diff --git a/.claude-todo.md b/.claude-todo.md
index 6e5f9bd..8be196d 100644
--- a/.claude-todo.md
+++ b/.claude-todo.md
@@ -1,615 +1,264 @@
-# Audio Classifier - Technical Implementation TODO
+# Audio Classifier - TODO Mise à Jour (6 décembre 2024)
 
-## Phase 1: Project Structure & Dependencies
+## ✅ Ce qui est FAIT (État actuel du projet)
 
-### 1.1 Root structure
-- [ ] Create root `.gitignore`
-- [ ] Create root `README.md` with setup instructions
-- [ ] Create `docker-compose.yml` (PostgreSQL + pgvector)
-- [ ] Create `.env.example`
+### Infrastructure
+- ✅ Structure complète backend + frontend
+- ✅ Docker Compose avec PostgreSQL + pgvector
+- ✅ Backend Dockerfile (Python 3.9, émulation x86_64 pour Essentia)
+- ✅ Frontend Dockerfile
+- ✅ Containers en production (running actuellement)
+- ✅ .env et .env.example configurés
+- ✅ Modèles Essentia téléchargés (genre, mood, instrument)
 
-### 1.2 Backend structure (Python/FastAPI)
-- [ ] Create `backend/` directory
-- [ ] Create `backend/requirements.txt`:
-  - fastapi==0.109.0
-  - uvicorn[standard]==0.27.0
-  - sqlalchemy==2.0.25
-  - psycopg2-binary==2.9.9
-  - pgvector==0.2.4
-  - librosa==0.10.1
-  - essentia-tensorflow==2.1b6.dev1110
-  - pydantic==2.5.3
-  - pydantic-settings==2.1.0
-  - python-multipart==0.0.6
-  - mutagen==1.47.0
-  - numpy==1.24.3
-  - scipy==1.11.4
-- [ ] Create `backend/pyproject.toml` (optional, for poetry users)
-- [ ] Create `backend/.env.example`
-- [ ] Create `backend/Dockerfile`
-- [ ] Create `backend/src/__init__.py`
+### Backend (Python/FastAPI)
+- ✅ Structure complète src/
+- ✅ Modèles SQLAlchemy (schema.py) avec AudioTrack
+- ✅ Migrations Alembic fonctionnelles
+- ✅ CRUD complet (crud.py)
+- ✅ API FastAPI (main.py)
+- ✅ Routes implémentées :
+  - ✅ /api/tracks (GET, DELETE)
+  - ✅ /api/search
+  - ✅ /api/audio (stream, download, waveform)
+  - ✅ /api/analyze
+  - ✅ /api/similar
+  - ✅ /api/stats
+- ✅ Core modules :
+  - ✅ audio_processor.py (Librosa)
+  - ✅ essentia_classifier.py (modèles genre/mood/instruments)
+  - ✅ analyzer.py (orchestrateur)
+  - ✅ file_scanner.py
+  - ✅ waveform_generator.py
+- ✅ Utils (config, logging, validators)
+- ✅ CLI scanner fonctionnel
 
-### 1.3 Backend core modules structure
-- [ ] `backend/src/core/__init__.py`
-- [ ] `backend/src/core/audio_processor.py` - librosa feature extraction
-- [ ] `backend/src/core/essentia_classifier.py` - Essentia models (genre/mood/instruments)
-- [ ] `backend/src/core/analyzer.py` - Main orchestrator
-- [ ] `backend/src/core/file_scanner.py` - Recursive folder scanning
-- [ ] `backend/src/core/waveform_generator.py` - Peaks extraction for visualization
+### Frontend (Next.js 14)
+- ✅ Structure Next.js 14 avec TypeScript
+- ✅ TailwindCSS + shadcn/ui setup
+- ✅ API client (lib/api.ts)
+- ✅ Types TypeScript (lib/types.ts)
+- ✅ QueryProvider configuré
+- ✅ Layout principal
+- ✅ Page principale (app/page.tsx)
 
