche (HTML/CSS/JS, siehe `app/`), die im
Hintergrund drei eigenständige Open Source Werkzeuge als sogenannte Sidecar Programme
aufruft, alle im Installer enthalten, nichts muss separat installiert werden:
- **auto-editor** (Public Domain, Unlicense): schneidet Füllwörter/Stille anhand von
Lautstärke aus dem Video.
- **DeepFilterNet / deep-filter** (MIT/Apache 2.0): entfernt Hintergrundgeräusche aus
der Tonspur.
- **FFmpeg**: gleicht Lautstärke und Klangbalance an (`loudnorm`, EBU R128) und
übernimmt Audio Extraktion sowie das Wiederzusammenfügen von Bild- und Tonspur.
Alle drei laufen ohne Grafikkarte auf einer normalen CPU. Die Videodatei wird nie in
die Oberfläche selbst geladen, es werden nur Dateipfade zwischen Oberfläche und dem
Rust Kern (`tauri-app/src-tauri/`) ausgetauscht.
## Bauen
Siehe `tauri-app/BAUANLEITUNG.md` für die vollständige Anleitung, inklusive dem
Beschaffen der drei Sidecar Werkzeuge. Siehe `GITHUB_SETUP.md` für die einmalige
Einrichtung des GitHub Repositories und der automatischen Cloud Build Pipeline.
## Lizenz
GNU General Public License v3, siehe `LICENSE`.

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/*
* app.js
* NovaPhonic Oberfläche. Ruft ausschließlich Tauri Rust Commands auf, die im
* Hintergrund auto-editor, DeepFilterNet und FFmpeg als eigenständige Programme
* (Sidecars) ausführen. Die Videodatei selbst wird nie in dieses Skript geladen,
* es werden nur Dateipfade zwischen Oberfläche und Rust ausgetauscht.
*/
(function () {
"use strict";
function $(id) { return document.getElementById(id); }
const root = document.documentElement;
function isTauri() {
return typeof window.__TAURI__ !== 'undefined' && window.__TAURI__.core;
}
// ---------- Theme ----------
const THEME_KEY = 'novaphonic-theme';
const themeToggle = $('themeToggle');
const themeLabel = $('themeLabel');
function applyTheme(theme) {
root.setAttribute('data-theme', theme);
themeLabel.textContent = theme === 'dark' ? 'Dunkel' : 'Hell';
try { localStorage.setItem(THEME_KEY, theme); } catch (e) { /* ignore */ }
}
(function initTheme() {
let saved = null;
try { saved = localStorage.getItem(THEME_KEY); } catch (e) { /* ignore */ }
applyTheme(saved === 'light' ? 'light' : 'dark');
})();
themeToggle.addEventListener('click', () => {
const current = root.getAttribute('data-theme');
applyTheme(current === 'dark' ? 'light' : 'dark');
});
// ---------- Werkzeug Check ----------
async function checkTools() {
if (!isTauri()) return;
try {
const missing = await window.__TAURI__.core.invoke('check_tools');
if (Array.isArray(missing) && missing.length > 0) {
$('toolWarning').style.display = 'block';
$('toolWarningText').textContent =
'Nicht gefunden: ' + missing.join(', ') +
'. Bitte in der BAUANLEITUNG.md nachsehen, wie diese Werkzeuge bereitgestellt werden.';
}
} catch (e) {
// check_tools selbst nicht verfügbar, z.B. während der Entwicklung im Browser
}
}
// ---------- Dateiauswahl ----------
let selectedPath = null;
function formatBytes(bytes) {
if (!bytes || bytes <= 0) return '';
const units = ['B', 'KB', 'MB', 'GB'];
let i = 0, val = bytes;
while (val >= 1024 && i < units.length - 1) { val /= 1024; i++; }
return val.toFixed(val >= 10 || i === 0 ? 0 : 1) + ' ' + units[i];
}
function setSelectedFile(path, sizeBytes) {
selectedPath = path;
const name = path.split(/[\\/]/).pop();
$('sfName').textContent = name;
$('sfSize').textContent = sizeBytes ? formatBytes(sizeBytes) : '';
$('selectedFileBox').style.display = 'block';
$('startBtn').disabled = false;
}
function clearSelectedFile() {
selectedPath = null;
$('selectedFileBox').style.display = 'none';
$('startBtn').disabled = true;
}
async function pickFile() {
if (!isTauri()) {
alert('Dateiauswahl ist nur innerhalb der NovaPhonic Anwendung verfügbar, nicht im Browser.');
return;
}
try {
const result = await window.__TAURI__.core.invoke('pick_video_file');
if (result && result.path) {
setSelectedFile(result.path, result.sizeBytes);
}
} catch (e) {
console.error(e);
}
}
const dropzone = $('dropzone');
dropzone.addEventListener('click', pickFile);
dropzone.addEventListener('keydown', (e) => {
if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); pickFile(); }
});
$('sfRemove').addEventListener('click', (e) => { e.stopPropagation(); clearSelectedFile(); });
// Echtes Drag & Drop einer Datei aus dem Windows Explorer in das Fenster.
// Liefert direkt einen Dateipfad, es wird nichts im Browser eingelesen.
(function initDragDrop() {
if (!isTauri() || !window.__TAURI__.webview) return;
try {
window.__TAURI__.webview.getCurrentWebview().onDragDropEvent((event) => {
if (event.payload.type === 'over') {
dropzone.classList.add('drag');
} else if (event.payload.type === 'drop') {
dropzone.classList.remove('drag');
const paths = event.payload.paths || [];
if (paths.length > 0) {
const p = paths[0];
const ext = p.split('.').pop().toLowerCase();
if (['mp4', 'mov', 'mkv', 'avi', 'webm'].includes(ext)) {
setSelectedFile(p, null);
} else {
alert('Bitte eine Videodatei ablegen (MP4, MOV, MKV, AVI oder WEBM).');
}
}
} else {
dropzone.classList.remove('drag');
}
});
} catch (e) {
// Drag & Drop API in dieser Tauri Version evtl. anders benannt, kein Problem,
// Klicken zum Auswählen funktioniert trotzdem.
console.warn('Drag & Drop nicht verfügbar:', e);
}
})();
// ---------- Einstellungen ----------
const marginSlider = $('marginSlider');
const marginTag = $('marginTag');
function updateMarginTag() {
const val = (parseInt(marginSlider.value, 10) / 10).toFixed(1);
marginTag.textContent = val.replace('.', ',') + ' s';
}
marginSlider.addEventListener('input', updateMarginTag);
updateMarginTag();
const loudnormToggle = $('loudnormToggle');
const loudnormOptions = $('loudnormOptions');
function syncLoudnormOptions() {
loudnormOptions.style.display = loudnormToggle.checked ? 'block' : 'none';
}
loudnormToggle.addEventListener('change', syncLoudnormOptions);
syncLoudnormOptions();
// ---------- Pipeline Ablauf ----------
const STEP_IDS = ['cut', 'denoise', 'loudnorm'];
function resetSteps() {
for (const id of STEP_IDS) {
const el = $('step-' + id);
el.classList.remove('running', 'done', 'error');
$('step-' + id + '-detail').textContent = '';
}
$('logBox').textContent = '';
}
function appendLog(line) {
const box = $('logBox');
box.textContent += (box.textContent ? '\n' : '') + line;
box.scrollTop = box.scrollHeight;
}
function setStepStatus(step, status, detail) {
const el = $('step-' + step);
if (!el) return;
el.classList.remove('running', 'done', 'error');
if (status) el.classList.add(status);
if (detail !== undefined) $('step-' + step + '-detail').textContent = detail || '';
}
let unlistenProgress = null;
async function initProgressListener() {
if (!isTauri()) return;
unlistenProgress = await window.__TAURI__.event.listen('pipeline-progress', (event) => {
const p = event.payload || {};
if (p.step) setStepStatus(p.step, p.status, p.detail);
if (p.log) appendLog(p.log);
});
}
const startBtn = $('startBtn');
startBtn.addEventListener('click', async () => {
if (!selectedPath || !isTauri()) return;
startBtn.disabled = true;
dropzone.style.pointerEvents = 'none';
resetSteps();
$('resultArea').innerHTML = '<div class="empty-hint">Verarbeitung läuft…</div>';
const options = {
inputPath: selectedPath,
marginSeconds: parseInt(marginSlider.value, 10) / 10,
denoise: $('denoiseToggle').checked,
loudnorm: loudnormToggle.checked,
loudnormTarget: parseInt($('loudnormTarget').value, 10)
};
try {
const result = await window.__TAURI__.core.invoke('process_video', { options });
showResult(result);
} catch (e) {
console.error(e);
$('resultArea').innerHTML =
'<div class="status-error">Verarbeitung fehlgeschlagen: ' +
String(e).replace(/</g, '&lt;') + '</div>';
} finally {
startBtn.disabled = false;
dropzone.style.pointerEvents = '';
}
});
function showResult(result) {
const name = result.outputPath.split(/[\\/]/).pop();
$('resultArea').innerHTML =
'<div class="result-box">' +
'<span class="rb-name">' + name.replace(/</g, '&lt;') + '</span>' +
'<button id="saveResultBtn" type="button">Speichern unter…</button>' +
'</div>' +
'<div class="status-ok" style="margin-top:8px;">Fertig. Liegt vorerst unter: ' +
result.outputPath.replace(/</g, '&lt;') + '</div>';
$('saveResultBtn').addEventListener('click', async () => {
try {
const saved = await window.__TAURI__.core.invoke('save_output_as', {
sourcePath: result.outputPath,
suggestedName: name
});
if (saved) appendLog('Gespeichert unter: ' + saved);
} catch (e) {
console.error(e);
}
});
}
// ---------- Updater (wie bei NovaImage) ----------
const updateBanner = $('updateBanner');
const updateBannerText = $('updateBannerText');
let pendingUpdate = null;
$('updateDismissBtn').addEventListener('click', () => {
updateBanner.style.display = 'none';
});
$('updateInstallBtn').addEventListener('click', async () => {
if (!pendingUpdate) return;
updateBannerText.innerHTML = '<strong>Wird installiert…</strong>';
try {
await pendingUpdate.downloadAndInstall();
await window.__TAURI__.process.relaunch();
} catch (e) {
console.error(e);
updateBannerText.innerHTML = '<strong>Update fehlgeschlagen.</strong> Bitte später erneut versuchen oder den Installer manuell von GitHub laden.';
}
});
async function checkForUpdate(silent) {
if (!isTauri() || !window.__TAURI__.updater) return 'none';
try {
const update = await window.__TAURI__.updater.check();
if (update) {
pendingUpdate = update;
updateBannerText.innerHTML =
'<strong>Update verfügbar (' + update.version + ').</strong> Eine neue Version von NovaPhonic steht bereit.';
updateBanner.style.display = 'flex';
return 'available';
}
return 'none';
} catch (e) {
if (!silent) console.error(e);
return 'error';
}
}
const checkUpdateBtn = $('checkUpdateBtn');
if (isTauri() && window.__TAURI__.updater) {
checkUpdateBtn.style.display = 'inline-flex';
}
checkUpdateBtn.addEventListener('click', async () => {
checkUpdateBtn.disabled = true;
checkUpdateBtn.textContent = 'Prüfe…';
const status = await checkForUpdate(false);
if (status === 'available') {
checkUpdateBtn.disabled = false;
checkUpdateBtn.textContent = 'Nach Updates suchen';
} else if (status === 'error') {
checkUpdateBtn.textContent = 'Prüfung fehlgeschlagen';
setTimeout(() => {
checkUpdateBtn.disabled = false;
checkUpdateBtn.textContent = 'Nach Updates suchen';
}, 2500);
} else {
checkUpdateBtn.textContent = 'Bereits aktuell';
setTimeout(() => {
checkUpdateBtn.disabled = false;
checkUpdateBtn.textContent = 'Nach Updates suchen';
}, 2500);
}
});
// ---------- Start ----------
initProgressListener();
checkTools();
checkForUpdate(true);
})();

