fix(05_load_balancer): Address PR feedback comments

Changes:
- Use ComputeRequest model as parameter in compute_intensive() function for proper type safety and validation
- Update GPU router to pass full request object instead of extracting numbers
- Update test code to create ComputeRequest object properly

This ensures consistent use of Pydantic models for validation throughout the GPU worker endpoint.

All changes pass quality checks.

03_advanced_workers/05_load_balancer/workers/gpu/__init__.py

@@ -25,7 +25,7 @@ async def get_gpu_health():
 @gpu_router.post("/compute")
 async def post_gpu_compute(request: ComputeRequest):
     """Perform compute-intensive operation on GPU."""
-    return await compute_intensive(request.numbers)
+    return await compute_intensive(request)
 
 
 @gpu_router.get("/info")

03_advanced_workers/05_load_balancer/workers/gpu/endpoint.py

@@ -31,18 +31,19 @@ async def gpu_health() -> dict:
 
 
 @remote(gpu_config, method="POST", path="/compute")
-async def compute_intensive(numbers: list[int]) -> dict:
+async def compute_intensive(request: ComputeRequest) -> dict:
     """Perform compute-intensive operation on GPU.
 
     Args:
-        numbers: List of numbers to process
+        request: Request with numbers to process
 
     Returns:
         Computation results
     """
     import time
     from datetime import datetime, timezone
 
+    numbers = request.numbers
     start_time = time.time()
 
     # Simulate GPU-intensive computation
@@ -97,7 +98,8 @@ async def test():
         print(f"   {result}\n")
 
         print("2. Compute intensive:")
-        result = await compute_intensive([1, 2, 3, 4, 5])
+        request = ComputeRequest(numbers=[1, 2, 3, 4, 5])
+        result = await compute_intensive(request)
         print(f"   Sum of squares: {result['sum_of_squares']}")
         print(f"   Mean: {result['mean']}\n")