Update

app.py

@@ -1,5 +1,3 @@
-import random
-
 import gradio as gr
 import numpy as np
 import PIL.Image
@@ -17,17 +15,34 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
 
 
+def get_seed(randomize_seed: bool, seed: int) -> int:
+    """Determine and return the random seed to use for model generation.
+
+    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.
+    """
+    rng = np.random.default_rng()
+    return int(rng.integers(0, MAX_SEED)) if randomize_seed else seed
+
+
 @spaces.GPU(duration=75)
 def infer(
     prompt: str,
     seed: int,
-    randomize_seed: bool,
     width: int = 1024,
     height: int = 1024,
     guidance_scale: float = 3.5,
     num_inference_steps: int = 28,
     progress: gr.Progress = gr.Progress(track_tqdm=True),  # noqa: ARG001, B008
-) -> tuple[PIL.Image.Image, int]:
+) -> PIL.Image.Image:
     """Generate an image from a text prompt using the FLUX.1 [dev] model.
 
     Note:
@@ -37,7 +52,6 @@ def infer(
     Args:
         prompt: A text prompt in English to guide the image generation. Limited to 77 tokens.
         seed: The seed value used for reproducible image generation.
-        randomize_seed: If True, overrides the seed with a randomly generated one.
         width: Width of the output image in pixels. Defaults to 1024.
         height: Height of the output image in pixels. Defaults to 1024.
         guidance_scale: Controls how strongly the model follows the prompt.
@@ -46,13 +60,11 @@ def infer(
         progress: (Internal) Progress tracker for UI integration; should not be manually set by users.
 
     Returns:
-        A tuple containing the generated image and the seed value used.
+        A PIL.Image.Image object representing the generated image.
     """
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)  # noqa: S311
     generator = torch.Generator().manual_seed(seed)
 
-    image = pipe(
+    return pipe(
         prompt=prompt,
         width=width,
         height=height,
@@ -60,11 +72,10 @@ def infer(
         generator=generator,
         guidance_scale=guidance_scale,
     ).images[0]
-    return image, seed
 
 
 def run_example(prompt: str) -> tuple[PIL.Image.Image, int]:
-    return infer(prompt, seed=42, randomize_seed=False)
+    return infer(prompt, seed=42)
 
 
 examples = [
@@ -145,13 +156,17 @@ with gr.Blocks(css=css) as demo:
             examples=examples,
             fn=run_example,
             inputs=prompt,
-            outputs=[result, seed],
+            outputs=result,
         )
 
     prompt.submit(
+        fn=get_seed,
+        inputs=[randomize_seed, seed],
+        outputs=seed,
+    ).then(
         fn=infer,
-        inputs=[prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs=[result, seed],
+        inputs=[prompt, seed, width, height, guidance_scale, num_inference_steps],
+        outputs=result,
     )
 
 if __name__ == "__main__":