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Copyright 2020 The Inter Project Authors (https://github.com/rsms/inter)
This Font Software is licensed under the SIL Open Font License, Version 1.1.
This license is copied below, and is also available with a FAQ at:
https://scripts.sil.org/OFL
-----------------------------------------------------------
SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007
-----------------------------------------------------------
PREAMBLE
The goals of the Open Font License (OFL) are to stimulate worldwide
development of collaborative font projects, to support the font creation
efforts of academic and linguistic communities, and to provide a free and
open framework in which fonts may be shared and improved in partnership
with others.
The OFL allows the licensed fonts to be used, studied, modified and
redistributed freely as long as they are not sold by themselves. The
fonts, including any derivative works, can be bundled, embedded,
redistributed and/or sold with any software provided that any reserved
names are not used by derivative works. The fonts and derivatives,
however, cannot be released under any other type of license. The
requirement for fonts to remain under this license does not apply
to any document created using the fonts or their derivatives.
DEFINITIONS
"Font Software" refers to the set of files released by the Copyright
Holder(s) under this license and clearly marked as such. This may
include source files, build scripts and documentation.
"Reserved Font Name" refers to any names specified as such after the
copyright statement(s).
"Original Version" refers to the collection of Font Software components as
distributed by the Copyright Holder(s).
"Modified Version" refers to any derivative made by adding to, deleting,
or substituting -- in part or in whole -- any of the components of the
Original Version, by changing formats or by porting the Font Software to a
new environment.
"Author" refers to any designer, engineer, programmer, technical
writer or other person who contributed to the Font Software.
PERMISSION & CONDITIONS
Permission is hereby granted, free of charge, to any person obtaining
a copy of the Font Software, to use, study, copy, merge, embed, modify,
redistribute, and sell modified and unmodified copies of the Font
Software, subject to the following conditions:
1) Neither the Font Software nor any of its individual components,
in Original or Modified Versions, may be sold by itself.
2) Original or Modified Versions of the Font Software may be bundled,
redistributed and/or sold with any software, provided that each copy
contains the above copyright notice and this license. These can be
included either as stand-alone text files, human-readable headers or
in the appropriate machine-readable metadata fields within text or
binary files as long as those fields can be easily viewed by the user.
3) No Modified Version of the Font Software may use the Reserved Font
Name(s) unless explicit written permission is granted by the corresponding
Copyright Holder. This restriction only applies to the primary font name as
presented to the users.
4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
Software shall not be used to promote, endorse or advertise any
Modified Version, except to acknowledge the contribution(s) of the
Copyright Holder(s) and the Author(s) or with their explicit written
permission.
5) The Font Software, modified or unmodified, in part or in whole,
must be distributed entirely under this license, and must not be
distributed under any other license. The requirement for fonts to
remain under this license does not apply to any document created
using the Font Software.
TERMINATION
This license becomes null and void if any of the above conditions are
not met.
DISCLAIMER
THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
OTHER DEALINGS IN THE FONT SOFTWARE.