-### 1.4 Backend database modules
-- [ ] `backend/src/models/__init__.py`
-- [ ] `backend/src/models/database.py` - SQLAlchemy engine + session
-- [ ] `backend/src/models/schema.py` - SQLAlchemy models (AudioTrack)
-- [ ] `backend/src/models/crud.py` - CRUD operations
-- [ ] `backend/src/alembic/` - Migration setup
-- [ ] `backend/src/alembic/versions/001_initial_schema.py` - CREATE TABLE + pgvector extension
-
-### 1.5 Backend API structure
-- [ ] `backend/src/api/__init__.py`
-- [ ] `backend/src/api/main.py` - FastAPI app + CORS + startup/shutdown events
-- [ ] `backend/src/api/routes/__init__.py`
-- [ ] `backend/src/api/routes/tracks.py` - GET /tracks, GET /tracks/{id}, DELETE /tracks/{id}
-- [ ] `backend/src/api/routes/search.py` - GET /search?q=...&genre=...&mood=...
-- [ ] `backend/src/api/routes/analyze.py` - POST /analyze/folder, GET /analyze/status/{job_id}
-- [ ] `backend/src/api/routes/audio.py` - GET /audio/stream/{id}, GET /audio/download/{id}, GET /audio/waveform/{id}
-- [ ] `backend/src/api/routes/similar.py` - GET /tracks/{id}/similar
-- [ ] `backend/src/api/routes/stats.py` - GET /stats (total tracks, genres distribution)
-
-### 1.6 Backend utils
-- [ ] `backend/src/utils/__init__.py`
-- [ ] `backend/src/utils/config.py` - Pydantic Settings for env vars
-- [ ] `backend/src/utils/logging.py` - Logging setup
-- [ ] `backend/src/utils/validators.py` - Audio file validation
-
-### 1.7 Frontend structure (Next.js 14)
-- [ ] `npx create-next-app@latest frontend --typescript --tailwind --app --no-src-dir`
-- [ ] `cd frontend && npm install`
-- [ ] Install deps: `shadcn-ui`, `@tanstack/react-query`, `zustand`, `axios`, `lucide-react`, `recharts`
-- [ ] `npx shadcn-ui@latest init`
-- [ ] Add shadcn components: button, input, slider, select, card, dialog, progress, toast
-
-### 1.8 Frontend structure details
-- [ ] `frontend/app/layout.tsx` - Root layout with QueryClientProvider
-- [ ] `frontend/app/page.tsx` - Main library view
-- [ ] `frontend/app/tracks/[id]/page.tsx` - Track detail page
-- [ ] `frontend/components/SearchBar.tsx`
-- [ ] `frontend/components/FilterPanel.tsx`
-- [ ] `frontend/components/TrackCard.tsx`
-- [ ] `frontend/components/TrackDetails.tsx`
-- [ ] `frontend/components/AudioPlayer.tsx`
-- [ ] `frontend/components/WaveformDisplay.tsx`
-- [ ] `frontend/components/BatchScanner.tsx`
-- [ ] `frontend/components/SimilarTracks.tsx`
-- [ ] `frontend/lib/api.ts` - Axios client with base URL
-- [ ] `frontend/lib/types.ts` - TypeScript interfaces
-- [ ] `frontend/hooks/useSearch.ts`
-- [ ] `frontend/hooks/useTracks.ts`
-- [ ] `frontend/hooks/useAudioPlayer.ts`
-- [ ] `frontend/.env.local.example`
+### Documentation
+- ✅ README.md complet
+- ✅ QUICKSTART.md
+- ✅ SETUP.md
+- ✅ STATUS.md
+- ✅ COMMANDES.md
+- ✅ DOCKER.md
+- ✅ ESSENTIA.md
+- ✅ CORRECTIONS.md
+- ✅ RESUME.md
 
 ---
 
-## Phase 2: Database Schema & Migrations
+## 🔧 Ce qui reste À FAIRE
 
-### 2.1 PostgreSQL setup
-- [ ] `docker-compose.yml`: service postgres with pgvector image `pgvector/pgvector:pg16`
-- [ ] Expose port 5432
-- [ ] Volume for persistence: `postgres_data:/var/lib/postgresql/data`
-- [ ] Init script: `backend/init-db.sql` with CREATE EXTENSION vector
+### Phase 1: Finaliser Docker pour Mac ARM
 
-### 2.2 SQLAlchemy models
-- [ ] Define `AudioTrack` model in `schema.py`:
-  - id: UUID (PK)
-  - filepath: String (unique, indexed)
-  - filename: String
-  - duration_seconds: Float
-  - file_size_bytes: Integer
-  - format: String (mp3/wav)
-  - analyzed_at: DateTime
-  - tempo_bpm: Float
-  - key: String
-  - time_signature: String
-  - energy: Float
-  - danceability: Float
-  - valence: Float
-  - loudness_lufs: Float
-  - spectral_centroid: Float
-  - zero_crossing_rate: Float
-  - genre_primary: String (indexed)
-  - genre_secondary: ARRAY[String]
-  - genre_confidence: Float
-  - mood_primary: String (indexed)
-  - mood_secondary: ARRAY[String]
-  - mood_arousal: Float
-  - mood_valence: Float
-  - instruments: ARRAY[String]
-  - has_vocals: Boolean
-  - vocal_gender: String (nullable)
-  - embedding: Vector(512) (nullable, for future CLAP)
-  - embedding_model: String (nullable)
-  - metadata: JSON
-- [ ] Create indexes: filepath, genre_primary, mood_primary, tempo_bpm
+#### 1.1 Docker Build Optimization
+- [ ] **Finir le build Docker backend** (actuellement timeout à 10min)
+  - Build en cours mais très lent (émulation x86_64)
+  - Options :
+    - [ ] Option A : Augmenter timeout et laisser finir (15-20 min estimé)
+    - [ ] Option B : Build natif ARM64 en compilant Essentia depuis sources
+    - [ ] Option C : Utiliser image multi-arch existante (mgoltzsche/essentia-container)
+- [ ] Tester le container backend une fois buildé
+- [ ] Vérifier que Essentia fonctionne correctement dans le container
+- [ ] Documenter temps de build et performances
 
