Update app.py

app.py

@@ -26,12 +26,17 @@ unet.load_state_dict(load_file(hf_hub_download(repo, opts["4 Steps"][0])))
 pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=dtype, variant="fp16").to(device, dtype)
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
 
+with open("filter.txt") as f:
+    filter_words = {word for word in f.read().split("\n") if word}
+
 # Inference function.
 @spaces.GPU(enable_queue=True)
 def generate(prompt, option, progress=gr.Progress()):
     global step_loaded
     print(prompt, option)
     ckpt, step = opts[option]
+    if any(word in prompt for word in filter_words):
+        return None
     progress((0, step))
     if step != step_loaded:
         print(f"Switching checkpoint from {step_loaded} to {step}")