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Copyright 2020 The JetBrains Mono Project Authors (https://github.com/JetBrains/JetBrainsMono)
This Font Software is licensed under the SIL Open Font License, Version 1.1.
This license is copied below, and is also available with a FAQ at: https://scripts.sil.org/OFL
-----------------------------------------------------------
SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007
-----------------------------------------------------------
PREAMBLE
The goals of the Open Font License (OFL) are to stimulate worldwide
development of collaborative font projects, to support the font creation
efforts of academic and linguistic communities, and to provide a free and
open framework in which fonts may be shared and improved in partnership
with others.
The OFL allows the licensed fonts to be used, studied, modified and
redistributed freely as long as they are not sold by themselves. The
fonts, including any derivative works, can be bundled, embedded,
redistributed and/or sold with any software provided that any reserved
names are not used by derivative works. The fonts and derivatives,
however, cannot be released under any other type of license. The
requirement for fonts to remain under this license does not apply
to any document created using the fonts or their derivatives.
DEFINITIONS
"Font Software" refers to the set of files released by the Copyright
Holder(s) under this license and clearly marked as such. This may
include source files, build scripts and documentation.
"Reserved Font Name" refers to any names specified as such after the
copyright statement(s).
"Original Version" refers to the collection of Font Software components as
distributed by the Copyright Holder(s).
"Modified Version" refers to any derivative made by adding to, deleting,
or substituting -- in part or in whole -- any of the components of the
Original Version, by changing formats or by porting the Font Software to a
new environment.
"Author" refers to any designer, engineer, programmer, technical
writer or other person who contributed to the Font Software.
PERMISSION & CONDITIONS
Permission is hereby granted, free of charge, to any person obtaining
a copy of the Font Software, to use, study, copy, merge, embed, modify,
redistribute, and sell modified and unmodified copies of the Font
Software, subject to the following conditions:
1) Neither the Font Software nor any of its individual components,
in Original or Modified Versions, may be sold by itself.
2) Original or Modified Versions of the Font Software may be bundled,
redistributed and/or sold with any software, provided that each copy
contains the above copyright notice and this license. These can be
included either as stand-alone text files, human-readable headers or
in the appropriate machine-readable metadata fields within text or
binary files as long as those fields can be easily viewed by the user.
3) No Modified Version of the Font Software may use the Reserved Font
Name(s) unless explicit written permission is granted by the corresponding
Copyright Holder. This restriction only applies to the primary font name as
presented to the users.
4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
Software shall not be used to promote, endorse or advertise any
Modified Version, except to acknowledge the contribution(s) of the
Copyright Holder(s) and the Author(s) or with their explicit written
permission.
5) The Font Software, modified or unmodified, in part or in whole,
must be distributed entirely under this license, and must not be
distributed under any other license. The requirement for fonts to
remain under this license does not apply to any document created
using the Font Software.
TERMINATION
This license becomes null and void if any of the above conditions are
not met.
DISCLAIMER
THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
OTHER DEALINGS IN THE FONT SOFTWARE.

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@ -0,0 +1,93 @@
Copyright 2020 The Space Grotesk Project Authors (https://github.com/floriankarsten/space-grotesk)
This Font Software is licensed under the SIL Open Font License, Version 1.1.
This license is copied below, and is also available with a FAQ at:
http://scripts.sil.org/OFL
-----------------------------------------------------------
SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007
-----------------------------------------------------------
PREAMBLE
The goals of the Open Font License (OFL) are to stimulate worldwide
development of collaborative font projects, to support the font creation
efforts of academic and linguistic communities, and to provide a free and
open framework in which fonts may be shared and improved in partnership
with others.
The OFL allows the licensed fonts to be used, studied, modified and
redistributed freely as long as they are not sold by themselves. The
fonts, including any derivative works, can be bundled, embedded,
redistributed and/or sold with any software provided that any reserved
names are not used by derivative works. The fonts and derivatives,
however, cannot be released under any other type of license. The
requirement for fonts to remain under this license does not apply
to any document created using the fonts or their derivatives.
DEFINITIONS
"Font Software" refers to the set of files released by the Copyright
Holder(s) under this license and clearly marked as such. This may
include source files, build scripts and documentation.
"Reserved Font Name" refers to any names specified as such after the
copyright statement(s).
"Original Version" refers to the collection of Font Software components as
distributed by the Copyright Holder(s).
"Modified Version" refers to any derivative made by adding to, deleting,
or substituting -- in part or in whole -- any of the components of the
Original Version, by changing formats or by porting the Font Software to a
new environment.
"Author" refers to any designer, engineer, programmer, technical
writer or other person who contributed to the Font Software.
PERMISSION & CONDITIONS
Permission is hereby granted, free of charge, to any person obtaining
a copy of the Font Software, to use, study, copy, merge, embed, modify,
redistribute, and sell modified and unmodified copies of the Font
Software, subject to the following conditions:
1) Neither the Font Software nor any of its individual components,
in Original or Modified Versions, may be sold by itself.
2) Original or Modified Versions of the Font Software may be bundled,
redistributed and/or sold with any software, provided that each copy
contains the above copyright notice and this license. These can be
included either as stand-alone text files, human-readable headers or
in the appropriate machine-readable metadata fields within text or
binary files as long as those fields can be easily viewed by the user.
3) No Modified Version of the Font Software may use the Reserved Font
Name(s) unless explicit written permission is granted by the corresponding
Copyright Holder. This restriction only applies to the primary font name as
presented to the users.
4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
Software shall not be used to promote, endorse or advertise any
Modified Version, except to acknowledge the contribution(s) of the
Copyright Holder(s) and the Author(s) or with their explicit written
permission.
5) The Font Software, modified or unmodified, in part or in whole,
must be distributed entirely under this license, and must not be
distributed under any other license. The requirement for fonts to
remain under this license does not apply to any document created
using the Font Software.
TERMINATION
This license becomes null and void if any of the above conditions are
not met.
DISCLAIMER
THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
OTHER DEALINGS IN THE FONT SOFTWARE.

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app/assets/kiwerke-logo.ico Normal file