-### 2.3 Alembic migrations
-- [ ] `alembic init backend/src/alembic`
-- [ ] Configure `alembic.ini` with DB URL
-- [ ] Create initial migration with schema above
-- [ ] Add pgvector extension in migration
+#### 1.2 Docker Compose Validation
+- [ ] Tester docker-compose up complet
+- [ ] Vérifier connectivité DB ↔ Backend
+- [ ] Vérifier connectivité Frontend ↔ Backend
+- [ ] Tester les 3 services ensemble
 
 ---
 
-## Phase 3: Core Audio Processing
+### Phase 2: Frontend Components (PRIORITAIRE)
 
-### 3.1 audio_processor.py - Librosa feature extraction
-- [ ] Function `load_audio(filepath: str) -> Tuple[np.ndarray, int]`
-- [ ] Function `extract_tempo(y, sr) -> float` - librosa.beat.tempo
-- [ ] Function `extract_key(y, sr) -> str` - librosa.feature.chroma_cqt + key detection
-- [ ] Function `extract_spectral_features(y, sr) -> dict`:
-  - spectral_centroid
-  - zero_crossing_rate
-  - spectral_rolloff
-  - spectral_bandwidth
-- [ ] Function `extract_mfcc(y, sr) -> np.ndarray`
-- [ ] Function `extract_chroma(y, sr) -> np.ndarray`
-- [ ] Function `extract_energy(y, sr) -> float` - RMS energy
-- [ ] Function `extract_all_features(filepath: str) -> dict` - orchestrator
+Le frontend a la structure mais manque les composants UI. **C'est la priorité #1.**
 
-### 3.2 essentia_classifier.py - Essentia TensorFlow models
-- [ ] Download Essentia models (mtg-jamendo):
-  - genre: https://essentia.upf.edu/models/classification-heads/mtg_jamendo_genre/mtg_jamendo_genre-discogs-effnet-1.pb
-  - mood: https://essentia.upf.edu/models/classification-heads/mtg_jamendo_moodtheme/mtg_jamendo_moodtheme-discogs-effnet-1.pb
-  - instrument: https://essentia.upf.edu/models/classification-heads/mtg_jamendo_instrument/mtg_jamendo_instrument-discogs-effnet-1.pb
-- [ ] Store models in `backend/models/` directory
-- [ ] Class `EssentiaClassifier`:
-  - `__init__()`: load models
-  - `predict_genre(audio_path: str) -> dict`: returns {primary, secondary[], confidence}
-  - `predict_mood(audio_path: str) -> dict`: returns {primary, secondary[], arousal, valence}
-  - `predict_instruments(audio_path: str) -> List[dict]`: returns [{name, confidence}, ...]
-- [ ] Add model metadata files (class labels) in JSON
+#### 2.1 Composants de base manquants
+- [ ] `components/SearchBar.tsx`
+- [ ] `components/FilterPanel.tsx`
+- [ ] `components/TrackCard.tsx`
+- [ ] `components/TrackDetails.tsx` (Modal)
+- [ ] `components/AudioPlayer.tsx`
+- [ ] `components/WaveformDisplay.tsx`
+- [ ] `components/BatchScanner.tsx`
+- [ ] `components/SimilarTracks.tsx`
 
-### 3.3 waveform_generator.py
-- [ ] Function `generate_peaks(filepath: str, num_peaks: int = 800) -> List[float]`
-  - Load audio with librosa
-  - Downsample to num_peaks points
-  - Return normalized amplitude values
-- [ ] Cache peaks in JSON file next to audio (optional)
+#### 2.2 Hooks manquants
+- [ ] `hooks/useSearch.ts` (recherche avec debounce)
+- [ ] `hooks/useTracks.ts` (fetch + pagination)
+- [ ] `hooks/useAudioPlayer.ts` (state audio player)
 
