Update app.py

app.py

@@ -23,6 +23,7 @@ MAX_IMAGE_SIZE = 1024
 @spaces.GPU  # [uncomment to use ZeroGPU]
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, tag_selection_1, tag_selection_2, use_tags, progress=gr.Progress(track_tqdm=True)):
 
+    # Determine final prompt
     if use_tags:
         selected_tags_1 = [tag_options_1[tag] for tag in tag_selection_1 if tag in tag_options_1]
         selected_tags_2 = [tag_options_2[tag] for tag in tag_selection_2 if tag in tag_options_2]
@@ -31,14 +32,19 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     else:
         final_prompt = f'score_9, score_8_up, score_7_up, source_anime, {prompt}'
 
+    # Concatenate user-provided negative prompt with additional restrictions
+    additional_negatives = "worst quality, bad quality, jpeg artifacts, source_cartoon, 3d, (censor), monochrome, blurry, lowres, watermark"
+    full_negative_prompt = f"{additional_negatives}, {negative_prompt}"
+
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator().manual_seed(seed)
 
+    # Generate the image with the final prompts
     image = pipe(
         prompt=final_prompt,
-        negative_prompt='worst quality, bad quality, jpeg artifacts, source_cartoon, 3d, (censor), monochrome, blurry, lowres, watermark, ' + negative_prompt,
+        negative_prompt=full_negative_prompt,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
         width=width,
@@ -47,7 +53,8 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     ).images[0]
 
     # Return image, seed, and the used prompts
-    return image, seed, f"Prompt used: {final_prompt}\nNegative prompt used: {negative_prompt}"
+    return image, seed, f"Prompt used: {final_prompt}\nNegative prompt used: {full_negative_prompt}"
+
 
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",