feat: fix frontend and activate imports

This commit is contained in:
2026-03-17 13:53:12 -03:00
parent be699ad6ab
commit 31939e31ad
24 changed files with 34 additions and 2117 deletions
-3
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@@ -36,9 +36,6 @@ MYSQL_DATABASE_URL=mysql://db_user:db_password@localhost:3306/external_database_
EXTERNAL_TABLE_GRADES=notas
EXTERNAL_ID_TIPO_NOTA=1
# Bark TTS API (Text-to-Speech for questions)
BARK_API_URL=http://t-800:8443
# Branding Defaults
DEFAULT_ORG_NAME="Norteamericano"
DEFAULT_PLATFORM_NAME="Norteamericano Learning"
-4
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@@ -290,10 +290,6 @@ if user_usage > DAILY_LIMIT {
- Gráficos de tendencia
- Comparativa mes a mes
4. **Integrar con Bark**
- Track tokens de audio generation
- Costos específicos de TTS
---
**Implementación: 100% Completa** 🎉
+11 -63
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@@ -1,4 +1,4 @@
# 🚀 Resumen de Implementación - Question Bank con Audio
# 🚀 Resumen de Implementación - Question Bank
## ✅ Estado de la Implementación
@@ -6,21 +6,18 @@
- ✅ Migración de base de datos con `skill_assessed`
- ✅ Endpoints CRUD para Question Bank
- ✅ Importación desde MySQL
- ✅ Generación de audio con Bark
- ✅ RAG con verificación de 4 habilidades
- ✅ Compilación exitosa (8 warnings menores)
- ✅ Compilación exitosa
### Frontend (TypeScript/React) - COMPLETO
### Frontend (TypeScript/React) - COMPLETO
- ✅ Página `/question-bank` con dashboard
- ✅ Componente QuestionBankCard con badge de skills
- ✅ QuestionBankEditor con generación IA de skills
- ✅ MySQLImportModal
- ✅ AudioGeneratorModal
- ✅ Navegación actualizada con link
- ✅ TypeScript: 3 errores menores (admin, no críticos)
### Infraestructura - LISTO PARA DESPLEGAR
- ✅ Scripts de instalación de Bark
### Infraestructura - LISTO
- ✅ install.sh actualizado con detección dev/prod
- ✅ Documentación completa
@@ -43,52 +40,19 @@ web/studio/src/app/question-bank/page.tsx (NUEVO)
web/studio/src/components/QuestionBank/QuestionBankCard.tsx (NUEVO)
web/studio/src/components/QuestionBank/QuestionBankEditor.tsx (NUEVO)
web/studio/src/components/QuestionBank/MySQLImportModal.tsx (NUEVO)
web/studio/src/components/QuestionBank/AudioGeneratorModal.tsx (NUEVO)
web/studio/src/components/Navbar.tsx (link agregado)
web/studio/src/lib/api.ts (API client)
```
### Scripts & Docs
```
scripts/install_bark_tts.sh (NUEVO)
scripts/deploy_to_t800.sh (NUEVO)
docs/BARK_TTS_GUIDE.md (NUEVO)
docs/QUESTION_BANK_UI.md (NUEVO)
docs/BARK_MANUAL_INSTALL.md (NUEVO)
install.sh (actualizado con Bark)
.env.example (BARK_API_URL agregado)
docs/EXCEL_IMPORT_TEMPLATE.md
install.sh (actualizado)
```
---
## 🔧 Instalación de Bark en t-800
### Opción Automática (Recomendada)
```bash
cd /home/juan/dev/openccb
./scripts/deploy_to_t800.sh
# Ingresar contraseña: apoca11
```
### Opción Manual
```bash
# Copiar script
scp scripts/install_bark_tts.sh juan@t-800:/tmp/
# Conectarse
ssh juan@t-800
# Ejecutar
sudo /tmp/install_bark_tts.sh
# Verificar
curl http://localhost:8000/health
```
**Ver documentación completa en:** `docs/BARK_MANUAL_INSTALL.md`
---
## 🎯 Características de 4 Habilidades
### Implementación
@@ -123,14 +87,12 @@ curl http://localhost:8000/health
**Desarrollo:**
```bash
BARK_API_URL=http://t-800:8000
OLLAMA_URL=http://t-800:11434
WHISPER_URL=http://t-800:9000
```
**Producción:**
```bash
BARK_API_URL=http://t-800.norteamericano.cl:8000
OLLAMA_URL=http://t-800.norteamericano.cl:11434
WHISPER_URL=http://t-800.norteamericano.cl:9000
```
@@ -147,8 +109,8 @@ GET /question-bank/{id} # Obtener pregunta
PUT /question-bank/{id} # Actualizar pregunta
DELETE /question-bank/{id} # Eliminar pregunta
POST /question-bank/import-mysql # Importar desde MySQL
POST /question-bank/{id}/generate-audio # Generar audio Bark
GET /question-bank/mysql-courses # Listar cursos MySQL
POST /question-bank/import-mysql-all # Importar todo desde MySQL
```
### Test Templates (actualizado)
@@ -175,12 +137,6 @@ npm run type-check
# ⚠️ 3 errores menores en admin (no afectan Question Bank)
```
### 3. Bark (después de instalar)
```bash
curl http://t-800:8000/health
# Expected: {"status":"healthy","service":"bark-tts"}
```
---
## 🎨 UI Features
@@ -201,25 +157,20 @@ curl http://t-800:8000/health
- 10 tipos de preguntas
- Generación IA con skills
- Tags automáticos
- Audio generation checkbox
---
## 📝 Próximos Pasos (Opcionales)
1. **Desplegar Bark en t-800**
- Ejecutar `./scripts/deploy_to_t800.sh`
- O seguir `docs/BARK_MANUAL_INSTALL.md`
2. **Filtrar errores de admin** (no críticos)
1. **Filtrar errores de admin** (no críticos)
- `getOrganizations` no existe
- `BrandingContext` type error
3. **Integración con Test Templates**
2. **Integración con Test Templates**
- Selector de preguntas desde banco
- Bulk selection
4. **Analytics de Skills**
3. **Analytics de Skills**
- Dashboard de distribución de skills
- Reportes por habilidad
@@ -231,10 +182,9 @@ curl http://t-800:8000/health
|------------|--------|-------|
| Backend Question Bank | ✅ 100% | Compila exitosamente |
| Frontend Question Bank | ✅ 95% | UI completa, 3 errores admin menores |
| Bark Scripts | ✅ 100% | Listos para desplegar |
| install.sh | ✅ 100% | Detecta dev/prod automáticamente |
| Skills Verification | ✅ 100% | Implementado en IA y BD |
| Documentación | ✅ 100% | 4 archivos docs completos |
| Documentación | ✅ 100% | Archivos docs completos |
**Progreso Total: 98%** 🎉
@@ -242,7 +192,5 @@ curl http://t-800:8000/health
## 📞 Soporte
- **Bark Installation**: `docs/BARK_MANUAL_INSTALL.md`
- **UI Usage**: `docs/QUESTION_BANK_UI.md`
- **Bark API**: `docs/BARK_TTS_GUIDE.md`
- **General**: `README.md` del proyecto
-206
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@@ -1,206 +0,0 @@
# Instalación Manual de Bark TTS en t-800
## Opción A: Instalación Automática (Recomendada)
```bash
# 1. Copiar script a t-800
scp scripts/install_bark_tts.sh juan@t-800:/tmp/install_bark_tts.sh
# 2. Conectarse a t-800
ssh juan@t-800
# 3. Ejecutar instalación
chmod +x /tmp/install_bark_tts.sh
sudo /tmp/install_bark_tts.sh
# 4. Verificar instalación
curl http://localhost:8000/health
```
## Opción B: Instalación Paso a Paso
```bash
# Conectarse a t-800
ssh juan@t-800
# Contraseña: apoca11
# Actualizar sistema
sudo apt-get update
sudo apt-get install -y python3 python3-pip python3-venv git ffmpeg curl
# Crear directorio
sudo mkdir -p /opt/bark
sudo chown juan:juan /opt/bark
cd /opt/bark
# Clonar Bark
git clone https://github.com/suno-ai/bark.git
cd bark
# Crear entorno virtual
python3 -m venv venv
source venv/bin/activate
# Instalar dependencias
pip install --upgrade pip
pip install -e .
pip install fastapi uvicorn[standard] python-multipart numpy scipy
# Crear archivo de API
cat > bark_api.py << 'PYEOF'
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import StreamingResponse
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
import numpy as np
import io
app = FastAPI(title="Bark TTS API", version="1.0.0")
print("Preloading Bark models...")
preload_models()
print("Models loaded!")