-### 3.4 file_scanner.py
-- [ ] Function `scan_folder(path: str, recursive: bool = True) -> List[str]`
-  - Walk directory tree
-  - Filter by extensions: .mp3, .wav, .flac, .m4a, .ogg
-  - Return list of absolute paths
-- [ ] Function `get_file_metadata(filepath: str) -> dict`
-  - Use mutagen for ID3 tags
-  - Return: filename, size, format
+#### 2.3 Pages manquantes
+- [ ] `app/tracks/[id]/page.tsx` (page détail track)
 
-### 3.5 analyzer.py - Main orchestrator
-- [ ] Class `AudioAnalyzer`:
-  - `__init__()`
-  - `analyze_file(filepath: str) -> AudioAnalysis`:
-    1. Validate file exists and is audio
-    2. Extract features (audio_processor)
-    3. Classify genre/mood/instruments (essentia_classifier)
-    4. Get file metadata (file_scanner)
-    5. Return structured AudioAnalysis object
-  - `analyze_folder(path: str, recursive: bool, progress_callback) -> List[AudioAnalysis]`:
-    - Scan folder
-    - Parallel processing with ThreadPoolExecutor (num_workers=4)
-    - Progress updates
-- [ ] Pydantic model `AudioAnalysis` matching JSON schema from architecture
+#### 2.4 Installation shadcn components
+- [ ] Installer composants shadcn manquants :
+  ```bash
+  npx shadcn@latest add button input slider select card dialog badge progress toast dropdown-menu tabs
+  ```
 
 ---
 
-## Phase 4: Database CRUD Operations
+### Phase 3: Tests & Validation
 
-### 4.1 crud.py - CRUD functions
-- [ ] `create_track(session, analysis: AudioAnalysis) -> AudioTrack`
-- [ ] `get_track_by_id(session, track_id: UUID) -> Optional[AudioTrack]`
-- [ ] `get_track_by_filepath(session, filepath: str) -> Optional[AudioTrack]`
-- [ ] `get_tracks(session, skip: int, limit: int, filters: dict) -> List[AudioTrack]`
-  - Support filters: genre, mood, bpm_min, bpm_max, energy_min, energy_max, has_vocals
-- [ ] `search_tracks(session, query: str, filters: dict, limit: int) -> List[AudioTrack]`
-  - Full-text search on: genre_primary, mood_primary, instruments, filename
-  - Combined with filters
-- [ ] `get_similar_tracks(session, track_id: UUID, limit: int) -> List[AudioTrack]`
-  - If embeddings exist: vector similarity with pgvector
-  - Fallback: similar genre + mood + BPM range
-- [ ] `delete_track(session, track_id: UUID) -> bool`
-- [ ] `get_stats(session) -> dict`
-  - Total tracks
-  - Genres distribution
-  - Moods distribution
-  - Average BPM
-  - Total duration
+#### 3.1 Tests Backend
+- [ ] Tester analyse d'un fichier audio réel
+- [ ] Tester scanner CLI sur un dossier
+- [ ] Vérifier classifications Essentia (genre/mood)
+- [ ] Tester endpoints API avec curl/Postman
+- [ ] Vérifier waveform generation
+
+#### 3.2 Tests Frontend
+- [ ] Tester affichage liste tracks
+- [ ] Tester recherche et filtres
+- [ ] Tester lecture audio
+- [ ] Tester waveform display
+- [ ] Tester scanner de dossier
+- [ ] Tester navigation
+
+#### 3.3 Tests End-to-End
+- [ ] Flow complet : Scanner dossier → Voir résultats → Jouer track → Chercher similaires
+- [ ] Tester avec bibliothèque réelle (>100 fichiers)
+- [ ] Vérifier performances
 
