Update backend/server.py

backend/server.py

@@ -12,17 +12,17 @@ import time
 from deepface import DeepFace
 from supabase import create_client, Client
 
-# --- SETUP SUPABASE ---
+# --- 1. SETUP SUPABASE ---
 SUPABASE_URL = os.getenv("SUPABASE_URL", "https://gwjrwejdjpctizolfkcz.supabase.co")
 SUPABASE_KEY = os.getenv("SUPABASE_KEY", "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Imd3anJ3ZWpkanBjdGl6b2xma2N6Iiwicm9sZSI6InNlcnZpY2Vfcm9sZSIsImlhdCI6MTc2OTA5ODEyNCwiZXhwIjoyMDg0Njc0MTI0fQ.EjU1DGTN-jrdkaC6nJWilFtYZgtu-NKjnfiMVMnHal0")
 
 try:
     supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
-    print("☁️ SUPABASE OK")
+    print("☁️ SUPABASE CONNECTÉ")
 except Exception as e:
     print(f"❌ ERREUR SUPABASE: {e}")
 
-# --- SOCKET SETUP (La config qui marche !) ---
+# --- 2. CONFIG SOCKET ---
 sio = socketio.AsyncServer(
     async_mode='asgi', 
     cors_allowed_origins='*',
@@ -34,16 +34,13 @@ app = FastAPI()
 app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
 socket_app = socketio.ASGIApp(sio, app)
 
-# --- API REST (RETOUR DE L'ADMIN) ---
+# --- 3. API ADMIN ---
 @app.get("/api/sessions")
 def get_sessions():
-    # Récupère l'historique pour la page Admin
     try:
         response = supabase.table('sessions').select("*").order('id', desc=True).execute()
         return response.data
-    except Exception as e:
-        print(f"API Error: {e}")
-        return []
+    except: return []
 
 @app.get("/api/sessions/{session_id}")
 def get_session_details(session_id: int):
@@ -63,18 +60,17 @@ def delete_session(session_id: int):
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-# --- GLOBAL STATE ---
+# --- 4. GESTION DES SESSIONS ---
 sessions = {}
 
-# --- EVENTS SOCKET ---
-
 @sio.event
 async def connect(sid, environ):
-    print(f"✅ CONNECTÉ : {sid}")
+    print(f"✅ Client: {sid}")
     sessions[sid] = {
         "active": False, 
         "start_time": 0, 
-        "db_id": None
+        "db_id": None,
+        "last_save_time": 0 # Pour éviter de saturer la DB
     }
 
 @sio.event
@@ -83,13 +79,14 @@ async def disconnect(sid):
 
 @sio.event
 async def start_session(sid, data):
-    print(f"▶️ START : {sid}")
+    print(f"▶️ START: {sid}")
     if sid in sessions:
         sessions[sid]["active"] = True
-        sessions[sid]["start_time"] = time.time() # On note l'heure de départ
+        sessions[sid]["start_time"] = time.time()
+        sessions[sid]["last_save_time"] = 0
         
-        # Création dans la DB
         try:
+            # Création de la ligne "Session"
             new_session = { 
                 "first_name": data.get('firstName', 'Inconnu'), 
                 "last_name": data.get('lastName', ''), 
@@ -97,79 +94,105 @@ async def start_session(sid, data):
             }
             res = supabase.table('sessions').insert(new_session).execute()
             sessions[sid]["db_id"] = res.data[0]['id']
-            print(f"💾 Session sauvée en DB : ID {sessions[sid]['db_id']}")
+            print(f"💾 Session ID {sessions[sid]['db_id']} créée.")
         except Exception as e:
-            print(f"⚠️ Erreur DB: {e}")
+            print(f"⚠️ Erreur Création Session: {e}")
 
 @sio.event
 async def stop_session(sid):
-    print(f"⏹️ STOP : {sid}")
-    if sid in sessions: 
-        sessions[sid]["active"] = False
+    print(f"⏹️ STOP: {sid}")
+    if sid in sessions: sessions[sid]["active"] = False
 
 @sio.event
 async def process_frame(sid, data_uri):
     if sid not in sessions: return
 
     try:
-        # 1. Décodage
+        # A. Décodage
         encoded_data = data_uri.split(',')[1]
         nparr = np.frombuffer(base64.b64decode(encoded_data), np.uint8)
         frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
 
-        # 2. Analyse DeepFace
-        # enforce_detection=False permet de ne pas planter si le visage est flou
+        # B. Analyse IA
         result = DeepFace.analyze(frame, actions=['emotion'], enforce_detection=False, silent=True)
         data = result[0] if isinstance(result, list) else result
+        
         emotion = data['dominant_emotion']
+        emotion_score = data['emotion'][emotion] # On récupère le score de confiance (ex: 98.5)
         