@app.get("/health")
async def health_check():
return {"status": "healthy", "service": "bark-tts"}
@app.get("/api/voices")
async def list_voices():
return {
"voices": [
{"id": "v2/en_speaker_0", "name": "English Speaker 0", "language": "en"},
{"id": "v2/en_speaker_1", "name": "English Speaker 1", "language": "en"},
{"id": "v2/en_speaker_6", "name": "English Speaker 6", "language": "en"},
{"id": "v2/es_speaker_0", "name": "Spanish Speaker 0", "language": "es"},
{"id": "v2/es_speaker_1", "name": "Spanish Speaker 1", "language": "es"},
{"id": "v2/es_speaker_3", "name": "Spanish Speaker 3", "language": "es"},
]
}
@app.post("/api/generate")
async def generate_speech(
text: str = Query(..., min_length=1, max_length=500),
voice: str = Query(default="v2/en_speaker_1"),
speed: float = Query(default=1.0, ge=0.5, le=2.0),
output_format: str = Query(default="wav", regex="^(mp3|wav|ogg)$")
):
try:
audio_array = generate_audio(text, history_prompt=voice)
if speed != 1.0:
new_length = int(len(audio_array) / speed)
audio_array = audio_array[:new_length]
audio_buffer = io.BytesIO()
write_wav(audio_buffer, SAMPLE_RATE, audio_array)
audio_buffer.seek(0)
return StreamingResponse(
audio_buffer,
media_type="audio/wav",
headers={"Content-Disposition": f"attachment; filename=speech.wav"}
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
PYEOF
# Crear servicio systemd
cat > /tmp/bark-tts.service << EOF
[Unit]
Description=Bark TTS API Server
After=network.target
[Service]
Type=simple
User=juan
Group=juan
WorkingDirectory=/opt/bark/bark
Environment="PATH=/opt/bark/bark/venv/bin"
ExecStart=/opt/bark/bark/venv/bin/uvicorn bark_api:app --host 0.0.0.0 --port 8000 --workers 1
Restart=always
RestartSec=10
MemoryMax=4G
MemoryHigh=3G
CPUQuota=80%
[Install]
WantedBy=multi-user.target
EOF
sudo mv /tmp/bark-tts.service /etc/systemd/system/
sudo systemctl daemon-reload
sudo systemctl enable bark-tts
sudo systemctl start bark-tts
# Verificar
sudo systemctl status bark-tts
curl http://localhost:8000/health
```
## Prueba de Funcionamiento
```bash
# Test básico
curl "http://localhost:8000/api/generate?text=Hello%20World&voice=v2/en_speaker_1" -o test.wav
# Test desde OpenCCB
curl http://t-800:8000/health
# Ver logs
sudo journalctl -u bark-tts -f
```
## Configuración en OpenCCB
Agregar a `.env`:
```bash
BARK_API_URL=http://t-800:8000
# O para producción:
# BARK_API_URL=http://t-800.norteamericano.cl:8000
```
## Solución de Problemas
### Error: "Out of Memory"
```bash
# Reducir límite de memoria en systemd
sudo systemctl edit bark-tts
# Agregar:
# [Service]
# MemoryMax=2G
```
### Error: "Model not found"
```bash
# Reinstalar modelos
cd /opt/bark/bark
source venv/bin/activate
python -c "from bark import preload_models; preload_models()"
```
### Servicio no inicia
```bash
# Ver logs
sudo journalctl -u bark-tts -n 50
# Reiniciar
sudo systemctl restart bark-tts
```
## URLs de Acceso
- **Health**: http://t-800:8000/health
- **Voices**: http://t-800:8000/api/voices
- **Generate**: http://t-800:8000/api/generate?text=Hello&voice=v2/en_speaker_1
## Producción (t-800.norteamericano.cl)
Para producción, asegurar que:
1. El puerto 8000 esté abierto en el firewall
2. El dominio t-800.norteamericano.cl apunte a la IP correcta
3. Usar BARK_API_URL=http://t-800.norteamericano.cl:8000
-221
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@@ -1,221 +0,0 @@
# Bark TTS Integration Guide
## Overview
OpenCCB now integrates with **Suno AI's Bark** text-to-speech system for generating audio versions of questions. This allows students to listen to questions instead of just reading them, improving accessibility and supporting different learning styles.
## Architecture
```
┌─────────────────┐ HTTP ┌─────────────────┐
│ OpenCCB CMS │ ────────────> │ Bark TTS API │
│ (PostgreSQL) │ <──────────── │ (Server t-800)│
│ │ Audio │ │
└─────────────────┘ └─────────────────┘
```
## Deployment to t-800 Server
### Prerequisites
- SSH access to t-800 server
- At least 8GB RAM recommended (Bark loads large models)
- 10GB free disk space
- Python 3.8+
- GPU optional (CUDA support for faster generation)
### Quick Deploy
```bash
# From your local machine
cd /home/juan/dev/openccb
./scripts/deploy_to_t800.sh
```
This will:
1. SSH into t-800
2. Install Python dependencies
3. Clone Bark repository
4. Set up systemd service
5. Start the API server
### Manual Deploy
```bash
# SSH into t-800
ssh juan@t-800
# Run installation script
wget https://raw.githubusercontent.com/suno-ai/bark/main/scripts/install.sh
sudo bash install.sh
```
## API Endpoints
Once deployed, Bark API is available at `http://t-800:8000`
### Health Check
```bash
curl http://t-800:8000/health
```
### List Available Voices
```bash
curl http://t-800:8000/api/voices
```
### Generate Speech
```bash
# Basic usage
curl "http://t-800:8000/api/generate?text=What%20color%20is%20the%20sky%3F" \
-o question.wav
# With specific voice and speed
curl "http://t-800:8000/api/generate?text=Hello%20World&voice=v2/en_speaker_6&speed=1.2" \
-o greeting.wav
# Spanish voice
curl "http://t-800:8000/api/generate?text=Hola%20mundo&voice=v2/es_speaker_0" \
-o saludo.wav
```
## Available Voices
### English Voices
- `v2/en_speaker_0` through `v2/en_speaker_9`
### Spanish Voices
- `v2/es_speaker_0` through `v2/es_speaker_9`
## Integration with OpenCCB
### Generate Audio for a Question
```bash
# Via API
curl -X POST "http://localhost:3001/question-bank/{question_id}/generate-audio" \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"text": "What color is the sky?",
"voice": "v2/en_speaker_1",
"speed": 1.0
}'
```
### Automatic Audio Generation
When creating a question:
```json
POST /question-bank
{
"question_text": "What is the capital of France?",
"question_type": "multiple-choice",
"options": ["Paris", "London", "Berlin", "Madrid"],
"correct_answer": 0,
"explanation": "Paris is the capital of France.",
"generate_audio": true // Triggers async audio generation
}
```
## Configuration
### Environment Variables
Add to your `.env` file:
```bash
# Bark TTS API URL
BARK_API_URL=http://t-800:8000
# Optional: Default voice for audio generation
BARK_DEFAULT_VOICE=v2/en_speaker_1
# Optional: Default speed
BARK_DEFAULT_SPEED=1.0
```
## Performance Optimization
### Model Preloading
Bark preloads models on startup (takes ~30 seconds). The systemd service handles this automatically.
### Memory Management
The systemd service includes memory limits:
```ini
MemoryMax=4G
MemoryHigh=3G
```
Adjust based on your server's capacity.
### Batch Generation
For importing many questions:
```bash
# Generate audio for multiple questions
curl "http://t-800:8000/api/generate/batch?texts=Question%201&texts=Question%202&voice=v2/en_speaker_1"
```
## Troubleshooting
### Service Not Starting
```bash
# Check status
sudo systemctl status bark-tts
# View logs
sudo journalctl -u bark-tts -f
# Restart service
sudo systemctl restart bark-tts
```
### Out of Memory
If Bark crashes due to memory:
1. Reduce `MemoryMax` in systemd service
2. Use smaller models: `suno/bark-small`
3. Process questions one at a time
### Slow Generation
- GPU acceleration: Install CUDA-enabled PyTorch
- Reduce audio quality settings
- Use shorter text segments
## Testing
```bash
# Test English voice
curl "http://t-800:8000/api/generate?text=The%20quick%20brown%20fox&voice=v2/en_speaker_1" | play -
# Test Spanish voice
curl "http://t-800:8000/api/generate?text=El%20rápido%20zorro%20marrón&voice=v2/es_speaker_0" | play -
```
## Security Notes
- Bark API runs on internal network only
- No authentication required (assumes trusted network)
- Rate limiting handled by OpenCCB
- Audio files stored in `uploads/audio/` directory
## Future Enhancements
- [ ] Add authentication to Bark API
- [ ] Support for custom voice cloning
- [ ] Audio preprocessing (noise reduction, normalization)
- [ ] Caching layer for repeated requests
- [ ] WebSocket support for streaming audio
## References
- [Bark GitHub](https://github.com/suno-ai/bark)
- [Bark Hugging Face](https://huggingface.co/suno/bark)
- [OpenCCB Question Bank Documentation](../docs/question-bank.md)
-40
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@@ -101,40 +101,6 @@ Modal para importar preguntas desde MySQL:
- Progreso de importación
- Resultado (éxito/error)
### 5. AudioGeneratorModal (`AudioGeneratorModal.tsx`)
Modal para generar audio con Bark TTS:
**Configuración:**
- Vista previa del texto de la pregunta
- Texto personalizable (opcional)
- Selector de voz (6 opciones: 3 inglés, 3 español)
- Control de velocidad (0.5x - 2.0x)
**Voces disponibles:**
```
Inglés:
- v2/en_speaker_0 (English Speaker 0)
- v2/en_speaker_1 (English Speaker 1) ← default
- v2/en_speaker_6 (English Speaker 6)
Español:
- v2/es_speaker_0 (Spanish Speaker 0)
- v2/es_speaker_1 (Spanish Speaker 1)
- v2/es_speaker_3 (Spanish Speaker 3)
```
**Estados:**
- ⏳ Generando... (polling cada 1s, max 30s)
- ✅ Audio generado (con preview play/pause)
- ❌ Error (mensaje descriptivo)
**Características:**
- Polling automático para verificar estado
- Reproductor de audio integrado
- Botón Play/Pause
- Indicador visual de estado
## Flujos de Usuario
### Crear Pregunta Manualmente
@@ -288,11 +254,6 @@ GET /question-bank/mysql-courses
- Verificar que `MYSQL_DATABASE_URL` esté configurado en `.env`
- Verificar conectividad al servidor MySQL
**Error: "Error al generar audio"**
- Verificar que Bark TTS esté corriendo en t-800
- Verificar que `BARK_API_URL` esté configurado
- Revisar logs de Bark: `ssh juan@t-800 && journalctl -u bark-tts -f`
**Audio no se reproduce**
- Verificar formato de audio (WAV soportado)
- Verificar permisos del navegador
@@ -301,5 +262,4 @@ GET /question-bank/mysql-courses
## Referencias
- [Question Bank Backend](../../services/cms-service/src/handlers_question_bank.rs)
- [Bark TTS Guide](../../docs/BARK_TTS_GUIDE.md)
- [Test Templates UI](./TestTemplates/)
-7
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@@ -120,11 +120,9 @@ echo "🔍 Configurando Servicios de IA Remota ($ENV_CHOICE)..."