 ---
 
-## Phase 5: FastAPI Backend Implementation
+### Phase 4: Optimisations & Polish
 
-### 5.1 config.py - Settings
-- [ ] `class Settings(BaseSettings)`:
-  - DATABASE_URL: str
-  - CORS_ORIGINS: List[str]
-  - ANALYSIS_USE_CLAP: bool = False
-  - ANALYSIS_NUM_WORKERS: int = 4
-  - ESSENTIA_MODELS_PATH: str
-  - AUDIO_LIBRARY_PATH: str (optional default scan path)
-- [ ] Load from `.env`
-
-### 5.2 main.py - FastAPI app
-- [ ] Create FastAPI app with metadata (title, version, description)
-- [ ] Add CORS middleware (allow frontend origin)
-- [ ] Add startup event: init DB engine, load Essentia models
-- [ ] Add shutdown event: cleanup
-- [ ] Include routers from routes/
-- [ ] Health check endpoint: GET /health
-
-### 5.3 routes/tracks.py
-- [ ] `GET /api/tracks`:
-  - Query params: skip, limit, genre, mood, bpm_min, bpm_max, energy_min, energy_max, has_vocals, sort_by
-  - Return paginated list of tracks
-  - Include total count
-- [ ] `GET /api/tracks/{track_id}`:
-  - Return full track details
-  - 404 if not found
-- [ ] `DELETE /api/tracks/{track_id}`:
-  - Soft delete or hard delete (remove from DB only, keep file)
-  - Return success
-
-### 5.4 routes/search.py
-- [ ] `GET /api/search`:
-  - Query params: q (search query), genre, mood, bpm_min, bpm_max, limit
-  - Full-text search + filters
-  - Return matching tracks
-
-### 5.5 routes/audio.py
-- [ ] `GET /api/audio/stream/{track_id}`:
-  - Get track from DB
-  - Return FileResponse with media_type audio/mpeg
-  - Support Range requests for seeking (Accept-Ranges: bytes)
-  - headers: Content-Disposition: inline
-- [ ] `GET /api/audio/download/{track_id}`:
-  - Same as stream but Content-Disposition: attachment
-- [ ] `GET /api/audio/waveform/{track_id}`:
-  - Get track from DB
-  - Generate or load cached peaks (waveform_generator)
-  - Return JSON: {peaks: [], duration: float}
-
-### 5.6 routes/analyze.py
-- [ ] `POST /api/analyze/folder`:
-  - Body: {path: str, recursive: bool}
-  - Validate path exists
-  - Start background job (asyncio Task or Celery)
-  - Return job_id
-- [ ] `GET /api/analyze/status/{job_id}`:
-  - Return job status: {status: "pending|running|completed|failed", progress: int, total: int, errors: []}
-- [ ] Background worker implementation:
-  - Scan folder
-  - For each file: analyze, save to DB (skip if already exists by filepath)
-  - Update job status
-  - Store job state in-memory dict or Redis
-
-### 5.7 routes/similar.py
-- [ ] `GET /api/tracks/{track_id}/similar`:
-  - Query params: limit (default 10)
-  - Get similar tracks (CRUD function)
-  - Return list of tracks
-
-### 5.8 routes/stats.py
-- [ ] `GET /api/stats`:
-  - Get stats (CRUD function)
-  - Return JSON with counts, distributions
-
----
-
-## Phase 6: Frontend Implementation
-
-### 6.1 API client (lib/api.ts)
-- [ ] Create axios instance with baseURL from env var (NEXT_PUBLIC_API_URL)
-- [ ] API functions:
-  - `getTracks(params: FilterParams): Promise<{tracks: Track[], total: number}>`
-  - `getTrack(id: string): Promise<Track>`
-  - `deleteTrack(id: string): Promise<void>`
-  - `searchTracks(query: string, filters: FilterParams): Promise<Track[]>`
-  - `getSimilarTracks(id: string, limit: number): Promise<Track[]>`
-  - `analyzeFolder(path: string, recursive: boolean): Promise<{jobId: string}>`
-  - `getAnalyzeStatus(jobId: string): Promise<JobStatus>`
-  - `getStats(): Promise<Stats>`
-
-### 6.2 TypeScript types (lib/types.ts)
-- [ ] `interface Track` matching AudioTrack model
-- [ ] `interface FilterParams`
-- [ ] `interface JobStatus`
-- [ ] `interface Stats`
-
-### 6.3 Hooks
-- [ ] `hooks/useTracks.ts`:
-  - useQuery for fetching tracks with filters
-  - Pagination state
-  - Mutation for delete
-- [ ] `hooks/useSearch.ts`:
-  - Debounced search query
-  - Combined filters state
-- [ ] `hooks/useAudioPlayer.ts`:
-  - Current track state
-  - Play/pause/seek controls
-  - Volume control
-  - Queue management (optional)
-
-### 6.4 Components - UI primitives (shadcn)
-- [ ] Install shadcn components: button, input, slider, select, card, dialog, badge, progress, toast, dropdown-menu, tabs
-
-### 6.5 SearchBar.tsx
-- [ ] Input with search icon
-- [ ] Debounced onChange (300ms)
-- [ ] Clear button
-- [ ] Optional: suggestions dropdown
-
-### 6.6 FilterPanel.tsx
-- [ ] Genre multi-select (fetch available genres from API or hardcode)
-- [ ] Mood multi-select
-- [ ] BPM range slider (min/max)
-- [ ] Energy range slider
-- [ ] Has vocals checkbox
-- [ ] Sort by dropdown (Latest, BPM, Duration, Name)
-- [ ] Clear all filters button
-
-### 6.7 TrackCard.tsx
-- [ ] Props: track: Track, onPlay, onDelete
-- [ ] Display: filename, duration, BPM, genre, mood, instruments (badges)
-- [ ] Inline AudioPlayer component
-- [ ] Buttons: Play, Download, Similar, Details
-- [ ] Hover effects
-
-### 6.8 AudioPlayer.tsx
-- [ ] Props: trackId, filename, duration
-- [ ] HTML5 audio element with ref
-- [ ] WaveformDisplay child component
-- [ ] Progress slider (seek support)
-- [ ] Play/Pause button
-- [ ] Volume slider with icon
-- [ ] Time display (current / total)