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<?xml version="1.0" standalone="no"?>
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<svg version="1.0" xmlns="http://www.w3.org/2000/svg"
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app/index.html Normal file
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<!DOCTYPE html>
<html lang="de" data-theme="dark">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>NovaPhonic, ein Tool von KI-WERKE</title>
<link rel="icon" href="assets/kiwerke-logo.ico">
<link rel="stylesheet" href="style.css">
</head>
<body>
<div class="wrap">
<header>
<div class="brand-row">
<div class="brand-logo"><img src="assets/kiwerke-logo-master.png" alt="KI-WERKE Logo"></div>
<div>
<div class="product-of">Ein Tool von KI-WERKE</div>
<h1>NovaPhonic</h1>
<div class="sub">
Schneidet Füllwörter und Stille automatisch aus deinem Video, entfernt
Hintergrundgeräusche und gleicht Lautstärke sowie Klangbalance an.
Komplett lokal, ohne Upload, ohne Internetverbindung.
</div>
<span class="badge-hint">Einzelperson Aufnahmen, kostenlose Version</span>
</div>
</div>
<div class="header-actions">
<span class="version-tag" id="versionTag">v0.1.0</span>
<button id="checkUpdateBtn" class="secondary check-update-btn" type="button" style="display:none;">
Nach Updates suchen
</button>
<button id="themeToggle" class="theme-toggle" type="button" aria-label="Farbschema wechseln">
<svg class="ico-sun" viewBox="0 0 24 24"><circle cx="12" cy="12" r="4"/><path d="M12 2v2M12 20v2M4.9 4.9l1.4 1.4M17.7 17.7l1.4 1.4M2 12h2M20 12h2M4.9 19.1l1.4-1.4M17.7 6.3l1.4-1.4"/></svg>
<svg class="ico-moon" viewBox="0 0 24 24"><path d="M21 12.8A9 9 0 1 1 11.2 3a7 7 0 0 0 9.8 9.8z"/></svg>
<span id="themeLabel">Dunkel</span>
</button>
</div>
</header>
<main>
<div class="update-banner" id="updateBanner" style="display:none;" role="status" aria-live="polite">
<span id="updateBannerText"><strong>Update verfügbar.</strong> Eine neue Version von NovaPhonic steht bereit.</span>
<div class="update-banner-actions">
<button id="updateInstallBtn" type="button">Jetzt installieren</button>
<button id="updateDismissBtn" type="button" class="secondary">Später</button>
</div>
</div>
<div class="privacy-note">
<strong>Läuft lokal:</strong> Dein Video verlässt diesen Rechner nicht. Schnitt,
Entrauschen und Lautstärke Angleichung passieren ausschließlich hier, es wird
nichts hochgeladen und keine Verbindung zu einem Server aufgebaut.
</div>
<div id="toolWarning" class="tool-warning" style="display:none;">
<strong>Werkzeuge fehlen.</strong>
<span id="toolWarningText">Es konnten nicht alle benötigten Programme gefunden werden.</span>
</div>
<div class="grid">
<div>
<div class="panel">
<h2>Einstellungen</h2>
<div class="row">
<label for="marginSlider">Zeitpuffer um jeden Schnitt <span class="value-tag" id="marginTag">0,2 s</span></label>
<input type="range" id="marginSlider" min="0" max="10" step="1" value="2">
<div class="hint-small">Kleiner Puffer vor und nach jedem Schnitt, damit Wörter nicht mitten im Laut abgeschnitten werden.</div>
</div>
<div class="checkbox-row" style="margin-top:16px;">
<input type="checkbox" id="denoiseToggle" checked>
<label for="denoiseToggle">Hintergrundgeräusche entfernen (DeepFilterNet)</label>
</div>
<div class="checkbox-row" style="margin-top:10px;">
<input type="checkbox" id="loudnormToggle" checked>
<label for="loudnormToggle">Lautstärke &amp; Klangbalance angleichen (EBU R128)</label>
</div>
<div class="row" id="loudnormOptions" style="margin-top:14px;">
<label for="loudnormTarget">Ziel Lautheit</label>
<select id="loudnormTarget">
<option value="-16" selected>-16 LUFS (Podcast / YouTube)</option>
<option value="-23">-23 LUFS (Rundfunk, EBU R128)</option>
<option value="-14">-14 LUFS (Streaming, laut)</option>
</select>
</div>
</div>
<div class="panel">
<h2>Über die Werkzeuge</h2>
<div class="hint-small">
Schnitt: <strong>auto-editor</strong> (Public Domain). Entrauschen:
<strong>DeepFilterNet</strong> (MIT/Apache 2.0). Lautstärke: <strong>FFmpeg</strong>
loudnorm Filter (LGPL/GPL). Alle drei laufen als eigenständige Programme neben
NovaPhonic auf diesem Rechner, keines davon braucht eine Grafikkarte.
</div>
</div>
</div>
<div>
<div class="panel">
<h2>Video</h2>
<div class="dropzone" id="dropzone" role="button" tabindex="0"
aria-label="Video auswählen. Klicken oder Datei hierher ziehen">
<div class="dz-icon" aria-hidden="true">
<svg viewBox="0 0 24 24"><path d="M4 16v2a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2v-2M7 10l5-5 5 5M12 5v13"/></svg>
</div>
<div><strong>Video hierher ziehen</strong> oder klicken zum Auswählen</div>
<div style="font-size:12px;margin-top:6px;">MP4, MOV, MKV, eine Aufnahme mit einer sprechenden Person</div>
</div>
<div id="selectedFileBox" style="display:none;">
<div class="selected-file">
<span class="sf-name" id="sfName"></span>
<span class="sf-size" id="sfSize"></span>
<button class="sf-remove" id="sfRemove" type="button" aria-label="Auswahl entfernen">
<svg viewBox="0 0 24 24"><path d="M18 6L6 18M6 6l12 12"/></svg>
</button>
</div>
</div>
<div class="actions">
<button id="startBtn" disabled>Verarbeitung starten</button>
</div>
</div>
<div class="panel">
<h2>Ablauf</h2>
<div class="pipeline-steps">
<div class="pipeline-step" id="step-cut">
<span class="ps-dot"></span>
<span class="ps-label">Füllwörter &amp; Stille schneiden</span>
<span class="ps-detail" id="step-cut-detail"></span>
</div>
<div class="pipeline-step" id="step-denoise">
<span class="ps-dot"></span>
<span class="ps-label">Rauschen entfernen</span>
<span class="ps-detail" id="step-denoise-detail"></span>
</div>
<div class="pipeline-step" id="step-loudnorm">
<span class="ps-dot"></span>
<span class="ps-label">Lautstärke angleichen</span>
<span class="ps-detail" id="step-loudnorm-detail"></span>
</div>
</div>
<div class="log-box" id="logBox">Noch nichts gestartet.</div>
</div>
<div class="panel">
<h2>Ergebnis</h2>
<div id="resultArea">
<div class="empty-hint" id="resultEmptyHint">Noch kein Video verarbeitet.</div>
</div>
</div>
</div>
</div>
</main>
<div class="footer-note">
Hinweis: NovaPhonic bearbeitet ausschließlich technische Aspekte deiner Aufnahme
(Schnitt, Rauschunterdrückung, Lautstärke). Es werden keine neuen Inhalte erzeugt
und keine Aussagen im Video verändert. NovaPhonic ersetzt keine manuelle
Endkontrolle, insbesondere Bildsprünge an Schnittstellen solltest du dir vor der
Veröffentlichung kurz ansehen.
</div>
</div>
<script src="app.js"></script>
</body>
</html>