if [ "$ENV_CHOICE" == "dev" ]; then
DEFAULT_OLLAMA="http://t-800:11434"
DEFAULT_WHISPER="http://t-800:9000"
DEFAULT_BARK="http://t-800:8000"
else
DEFAULT_OLLAMA="http://t-800.norteamericano.cl:11434"
DEFAULT_WHISPER="http://t-800.norteamericano.cl:9000"
DEFAULT_BARK="http://t-800.norteamericano.cl:8000"
fi
read -p "Ingrese la URL de Ollama Remoto [$DEFAULT_OLLAMA]: " REMOTE_OLLAMA_URL
@@ -133,27 +131,22 @@ read -p "Ingrese la URL de Whisper Remoto [$DEFAULT_WHISPER]: " REMOTE_WHISPER_U
REMOTE_WHISPER_URL=${REMOTE_WHISPER_URL:-$DEFAULT_WHISPER}
read -p "Ingrese la URL del Image Bridge Remoto [http://t-800:8080]: " REMOTE_IMAGE_URL
REMOTE_IMAGE_URL=${REMOTE_IMAGE_URL:-"http://t-800:8080"}
read -p "Ingrese la URL de Bark TTS Remoto [$DEFAULT_BARK]: " REMOTE_BARK_URL
REMOTE_BARK_URL=${REMOTE_BARK_URL:-$DEFAULT_BARK}
read -p "Ingrese el nombre del Modelo (en el servidor remoto) [llama3.2:3b]: " LLM_MODEL
LLM_MODEL=${LLM_MODEL:-llama3.2:3b}
update_env "AI_PROVIDER" "local"
update_env "LOCAL_LLM_MODEL" "$LLM_MODEL"
update_env "LOCAL_VIDEO_BRIDGE_URL" "$REMOTE_IMAGE_URL"
update_env "BARK_API_URL" "$REMOTE_BARK_URL"
if [ "$ENV_CHOICE" == "dev" ]; then
update_env "DEV_OLLAMA_URL" "$REMOTE_OLLAMA_URL"
update_env "DEV_WHISPER_URL" "$REMOTE_WHISPER_URL"
update_env "DEV_BARK_URL" "$REMOTE_BARK_URL"
# Portavilidad: set base URLs too
update_env "LOCAL_OLLAMA_URL" "$REMOTE_OLLAMA_URL"
update_env "LOCAL_WHISPER_URL" "$REMOTE_WHISPER_URL"
else
update_env "PROD_OLLAMA_URL" "$REMOTE_OLLAMA_URL"
update_env "PROD_WHISPER_URL" "$REMOTE_WHISPER_URL"
update_env "PROD_BARK_URL" "$REMOTE_BARK_URL"
# Portavilidad: set base URLs too
update_env "LOCAL_OLLAMA_URL" "$REMOTE_OLLAMA_URL"
update_env "LOCAL_WHISPER_URL" "$REMOTE_WHISPER_URL"
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@@ -1,69 +0,0 @@
#!/bin/bash
# Check and start Bark TTS service on t-800
echo "=== Checking Bark TTS Status on t-800 ==="
echo ""
# Check if systemd service exists
if systemctl list-unit-files | grep -q bark-tts; then
echo "✅ Bark systemd service found"
# Check service status
echo ""
echo "Service Status:"
sudo systemctl status bark-tts --no-pager
# If not running, try to start
if ! systemctl is-active --quiet bark-tts; then
echo ""
echo "⚠️ Service is not running. Attempting to start..."
sudo systemctl start bark-tts
sleep 5
if systemctl is-active --quiet bark-tts; then
echo "✅ Service started successfully!"
else
echo "❌ Failed to start service. Checking logs..."
echo ""
echo "Recent logs:"
sudo journalctl -u bark-tts -n 20 --no-pager
fi
else
echo "✅ Service is running"
fi
else
echo "❌ Bark systemd service not found"
echo ""
echo "The installation may not have completed successfully."
echo "Check if Bark is installed manually:"
echo ""
echo " ls -la /opt/bark/bark/"
echo " ps aux | grep uvicorn"
echo ""
echo "To install manually, run:"
echo " ssh juan@t-800"
echo " sudo /tmp/install_bark_tts.sh (if script exists)"
echo ""
fi
# Test API if service is running
if systemctl is-active --quiet bark-tts; then
echo ""
echo "=== Testing Bark API ==="
# Health check
echo "Health endpoint:"
curl -s http://localhost:8443/health | head -5
echo ""
echo ""
echo "Voices endpoint:"
curl -s http://localhost:8443/api/voices | head -10
echo ""
echo ""
echo "=== API is accessible ==="
echo "You can now generate audio with:"
echo " curl 'http://localhost:8443/api/generate?text=Hello%20World&voice=v2/en_speaker_1' -o test.wav"
fi
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@@ -1,193 +0,0 @@
#!/bin/bash
# Bark TTS Cleanup Script for t-800
# This script removes all Bark TTS components from the server
set -e
T800_HOST="t-800"
T800_USER="juan"
echo "=========================================="
echo " Bark TTS Cleanup for t-800"
echo "=========================================="
echo ""
echo "This script will completely remove Bark TTS from t-800"
echo "Including:"
echo " - Systemd service"
echo " - Installation directory (/opt/bark)"
echo " - User account (bark)"
echo " - All cached models (~3.6 GB)"
echo ""
read -p "Continue? [y/N]: " confirm
if [ "$confirm" != "y" ] && [ "$confirm" != "Y" ]; then
echo "❌ Cancelled"
exit 0
fi
echo ""
echo "📤 Copying cleanup script to t-800..."
# Create cleanup script
cat > /tmp/cleanup_bark_remote.sh << 'INNEREOF'
#!/bin/bash
set -e
echo ""
echo "=== Stopping Bark Service ==="
sudo systemctl stop bark-tts 2>/dev/null && echo "✅ Service stopped" || echo "⚠️ Service not running"
echo ""
echo "=== Disabling Bark Service ==="
sudo systemctl disable bark-tts 2>/dev/null && echo "✅ Service disabled" || echo "⚠️ Service not enabled"
echo ""
echo "=== Removing Systemd Service ==="
if [ -f /etc/systemd/system/bark-tts.service ]; then
sudo rm -f /etc/systemd/system/bark-tts.service
sudo systemctl daemon-reload
echo "✅ Systemd service removed"
else
echo "⚠️ Systemd service not found"
fi
echo ""
echo "=== Removing Installation Directory ==="
if [ -d /opt/bark ]; then
SIZE=$(du -sh /opt/bark 2>/dev/null | cut -f1)
echo "📊 Directory size: $SIZE"
sudo rm -rf /opt/bark
echo "✅ Directory removed"
else
echo "⚠️ Directory /opt/bark not found"
fi
echo ""
echo "=== Removing User Account ==="
if id bark &>/dev/null; then
sudo userdel -r bark 2>/dev/null && echo "✅ User removed" || echo "⚠️ Could not remove user"
else
echo "⚠️ User 'bark' does not exist"
fi
echo ""
echo "=== Cleaning Python Cache ==="
sudo rm -rf /root/.cache/pip 2>/dev/null || true
echo "✅ Cache cleaned"
echo ""
echo "=========================================="
echo " Verification"
echo "=========================================="
echo ""
echo "Services:"
if systemctl list-unit-files 2>/dev/null | grep -q bark; then
echo "❌ Bark services still exist:"
systemctl list-unit-files 2>/dev/null | grep bark
else
echo "✅ No Bark services found"
fi
echo ""
echo "Directories:"
if [ -d /opt/bark ]; then
echo "❌ Directory still exists: /opt/bark"
else
echo "✅ No Bark directories found"
fi
echo ""
echo "Users:"
if id bark &>/dev/null 2>&1; then
echo "❌ User 'bark' still exists"
else
echo "✅ User 'bark' removed"
fi
echo ""
echo "Processes:"
if ps aux | grep -v grep | grep -q "bark_api"; then
echo "❌ Bark processes still running"
ps aux | grep -v grep | grep "bark_api"
else
echo "✅ No Bark processes running"
fi
echo ""
echo "Ports:"
if sudo netstat -tlnp 2>/dev/null | grep -q 8443; then
echo "❌ Port 8443 still in use"
sudo netstat -tlnp 2>/dev/null | grep 8443
else
echo "✅ Port 8443 is free"
fi
echo ""
echo "Disk Space Recovered:"
echo "Previous: $(df -h /opt 2>/dev/null | tail -1 | awk '{print $4}') available"
echo ""
echo "=========================================="
echo " ✅ Cleanup Complete!"
echo "=========================================="
echo ""
echo "Next steps:"
echo " 1. Verify disk space: df -h"
echo " 2. Check available ports: sudo netstat -tlnp"
echo " 3. Continue with OpenCCB features"
echo ""
INNEREOF
# Copy to t-800
scp /tmp/cleanup_bark_remote.sh ${T800_USER}@${T800_HOST}:/tmp/cleanup_bark_remote.sh
echo ""
echo "🔌 Connecting to t-800 and running cleanup..."
echo ""
# Execute on t-800
ssh -t ${T800_USER}@${T800_HOST} << 'ENDSSH'
chmod +x /tmp/cleanup_bark_remote.sh
sudo /tmp/cleanup_bark_remote.sh
# Clean up temp file
rm /tmp/cleanup_bark_remote.sh
ENDSSH
echo ""
echo "=========================================="
echo " Local Cleanup Complete"
echo "=========================================="
echo ""
# Clean up local temp file
rm -f /tmp/cleanup_bark_remote.sh
echo "✅ All Bark TTS components have been removed from t-800"
echo ""
echo "📊 Next Steps - Choose What to Do Next:"
echo ""
echo " 1️⃣ Question Bank (sin audio)"
echo " - Crear preguntas manualmente"
echo " - Importar desde MySQL"
echo " - Generar con IA"
echo " - Acceder: /question-bank"
echo ""
echo " 2️⃣ Token Usage Dashboard"
echo " - Ver consumo de IA por usuario"
echo " - Monitorear costos"
echo " - Detectar alto consumo"
echo " - Acceder: /admin/token-usage"
echo ""
echo " 3️⃣ Importar Preguntas desde MySQL"
echo " - Traer preguntas del sistema legacy"
echo " - Marcar para no duplicar"
echo " - Asignar skills automáticamente"
echo ""
echo "💡 Recommended: Try all three!"
echo ""
echo " cd /home/juan/dev/openccb"
echo " # Start Studio"
echo " cd web/studio && npm run dev"
echo ""
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#!/bin/bash
# Deploy Bark TTS to t-800 server
# Usage: ./deploy_to_t800.sh
set -e
T800_HOST="t-800"
T800_USER="juan"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
echo "=========================================="
echo " Deploying Bark TTS to t-800"
echo "=========================================="
echo ""
# Check if SSH key exists
if [ ! -f ~/.ssh/id_rsa.pub ]; then
echo "SSH key not found. Generating one..."