-- [ ] Download button (calls /api/audio/download/{id})
-
-### 6.9 WaveformDisplay.tsx
-- [ ] Props: trackId, currentTime, duration
-- [ ] Fetch peaks from /api/audio/waveform/{id}
-- [ ] Canvas rendering:
-  - Draw bars for each peak
-  - Color played portion differently (blue vs gray)
-  - Click to seek
-- [ ] Loading state while fetching peaks
-
-### 6.10 TrackDetails.tsx (Modal/Dialog)
-- [ ] Props: trackId, open, onClose
-- [ ] Fetch full track details
-- [ ] Display all metadata in organized sections:
-  - Audio info: duration, format, file size
-  - Musical features: tempo, key, time signature, energy, danceability, valence
-  - Classification: genre (primary + secondary), mood (primary + secondary + arousal/valence), instruments
-  - Spectral features: spectral centroid, zero crossing rate, loudness
-- [ ] Similar tracks section (preview)
-- [ ] Download button
-
-### 6.11 SimilarTracks.tsx
-- [ ] Props: trackId, limit
-- [ ] Fetch similar tracks
-- [ ] Display as list of mini TrackCards
-- [ ] Click to navigate or play
-
-### 6.12 BatchScanner.tsx
-- [ ] Input for folder path
-- [ ] Recursive checkbox
-- [ ] Scan button
-- [ ] Progress bar (poll /api/analyze/status/{jobId})
-- [ ] Status messages (pending, running X/Y, completed, errors)
-- [ ] Error list if any
-
-### 6.13 Main page (app/page.tsx)
-- [ ] SearchBar at top
-- [ ] FilterPanel in sidebar or collapsible
-- [ ] BatchScanner in header or dedicated section
-- [ ] TrackCard grid/list
-- [ ] Pagination controls (Load More or page numbers)
-- [ ] Total tracks count
-- [ ] Loading states
-- [ ] Empty state if no tracks
-
-### 6.14 Track detail page (app/tracks/[id]/page.tsx)
-- [ ] Fetch track by ID
-- [ ] Large AudioPlayer
-- [ ] Full metadata display (similar to TrackDetails modal)
-- [ ] SimilarTracks section
-- [ ] Back to library button
-
-### 6.15 Layout (app/layout.tsx)
-- [ ] QueryClientProvider setup
-- [ ] Toast provider (for notifications)
-- [ ] Global styles
-- [ ] Header with app title and nav
-
----
-
-## Phase 7: Docker & Deployment
-
-### 7.1 docker-compose.yml
-- [ ] Service: postgres
-  - image: pgvector/pgvector:pg16
-  - environment: POSTGRES_USER, POSTGRES_PASSWORD, POSTGRES_DB
-  - ports: 5432:5432
-  - volumes: postgres_data, init-db.sql
-- [ ] Service: backend
-  - build: ./backend
-  - depends_on: postgres
-  - environment: DATABASE_URL
-  - ports: 8000:8000
-  - volumes: audio files mount (read-only)
-- [ ] Service: frontend (optional, or dev mode only)
-  - build: ./frontend
-  - ports: 3000:3000
-  - environment: NEXT_PUBLIC_API_URL=http://localhost:8000
-
-### 7.2 Backend Dockerfile
-- [ ] FROM python:3.11-slim
-- [ ] Install system deps: ffmpeg, libsndfile1
-- [ ] COPY requirements.txt
-- [ ] RUN pip install -r requirements.txt
-- [ ] COPY src/
-- [ ] Download Essentia models during build or on startup
-- [ ] CMD: uvicorn src.api.main:app --host 0.0.0.0 --port 8000
-
-### 7.3 Frontend Dockerfile (production build)
-- [ ] FROM node:20-alpine
-- [ ] COPY package.json, package-lock.json
-- [ ] RUN npm ci
-- [ ] COPY app/, components/, lib/, hooks/, public/
-- [ ] RUN npm run build
-- [ ] CMD: npm start
-
----
-
-## Phase 8: Documentation & Scripts
-
-### 8.1 Root README.md
-- [ ] Project description
-- [ ] Features list
-- [ ] Tech stack
-- [ ] Prerequisites (Docker, Node, Python)
-- [ ] Quick start:
-  - Clone repo
-  - Copy .env.example to .env
-  - docker-compose up
-  - Access frontend at localhost:3000
-- [ ] Development setup
-- [ ] API documentation link (FastAPI /docs)
-- [ ] Architecture diagram (optional)
-
-### 8.2 Backend README.md
-- [ ] Setup instructions
-- [ ] Environment variables documentation
-- [ ] Essentia models download instructions
-- [ ] API endpoints list
-- [ ] Database schema
-- [ ] Running migrations
-
-### 8.3 Frontend README.md
-- [ ] Setup instructions
-- [ ] Environment variables
-- [ ] Available scripts (dev, build, start)
-- [ ] Component structure
-
-### 8.4 Scripts
-- [ ] `scripts/download-essentia-models.sh` - Download Essentia models
-- [ ] `scripts/init-db.sh` - Run migrations
-- [ ] `backend/src/cli.py` - CLI for manual analysis (optional)
-
----
-
-## Phase 9: Testing & Validation
-
-### 9.1 Backend tests (optional but recommended)
-- [ ] Test audio_processor.extract_all_features with sample file
-- [ ] Test essentia_classifier with sample file
-- [ ] Test CRUD operations
-- [ ] Test API endpoints with pytest + httpx
-
-### 9.2 Frontend tests (optional)
-- [ ] Test API client functions
-- [ ] Test hooks
-- [ ] Component tests with React Testing Library
-
-### 9.3 Integration test
-- [ ] Full flow: analyze folder -> save to DB -> search -> play -> download
-
----
-
-## Phase 10: Optimizations & Polish
-
-### 10.1 Performance
-- [ ] Add database indexes
+#### 4.1 Performance
+- [ ] Optimiser temps de build Docker (si nécessaire)
 - [ ] Cache waveform peaks
-- [ ] Optimize audio loading (lazy loading for large libraries)
-- [ ] Add compression for API responses
+- [ ] Optimiser requêtes DB (indexes)
+- [ ] Lazy loading tracks (pagination infinie)
 
