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Audio-Classifier/backend/src/api/routes/analyze.py
Benoit 95194eadfc initial commit
 Ce qui a été implémenté
Backend Python (FastAPI)
 Architecture complète avec FastAPI
 Extraction de features audio avec Librosa (tempo, key, spectral features, energy, danceability, valence)
 Classification intelligente avec Essentia (genre, mood, instruments)
 Base de données PostgreSQL + pgvector (prête pour embeddings)
 API REST complète (tracks, search, similar, analyze, audio streaming/download)
 Génération de waveform pour visualisation
 Scanner de dossiers avec analyse parallèle
 Jobs d'analyse en arrière-plan
 Migrations Alembic
Frontend Next.js 14
 Interface utilisateur moderne avec TailwindCSS
 Client API TypeScript complet
 Page principale avec liste des pistes
 Statistiques globales
 Recherche et filtres
 Streaming et téléchargement audio
 Pagination
Infrastructure
 Docker Compose (PostgreSQL + Backend)
 Script de téléchargement des modèles Essentia
 Variables d'environnement configurables
 Documentation complète
📁 Structure Finale
Audio Classifier/
├── backend/
│   ├── src/
│   │   ├── core/                    # Audio processing
│   │   ├── models/                  # Database models
│   │   ├── api/                     # FastAPI routes
│   │   └── utils/                   # Config, logging
│   ├── models/                      # Essentia .pb files
│   ├── requirements.txt
│   ├── Dockerfile
│   └── alembic.ini
├── frontend/
│   ├── app/                         # Next.js pages
│   ├── components/                  # React components
│   ├── lib/                         # API client, types
│   └── package.json
├── scripts/
│   └── download-essentia-models.sh
├── docker-compose.yml
├── README.md
├── SETUP.md                         # Guide détaillé
├── QUICKSTART.md                    # Démarrage rapide
└── .claude-todo.md                  # Documentation technique
🚀 Pour Démarrer
3 commandes suffisent :
# 1. Télécharger modèles IA
./scripts/download-essentia-models.sh

# 2. Configurer et lancer backend
cp .env.example .env  # Éditer AUDIO_LIBRARY_PATH
docker-compose up -d

# 3. Lancer frontend
cd frontend && npm install && npm run dev
🎯 Fonctionnalités Clés
 CPU-only : Fonctionne sans GPU  100% local : Aucune dépendance cloud  Analyse complète : Genre, mood, tempo, instruments, energy  Recherche avancée : Texte + filtres (BPM, genre, mood, energy)  Recommandations : Pistes similaires  Streaming audio : Lecture directe dans le navigateur  Téléchargement : Export des fichiers originaux  API REST : Documentation interactive sur /docs
📊 Performance
~2-3 secondes par fichier (CPU 4 cores)
Analyse parallèle (configurable via ANALYSIS_NUM_WORKERS)
Formats supportés : MP3, WAV, FLAC, M4A, OGG
📖 Documentation
README.md : Vue d'ensemble
QUICKSTART.md : Démarrage en 5 minutes
SETUP.md : Guide complet + troubleshooting
API Docs : http://localhost:8000/docs (après lancement)
Le projet est prêt à être utilisé ! 🎵
2025-11-27 13:54:34 +01:00