ssh-keygen -t rsa -b 4096 -f ~/.ssh/id_rsa -N "" -C "openccb_bark_deployment"
echo ""
echo "Now copy your SSH key to t-800:"
echo " ssh-copy-id ${T800_USER}@${T800_HOST}"
echo ""
read -p "Press Enter after copying the key..."
fi
# Copy installation script to t-800
echo "Copying installation script to t-800..."
scp "${SCRIPT_DIR}/install_bark_tts.sh" ${T800_USER}@${T800_HOST}:/tmp/install_bark_tts.sh
# Execute installation on t-800 with pseudo-terminal
echo ""
echo "Connecting to t-800 and installing Bark TTS..."
echo "This may take 10-15 minutes depending on internet speed..."
echo "You'll be prompted for your password..."
echo ""
ssh -t ${T800_USER}@${T800_HOST} << 'ENDSSH'
echo "Connected to t-800"
echo "Hostname: $(hostname)"
echo "Memory: $(free -h | grep Mem | awk '{print $2}')"
echo "Disk: $(df -h / | tail -1 | awk '{print $4}') available"
echo ""
# Install jq if not present
if ! command -v jq &> /dev/null; then
echo "Installing jq..."
sudo apt-get update && sudo apt-get install -y jq
fi
# Make script executable and run
chmod +x /tmp/install_bark_tts.sh
echo "Running Bark installation..."
sudo /tmp/install_bark_tts.sh
# Clean up
rm /tmp/install_bark_tts.sh
# Wait for service to be ready
echo ""
echo "Waiting for Bark API to be ready..."
sleep 10
# Test the API
echo "Testing Bark API..."
if curl -s http://localhost:8443/health | jq . > /dev/null 2>&1; then
echo "✅ Bark API is running!"
curl -s http://localhost:8443/health | jq .
else
echo "⚠️ API may still be starting up..."
echo "Check status with: sudo systemctl status bark-tts"
echo "View logs with: sudo journalctl -u bark-tts -f"
fi
echo ""
echo "Bark TTS installation complete on t-800!"
ENDSSH
echo ""
echo "=========================================="
echo " Deployment Complete!"
echo "=========================================="
echo ""
echo "Next steps:"
echo "1. Add BARK_API_URL to your .env file:"
echo " BARK_API_URL=http://t-800:8443"
echo ""
echo "2. Test the API:"
echo " curl 'http://t-800:8443/api/generate?text=Hello%20World&voice=v2/en_speaker_1' -o test.wav"
echo ""
echo "3. Generate audio for questions in OpenCCB:"
echo " POST /question-bank/{id}/generate-audio"
echo ""
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#!/bin/bash
# Fix Bark PyTorch 2.6+ compatibility issue
# Run this on t-800
set -e
echo "=== Fixing Bark PyTorch 2.6+ Compatibility ==="
echo ""
BARK_DIR="/opt/bark/bark"
# Backup original generation.py
echo "[1/3] Backing up original generation.py..."
cp $BARK_DIR/bark/generation.py $BARK_DIR/bark/generation.py.backup
# Patch generation.py to use weights_only=False
echo "[2/3] Patching generation.py..."
sed -i 's/torch.load(ckpt_path, map_location=device)/torch.load(ckpt_path, map_location=device, weights_only=False)/g' $BARK_DIR/bark/generation.py
# Create fixed bark_api.py
echo "[3/3] Creating fixed bark_api.py..."
cat > $BARK_DIR/bark/bark_api.py << 'PYEOF'
"""
Bark TTS API Server - Fixed for PyTorch 2.6+
Simple FastAPI wrapper for Bark text-to-speech
"""
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import StreamingResponse
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
import numpy as np
import io
import torch
# Fix PyTorch 2.6+ weights_only issue
# This must be done BEFORE preload_models()
print("Configuring PyTorch for Bark compatibility...")
app = FastAPI(
title="Bark TTS API",
description="Text-to-Speech API using Suno AI's Bark",
version="1.0.0"
)
# Preload models on startup (with warm-up)
@app.on_event("startup")
async def startup_event():
print("Preloading Bark models...")
try:
preload_models()
print("Models loaded successfully!")
# Warm-up with a short generation
print("Warming up models with short generation...")
from bark import generate_text_semantic
text_semantic = generate_text_semantic("Hi", temp=0.7)
print("Warm-up complete! API ready.")
except Exception as e:
print(f"ERROR loading models: {e}")
raise
@app.get("/health")
async def health_check():
return {"status": "healthy", "service": "bark-tts"}
@app.get("/api/voices")
async def list_voices():
"""List available voice presets"""
return {
"voices": [
{"id": "v2/en_speaker_0", "name": "English Speaker 0", "language": "en"},
{"id": "v2/en_speaker_1", "name": "English Speaker 1", "language": "en"},
{"id": "v2/en_speaker_6", "name": "English Speaker 6", "language": "en"},
{"id": "v2/es_speaker_0", "name": "Spanish Speaker 0", "language": "es"},
{"id": "v2/es_speaker_1", "name": "Spanish Speaker 1", "language": "es"},
{"id": "v2/es_speaker_3", "name": "Spanish Speaker 3", "language": "es"},
]
}
@app.post("/api/generate")
async def generate_speech(
text: str = Query(..., min_length=1, max_length=500, description="Text to convert to speech"),
voice: str = Query(default="v2/en_speaker_1", description="Voice preset to use"),
speed: float = Query(default=1.0, ge=0.5, le=2.0, description="Speech speed multiplier"),
output_format: str = Query(default="wav", regex="^(mp3|wav|ogg)$", description="Output audio format")
):
"""Generate speech from text using Bark TTS"""
try:
# Generate audio
audio_array = generate_audio(text, history_prompt=voice)
# Apply speed adjustment if needed
if speed != 1.0:
new_length = int(len(audio_array) / speed)
audio_array = audio_array[:new_length]
# Convert to bytes
audio_buffer = io.BytesIO()
write_wav(audio_buffer, SAMPLE_RATE, audio_array)
audio_buffer.seek(0)
return StreamingResponse(
audio_buffer,
media_type="audio/wav",
headers={
"Content-Disposition": f"attachment; filename=speech.wav",
"X-Voice-Used": voice,
"X-Speed": str(speed),
"X-Duration-Seconds": str(len(audio_array) / SAMPLE_RATE)
}
)
except Exception as e:
print(f"Generation error: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/generate/batch")
async def generate_batch_speech(
texts: list[str] = Query(..., description="List of texts to convert"),
voice: str = Query(default="v2/en_speaker_1", description="Voice preset"),
speed: float = Query(default=1.0, description="Speech speed")
):
"""Generate multiple audio files in batch"""
results = []
for i, text in enumerate(texts):
try:
audio_array = generate_audio(text, history_prompt=voice)
# Save to temp file
import tempfile
with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
write_wav(f.name, SAMPLE_RATE, audio_array)
results.append({
"index": i,
"text": text,
"duration_seconds": len(audio_array) / SAMPLE_RATE,
"status": "success"
})
except Exception as e:
results.append({
"index": i,
"text": text,
"error": str(e),
"status": "failed"
})
return {"results": results}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
PYEOF
# Fix ownership
chown bark:bark $BARK_DIR/bark/generation.py
chown bark:bark $BARK_DIR/bark/bark_api.py
echo ""
echo "=== Patch Applied ==="
echo ""
echo "Restarting Bark service..."
systemctl restart bark-tts
echo ""
echo "Waiting for models to load (this takes 1-2 minutes)..."
sleep 30
echo ""
echo "Checking service status..."
systemctl status bark-tts --no-pager
echo ""
echo "Testing API..."
if curl -s http://localhost:8443/health | jq . > /dev/null 2>&1; then
echo "✅ Bark API is running!"
curl -s http://localhost:8443/health | jq .
else
echo "⚠️ API is still loading models..."
echo "Check logs with: journalctl -u bark-tts -f"
fi
echo ""
echo "=== Fix Complete ==="
echo ""
echo "If you see errors, check:"
echo " 1. journalctl -u bark-tts -f"
echo " 2. systemctl status bark-tts"
echo ""
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#!/bin/bash
# Manual Bark TTS Installation for t-800
# Run this ONCE on t-800 server
set -e
echo "=========================================="
echo " Manual Bark TTS Installation"
echo "=========================================="
echo ""
# Check if running as root or with sudo
if [ "$EUID" -ne 0 ]; then
echo "Please run with: sudo ./install_bark_manual.sh"
exit 1
fi
echo "[1/6] Installing system dependencies..."
apt-get update
apt-get install -y python3 python3-pip python3-venv git ffmpeg curl jq
echo ""
echo "[2/6] Creating bark user..."
if ! id -u bark > /dev/null 2>&1; then
useradd -r -m -s /bin/bash bark
echo "User 'bark' created"
else
echo "User 'bark' already exists"
fi
echo ""
echo "[3/6] Setting up application directory..."
BARK_DIR="/opt/bark"
mkdir -p $BARK_DIR
chown bark:bark $BARK_DIR
echo ""
echo "[4/6] Cloning Bark repository..."
cd $BARK_DIR
su - bark -c "cd $BARK_DIR && git clone https://github.com/suno-ai/bark.git"
chown -R bark:bark $BARK_DIR/bark
echo ""
echo "[5/6] Creating Python virtual environment and installing dependencies..."
cd $BARK_DIR/bark
su - bark -c "cd $BARK_DIR/bark && python3 -m venv venv"
su - bark -c "cd $BARK_DIR/bark && source venv/bin/activate && pip install --upgrade pip"
su - bark -c "cd $BARK_DIR/bark && source venv/bin/activate && pip install -e ."
su - bark -c "cd $BARK_DIR/bark && source venv/bin/activate && pip install fastapi uvicorn[standard] python-multipart numpy scipy"
echo ""
echo "[6/6] Creating systemd service..."
cat > /etc/systemd/system/bark-tts.service << EOF
[Unit]
Description=Bark TTS API Server
After=network.target
[Service]
Type=simple
User=bark
Group=bark
WorkingDirectory=$BARK_DIR/bark
Environment="PATH=$BARK_DIR/bark/venv/bin"
ExecStart=$BARK_DIR/bark/venv/bin/uvicorn bark_api:app --host 0.0.0.0 --port 8443 --workers 1
Restart=always
RestartSec=10
# Memory limits
MemoryMax=4G
MemoryHigh=3G
# CPU limits
CPUQuota=80%
[Install]
WantedBy=multi-user.target
EOF
# Create Bark API wrapper
cat > $BARK_DIR/bark/bark_api.py << 'PYEOF'
"""
Bark TTS API Server
Simple FastAPI wrapper for Bark text-to-speech
"""
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import StreamingResponse
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
import numpy as np
import io
app = FastAPI(
title="Bark TTS API",
description="Text-to-Speech API using Suno AI's Bark",
version="1.0.0"
)
# Preload models on startup
print("Preloading Bark models...")
preload_models()
print("Models loaded!")
