Update app.py

app.py

@@ -127,9 +127,9 @@ def inference(model_name, prompt, guidance, steps, n_images=1, width=512, height
 
   try:
     if img is not None:
-      return img_to_img(model_path, prompt, n_images, neg_prompt, img, strength, guidance, steps, width, height, generator, seed), f"Done. Seed: {seed}"
+      return img_to_img(model_path, prompt, n_images, neg_prompt, img, strength, guidance, steps, width, height, generator), f"Done. Seed: {seed}"
     else:
-      return txt_to_img(model_path, prompt, n_images, neg_prompt, guidance, steps, width, height, generator, seed), f"Done. Seed: {seed}"
+      return txt_to_img(model_path, prompt, n_images, neg_prompt, guidance, steps, width, height, generator), f"Done. Seed: {seed}"
   except Exception as e:
     return None, error_str(e)
 
@@ -181,7 +181,7 @@ def inference_image(model_path, prompt, mode, *args, **kwargs):
     )
     return replace_nsfw_images(result)
 
-def txt_to_img(model_path, prompt, n_images, neg_prompt, guidance, steps, width, height, generator, seed):
+def txt_to_img(model_path, prompt, n_images, neg_prompt, guidance, steps, width, height, generator):
     return inference_image(model_path, prompt, "txt2img", 
         negative_prompt=neg_prompt, 
         num_images_per_prompt=n_images,
@@ -189,11 +189,10 @@ def txt_to_img(model_path, prompt, n_images, neg_prompt, guidance, steps, width,
         guidance_scale=guidance,
         width=width,
         height=height,
-        generator=generator,
-        seed=seed
+        generator=generator
     )
 
-def img_to_img(model_path, prompt, n_images, neg_prompt, img, strength, guidance, steps, width, height, generator, seed):
+def img_to_img(model_path, prompt, n_images, neg_prompt, img, strength, guidance, steps, width, height, generator):
     img = process_image(img, width, height)
     return inference_image(model_path, prompt, "img2img", 
         negative_prompt=neg_prompt,
@@ -202,8 +201,7 @@ def img_to_img(model_path, prompt, n_images, neg_prompt, img, strength, guidance
         num_inference_steps=int(steps),
         strength=strength,
         guidance_scale=guidance,
-        generator=generator,
-        seed=seed
+        generator=generator
     )
 
 def replace_nsfw_images(results):