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/*
* NovaPhonic, ein Tool von KI-WERKE.
* Farben, Schriften und Grundlayout übernommen aus NovaImage (gleicher Brand Guide).
* Dark Mode ist Standard (Deep Navy), Light Mode als Umschaltoption.
*/
/* Schriften lokal eingebunden (kein Google Fonts, keine externe Verbindung), Space Grotesk
und Inter und JetBrains Mono, jeweils als Variable Font unter SIL Open Font License,
Lizenztexte liegen in assets/fonts/. */
@font-face {
font-family: 'Space Grotesk';
src: url('assets/fonts/SpaceGrotesk-Variable.woff2') format('woff2-variations'),
url('assets/fonts/SpaceGrotesk-Variable.woff2') format('woff2');
font-weight: 300 700;
font-style: normal;
font-display: swap;
}
@font-face {
font-family: 'Inter';
src: url('assets/fonts/Inter-Variable.woff2') format('woff2-variations'),
url('assets/fonts/Inter-Variable.woff2') format('woff2');
font-weight: 100 900;
font-style: normal;
font-display: swap;
}
@font-face {
font-family: 'JetBrains Mono';
src: url('assets/fonts/JetBrainsMono-Variable.woff2') format('woff2-variations'),
url('assets/fonts/JetBrainsMono-Variable.woff2') format('woff2');
font-weight: 100 800;
font-style: normal;
font-display: swap;
}
:root,
html[data-theme="dark"] {
color-scheme: dark;
--bg: #0A0F1A;
--panel: #111827;
--panel-2: #161d2b;
--border: #1F2937;
--text: #F4F5F7;
--muted: #93a0b4;
--accent: #00E0B8;
--accent-text: #00E0B8;
--accent-text-on: #04211c;
--ok: #3ddc84;
--danger: #ff6b6b;
--danger-bg: #3a1f1f;
--shadow: 0 8px 24px rgba(0, 0, 0, 0.35);
}
html[data-theme="light"] {
color-scheme: light;
--bg: #F4F5F7;
--panel: #ffffff;
--panel-2: #eef0f3;
--border: #d8dee6;
--text: #0A0F1A;
--muted: #5b6472;
--accent: #00E0B8;
--accent-text: #006B5C;
--accent-text-on: #04211c;
--ok: #1a7f37;
--danger: #b3261e;
--danger-bg: #fdecea;
--shadow: 0 4px 14px rgba(15, 23, 42, 0.08);
}
* { box-sizing: border-box; }
body {
margin: 0;
font-family: 'Inter', -apple-system, "Segoe UI", Roboto, Arial, sans-serif;
background: var(--bg);
color: var(--text);
padding: 24px;
transition: background 0.15s ease, color 0.15s ease;
}
.wrap { max-width: 1180px; margin: 0 auto; }
header {
margin-bottom: 24px;
display: flex;
align-items: flex-start;
justify-content: space-between;
gap: 16px;
}
.brand-row { display: flex; align-items: center; gap: 20px; }
.brand-logo { width: 92px; height: 92px; flex-shrink: 0; }
.brand-logo img { width: 100%; height: 100%; border-radius: 18px; display: block; box-shadow: var(--shadow); }
h1 {
font-family: 'Space Grotesk', -apple-system, "Segoe UI", sans-serif;
font-weight: 700;
font-size: 24px;
margin: 0 0 4px 0;
color: var(--text);
letter-spacing: -0.01em;
}
.product-of {
font-family: 'JetBrains Mono', monospace;
font-size: 11px;
color: var(--muted);
text-transform: uppercase;
letter-spacing: 0.06em;
}
.sub { color: var(--muted); font-size: 14px; line-height: 1.5; max-width: 760px; }
.badge-hint {
display: inline-block;
background: var(--panel-2);
color: var(--accent-text);
border: 1px solid var(--accent-text);
padding: 3px 10px;
border-radius: 6px;
font-family: 'JetBrains Mono', monospace;
font-size: 11px;
margin-top: 8px;
}
.theme-toggle {
display: flex;
align-items: center;
gap: 8px;
background: var(--panel);
border: 1px solid var(--border);
border-radius: 999px;
padding: 6px 12px;
cursor: pointer;
color: var(--text);
font-size: 12px;
font-family: 'JetBrains Mono', monospace;
flex-shrink: 0;
height: fit-content;
}
.theme-toggle svg { width: 15px; height: 15px; stroke: var(--accent-text); fill: none; stroke-width: 2; }
.theme-toggle .ico-sun { display: none; }
.theme-toggle .ico-moon { display: none; }
html[data-theme="dark"] .theme-toggle .ico-moon { display: block; }
html[data-theme="light"] .theme-toggle .ico-sun { display: block; }
.header-actions { display: flex; align-items: center; gap: 10px; flex-shrink: 0; }
.version-tag {
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--muted);
white-space: nowrap;
}
.check-update-btn { padding: 8px 12px; font-size: 13px; white-space: nowrap; }
.grid {
display: grid;
grid-template-columns: 340px 1fr;
gap: 20px;
align-items: start;
}
@media (max-width: 900px) {
.grid { grid-template-columns: 1fr; }
}
.panel {
background: var(--panel);
border: 1px solid var(--border);
border-radius: 12px;
padding: 18px;
margin-bottom: 18px;
box-shadow: var(--shadow);
}
.panel h2 {
font-family: 'Space Grotesk', sans-serif;
font-weight: 700;
font-size: 13px;
text-transform: uppercase;
letter-spacing: 0.05em;
color: var(--muted);
margin: 0 0 14px 0;
}
label { font-size: 13px; font-weight: 600; display: block; margin-bottom: 4px; color: var(--text); }
.row { margin-bottom: 14px; }
.row-inline { display: flex; gap: 10px; align-items: center; }
input[type="text"], select, textarea {
width: 100%;
padding: 8px 10px;
border: 1px solid var(--border);
border-radius: 8px;
font-size: 14px;
font-family: inherit;
background: var(--panel-2);
color: var(--text);
}
input:focus-visible, select:focus-visible, textarea:focus-visible, button:focus-visible {
outline: 2px solid var(--accent-text);
outline-offset: 1px;
}
input[disabled] { opacity: 0.45; }
input[type="range"] { width: 100%; accent-color: var(--accent); }
input[type="checkbox"] { accent-color: var(--accent); width: 16px; height: 16px; }
.checkbox-row { display: flex; align-items: center; gap: 8px; font-weight: 400; font-size: 14px; }
.checkbox-row label { font-weight: 400; margin: 0; }
.hint-small { font-size: 12px; color: var(--muted); margin-top: 4px; }
.value-tag { font-size: 12px; color: var(--muted); float: right; font-family: 'JetBrains Mono', monospace; }
.dropzone {
border: 2px dashed var(--border);
border-radius: 12px;
padding: 28px 16px;
text-align: center;
color: var(--muted);
cursor: pointer;
background: var(--panel-2);
}
.dropzone.drag { border-color: var(--accent-text); background: rgba(0, 224, 184, 0.08); }
.dropzone strong { color: var(--accent-text); }
.dropzone:focus-visible { outline: 2px solid var(--accent-text); outline-offset: 2px; }
.dropzone .dz-icon { width: 30px; height: 30px; margin: 0 auto 8px; }
.dropzone .dz-icon svg { width: 100%; height: 100%; stroke: var(--accent-text); fill: none; stroke-width: 1.5; }
.selected-file {
display: flex;
align-items: center;
gap: 10px;
border: 1px solid var(--border);
border-radius: 8px;
padding: 10px 12px;
background: var(--panel-2);
margin-top: 12px;
}
.selected-file .sf-name { font-size: 13px; font-weight: 600; word-break: break-all; flex: 1; color: var(--text); }
.selected-file .sf-size { font-size: 11px; color: var(--muted); font-family: 'JetBrains Mono', monospace; }
.selected-file .sf-remove {
background: none;
border: none;
color: var(--danger);
cursor: pointer;
padding: 8px;
margin: -6px;
display: flex;
border-radius: 6px;
}
.selected-file .sf-remove svg { width: 16px; height: 16px; stroke: currentColor; fill: none; stroke-width: 2; }
button {
background: var(--accent);
color: var(--accent-text-on);
border: none;
padding: 10px 16px;
border-radius: 8px;
font-size: 14px;
cursor: pointer;
font-weight: 700;
font-family: 'Inter', sans-serif;
display: inline-flex;
align-items: center;
gap: 6px;
}
button svg { width: 15px; height: 15px; stroke: currentColor; fill: none; stroke-width: 2; }
button.secondary { background: var(--panel-2); color: var(--text); border: 1px solid var(--border); }
button.danger { background: var(--danger-bg); color: var(--danger); }
button:disabled { opacity: 0.4; cursor: not-allowed; }
.actions { display: flex; gap: 10px; margin-top: 14px; flex-wrap: wrap; }
/* Fortschritt / Pipeline Log */
.pipeline-steps { display: flex; flex-direction: column; gap: 8px; margin-top: 4px; }
.pipeline-step {
display: flex;
align-items: center;
gap: 10px;
border: 1px solid var(--border);
border-radius: 8px;
padding: 8px 10px;
background: var(--panel-2);
font-size: 13px;
}
.pipeline-step .ps-dot {
width: 9px; height: 9px; border-radius: 50%;
background: var(--border); flex-shrink: 0;
}
.pipeline-step.running .ps-dot { background: var(--accent); box-shadow: 0 0 0 3px rgba(0,224,184,0.25); }
.pipeline-step.done .ps-dot { background: var(--ok); }
.pipeline-step.error .ps-dot { background: var(--danger); }
.pipeline-step .ps-label { flex: 1; }
.pipeline-step .ps-detail { font-size: 11px; color: var(--muted); font-family: 'JetBrains Mono', monospace; }
.log-box {
margin-top: 12px;
background: var(--panel-2);
border: 1px solid var(--border);
border-radius: 8px;
padding: 10px 12px;
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--muted);
max-height: 160px;
overflow-y: auto;
white-space: pre-wrap;
word-break: break-word;
}
.result-box {
display: flex;
align-items: center;
gap: 12px;
border: 1px solid var(--accent-text);
border-radius: 10px;
padding: 12px 14px;
background: var(--panel-2);
}
.result-box .rb-name { font-weight: 600; word-break: break-all; flex: 1; font-size: 13px; }
.status-ok { color: var(--ok); font-size: 12px; font-family: 'JetBrains Mono', monospace; }
.status-error { color: var(--danger); font-size: 13px; }
.empty-hint { color: var(--muted); font-size: 13px; padding: 20px 0; text-align: center; }
.footer-note {
font-size: 12px;
color: var(--muted);
line-height: 1.6;
margin-top: 26px;
padding-top: 14px;
border-top: 1px solid var(--border);
}
.privacy-note {
font-size: 13px;
background: var(--panel);
border: 1px solid var(--accent-text);
color: var(--text);
padding: 10px 12px;
border-radius: 10px;
margin-bottom: 18px;
}
.privacy-note strong { color: var(--accent-text); }
.tool-warning {
font-size: 13px;
background: var(--danger-bg);
border: 1px solid var(--danger);
color: var(--text);
padding: 10px 12px;
border-radius: 10px;
margin-bottom: 18px;
}
.tool-warning strong { color: var(--danger); }
.update-banner {
display: flex;
align-items: center;
justify-content: space-between;
gap: 12px;
flex-wrap: wrap;
font-size: 13px;
background: var(--panel);
border: 1px solid var(--accent);
color: var(--text);
padding: 10px 12px;
border-radius: 10px;
margin-bottom: 18px;
}
.update-banner strong { color: var(--accent-text); }
.update-banner-actions { display: flex; gap: 8px; flex-shrink: 0; }
.update-banner-actions button { padding: 7px 12px; font-size: 13px; }