@app.get("/health")
async def health_check():
return {"status": "healthy", "service": "bark-tts"}
@app.get("/api/voices")
async def list_voices():
"""List available voice presets"""
return {
"voices": [
{"id": "v2/en_speaker_0", "name": "English Speaker 0", "language": "en"},
{"id": "v2/en_speaker_1", "name": "English Speaker 1", "language": "en"},
{"id": "v2/en_speaker_6", "name": "English Speaker 6", "language": "en"},
{"id": "v2/es_speaker_0", "name": "Spanish Speaker 0", "language": "es"},
{"id": "v2/es_speaker_1", "name": "Spanish Speaker 1", "language": "es"},
{"id": "v2/es_speaker_3", "name": "Spanish Speaker 3", "language": "es"},
]
}
@app.post("/api/generate")
async def generate_speech(
text: str = Query(..., min_length=1, max_length=500, description="Text to convert to speech"),
voice: str = Query(default="v2/en_speaker_1", description="Voice preset to use"),
speed: float = Query(default=1.0, ge=0.5, le=2.0, description="Speech speed multiplier"),
output_format: str = Query(default="wav", regex="^(mp3|wav|ogg)$", description="Output audio format")
):
"""Generate speech from text using Bark TTS"""
try:
# Generate audio
audio_array = generate_audio(text, history_prompt=voice)
# Apply speed adjustment if needed
if speed != 1.0:
new_length = int(len(audio_array) / speed)
audio_array = audio_array[:new_length]
# Convert to bytes
audio_buffer = io.BytesIO()
write_wav(audio_buffer, SAMPLE_RATE, audio_array)
audio_buffer.seek(0)
return StreamingResponse(
audio_buffer,
media_type="audio/wav",
headers={
"Content-Disposition": f"attachment; filename=speech.wav",
"X-Voice-Used": voice,
"X-Speed": str(speed),
"X-Duration-Seconds": str(len(audio_array) / SAMPLE_RATE)
}
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
PYEOF
chown bark:bark $BARK_DIR/bark/bark_api.py
echo ""
echo "Enabling and starting service..."
systemctl daemon-reload
systemctl enable bark-tts
systemctl start bark-tts
echo ""
echo "=========================================="
echo " Installation Complete!"
echo "=========================================="
echo ""
echo "Service Status:"
systemctl status bark-tts --no-pager
echo ""
echo "Waiting for Bark to preload models (this takes 1-2 minutes)..."
sleep 30
echo ""
echo "Testing API..."
if curl -s http://localhost:8000/health | jq . > /dev/null 2>&1; then
echo "✅ Bark API is running!"
curl -s http://localhost:8000/health | jq .
else
echo "⚠️ API is starting up, models are loading..."
echo "Check status with: systemctl status bark-tts"
echo "View logs with: journalctl -u bark-tts -f"
fi
echo ""
echo "=========================================="
echo " Next Steps"
echo "=========================================="
echo ""
echo "1. Test the API:"
echo " curl 'http://localhost:8000/api/generate?text=Hello%20World&voice=v2/en_speaker_1' -o test.wav"
echo ""
echo "2. Check service status anytime:"
echo " systemctl status bark-tts"
echo ""
echo "3. View logs:"
echo " journalctl -u bark-tts -f"
echo ""
echo "4. Restart service if needed:"
echo " systemctl restart bark-tts"
echo ""
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#!/bin/bash
# Bark TTS Installation Script for t-800 server
# This script installs Suno AI's Bark text-to-speech system
set -e
echo "=========================================="
echo " Bark TTS Installation - Server t-800"
echo "=========================================="
# Check if running as root
if [ "$EUID" -ne 0 ]; then
echo "Please run as root (sudo ./install_bark.sh)"
exit 1
fi
# System requirements check
echo "[1/8] Checking system requirements..."
REQUIRED_RAM=8
AVAILABLE_RAM=$(free -g | awk '/^Mem:/{print $2}')
if [ $AVAILABLE_RAM -lt $REQUIRED_RAM ]; then
echo "WARNING: Bark requires at least ${REQUIRED_RAM}GB RAM (found: ${AVAILABLE_RAM}GB)"
echo "Continuing anyway, but performance may be poor..."
fi
# Update system packages
echo "[2/8] Updating system packages..."
apt-get update
apt-get install -y python3 python3-pip python3-venv git ffmpeg curl
# Create bark user
echo "[3/8] Creating bark user..."
if ! id -u bark > /dev/null 2>&1; then
useradd -r -m -s /bin/bash bark
echo "User 'bark' created"
else
echo "User 'bark' already exists"
fi
# Create application directory
echo "[4/8] Setting up application directory..."
BARK_DIR="/opt/bark"
mkdir -p $BARK_DIR
chown bark:bark $BARK_DIR
# Clone Bark repository
echo "[5/8] Cloning Bark repository..."
cd $BARK_DIR
if [ ! -d "bark" ]; then
su - bark -c "cd $BARK_DIR && git clone https://github.com/suno-ai/bark.git"
chown -R bark:bark $BARK_DIR/bark
else
echo "Bark repository already exists, updating..."
su - bark -c "cd $BARK_DIR/bark && git pull"
fi
# Create virtual environment
echo "[6/8] Creating Python virtual environment..."
cd $BARK_DIR/bark
su - bark -c "cd $BARK_DIR/bark && python3 -m venv venv"
# Install dependencies
echo "[7/8] Installing Python dependencies..."
su - bark -c "cd $BARK_DIR/bark && source venv/bin/activate && pip install --upgrade pip && pip install -e ."
# Additional dependencies for API server
su - bark -c "source $BARK_DIR/bark/venv/bin/activate && pip install fastapi uvicorn[standard] python-multipart numpy scipy"
# Create systemd service
echo "[8/8] Creating systemd service..."
cat > /etc/systemd/system/bark-tts.service << EOF
[Unit]
Description=Bark TTS API Server
After=network.target
[Service]
Type=simple
User=bark
Group=bark
WorkingDirectory=$BARK_DIR/bark
Environment="PATH=$BARK_DIR/bark/venv/bin"
ExecStart=$BARK_DIR/bark/venv/bin/uvicorn bark_api:app --host 0.0.0.0 --port 8000 --workers 1
Restart=always
RestartSec=10
# Memory limits
MemoryMax=4G
MemoryHigh=3G
# CPU limits
CPUQuota=80%
[Install]
WantedBy=multi-user.target
EOF
# Create Bark API wrapper
cat > $BARK_DIR/bark/bark_api.py << 'PYEOF'
"""
Bark TTS API Server
Simple FastAPI wrapper for Bark text-to-speech
"""
from fastapi import FastAPI, HTTPException, Query
from fastapi.responses import StreamingResponse, JSONResponse
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
import numpy as np
import io
import os
import tempfile
app = FastAPI(
title="Bark TTS API",
description="Text-to-Speech API using Suno AI's Bark",
version="1.0.0"
)
# Preload models on startup
print("Preloading Bark models...")
preload_models()
print("Models loaded!")
@app.get("/health")
async def health_check():
return {"status": "healthy", "service": "bark-tts"}
@app.get("/api/voices")
async def list_voices():
"""List available voice presets"""
return {
"voices": [
{"id": "v2/en_speaker_0", "name": "English Speaker 0", "language": "en"},
{"id": "v2/en_speaker_1", "name": "English Speaker 1", "language": "en"},
{"id": "v2/en_speaker_2", "name": "English Speaker 2", "language": "en"},
{"id": "v2/en_speaker_3", "name": "English Speaker 3", "language": "en"},
{"id": "v2/en_speaker_4", "name": "English Speaker 4", "language": "en"},
{"id": "v2/en_speaker_5", "name": "English Speaker 5", "language": "en"},
{"id": "v2/en_speaker_6", "name": "English Speaker 6", "language": "en"},
{"id": "v2/en_speaker_7", "name": "English Speaker 7", "language": "en"},
{"id": "v2/en_speaker_8", "name": "English Speaker 8", "language": "en"},
{"id": "v2/en_speaker_9", "name": "English Speaker 9", "language": "en"},
{"id": "v2/es_speaker_0", "name": "Spanish Speaker 0", "language": "es"},
{"id": "v2/es_speaker_1", "name": "Spanish Speaker 1", "language": "es"},
{"id": "v2/es_speaker_2", "name": "Spanish Speaker 2", "language": "es"},
{"id": "v2/es_speaker_3", "name": "Spanish Speaker 3", "language": "es"},
{"id": "v2/es_speaker_4", "name": "Spanish Speaker 4", "language": "es"},
{"id": "v2/es_speaker_5", "name": "Spanish Speaker 5", "language": "es"},
{"id": "v2/es_speaker_6", "name": "Spanish Speaker 6", "language": "es"},
{"id": "v2/es_speaker_7", "name": "Spanish Speaker 7", "language": "es"},
{"id": "v2/es_speaker_8", "name": "Spanish Speaker 8", "language": "es"},
{"id": "v2/es_speaker_9", "name": "Spanish Speaker 9", "language": "es"},
]
}
@app.post("/api/generate")
async def generate_speech(
text: str = Query(..., min_length=1, max_length=500, description="Text to convert to speech"),
voice: str = Query(default="v2/en_speaker_1", description="Voice preset to use"),
speed: float = Query(default=1.0, ge=0.5, le=2.0, description="Speech speed multiplier"),
output_format: str = Query(default="mp3", regex="^(mp3|wav|ogg)$", description="Output audio format")
):
"""Generate speech from text using Bark TTS"""
try:
# Extract speaker number from voice preset
parts = voice.split("_")
if len(parts) >= 3:
speaker = f"{parts[0]}_{parts[1]}_{parts[2]}"
else:
speaker = "v2/en_speaker_1"
# Generate audio
audio_array = generate_audio(text, history_prompt=speaker)
# Apply speed adjustment if needed
if speed != 1.0:
# Simple speed adjustment by resampling
new_length = int(len(audio_array) / speed)
audio_array = audio_array[:new_length]
# Convert to bytes
audio_buffer = io.BytesIO()
write_wav(audio_buffer, SAMPLE_RATE, audio_array)
audio_buffer.seek(0)
# For MP3 output, we'd need to add pydub/ffmpeg
# For now, return WAV
media_type = "audio/wav"
filename = f"speech_{voice}.{output_format}"
return StreamingResponse(
audio_buffer,
media_type=media_type,
headers={
"Content-Disposition": f"attachment; filename={filename}",
"X-Voice-Used": voice,
"X-Speed": str(speed),
"X-Duration-Seconds": str(len(audio_array) / SAMPLE_RATE)
}
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/generate/batch")
async def generate_batch_speech(
texts: list[str] = Query(..., description="List of texts to convert"),
voice: str = Query(default="v2/en_speaker_1", description="Voice preset"),
speed: float = Query(default=1.0, description="Speech speed")
):
"""Generate multiple audio files in batch"""
results = []
for i, text in enumerate(texts):
try:
audio_array = generate_audio(text, history_prompt=voice)
# Save to temp file
with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
write_wav(f.name, SAMPLE_RATE, audio_array)
results.append({
"index": i,
"text": text,
"duration_seconds": len(audio_array) / SAMPLE_RATE,
"status": "success"
})
except Exception as e:
results.append({
"index": i,
"text": text,
"error": str(e),
"status": "failed"
})
return JSONResponse(content={"results": results})
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
PYEOF
chown bark:bark $BARK_DIR/bark/bark_api.py
# Enable and start service
systemctl daemon-reload
systemctl enable bark-tts
systemctl start bark-tts
echo ""
echo "=========================================="
echo " Installation Complete!"
