Initial commit: Documentation Effi v1.0
- Structure complète du projet - Docker compose de production - Documentation organisée par thèmes - Guides d'installation et configuration - Section dépannage détaillée - Journal historique
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Folzo
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# 🎤 Configuration Audio (STT + TTS)
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## Vue d'ensemble
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Effi dispose d'un pipeline vocal complet fonctionnant sur **folzo-Corp** (PC Gaming avec RX 7800 XT) :
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- **STT** (Speech-to-Text) : Whisper via speaches avec ROCm
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- **TTS** (Text-to-Speech) : Piper/XTTS via openedai-speech
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---
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## STT - Speaches (Whisper)
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### Configuration Docker Compose
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Fichier : `~/speaches/docker-compose.yml` (sur folzo-Corp)
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```yaml
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services:
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speaches:
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image: speaches:rocm-ct2
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container_name: speaches-stt
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restart: unless-stopped
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ports:
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- "8200:8000"
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devices:
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- /dev/kfd
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- /dev/dri
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group_add:
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- "44"
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- "991"
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security_opt:
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- seccomp=unconfined
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environment:
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- HSA_OVERRIDE_GFX_VERSION=11.0.0
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- WHISPER__MODEL=deepdml/faster-whisper-large-v3-turbo-ct2
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- WHISPER__LANGUAGE=fr
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- WHISPER__COMPUTE_TYPE=float32
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- WHISPER__DEVICE=auto
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volumes:
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- speaches-models:/root/.cache/huggingface
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speaches-init:
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image: curlimages/curl:latest
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container_name: speaches-init
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restart: "no"
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depends_on:
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- speaches
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entrypoint: >
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sh -c "sleep 5 &&
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curl -sf -X POST http://speaches:8000/v1/models/deepdml%2Ffaster-whisper-large-v3-turbo-ct2 &&
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echo 'Modèle enregistré'"
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volumes:
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speaches-models:
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```
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### Modèle utilisé
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**`deepdml/faster-whisper-large-v3-turbo-ct2`**
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- Version optimisée CTranslate2
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- Support ROCm (GPU AMD)
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- Turbo = version rapide du large-v3
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- Langue : Français forcé (`fr`)
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### Points importants
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1. **Build personnalisé** : L'image `speaches:rocm-ct2` doit être construite localement
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2. **Architecture GPU** : gfx1100 (RX 7800 XT)
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3. **Compute type** : `float32` en CPU, `float16` en GPU
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4. **Initialisation** : Le service `speaches-init` enregistre le modèle au démarrage
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---
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## TTS - OpenedAI-Speech (Piper)
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### Configuration Docker Compose
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Fichier : `~/openedai-speech/docker-compose.yml` (sur folzo-Corp)
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```yaml
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services:
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openedai-speech:
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image: ghcr.io/matatonic/openedai-speech
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container_name: openedai-speech
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restart: unless-stopped
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ports:
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- "8100:8000"
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volumes:
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- ./tts-voices:/app/voices
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- ./tts-config:/app/config
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devices:
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- /dev/kfd
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- /dev/dri
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group_add:
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- "44"
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- "991"
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environment:
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- HSA_OVERRIDE_GFX_VERSION=11.0.0
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- HIP_VISIBLE_DEVICES=0
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```
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### Voix disponibles
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#### Piper (CPU - Recommandé pour usage standard)
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**Voix française** : `fr_FR-upmc-medium`
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```bash
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# Téléchargement
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cd ~/openedai-speech/tts-voices
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wget https://huggingface.co/rhasspy/piper-voices/resolve/main/fr/fr_FR/upmc/medium/fr_FR-upmc-medium.onnx
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wget https://huggingface.co/rhasspy/piper-voices/resolve/main/fr/fr_FR/upmc/medium/fr_FR-upmc-medium.onnx.json
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```
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Configuration (`tts-config/config.yaml`) :
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```yaml
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tts-1:
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alloy:
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model: voices/fr_FR-upmc-medium.onnx
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speaker: 0 # 0 = voix féminine
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```
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### Points importants
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1. **group_add numériques** : Utiliser `"44"` et `"991"` (pas les noms)
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2. **ROCm activé** : `HSA_OVERRIDE_GFX_VERSION=11.0.0`
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3. **Fallback CPU** : Piper fonctionne aussi en CPU si GPU indisponible
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---
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## Configuration Open WebUI
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**Admin Panel → Settings → Audio**
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### Paramètres STT
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| Paramètre | Valeur |
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|-----------|--------|
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| Engine | `OpenAI` |
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| URL | `http://192.168.1.11:8200/v1` |
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| Model | `deepdml/faster-whisper-large-v3-turbo-ct2` |
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| API Key | `anything` (valeur quelconque) |
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### Paramètres TTS
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| Paramètre | Valeur |
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|-----------|--------|
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| Engine | `OpenAI` |
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| URL | `http://192.168.1.11:8100/v1` |
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| Model | `tts-1` (Piper) ou `tts-1-hd` (XTTS) |
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| Voice | `alloy` |
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---
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## Build CTranslate2 ROCm (speaches)
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### Pourquoi un build personnalisé ?
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L'image officielle speaches ne publie pas d'image ROCm. Il faut builder CTranslate2 depuis les sources avec :
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- Support MIOpen (équivalent ROCm de cuDNN)
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- Architecture gfx1100 (RX 7800 XT)
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### Procédure de build
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```bash
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# 1. Cloner le repo
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cd ~
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git clone https://github.com/speaches-ai/speaches.git
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cd speaches
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# 2. Modifier le Dockerfile pour gfx1100
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cd src
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sed -i 's/gfx1101/gfx1100/g' Dockerfile.rocm-ct2
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# 3. Build (~50 min la première fois)
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docker build -f Dockerfile.rocm-ct2 -t speaches:rocm-ct2 .
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```
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### Architecture GPU
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Vérifier votre architecture :
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```bash
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docker run --device /dev/kfd --device /dev/dri \
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-e HSA_OVERRIDE_GFX_VERSION=11.0.0 speaches:rocm-ct2 \
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/opt/rocm-6.3.4/bin/rocminfo | grep -E "gfx|Name"
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```
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Cartes courantes :
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- RX 7800 XT : `gfx1100`
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- RX 7900 XTX : `gfx1100`
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- RX 7700 XT : `gfx1101`
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---
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## Dépannage audio
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### Erreur : "float16 not supported on CPU backend"
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**Solution** : Changer `WHISPER__COMPUTE_TYPE` :
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```yaml
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environment:
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- WHISPER__COMPUTE_TYPE=int8 # ou float32
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```
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### Erreur : "Unable to find group render"
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**Solution** : Utiliser les GID numériques :
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```yaml
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group_add:
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- "44" # video
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- "991" # render
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```
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### Erreur : "hipErrorInvalidDeviceFunction"
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**Cause** : Mauvaise architecture GPU dans le build
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**Solution** : Rebuilder avec la bonne valeur gfx (voir section Build)
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---
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## Performance attendue
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| Composant | Mode | Latence | Notes |
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|-----------|------|---------|-------|
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| STT | CPU (int8) | ~10s pour 5s audio | Utilisation 100% CPU |
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| STT | GPU (ROCm) | ~1s pour 5s audio | Objectif après rebuild |
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| TTS Piper | CPU | ~300ms | Léger, utilisable |
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| TTS XTTS | GPU | ~500ms-2s | Qualité supérieure |
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