218 lines
5.5 KiB
Python

"""Analysis job endpoints."""
from fastapi import APIRouter, Depends, HTTPException, BackgroundTasks
from sqlalchemy.orm import Session
from pydantic import BaseModel
from typing import Dict, Optional
from uuid import uuid4
import asyncio
from ...models.database import get_db
from ...models import crud
from ...core.analyzer import AudioAnalyzer
from ...utils.logging import get_logger
from ...utils.validators import validate_directory_path
router = APIRouter()
logger = get_logger(__name__)
# In-memory job storage (in production, use Redis)
jobs: Dict[str, dict] = {}
class AnalyzeFolderRequest(BaseModel):
"""Request to analyze a folder."""
path: str
recursive: bool = True
class JobStatus(BaseModel):
"""Analysis job status."""
job_id: str
status: str # pending, running, completed, failed
progress: int
total: int
current_file: Optional[str] = None
errors: list = []
def analyze_folder_task(job_id: str, path: str, recursive: bool, db_url: str):
"""Background task to analyze folder.
Args:
job_id: Job UUID
path: Directory path
recursive: Scan recursively
db_url: Database URL for new session
"""
from ...models.database import SessionLocal
try:
logger.info(f"Starting analysis job {job_id} for {path}")
# Update job status
jobs[job_id]["status"] = "running"
# Create analyzer
analyzer = AudioAnalyzer()
# Progress callback
def progress_callback(current: int, total: int, filename: str):
jobs[job_id]["progress"] = current
jobs[job_id]["total"] = total
jobs[job_id]["current_file"] = filename
# Analyze folder
results = analyzer.analyze_folder(
path=path,
recursive=recursive,
progress_callback=progress_callback,
)
# Save to database
db = SessionLocal()
try:
saved_count = 0
for analysis in results:
try:
crud.upsert_track(db, analysis)
saved_count += 1
except Exception as e:
logger.error(f"Failed to save track {analysis.filename}: {e}")
jobs[job_id]["errors"].append({
"file": analysis.filename,
"error": str(e)
})
logger.info(f"Job {job_id} completed: {saved_count}/{len(results)} tracks saved")
# Update job status
jobs[job_id]["status"] = "completed"
jobs[job_id]["progress"] = len(results)
jobs[job_id]["total"] = len(results)
jobs[job_id]["current_file"] = None
jobs[job_id]["saved_count"] = saved_count
finally:
db.close()
except Exception as e:
logger.error(f"Job {job_id} failed: {e}")
jobs[job_id]["status"] = "failed"
jobs[job_id]["errors"].append({
"error": str(e)
})
@router.post("/folder")
async def analyze_folder(
request: AnalyzeFolderRequest,
background_tasks: BackgroundTasks,
db: Session = Depends(get_db),
):
"""Start folder analysis job.
Args:
request: Folder analysis request
background_tasks: FastAPI background tasks
db: Database session
Returns:
Job ID for status tracking
Raises:
HTTPException: 400 if path is invalid
"""
# Validate path
validated_path = validate_directory_path(request.path)
if not validated_path:
raise HTTPException(
status_code=400,
detail=f"Invalid or inaccessible directory: {request.path}"
)
# Create job
job_id = str(uuid4())
jobs[job_id] = {
"job_id": job_id,
"status": "pending",
"progress": 0,
"total": 0,
"current_file": None,
"errors": [],
"path": validated_path,
"recursive": request.recursive,
}
# Get database URL for background task
from ...utils.config import settings
# Start background task
background_tasks.add_task(
analyze_folder_task,
job_id,
validated_path,
request.recursive,
settings.DATABASE_URL,
)
logger.info(f"Created analysis job {job_id} for {validated_path}")
return {
"job_id": job_id,
"message": "Analysis job started",
"path": validated_path,
"recursive": request.recursive,
}
@router.get("/status/{job_id}")
async def get_job_status(job_id: str):
"""Get analysis job status.
Args:
job_id: Job UUID
Returns:
Job status
Raises:
HTTPException: 404 if job not found
"""
if job_id not in jobs:
raise HTTPException(status_code=404, detail="Job not found")
job_data = jobs[job_id]
return {
"job_id": job_data["job_id"],
"status": job_data["status"],
"progress": job_data["progress"],
"total": job_data["total"],
"current_file": job_data.get("current_file"),
"errors": job_data.get("errors", []),
"saved_count": job_data.get("saved_count"),
}
@router.delete("/job/{job_id}")
async def delete_job(job_id: str):
"""Delete job from memory.
Args:
job_id: Job UUID
Returns:
Success message
Raises:
HTTPException: 404 if job not found
"""
if job_id not in jobs:
raise HTTPException(status_code=404, detail="Job not found")
del jobs[job_id]
return {"message": "Job deleted", "job_id": job_id}