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# Bauanleitung: NovaPhonic Windows Installer
Dieses Verzeichnis enthält das Tauri Projekt, das NovaPhonic als eigenständige Windows
Anwendung mit NSIS Installer (.exe) verpackt, nach demselben Muster wie NovaImage.
Der Installer selbst kann nicht in der Cloud Sandbox gebaut werden (Linux, kein Rust,
keine Windows Build Werkzeuge, keine Root Rechte), sondern nur auf einem Windows
Rechner oder per GitHub Actions.
## Wichtiger Hinweis zum Rust Code
In der Umgebung, in der dieses Projekt erstellt wurde, gab es keinen Rust Compiler.
`src-tauri/src/main.rs` wurde also nicht kompiliert, nur sorgfältig von Hand
geschrieben und geprüft. Der erste Build (lokal oder per GitHub Actions) ist damit
der erste echte Kompilier-Test. Zwei Stellen im Code sind mit Kommentaren markiert
und sollten dabei besonders beachtet werden:
1. Die genauen Kommandozeilen-Optionen von `deep-filter` (Entrauschungs-Werkzeug).
Der Code nimmt `-o <Zieldatei>` an, manche Versionen erwarten stattdessen einen
Ausgabeordner. Mit `deep-filter --help` (oder `binaries\deep-filter-x86_64-pc-windows-msvc.exe --help`
im PowerShell Fenster) lässt sich das direkt prüfen.
2. Ob `auto-editor --no-open` in der installierten Version noch so heißt.
Falls der Build fehlschlägt, bitte die Fehlermeldung schicken, dann wird gezielt
nachgebessert.
## Schritt 1: Sidecar Werkzeuge besorgen
NovaPhonic bringt auto-editor, DeepFilterNet (`deep-filter`) und FFmpeg direkt im
Installer mit (sogenannte Sidecar Programme), damit niemand diese drei Werkzeuge
selbst von Hand herunterladen und im PATH einrichten muss. Dafür müssen die drei
Dateien vor dem Bauen einmalig in `tauri-app/src-tauri/binaries/` liegen, mit dem
Ziel-Tripel im Namen (auf einem normalen Windows PC ist das `x86_64-pc-windows-msvc`,
zur Sicherheit mit `rustc -vV` prüfen, Zeile "host"):
```
tauri-app/src-tauri/binaries/auto-editor-x86_64-pc-windows-msvc.exe
tauri-app/src-tauri/binaries/ffmpeg-x86_64-pc-windows-msvc.exe
tauri-app/src-tauri/binaries/deep-filter-x86_64-pc-windows-msvc.exe
```
Diese PowerShell Befehle laden alle drei automatisch herunter und benennen sie
richtig (im Ordner `tauri-app` ausführen):
```powershell
New-Item -ItemType Directory -Force -Path "src-tauri\binaries" | Out-Null
# auto-editor (kennen wir schon vom Test)
Invoke-WebRequest -Uri "https://github.com/WyattBlue/auto-editor/releases/latest/download/auto-editor-windows-x86_64.exe" `
-OutFile "src-tauri\binaries\auto-editor-x86_64-pc-windows-msvc.exe"
# FFmpeg (gyan.dev essentials build, gepackt als Zip)
Invoke-WebRequest -Uri "https://www.gyan.dev/ffmpeg/builds/ffmpeg-release-essentials.zip" -OutFile "ffmpeg.zip"
Expand-Archive -Path "ffmpeg.zip" -DestinationPath "ffmpeg-extracted"
$ffmpegExe = Get-ChildItem -Path "ffmpeg-extracted" -Recurse -Filter "ffmpeg.exe" | Select-Object -First 1
Copy-Item $ffmpegExe.FullName "src-tauri\binaries\ffmpeg-x86_64-pc-windows-msvc.exe"
Remove-Item "ffmpeg.zip", "ffmpeg-extracted" -Recurse -Force
# DeepFilterNet: Release Seite oeffnen und die aktuelle Windows Datei manuell laden,
# da sich der genaue Dateiname von Version zu Version aendern kann:
# https://github.com/Rikorose/DeepFilterNet/releases/latest
# Danach die heruntergeladene Datei umbenennen/kopieren nach:
# src-tauri\binaries\deep-filter-x86_64-pc-windows-msvc.exe
```
Die GitHub Actions Pipeline (`.github/workflows/build.yml`) erledigt genau diese drei
Downloads bereits automatisch bei jedem Cloud Build, inklusive einer automatischen
Suche nach der aktuellen DeepFilterNet Windows Datei. Für einen lokalen Build auf
dem eigenen Rechner müssen die Dateien wie oben einmalig von Hand besorgt werden.
## Weg 1: Auf dem eigenen Windows Rechner bauen
Einmalige Voraussetzungen:
1. Node.js (LTS Version): https://nodejs.org
2. Rust über https://rustup.rs
3. Während/nach der Rust Installation: "Microsoft C++ Build Tools" (Komponente
"Desktop development with C++" aus dem Visual Studio Installer).
4. WebView2 Runtime ist auf aktuellen Windows 10/11 Systemen normalerweise schon dabei.
5. Die drei Sidecar Dateien aus Schritt 1 liegen in `src-tauri/binaries/`.
```
cd tauri-app
npm install
npm run tauri build
```
Installer liegt danach unter:
```
src-tauri\target\release\bundle\nsis\NovaPhonic_<Version>_x64-setup.exe
```
Zum Testen ohne Installer, mit Live Neuladen: `npm run tauri dev`
## Weg 2: Automatisch in der Cloud bauen (GitHub Actions)
Ist bereits eingerichtet unter `.github/workflows/build.yml`, inklusive dem
automatischen Herunterladen der drei Sidecar Werkzeuge. Läuft automatisch bei jedem
Push, der `tauri-app/` verändert, und kann jederzeit manuell über "Run workflow" im
Actions Tab gestartet werden. Ergebnis liegt dort als Artifact.
## Ein echtes Release veröffentlichen (mit Versionsnummer)
Ohne Versions-Tag baut die Cloud nur ein Artifact, das nach 30 Tagen automatisch
verschwindet. Für ein dauerhaftes, versioniertes GitHub Release:
1. Versionsnummer an drei Stellen anheben (muss überall gleich sein), z.B. von 0.1.0
auf 0.2.0:
- `tauri-app/package.json` -> `"version"`
- `tauri-app/src-tauri/Cargo.toml` -> `version = "..."`
- `tauri-app/src-tauri/tauri.conf.json` -> `"version"`
2. Änderungen committen wie gewohnt.
3. Einen Versions-Tag setzen und pushen:
```
git tag v0.2.0
git push origin v0.2.0
```
4. Der Tag-Push löst den Workflow erneut aus, baut den Installer und legt diesmal
zusätzlich automatisch ein GitHub Release mit dem Namen des Tags an, der NSIS
Installer (.exe) hängt als Download-Datei direkt am Release, dauerhaft, nicht nur
30 Tage.
## Wie Updates beim Nutzer ankommen
Genau wie bei NovaImage prüft NovaPhonic beim Start automatisch, ob eine neue Version
auf GitHub Releases liegt. Voraussetzung, damit das funktioniert:
1. Ein eigenes Signierschlüsselpaar erzeugen (Minisign):
```
npx @tauri-apps/cli signer generate
```
2. Den ausgegebenen öffentlichen Schlüssel in `tauri-app/src-tauri/tauri.conf.json`
unter `plugins.updater.pubkey` eintragen, anstelle des Platzhaltertexts.
3. Den privaten Schlüssel als GitHub Actions Secrets hinterlegen (Repository ->
Settings -> Secrets and variables -> Actions -> "New repository secret"):
- `TAURI_SIGNING_PRIVATE_KEY`: Inhalt der privaten Schlüsseldatei.
- `TAURI_SIGNING_PRIVATE_KEY_PASSWORD`: Passwort des Schlüssels (leer lassen, falls
ohne Passwort erzeugt, das Secret dann mit leerem Wert anlegen).
Ohne diese beiden Secrets schlägt der Release-Build bei einem Versions-Tag fehl.
## Deinstallieren
Ganz normal wie jedes andere Windows Programm, über Windows Einstellungen -> Apps ->
Installierte Apps -> "NovaPhonic" suchen -> Deinstallieren.
## Warum überhaupt eine eigene App
NovaPhonic bündelt drei separate Open Source Werkzeuge (auto-editor, DeepFilterNet,
FFmpeg) hinter einer einzigen, einfachen Bedienoberfläche mit Fortschrittsanzeige,
sodass niemand PowerShell Befehle von Hand eintippen muss.