echo "=========================================="
echo ""
echo "Service Status:"
systemctl status bark-tts --no-pager
echo ""
echo "API Endpoints:"
echo " - Health: http://localhost:8000/health"
echo " - Voices: http://localhost:8000/api/voices"
echo " - Generate: http://localhost:8000/api/generate?text=Hello&voice=v2/en_speaker_1"
echo ""
echo "Usage Example:"
echo " curl 'http://localhost:8000/api/generate?text=What%20color%20is%20the%20sky%3F&voice=v2/en_speaker_1' -o question.wav"
echo ""
echo "Logs: journalctl -u bark-tts -f"
echo ""
@@ -43,19 +43,11 @@ pub async fn create_question(
.bind(payload.difficulty.as_deref().unwrap_or("medium"))
.bind(payload.tags.as_deref())
.bind(payload.skill_assessed.as_deref())
.bind(payload.media_url.as_deref())
.bind(payload.media_type.as_deref())
.fetch_one(&pool)
.await
.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
// If audio generation requested, trigger it asynchronously
if payload.generate_audio.unwrap_or(false) {
tokio::spawn(async move {
let _ = generate_audio_for_question(question.id, pool.clone()).await;
});
}
Ok(Json(question))
}
@@ -437,129 +429,6 @@ pub async fn import_from_mysql(
Ok(Json(imported_questions))
}
// ==================== Audio Generation ====================
/// POST /api/question-bank/{id}/generate-audio - Generate audio for a question using Bark
pub async fn generate_audio(
Org(org_ctx): Org,
Path(id): Path<Uuid>,
State(pool): State<PgPool>,
payload: Option<Json<common::models::GenerateAudioPayload>>,
) -> Result<StatusCode, (StatusCode, String)> {
// Get question
let question: QuestionBank = sqlx::query_as(
"SELECT * FROM question_bank WHERE id = $1 AND organization_id = $2"
)
.bind(id)
.bind(org_ctx.id)
.fetch_one(&pool)
.await
.map_err(|e| match e {
sqlx::Error::RowNotFound => (StatusCode::NOT_FOUND, "Question not found".to_string()),
_ => (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()),
})?;
// Spawn async task for audio generation
tokio::spawn(async move {
let _ = generate_audio_for_question_with_params(id, pool, payload.map(|p| p.0)).await;
});
Ok(StatusCode::ACCEPTED)
}
async fn generate_audio_for_question(
question_id: Uuid,
pool: PgPool,
) -> Result<(), String> {
generate_audio_for_question_with_params(question_id, pool, None).await
}
async fn generate_audio_for_question_with_params(
question_id: Uuid,
pool: PgPool,
payload: Option<common::models::GenerateAudioPayload>,
) -> Result<(), String> {
use reqwest::Client;
use serde_json::json;
// Get question text
let question_text: String = sqlx::query_scalar("SELECT audio_text FROM question_bank WHERE id = $1")
.bind(question_id)
.fetch_optional(&pool)
.await
.map_err(|e| format!("Failed to get question: {}", e))?
.unwrap_or_default();
let text = payload.as_ref().map(|p| p.text.clone()).unwrap_or(question_text);
// Update status to generating
sqlx::query("UPDATE question_bank SET audio_status = 'generating' WHERE id = $1")
.bind(question_id)
.execute(&pool)
.await
.map_err(|e| format!("Failed to update status: {}", e))?;
// Call Bark TTS API
let bark_url = std::env::var("BARK_API_URL").unwrap_or_else(|_| "http://localhost:8000".to_string());
let client = Client::new();
let voice = payload.as_ref().and_then(|p| p.voice.clone()).unwrap_or_else(|| "v2/en_speaker_1".to_string());
let speed = payload.as_ref().and_then(|p| p.speed).unwrap_or(1.0);
let response = client
.post(&format!("{}/api/generate", bark_url))
.json(&json!({
"text": text,
"voice": voice,
"speed": speed,
"output_format": "mp3"
}))
.send()
.await
.map_err(|e| format!("Bark API request failed: {}", e))?;
if !response.status().is_success() {
sqlx::query("UPDATE question_bank SET audio_status = 'failed' WHERE id = $1")
.bind(question_id)
.execute(&pool)
.await
.map_err(|_| "Failed to update status".to_string())?;
return Err(format!("Bark API returned error: {}", response.status()));
}
// Save audio file
let audio_bytes = response.bytes().await.map_err(|e| format!("Failed to get audio bytes: {}", e))?;
// Save to uploads directory
let filename = format!("question_{}.mp3", question_id);
let file_path = format!("uploads/audio/{}", filename);
std::fs::create_dir_all("uploads/audio").map_err(|e| format!("Failed to create directory: {}", e))?;
std::fs::write(&file_path, &audio_bytes).map_err(|e| format!("Failed to save audio: {}", e))?;
// Update question with audio URL
let audio_url = format!("/audio/{}", filename);
sqlx::query(
"UPDATE question_bank SET audio_url = $1, audio_status = 'ready', audio_metadata = $2 WHERE id = $3"
)
.bind(&audio_url)
.bind(&json!({
"voice": voice,
"speed": speed,
"generated_at": chrono::Utc::now().to_rfc3339(),
"file_size": audio_bytes.len(),
}))
.bind(question_id)
.execute(&pool)
.await
.map_err(|e| format!("Failed to update question: {}", e))?;
tracing::info!("Generated audio for question {}", question_id);
Ok(())
}
// ==================== Helpers ====================
fn map_mysql_question_type(mysql_type: i32) -> QuestionBankType {
+2 -10
View File
@@ -96,7 +96,7 @@ async fn main() {
});
let cors = CorsLayer::new()
.allow_origin(Any)
.allow_origin("http://localhost:3000".parse::<http::HeaderValue>().unwrap())
.allow_methods([Method::GET, Method::POST, Method::PUT, Method::DELETE, Method::OPTIONS, Method::PATCH])
.allow_headers([
header::CONTENT_TYPE,
@@ -104,7 +104,7 @@ async fn main() {
header::HeaderName::from_static("x-requested-with"),
header::HeaderName::from_static("x-organization-id"),
])
.expose_headers([header::CONTENT_LENGTH]);
.expose_headers([header::CONTENT_LENGTH, header::CONTENT_TYPE]);
// Rate limiting: Deshabilitado temporalmente por problemas de compatibilidad con tower-governor
// Para habilitar en producción, configurar con GovernorLayer y ajustar los límites apropiadamente
@@ -343,10 +343,6 @@ async fn main() {
"/question-bank/import-mysql",
post(handlers_question_bank::import_from_mysql),
)
.route(
"/question-bank/{id}/generate-audio",
post(handlers_question_bank::generate_audio),
)
.route(
"/question-bank/mysql-courses",
get(handlers_question_bank::list_mysql_courses),
@@ -392,10 +388,6 @@ async fn main() {
.route(
"/branding",
get(handlers_branding::get_organization_branding),
)
.route(
"/organization",
get(handlers::get_public_organization),
);
let public_routes = Router::new()
-8
View File
@@ -1408,7 +1408,6 @@ pub struct CreateQuestionBankPayload {
pub tags: Option<Vec<String>>,
pub media_url: Option<String>,
pub media_type: Option<String>,
pub generate_audio: Option<bool>,
pub skill_assessed: Option<String>, // reading, listening, speaking, writing
}
@@ -1433,13 +1432,6 @@ pub struct ImportQuestionFromMySQLPayload {
pub import_all: Option<bool>, // Import all questions from MySQL
}
#[derive(Debug, Serialize, Deserialize, Clone)]
pub struct GenerateAudioPayload {
pub text: String,
pub voice: Option<String>, // Bark voice preset
pub speed: Option<f32>,
}
#[derive(Debug, Serialize, Deserialize, Clone)]
pub struct QuestionBankFilters {
pub question_type: Option<QuestionBankType>,
+4 -4
View File
@@ -23,15 +23,15 @@ export default function AdminDashboard() {
useEffect(() => {
const fetchStats = async () => {
try {
// In a real app we'd have a specific stats endpoint,
// In a real app we'd have a specific stats endpoint,
// but for now we'll calculate from lists
const [orgs, users] = await Promise.all([
cmsApi.getOrganizations(),
const [org, users] = await Promise.all([
cmsApi.getOrganization(),
cmsApi.getAllUsers()
]);
setStats({
orgs: orgs.length,
orgs: 1, // Single tenant architecture
users: users.length,
courses: 0 // We'd need a global courses count
});
+3 -3
View File
@@ -29,12 +29,12 @@ export default function UsersPage() {
const loadData = async () => {
try {
const [usersData, orgsData] = await Promise.all([
const [usersData, orgData] = await Promise.all([
cmsApi.getAllUsers(),
cmsApi.getOrganizations()
cmsApi.getOrganization()
]);
setUsers(usersData);
setOrganizations(orgsData);
setOrganizations([orgData]); // Single tenant - wrap in array for compatibility
} catch (error) {
console.error('Failed to load data', error);
} finally {
+2 -29
View File
@@ -2,15 +2,14 @@
import React, { useState, useEffect } from 'react';
import { questionBankApi, QuestionBank, QuestionBankFilters, QuestionBankType } from '@/lib/api';
import {
Plus, Search, Filter, Edit2, Trash2, Volume2, VolumeX, Download,
import {
Plus, Search, Filter, Edit2, Trash2, Download,
Upload, Sparkles, ChevronDown, ChevronUp, X, Check, AlertCircle,
Headphones, BookOpen, Tag, Hash, Globe
} from 'lucide-react';
import QuestionBankEditor from '@/components/QuestionBank/QuestionBankEditor';
import QuestionBankCard from '@/components/QuestionBank/QuestionBankCard';
import MySQLImportModal from '@/components/QuestionBank/MySQLImportModal';
import AudioGeneratorModal from '@/components/QuestionBank/AudioGeneratorModal';
export default function QuestionBankPage() {
const [questions, setQuestions] = useState<QuestionBank[]>([]);
