enable width param and contains nfsw response on API

app.py

@@ -19,7 +19,7 @@ torch.backends.cudnn.benchmark = True
 word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
 word_list = word_list_dataset["train"]['text']
 
-def infer(prompt, samples, steps, scale, seed):
+def infer(prompt, samples, steps, scale, seed, width):
     #When running locally you can also remove this filter
     for filter in word_list:
         if re.search(rf"\b{filter}\b", prompt):
@@ -32,15 +32,20 @@ def infer(prompt, samples, steps, scale, seed):
         num_inference_steps=steps,
         guidance_scale=scale,
         generator=generator,
+        width=int(width),
+        height=int(width),
     )
     images = []
     safe_image = Image.open(r"unsafe.png")
+    contains_nfsw = []
     for i, image in enumerate(images_list["sample"]):
         if(images_list["nsfw_content_detected"][i]):
             images.append(safe_image)
+            contains_nfsw.append([True])
         else:
             images.append(image)
-    return images
+            contains_nfsw.append([False])
+    return [images, contains_nfsw]
     
 css = """
         .gradio-container {
@@ -136,6 +141,7 @@ examples = [
         45,
         7.5,
         1024,
+        512,
     ],
     [
         'A pikachu fine dining with a view to the Eiffel Tower',
@@ -143,6 +149,7 @@ examples = [
         45,
         7,
         1024,
+        512,
     ],
     [
         'A mecha robot in a favela in expressionist style',
@@ -150,6 +157,7 @@ examples = [
         45,
         7,
         1024,
+        512,
     ],
     [
         'an insect robot preparing a delicious meal',
@@ -157,6 +165,7 @@ examples = [
         45,
         7,
         1024,
+        512,
     ],
     [
         "A small cabin on top of a snowy mountain in the style of Disney, artstation",
@@ -164,6 +173,7 @@ examples = [
         45,
         7,
         1024,
+        512,
     ],
 ]
 
@@ -253,7 +263,6 @@ with block:
         ).style(grid=[2], height="auto")
 
         advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
-
         with gr.Row(elem_id="advanced-options"):
             samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1)
             steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1)
@@ -267,13 +276,14 @@ with block:
                 step=1,
                 randomize=True,
             )
-
-        ex = gr.Examples(examples=examples, fn=infer, inputs=[text, samples, steps, scale, seed], outputs=gallery, cache_examples=True)
+        contains_nfsw = gr.Dataframe(type="numpy", datatype="bool", visible=False)
+        width = gr.Number(value=128, visible=False)
+        ex = gr.Examples(examples=examples, fn=infer, inputs=[text, samples, steps, scale, seed, width], outputs=[gallery, contains_nfsw], cache_examples=False)
         ex.dataset.headers = [""]
 
         
-        text.submit(infer, inputs=[text, samples, steps, scale, seed], outputs=gallery)
-        btn.click(infer, inputs=[text, samples, steps, scale, seed], outputs=gallery)
+        text.submit(infer, inputs=[text, samples, steps, scale, seed, width], outputs=[gallery, contains_nfsw])
+        btn.click(infer, inputs=[text, samples, steps, scale, seed, width], outputs=[gallery, contains_nfsw])
         advanced_button.click(
             None,
             [],