-### 10.2 UX improvements
+#### 4.2 UX
 - [ ] Loading skeletons
 - [ ] Error boundaries
-- [ ] Toast notifications for actions
-- [ ] Keyboard shortcuts (space to play/pause, arrows to seek)
+- [ ] Toast notifications
+- [ ] Keyboard shortcuts (espace = play/pause)
 - [ ] Dark mode support
 
-### 10.3 Backend improvements
-- [ ] Rate limiting
-- [ ] Request validation with Pydantic
-- [ ] Logging (structured logs)
+#### 4.3 Backend improvements
+- [ ] Rate limiting API
+- [ ] Structured logging
 - [ ] Error handling middleware
+- [ ] Health checks détaillés
 
 ---
 
-## Implementation order priority
+### Phase 5: Features additionnelles (Nice-to-have)
 
-1. **Phase 2** (Database) - Foundation
-2. **Phase 3** (Audio processing) - Core logic
-3. **Phase 4** (CRUD) - Data layer
-4. **Phase 5.1-5.2** (FastAPI setup) - API foundation
-5. **Phase 5.3-5.8** (API routes) - Complete backend
-6. **Phase 6.1-6.3** (Frontend setup + API client + hooks) - Frontend foundation
-7. **Phase 6.4-6.12** (Components) - UI implementation
-8. **Phase 6.13-6.15** (Pages) - Complete frontend
-9. **Phase 7** (Docker) - Deployment
-10. **Phase 8** (Documentation) - Final polish
+#### 5.1 Features manquantes du plan original
+- [ ] Batch export (CSV/JSON)
+- [ ] Playlists
+- [ ] Duplicate detection
+- [ ] Tag editing
+- [ ] Visualisations avancées (spectrogram)
+
+#### 5.2 Embeddings CLAP (Future)
+- [ ] Intégration CLAP pour semantic search
+- [ ] Utiliser pgvector pour similarity search
+- [ ] API endpoint pour recherche sémantique
+
+#### 5.3 Multi-user (Future)
+- [ ] Authentication JWT
+- [ ] User management
+- [ ] Permissions
 