@@ -21,8 +20,6 @@ export default function QuestionBankPage() {
const [showEditor, setShowEditor] = useState(false);
const [editingQuestion, setEditingQuestion] = useState<QuestionBank | null>(null);
const [showImportModal, setShowImportModal] = useState(false);
const [showAudioModal, setShowAudioModal] = useState(false);
const [selectedForAudio, setSelectedForAudio] = useState<string | null>(null);
const loadQuestions = async () => {
try {
@@ -67,17 +64,6 @@ export default function QuestionBankPage() {
await loadQuestions();
};
const handleAudioGenerate = (questionId: string) => {
setSelectedForAudio(questionId);
setShowAudioModal(true);
};
const handleAudioSuccess = async () => {
setShowAudioModal(false);
setSelectedForAudio(null);
await loadQuestions();
};
const getQuestionTypeLabel = (type: QuestionBankType) => {
const labels: Record<QuestionBankType, string> = {
'multiple-choice': 'Opción Múltiple',
@@ -311,7 +297,6 @@ export default function QuestionBankPage() {
question={question}
onEdit={() => handleEdit(question)}
onDelete={() => handleDelete(question.id)}
onGenerateAudio={() => handleAudioGenerate(question.id)}
/>
))}
</div>
@@ -337,18 +322,6 @@ export default function QuestionBankPage() {
onCancel={() => setShowImportModal(false)}
/>
)}
{/* Audio Generator Modal */}
{showAudioModal && selectedForAudio && (
<AudioGeneratorModal
questionId={selectedForAudio}
onSuccess={handleAudioSuccess}
onCancel={() => {
setShowAudioModal(false);
setSelectedForAudio(null);
}}
/>
)}
</div>
);
}
@@ -1,320 +0,0 @@
'use client';
import React, { useState, useEffect } from 'react';
import { questionBankApi, QuestionBank } from '@/lib/api';
import { X, Volume2, Check, AlertCircle, Play, Pause } from 'lucide-react';
interface AudioGeneratorModalProps {
questionId: string;
onSuccess?: () => void;
onCancel?: () => void;
}
export default function AudioGeneratorModal({ questionId, onSuccess, onCancel }: AudioGeneratorModalProps) {
const [question, setQuestion] = useState<QuestionBank | null>(null);
const [loading, setLoading] = useState(true);
const [generating, setGenerating] = useState(false);
const [generated, setGenerated] = useState(false);
const [error, setError] = useState<string | null>(null);
const [isPlaying, setIsPlaying] = useState(false);
const [audio, setAudio] = useState<HTMLAudioElement | null>(null);
const [voice, setVoice] = useState('v2/en_speaker_1');
const [speed, setSpeed] = useState(1.0);
const [customText, setCustomText] = useState('');
const voices = [
{ id: 'v2/en_speaker_0', name: 'English Speaker 0', language: 'en' },
{ id: 'v2/en_speaker_1', name: 'English Speaker 1', language: 'en' },
{ id: 'v2/en_speaker_6', name: 'English Speaker 6', language: 'en' },
{ id: 'v2/es_speaker_0', name: 'Spanish Speaker 0', language: 'es' },
{ id: 'v2/es_speaker_1', name: 'Spanish Speaker 1', language: 'es' },
{ id: 'v2/es_speaker_3', name: 'Spanish Speaker 3', language: 'es' },
];
useEffect(() => {
loadQuestion();
}, [questionId]);
const loadQuestion = async () => {
try {
const data = await questionBankApi.get(questionId);
setQuestion(data);
setCustomText(data.question_text);
} catch (error) {
console.error('Failed to load question:', error);
setError('No se pudo cargar la pregunta');
} finally {
setLoading(false);
}
};
const handleGenerate = async () => {
try {
setGenerating(true);
setError(null);
await questionBankApi.generateAudio(questionId, customText, voice, speed);
// Poll for completion
let attempts = 0;
const maxAttempts = 30; // 30 seconds max
while (attempts < maxAttempts) {
await new Promise(resolve => setTimeout(resolve, 1000));
const updated = await questionBankApi.get(questionId);
if (updated.audio_status === 'ready') {
setGenerated(true);
setQuestion(updated);
break;
} else if (updated.audio_status === 'failed') {
setError('Error al generar el audio');
break;
}
attempts++;
}
if (attempts >= maxAttempts) {
setError('Tiempo de espera agotado. El audio puede estar generándose aún.');
}
} catch (error: any) {
console.error('Audio generation failed:', error);
setError(error.message || 'Error al generar audio');
} finally {
setGenerating(false);
}
};
const handlePlay = () => {
if (!question?.audio_url) return;
if (audio) {
audio.remove();
}
const audioEl = new Audio(question.audio_url);
audioEl.onended = () => setIsPlaying(false);
audioEl.onerror = () => {
setIsPlaying(false);
alert('Error al reproducir el audio');
};
setAudio(audioEl);
setIsPlaying(true);
audioEl.play();
};
const handleStop = () => {
if (audio) {
audio.pause();
audio.currentTime = 0;
}
setIsPlaying(false);
};
if (loading) {
return (
<div className="fixed inset-0 bg-black bg-opacity-50 flex items-center justify-center z-50 p-4">
<div className="bg-white dark:bg-gray-800 rounded-lg max-w-lg w-full p-8 text-center">
<div className="animate-spin rounded-full h-12 w-12 border-b-2 border-blue-600 mx-auto"></div>
<p className="mt-4 text-gray-600 dark:text-gray-400">Cargando pregunta...</p>
</div>
</div>
);
}
return (
<div className="fixed inset-0 bg-black bg-opacity-50 flex items-center justify-center z-50 p-4">
<div className="bg-white dark:bg-gray-800 rounded-lg max-w-2xl w-full">
{/* Header */}
<div className="flex items-center justify-between p-6 border-b border-gray-200 dark:border-gray-700">
<div className="flex items-center gap-3">
<Volume2 className="w-6 h-6 text-blue-600" />
<div>
<h2 className="text-xl font-bold text-gray-900 dark:text-white">
Generar Audio con Bark
</h2>
<p className="text-sm text-gray-500 dark:text-gray-400">
Convierte el texto de la pregunta a audio
</p>
</div>
</div>
<button
onClick={onCancel}
className="p-2 hover:bg-gray-100 dark:hover:bg-gray-700 rounded-lg transition-colors"
>
<X className="w-5 h-5" />
</button>
</div>
{/* Content */}
<div className="p-6 space-y-4">
{/* Question Preview */}
<div className="bg-gray-50 dark:bg-gray-700 rounded-lg p-4">
<label className="block text-xs font-medium text-gray-500 dark:text-gray-400 mb-1">
Texto de la pregunta
</label>
<p className="text-gray-900 dark:text-white text-sm">
{question?.question_text}
</p>
</div>
{/* Custom Text */}
<div>
<label className="block text-sm font-medium text-gray-700 dark:text-gray-300 mb-1">
Texto para audio (opcional)
</label>
<textarea
value={customText}
onChange={(e) => setCustomText(e.target.value)}
rows={2}
className="w-full px-3 py-2 border border-gray-300 dark:border-gray-600 rounded-lg focus:ring-2 focus:ring-blue-500 dark:bg-gray-700 dark:text-white"
placeholder="Deja en blanco para usar el texto de la pregunta"
/>
<p className="text-xs text-gray-500 dark:text-gray-400 mt-1">
Puedes personalizar el texto si quieres una pronunciación diferente
</p>
</div>
{/* Voice Selection */}
<div>
<label className="block text-sm font-medium text-gray-700 dark:text-gray-300 mb-1">
Voz
</label>
<select
value={voice}
onChange={(e) => setVoice(e.target.value)}
className="w-full px-3 py-2 border border-gray-300 dark:border-gray-600 rounded-lg focus:ring-2 focus:ring-blue-500 dark:bg-gray-700 dark:text-white"
>
{voices.map((v) => (
<option key={v.id} value={v.id}>
{v.name} ({v.language === 'en' ? 'Inglés' : 'Español'})
</option>
))}
</select>
</div>
{/* Speed */}
<div>
<label className="block text-sm font-medium text-gray-700 dark:text-gray-300 mb-1">
Velocidad
</label>
<div className="flex items-center gap-3">
<input
type="range"
min="0.5"
max="2.0"
step="0.1"
value={speed}
onChange={(e) => setSpeed(parseFloat(e.target.value))}
className="flex-1"
/>
<span className="text-sm font-medium text-gray-700 dark:text-gray-300 w-12 text-right">
{speed.toFixed(1)}x
</span>
</div>
</div>
{/* Audio Preview */}
{question?.audio_status === 'ready' && question.audio_url && (
<div className="bg-green-50 dark:bg-green-900/20 border border-green-200 dark:border-green-800 rounded-lg p-4">
<div className="flex items-center justify-between">
<div className="flex items-center gap-3">
<div className="w-10 h-10 bg-green-100 dark:bg-green-900/40 rounded-full flex items-center justify-center">
<Volume2 className="w-5 h-5 text-green-600" />
</div>
<div>
<p className="text-sm font-medium text-green-900 dark:text-green-100">
Audio generado
</p>
<p className="text-xs text-green-700 dark:text-green-300">
Haz click para escuchar
</p>
</div>
</div>
<button
onClick={isPlaying ? handleStop : handlePlay}
className="flex items-center gap-2 px-4 py-2 bg-green-600 text-white rounded-lg hover:bg-green-700 transition-colors"
>
{isPlaying ? <Pause className="w-4 h-4" /> : <Play className="w-4 h-4" />}
{isPlaying ? 'Detener' : 'Reproducir'}
</button>
</div>
</div>
)}
{/* Generating Status */}
{generating && (
<div className="bg-blue-50 dark:bg-blue-900/20 border border-blue-200 dark:border-blue-800 rounded-lg p-4">
<div className="flex items-center gap-3">
<div className="animate-spin rounded-full h-5 w-5 border-b-2 border-blue-600"></div>
<div>
<p className="text-sm font-medium text-blue-900 dark:text-blue-100">
Generando audio...
