Fix GPU detection and OUTPUT_DIR attribute errors

app/routers/system.py

@@ -33,19 +33,24 @@ class SystemInfo(BaseModel):
     total_memory_gb: float
     
 
+class GPUInfo(BaseModel):
+    """GPU information."""
+    available: bool
+    count: int = 0
+    names: List[str] = []
+    memory_used_gb: Optional[float] = None
+    memory_total_gb: Optional[float] = None
+    utilization: Optional[float] = None
+
+
 class ResourceUsage(BaseModel):
     """Current resource usage."""
-    cpu_percent: float
-    memory_percent: float
-    memory_used_gb: float
-    memory_total_gb: float
-    gpu_memory_used: Optional[float]
-    gpu_memory_total: Optional[float]
-    gpu_utilization: Optional[float]
-    disk_used_gb: float
-    disk_total_gb: float
-    disk_percent: float
-    
+    cpu: Dict[str, float]
+    memory: Dict[str, float]
+    disk: Dict[str, float]
+    gpu: GPUInfo
+    cache: Dict[str, Any]
+
 
 class StorageInfo(BaseModel):
     """Storage information."""
@@ -103,29 +108,59 @@ async def get_resource_usage():
     # Disk
     disk = shutil.disk_usage('/')
     
-    # GPU memory
-    gpu_memory_used = None
-    gpu_memory_total = None
-    gpu_utilization = None
+    # GPU info
+    gpu_info = GPUInfo(available=False, count=0, names=[])
     
     if torch.cuda.is_available():
         try:
+            gpu_names = []
+            for i in range(torch.cuda.device_count()):
+                gpu_names.append(torch.cuda.get_device_name(i))
+            
             gpu_memory_used = round(torch.cuda.memory_allocated() / (1024**3), 2)
             gpu_memory_total = round(torch.cuda.get_device_properties(0).total_memory / (1024**3), 2)
-        except:
-            pass
+            
+            gpu_info = GPUInfo(
+                available=True,
+                count=torch.cuda.device_count(),
+                names=gpu_names,
+                memory_used_gb=gpu_memory_used,
+                memory_total_gb=gpu_memory_total,
+                utilization=None
+            )
+        except Exception as e:
+            logger.error(f"Error getting GPU info: {e}")
+    
+    # Cache info
+    cache_total_bytes = 0
+    cache_dirs = [settings.CACHE_DIR, settings.HF_CACHE_DIR]
+    for cache_path in cache_dirs:
+        if os.path.exists(cache_path):
+            for root, dirs, files in os.walk(cache_path):
+                for f in files:
+                    try:
+                        cache_total_bytes += os.path.getsize(os.path.join(root, f))
+                    except:
+                        pass
     
     return ResourceUsage(
-        cpu_percent=round(cpu_percent, 1),
-        memory_percent=round(memory.percent, 1),
-        memory_used_gb=round(memory.used / (1024**3), 2),
-        memory_total_gb=round(memory.total / (1024**3), 2),
-        gpu_memory_used=gpu_memory_used,
-        gpu_memory_total=gpu_memory_total,
-        gpu_utilization=gpu_utilization,
-        disk_used_gb=round(disk.used / (1024**3), 2),
-        disk_total_gb=round(disk.total / (1024**3), 2),
-        disk_percent=round((disk.used / disk.total) * 100, 1)
+        cpu={
+            "percent": round(cpu_percent, 1)
+        },
+        memory={
+            "percent": round(memory.percent, 1),
+            "used_gb": round(memory.used / (1024**3), 2),
+            "total_gb": round(memory.total / (1024**3), 2)
+        },
+        disk={
+            "percent": round((disk.used / disk.total) * 100, 1),
+            "used_gb": round(disk.used / (1024**3), 2),
+            "total_gb": round(disk.total / (1024**3), 2)
+        },
+        gpu=gpu_info,
+        cache={
+            "total_bytes": cache_total_bytes
+        }
     )
 
 
@@ -136,8 +171,8 @@ async def get_storage_info():
         ("Models", settings.MODELS_DIR),
         ("Cache", settings.CACHE_DIR),
         ("Logs", settings.LOGS_DIR),
-        ("Uploads", settings.UPLOADS_DIR),
-        ("Outputs", settings.OUTPUTS_DIR)
+        ("Uploads", settings.UPLOAD_DIR),
+        ("Outputs", settings.OUTPUT_DIR)
     ]
     
     result = []