-        # 3. Calculs KPIS & Temps
-        # Calcul du temps écoulé
+        # C. Calcul KPIs & Temps
         current_time = 0
         if sessions[sid]["active"]:
             current_time = int(time.time() - sessions[sid]["start_time"])
         
-        # Logique des carrés visages
+        # Coordonnées visage
         region = data['region']
         face_coords = {'x': region['x'], 'y': region['y'], 'w': region['w'], 'h': region['h']} if region['w'] > 0 else None
         
-        # Logique Fake KPIs intelligente
+        # Algorithme Métriques
         valence = 0.8 if emotion == "happy" else (-0.6 if emotion in ["sad", "angry", "fear"] else 0.0)
         arousal = 0.8 if emotion in ["angry", "fear", "surprise"] else 0.3
         
         def clamp(n): return max(0, min(100, int(n)))
+        
+        val_eng = clamp((arousal * 100) + random.uniform(0, 10))
+        val_sat = clamp(((valence + 1) / 2) * 100)
+        val_tru = clamp(50 + (valence * 20))
+        val_loy = clamp(50 + (valence * 10))
+        val_opi = clamp(((valence + 1) / 2) * 100)
+        
+        # Labels Textuels
+        lbl_eng = "Fort 🔥" if val_eng > 60 else ("Moyen" if val_eng > 30 else "Faible 💤")
+        lbl_sat = "Positif 😃" if val_sat > 60 else ("Négatif 😡" if val_sat < 40 else "Neutre 😐")
+
         metrics = {
-            "engagement": clamp((arousal * 100) + random.uniform(0, 10)),
-            "satisfaction": clamp(((valence + 1) / 2) * 100),
-            "trust": clamp(50 + (valence * 20)),
-            "loyalty": clamp(50 + (valence * 10)),
-            "opinion": clamp(((valence + 1) / 2) * 100)
+            "engagement": val_eng, "satisfaction": val_sat, "trust": val_tru, "loyalty": val_loy, "opinion": val_opi
         }
         
-        # 4. Envoi Réponse
+        # D. Envoi au Frontend (Temps Réel)
         payload = {
             "emotion": emotion,
             "face_coords": face_coords,
             "metrics": metrics,
-            "session_time": current_time, # LE TEMPS EST MAINTENANT CALCULÉ
+            "session_time": current_time,
             "is_recording": sessions[sid]["active"]
         }
         await sio.emit('metrics_update', payload, room=sid)
         
-        # 5. Sauvegarde en DB (toutes les secondes environ pour ne pas spammer)
-        if sessions[sid]["active"] and sessions[sid]["db_id"] and current_time % 1 == 0:
-             # On pourrait ajouter une logique ici pour ne pas sauvegarder à chaque frame
-             pass
+        # E. SAUVEGARDE EN BASE DE DONNÉES (La partie qui manquait !)
+        # On sauvegarde seulement si : 
+        # 1. L'enregistrement est actif
+        # 2. On a un ID de session valide
+        # 3. Ça fait plus d'1 seconde depuis la dernière sauvegarde (pour ne pas saturer)
+        now = time.time()
+        if sessions[sid]["active"] and sessions[sid]["db_id"]:
+            if now - sessions[sid]["last_save_time"] >= 1.0:
+                sessions[sid]["last_save_time"] = now
+                
+                # Préparation de la ligne à insérer
+                row_data = {
+                    "session_id": sessions[sid]["db_id"],
+                    "session_time": current_time,
+                    "emotion": emotion,
+                    "emotion_score": float(emotion_score),
+                    "engagement_val": val_eng, "engagement_lbl": lbl_eng,
+                    "satisfaction_val": val_sat, "satisfaction_lbl": lbl_sat,
+                    "trust_val": val_tru, "loyalty_val": val_loy, "opinion_val": val_opi
+                }
+                
+                # Insertion asynchrone (on ne bloque pas)
+                try:
+                    supabase.table('measurements').insert(row_data).execute()
+                    # print(f"💾 Data saved T={current_time}") # Décommenter pour vérifier
+                except Exception as db_err:
+                    print(f"⚠️ Erreur Insert Mesure: {db_err}")
 
     except Exception as e:
-        # On ignore les erreurs d'analyse pour fluidifier
-        pass
+        pass # On continue même si une frame est mauvaise
 
 if __name__ == "__main__":
-    # Pré-chargement au démarrage
     try:
         DeepFace.build_model("Emotion")
         print("✅ Modèle chargé !")
     except: pass
-    
     uvicorn.run(socket_app, host="0.0.0.0", port=7860)