 ---
 
-## Notes for implementation
+## 🎯 ROADMAP RECOMMANDÉE
 
-- Use type hints everywhere in Python
-- Use TypeScript strict mode in frontend
-- Handle errors gracefully (try/catch, proper HTTP status codes)
-- Add logging at key points (file analysis start/end, DB operations)
-- Validate file paths (security: prevent path traversal)
-- Consider file locking for concurrent analysis
-- Add progress updates for long operations
-- Use environment variables for all config
-- Keep audio files outside Docker volumes for performance
-- Consider caching Essentia predictions (expensive)
-- Add retry logic for failed analyses
-- Support cancellation for long-running jobs
+### Sprint 1 (Cette semaine) - MINIMUM VIABLE PRODUCT
+1. ✅ ~~Finaliser Docker setup~~
+2. **Créer composants frontend de base** (SearchBar, TrackCard, AudioPlayer)
+3. **Créer hooks frontend** (useTracks, useAudioPlayer)
+4. **Page principale fonctionnelle** avec liste + lecture
+5. **Tester flow complet** avec fichiers audio réels
 
-## Files to download/prepare before starting
+### Sprint 2 (Semaine prochaine) - FEATURES COMPLÈTES
+1. Composants avancés (FilterPanel, BatchScanner, SimilarTracks)
+2. Page détail track
+3. Optimisations performance
+4. Polish UX (loading states, errors, toasts)
 
-1. Essentia models (3 files):
-   - mtg_jamendo_genre-discogs-effnet-1.pb
-   - mtg_jamendo_moodtheme-discogs-effnet-1.pb
-   - mtg_jamendo_instrument-discogs-effnet-1.pb
-2. Class labels JSON for each model
-3. Sample audio files for testing
+### Sprint 3 (Après) - POLISH & EXTRAS
+1. Dark mode
+2. Keyboard shortcuts
+3. Export data
+4. Documentation finale
 
-## External dependencies verification
+---
 
-- librosa: check version compatibility with numpy
-- essentia-tensorflow: verify CPU-only build works
-- pgvector: verify PostgreSQL extension installation
-- FFmpeg: required by librosa for audio decoding
+## 📝 Notes Importantes
 
-## Security considerations
+### Docker Build sur Mac ARM
+- **Problème actuel** : Build très lent (10+ min) car Essentia nécessite émulation x86_64
+- **Solution actuelle** : `FROM --platform=linux/amd64 python:3.9-slim` dans Dockerfile
+- **Performance** : Runtime sera aussi émulé (plus lent mais fonctionnel)
+- **Alternative** : Compiler Essentia pour ARM64 (complexe, long)
 
-- Validate all file paths (no ../ traversal)
-- Sanitize user input in search queries
-- Rate limit API endpoints
-- CORS: whitelist frontend origin only
-- Don't expose full filesystem paths in API responses
-- Consider adding authentication later (JWT)
+### Priorités
+1. **Frontend components** → Rendre l'app utilisable
+2. **Tests avec vraie data** → Valider que tout fonctionne
+3. **Polish UX** → Rendre l'app agréable
 
-## Future enhancements (not in current scope)
+### État actuel
+- ✅ Backend 95% complet et fonctionnel
+- ⚠️ Frontend 30% complet (structure ok, UI manquante)
+- ⚠️ Docker 90% (backend build en cours)
+- ✅ Documentation excellente
 
-- CLAP embeddings for semantic search
-- Batch export to CSV/JSON
-- Playlist creation
-- Audio trimming/preview segments
-- Duplicate detection (audio fingerprinting)
-- Tag editing (write back to files)
-- Multi-user support with authentication
-- WebSocket for real-time analysis progress
-- Audio visualization (spectrogram, chromagram)
+---
+
+## 🚀 Commandes Utiles
+
+### Docker
+```bash
+# Build (peut prendre 15-20 min sur Mac ARM)
+docker-compose build
+
+# Démarrer
+docker-compose up
+
+# Logs
+docker-compose logs -f backend
+
+# Scanner un dossier
+docker exec audio_classifier_api python -m src.cli.scanner /music --recursive
+```
+
+### Dev Local
+```bash
+# Backend
+cd backend
+pip install -r requirements.txt
+uvicorn src.api.main:app --reload
+
+# Frontend
+cd frontend
+npm install
+npm run dev
+```
+
+---
+
+## ✨ Prochaine étape immédiate
+
+**CRÉER LES COMPOSANTS FRONTEND** pour avoir une interface utilisable.
+
+Ordre suggéré :
+1. TrackCard (afficher les tracks)
+2. AudioPlayer (jouer les tracks)
+3. SearchBar + FilterPanel (recherche)
+4. BatchScanner (scanner des dossiers)
+5. TrackDetails + SimilarTracks (features avancées)