</p>
<p className="text-xs text-blue-700 dark:text-blue-300">
Esto puede tomar unos segundos
</p>
</div>
</div>
</div>
)}
{/* Error Message */}
{error && (
<div className="bg-red-50 dark:bg-red-900/20 border border-red-200 dark:border-red-800 rounded-lg p-4 flex items-center gap-3">
<AlertCircle className="w-5 h-5 text-red-600" />
<div>
<p className="text-sm font-medium text-red-900 dark:text-red-100">
Error
</p>
<p className="text-xs text-red-700 dark:text-red-300">
{error}
</p>
</div>
</div>
)}
{/* Success Message */}
{generated && (
<div className="bg-green-50 dark:bg-green-900/20 border border-green-200 dark:border-green-800 rounded-lg p-4 flex items-center gap-3">
<Check className="w-5 h-5 text-green-600" />
<div>
<p className="text-sm font-medium text-green-900 dark:text-green-100">
¡Audio generado exitosamente!
</p>
<p className="text-xs text-green-700 dark:text-green-300">
El audio está disponible para los estudiantes
</p>
</div>
</div>
)}
</div>
{/* Actions */}
<div className="p-6 border-t border-gray-200 dark:border-gray-700 flex items-center justify-end gap-3">
<button
type="button"
onClick={onCancel}
disabled={generating}
className="px-4 py-2 border border-gray-300 dark:border-gray-600 text-gray-700 dark:text-gray-300 rounded-lg hover:bg-gray-50 dark:hover:bg-gray-700 transition-colors disabled:opacity-50"
>
{generated ? 'Cerrar' : 'Cancelar'}
</button>
{!question?.audio_url && (
<button
onClick={handleGenerate}
disabled={generating || generated}
className="px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700 transition-colors flex items-center gap-2 disabled:opacity-50"
>
<Volume2 className="w-4 h-4" />
{generating ? 'Generando...' : 'Generar Audio'}
</button>
)}
</div>
</div>
</div>
);
}
@@ -2,6 +2,7 @@
import React, { useState, useEffect } from 'react';
import { X, Download, Database, Check, AlertCircle, Upload, FileSpreadsheet } from 'lucide-react';
import { apiFetch } from '@/lib/api';
import ExcelImportModal from './ExcelImportModal';
interface MySQLImportModalProps {
@@ -23,17 +24,13 @@ export default function MySQLImportModal({ onSuccess, onCancel }: MySQLImportMod
try {
setImporting(true);
setError(null);
const result = await fetch(`${process.env.NEXT_PUBLIC_CMS_API_URL || 'http://localhost:3001'}/question-bank/import-mysql-all`, {
const result = await apiFetch('/question-bank/import-mysql-all', {
method: 'POST',
headers: {
'Authorization': `Bearer ${localStorage.getItem('token')}`,
'Content-Type': 'application/json',
},
}).then(r => r.json());
});
setImportResult(result);
setTimeout(() => {
onSuccess?.();
}, 1500);
@@ -2,16 +2,15 @@
import React, { useState } from 'react';
import { QuestionBank } from '@/lib/api';
import { Edit2, Trash2, Volume2, VolumeX, Sparkles, Globe, MoreVertical, Play, Pause } from 'lucide-react';
import { Edit2, Trash2, Volume2, Sparkles, Globe } from 'lucide-react';
interface QuestionBankCardProps {
question: QuestionBank;
onEdit: () => void;
onDelete: () => void;
onGenerateAudio: () => void;
}
export default function QuestionBankCard({ question, onEdit, onDelete, onGenerateAudio }: QuestionBankCardProps) {
export default function QuestionBankCard({ question, onEdit, onDelete }: QuestionBankCardProps) {
const [isPlaying, setIsPlaying] = useState(false);
const [audio, setAudio] = useState<HTMLAudioElement | null>(null);
@@ -87,21 +86,13 @@ export default function QuestionBankCard({ question, onEdit, onDelete, onGenerat
</div>
</div>
<div className="flex items-center gap-1">
{question.audio_status === 'ready' ? (
{question.audio_url && (
<button
onClick={isPlaying ? handleStopAudio : handlePlayAudio}
className="p-1.5 text-green-600 hover:bg-green-50 dark:hover:bg-green-900/20 rounded transition-colors"
title={isPlaying ? 'Detener audio' : 'Reproducir audio'}
>
{isPlaying ? <Pause className="w-4 h-4" /> : <Volume2 className="w-4 h-4" />}
</button>
) : (
<button
onClick={onGenerateAudio}
className="p-1.5 text-gray-400 hover:text-blue-600 hover:bg-blue-50 dark:hover:bg-blue-900/20 rounded transition-colors"
title="Generar audio"
>
<VolumeX className="w-4 h-4" />
<Volume2 className="w-4 h-4" />
</button>
)}
<button
@@ -175,14 +166,6 @@ export default function QuestionBankCard({ question, onEdit, onDelete, onGenerat
</div>
)}
</div>
{question.audio_status === 'ready' && (
<span className="text-xs text-green-600 dark:text-green-400 flex items-center gap-1">
<Volume2 className="w-3 h-3" /> Audio listo
</span>
)}
{question.audio_status === 'generating' && (
<span className="text-xs text-yellow-600 dark:text-yellow-400">Generando audio...</span>
)}
</div>
{/* Usage Stats */}
@@ -22,7 +22,6 @@ export default function QuestionBankEditor({ question, onSuccess, onCancel }: Qu
tags: question?.tags || [],
media_url: question?.media_url,
media_type: question?.media_type,
generate_audio: false,
skill_assessed: question?.skill_assessed,
});
@@ -499,21 +498,6 @@ export default function QuestionBankEditor({ question, onSuccess, onCancel }: Qu
</div>
)}
{/* Audio Generation Option */}
<div className="flex items-center gap-3 p-3 bg-green-50 dark:bg-green-900/20 border border-green-200 dark:border-green-800 rounded-lg">
<input
type="checkbox"
id="generate_audio"
checked={formData.generate_audio}
onChange={(e) => setFormData({ ...formData, generate_audio: e.target.checked })}
className="w-4 h-4 text-green-600 rounded"
/>
<label htmlFor="generate_audio" className="flex items-center gap-2 text-sm text-green-800 dark:text-green-200">
<Volume2 className="w-4 h-4" />
Generar audio automáticamente con Bark después de guardar
</label>
</div>
{/* Actions */}
<div className="flex items-center justify-end gap-3 pt-6 border-t border-gray-200 dark:border-gray-700 sticky bottom-0 bg-white dark:bg-gray-800 -mx-6 px-6 py-4">
<button
+2 -4
View File
@@ -594,7 +594,7 @@ interface ApiFetchOptions extends RequestInit {
query?: Record<string, string | number | boolean | undefined | null>;
}
const apiFetch = (url: string, options: ApiFetchOptions = {}, isLms: boolean = false) => {
export const apiFetch = (url: string, options: ApiFetchOptions = {}, isLms: boolean = false) => {
const token = getToken();
const selectedOrgId = getSelectedOrgId();
const baseUrl = isLms ? LMS_API_BASE_URL : API_BASE_URL;
@@ -654,6 +654,7 @@ export const cmsApi = {
},
getSSOConfig: (): Promise<OrganizationSSOConfig> => apiFetch('/organization/sso'),
updateSSOConfig: (payload: Partial<OrganizationSSOConfig>): Promise<void> => apiFetch('/organization/sso', { method: 'PUT', body: JSON.stringify(payload) }),
getOrganization: (): Promise<Organization> => apiFetch('/organization'),
// Auth
register: (payload: AuthPayload): Promise<AuthResponse> => apiFetch('/auth/register', { method: 'POST', body: JSON.stringify(payload) }),
@@ -980,7 +981,6 @@ export interface CreateQuestionBankPayload {
tags?: string[];
media_url?: string;
media_type?: string;
generate_audio?: boolean;
skill_assessed?: string;
audio_url?: string;
audio_text?: string;
@@ -1015,8 +1015,6 @@ export const questionBankApi = {
apiFetch(`/question-bank/${id}`, { method: 'DELETE' }, false),
importFromMySQL: (courseId?: number, questionIds?: number[], importAll?: boolean): Promise<QuestionBank[]> =>
apiFetch('/question-bank/import-mysql', { method: 'POST', body: JSON.stringify({ mysql_course_id: courseId, question_ids: questionIds, import_all: importAll }) }, false),
generateAudio: (id: string, text?: string, voice?: string, speed?: number): Promise<void> =>
apiFetch(`/question-bank/${id}/generate-audio`, { method: 'POST', body: JSON.stringify({ text, voice, speed }) }, false),
};
export const lmsApi = {