Enhance get_seed function documentation to clarify its purpose, arguments, return values, and usage notes for improved understanding and reproducibility in model generation.

app.py

@@ -107,8 +107,22 @@ def load_state_from_file(state_path: str) -> tuple[Gaussian, EasyDict]:
 
 
 def get_seed(randomize_seed: bool, seed: int) -> int:
-    """Get the random seed."""
-    return np.random.randint(0, MAX_SEED) if randomize_seed else seed
+    """Determine and return the random seed to use for model generation or sampling.
+
+    Args:
+        randomize_seed (bool): If True, a random seed (an integer in [0, MAX_SEED)) is generated using NumPy's default random number generator. If False, the provided seed argument is returned as-is.
+        seed (int): The seed value to use if randomize_seed is False.
+
+    Returns:
+        int: The selected seed value. If randomize_seed is True, a randomly generated integer; otherwise, the value of the seed argument.
+
+    Notes:
+        - MAX_SEED is the maximum value for a 32-bit integer (np.iinfo(np.int32).max).
+        - This function is typically used to ensure reproducibility or to introduce randomness in model generation.
+        - The random seed affects the stochastic processes in downstream model inference or sampling.
+    """
+    rng = np.random.default_rng()
+    return rng.integers(0, MAX_SEED) if randomize_seed else seed
 
 
 @spaces.GPU