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{
"name": "novaphonic",
"version": "0.1.0",
"private": true,
"scripts": {
"tauri": "tauri"
},
"devDependencies": {
"@tauri-apps/cli": "^2"
}
}

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[package]
name = "novaphonic"
version = "0.1.0"
edition = "2021"
description = "NovaPhonic, ein Tool von KI-WERKE zum automatischen Videoschnitt und zur Audio Veredelung"
[build-dependencies]
tauri-build = { version = "2", features = [] }
[dependencies]
tauri = { version = "2", features = [] }
serde = { version = "1", features = ["derive"] }
serde_json = "1"
rfd = "0.14"
tauri-plugin-updater = "2"
tauri-plugin-process = "2"
tauri-plugin-shell = "2"
[[bin]]
name = "novaphonic"
path = "src/main.rs"

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fn main() {
tauri_build::build()
}

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{
"$schema": "../gen/schemas/desktop-schema.json",
"identifier": "default",
"description": "Standard-Berechtigungen für das NovaPhonic Hauptfenster, inklusive Ausführung der drei gebündelten Sidecar Programme",
"windows": ["main"],
"permissions": [
"core:default",
"updater:default",
"process:default",
{
"identifier": "shell:allow-execute",
"allow": [
{ "name": "binaries/auto-editor", "sidecar": true },
{ "name": "binaries/deep-filter", "sidecar": true },
{ "name": "binaries/ffmpeg", "sidecar": true }
]
}
]
}

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#![cfg_attr(all(not(debug_assertions), target_os = "windows"), windows_subsystem = "windows")]
// NovaPhonic Kernlogik. Ruft drei eigenständige Programme (Sidecars) im Hintergrund
// auf: auto-editor (Schnitt), deep-filter/DeepFilterNet (Entrauschen), ffmpeg
// (Lautstärke Angleichung, Audio Extraktion, Remux). Es werden ausschließlich
// Dateipfade verarbeitet, nie Videoinhalte selbst in den Arbeitsspeicher der
// Oberfläche geladen.
//
// Wichtiger Hinweis für den ersten echten Build: In dieser Entwicklungsumgebung
// steht kein Rust Compiler zur Verfügung, dieser Code wurde also nicht kompiliert,
// nur sorgfältig von Hand geprüft. Zwei Stellen bitte beim ersten Testlauf gezielt
// gegenprüfen: 1) die genauen Kommandozeilen-Optionen von `deep-filter` (siehe
// `deep-filter --help`, hier als `-o <Zieldatei>` angenommen), 2) ob `auto-editor`
// den Flag `--no-open` in der installierten Version so kennt. Beides ist unten mit
// Kommentaren markiert.
use serde::{Deserialize, Serialize};
use std::fs;
use std::path::{Path, PathBuf};
use tauri::{AppHandle, Emitter};
use tauri_plugin_shell::process::CommandEvent;
use tauri_plugin_shell::ShellExt;
#[derive(Serialize)]
#[serde(rename_all = "camelCase")]
struct PickedFile {
path: String,
size_bytes: u64,
}
#[tauri::command]
fn pick_video_file() -> Option<PickedFile> {
let file = rfd::FileDialog::new()
.add_filter("Video", &["mp4", "mov", "mkv", "avi", "webm"])
.pick_file()?;
let size = fs::metadata(&file).map(|m| m.len()).unwrap_or(0);
Some(PickedFile {
path: file.to_string_lossy().to_string(),
size_bytes: size,
})
}
#[tauri::command]
fn save_output_as(source_path: String, suggested_name: String) -> Result<String, String> {
let dialog = rfd::FileDialog::new().set_file_name(&suggested_name);
match dialog.save_file() {
Some(dest) => {
fs::copy(&source_path, &dest)
.map_err(|e| format!("Konnte Datei nicht speichern: {e}"))?;
Ok(dest.to_string_lossy().to_string())
}
None => Err("abgebrochen".to_string()),
}
}
const SIDECARS: [(&str, &str); 3] = [
("binaries/auto-editor", "--version"),
("binaries/deep-filter", "--version"),
("binaries/ffmpeg", "-version"),
];
#[tauri::command]
async fn check_tools(app: AppHandle) -> Vec<String> {
let mut missing = Vec::new();
for (sidecar_name, version_flag) in SIDECARS {
let ok = match app.shell().sidecar(sidecar_name) {
Ok(cmd) => cmd
.args([version_flag])
.output()
.await
.map(|o| o.status.success())
.unwrap_or(false),
Err(_) => false,
};
if !ok {
// Kurzer, für Menschen lesbarer Name statt des internen Sidecar-Pfads.
let readable = sidecar_name.trim_start_matches("binaries/");
missing.push(readable.to_string());
}
}
missing
}
#[derive(Deserialize)]
#[serde(rename_all = "camelCase")]
struct ProcessOptions {
input_path: String,
margin_seconds: f64,
denoise: bool,
loudnorm: bool,
loudnorm_target: i32,
}
#[derive(Serialize)]
#[serde(rename_all = "camelCase")]
struct ProcessResult {
output_path: String,
}
#[derive(Clone, Serialize)]
struct ProgressPayload {
step: String,
status: String,
detail: Option<String>,
log: Option<String>,
}
fn emit_progress(
app: &AppHandle,
step: &str,
status: &str,
detail: Option<String>,
log: Option<String>,
) {
let _ = app.emit(
"pipeline-progress",
ProgressPayload {
step: step.to_string(),
status: status.to_string(),
detail,
log,
},
);
}
async fn run_sidecar(
app: &AppHandle,
sidecar_name: &str,
args: Vec<String>,
step: &str,
) -> Result<(), String> {
let cmd = app
.shell()
.sidecar(sidecar_name)
.map_err(|e| e.to_string())?
.args(args);
let (mut rx, _child) = cmd.spawn().map_err(|e| e.to_string())?;
while let Some(event) = rx.recv().await {
match event {
CommandEvent::Stdout(line) => {
emit_progress(
app,
step,
"running",
None,
Some(String::from_utf8_lossy(&line).trim().to_string()),
);
}
CommandEvent::Stderr(line) => {
emit_progress(
app,
step,
"running",
None,
Some(String::from_utf8_lossy(&line).trim().to_string()),
);
}
CommandEvent::Error(err) => {
return Err(err);
}
CommandEvent::Terminated(payload) => {
if payload.code != Some(0) {
return Err(format!(
"{sidecar_name} wurde mit Code {:?} beendet",
payload.code
));
}
}
_ => {}
}
}
Ok(())
}
#[tauri::command]
async fn process_video(app: AppHandle, options: ProcessOptions) -> Result<ProcessResult, String> {
let input = PathBuf::from(&options.input_path);
if !input.exists() {
return Err("Eingabedatei nicht gefunden.".to_string());
}
let stem = input
.file_stem()
.and_then(|s| s.to_str())
.unwrap_or("video");
let ext = input.extension().and_then(|s| s.to_str()).unwrap_or("mp4");
let parent = input.parent().unwrap_or_else(|| Path::new("."));
// ---------- 1) Schnitt (auto-editor) ----------
emit_progress(&app, "cut", "running", Some("startet…".into()), None);
let cut_path = parent.join(format!("{stem}_geschnitten.{ext}"));
let margin = format!("{}sec", options.margin_seconds);
run_sidecar(
&app,
"binaries/auto-editor",
vec![
input.to_string_lossy().to_string(),
"--margin".into(),
margin,
// Bitte beim ersten Testlauf prüfen, ob dieses Flag in der installierten
// auto-editor Version noch so heißt (verhindert, dass sich nach dem
// Schneiden automatisch ein Videoplayer öffnet).
"--no-open".into(),
"-o".into(),
cut_path.to_string_lossy().to_string(),
],
"cut",
)
.await
.map_err(|e| {
emit_progress(&app, "cut", "error", Some(e.clone()), None);
e
})?;
emit_progress(&app, "cut", "done", Some("fertig".into()), None);
let mut current = cut_path;
// ---------- 2) Entrauschen (DeepFilterNet), optional ----------
if options.denoise {
emit_progress(&app, "denoise", "running", Some("startet…".into()), None);
let raw_audio = parent.join(format!("{stem}_audio.wav"));
let denoised_audio = parent.join(format!("{stem}_entrauscht.wav"));
run_sidecar(
&app,
"binaries/ffmpeg",
vec![
"-y".into(),
"-i".into(),
current.to_string_lossy().to_string(),
"-vn".into(),
"-acodec".into(),
"pcm_s16le".into(),
"-ar".into(),
"48000".into(),
"-ac".into(),
"1".into(),
raw_audio.to_string_lossy().to_string(),
],
"denoise",
)
.await
.map_err(|e| {
emit_progress(&app, "denoise", "error", Some(e.clone()), None);
e
})?;
// Achtung, bitte gegen `deep-filter --help` prüfen: hier wird eine exakte
// Ausgabedatei per -o angenommen. Manche deep-filter Versionen erwarten
// stattdessen einen Ausgabeordner (z.B. -o <Ordner>), in dem eine Datei
// mit demselben Namen wie die Eingabe erzeugt wird. Falls das der Fall
// ist, muss diese Stelle entsprechend angepasst werden.
run_sidecar(
&app,
"binaries/deep-filter",
vec![
raw_audio.to_string_lossy().to_string(),
"-o".into(),
denoised_audio.to_string_lossy().to_string(),
],
"denoise",
)
.await
.map_err(|e| {
emit_progress(&app, "denoise", "error", Some(e.clone()), None);
e
})?;
let remuxed = parent.join(format!("{stem}_entrauscht_video.{ext}"));
run_sidecar(
&app,
"binaries/ffmpeg",
vec![
"-y".into(),
"-i".into(),
current.to_string_lossy().to_string(),
"-i".into(),
denoised_audio.to_string_lossy().to_string(),
"-map".into(),
"0:v:0".into(),
"-map".into(),
"1:a:0".into(),
"-c:v".into(),
"copy".into(),
"-shortest".into(),
remuxed.to_string_lossy().to_string(),
],
"denoise",
)
.await
.map_err(|e| {
emit_progress(&app, "denoise", "error", Some(e.clone()), None);
e
})?;
let _ = fs::remove_file(&raw_audio);
let _ = fs::remove_file(&denoised_audio);
let _ = fs::remove_file(&current);
current = remuxed;
emit_progress(&app, "denoise", "done", Some("fertig".into()), None);
} else {
emit_progress(&app, "denoise", "done", Some("übersprungen".into()), None);
}
// ---------- 3) Lautstärke & Klangbalance (FFmpeg loudnorm), optional ----------
let final_path = parent.join(format!("{stem}_nova.{ext}"));
if options.loudnorm {
emit_progress(&app, "loudnorm", "running", Some("startet…".into()), None);
// Bewusst Einzelpass-Loudnorm statt klassischem Zweipass-Verfahren: kein
// Parsen von FFmpeg Messwerten aus stderr nötig, dadurch robuster. Etwas
// weniger präzise als Zweipass, für Sprachaufnahmen in der Praxis meist
// ausreichend. Lässt sich als Ausbaustufe später nachrüsten.
let filter = format!("loudnorm=I={}:TP=-1.5:LRA=11", options.loudnorm_target);
run_sidecar(
&app,
"binaries/ffmpeg",
vec![
"-y".into(),
"-i".into(),
current.to_string_lossy().to_string(),
"-af".into(),
filter,
"-c:v".into(),
"copy".into(),
final_path.to_string_lossy().to_string(),
],
"loudnorm",
)
.await
.map_err(|e| {
emit_progress(&app, "loudnorm", "error", Some(e.clone()), None);
e
})?;
let _ = fs::remove_file(&current);
emit_progress(&app, "loudnorm", "done", Some("fertig".into()), None);
} else {
fs::rename(&current, &final_path).or_else(|_| fs::copy(&current, &final_path).map(|_| ()))
.map_err(|e| e.to_string())?;
emit_progress(&app, "loudnorm", "done", Some("übersprungen".into()), None);
}
Ok(ProcessResult {
output_path: final_path.to_string_lossy().to_string(),
})
}
fn main() {
tauri::Builder::default()
.plugin(tauri_plugin_updater::Builder::new().build())
.plugin(tauri_plugin_process::init())
.plugin(tauri_plugin_shell::init())
.invoke_handler(tauri::generate_handler![
pick_video_file,
save_output_as,
check_tools,
process_video
])
.run(tauri::generate_context!())
.expect("Fehler beim Starten der Tauri Anwendung");
}

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{
"$schema": "https://schema.tauri.app/config/2",
"productName": "NovaPhonic",
"version": "0.1.0",
"identifier": "com.kiwerkepro.novaphonic",
"build": {
"frontendDist": "../../app"
},
"app": {
"withGlobalTauri": true,
"windows": [
{
"title": "NovaPhonic, ein Tool von KI-WERKE",
"width": 1240,
"height": 900,
"minWidth": 960,
"minHeight": 700,
"resizable": true,
"dragDropEnabled": true
}
]
},
"bundle": {
"active": true,
"targets": ["nsis"],
"createUpdaterArtifacts": true,
"icon": [
"icons/32x32.png",
"icons/128x128.png",
"icons/128x128@2x.png",
"icons/icon.ico"
],
"externalBin": [
"binaries/auto-editor",
"binaries/deep-filter",
"binaries/ffmpeg"
],
"windows": {
"nsis": {
"installMode": "currentUser",
"languages": ["German"]
}
}
},
"plugins": {
"updater": {
"pubkey": "BITTE_EIGENEN_MINISIGN_PUBLIC_KEY_EINSETZEN_SIEHE_BAUANLEITUNG",
"endpoints": [
"https://github.com/kiwerkepro-org/novaphonic/releases/latest/download/latest.json"
]
}
}
}

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<!--
Nicht in Verwendung. Die Tauri App lädt direkt aus dem gemeinsamen
Quellordner ../../app (siehe src-tauri/tauri.conf.json, frontendDist).
Diese Datei bleibt nur als Platzhalter stehen, analog zu NovaImage.
-->