Update app.py

app.py

@@ -6,15 +6,15 @@ def generate_image(prompt, negative_prompt, seed, width, height, prior_inference
     result = client.predict(
         prompt,
         negative_prompt,
-        seed,
-        width,
-        height,
-        prior_inference_steps,
-        prior_guidance_scale,
-        decoder_inference_steps,
-        decoder_guidance_scale,
-        num_images,
-        api_name="/run"
+		0,	# float (numeric value between 0 and 2147483647) in 'Seed' Slider component
+		1024,	# float (numeric value between 1024 and 1536) in 'Width' Slider component
+		1024,	# float (numeric value between 1024 and 1536) in 'Height' Slider component
+		10,	# float (numeric value between 10 and 30) in 'Prior Inference Steps' Slider component
+		0,	# float (numeric value between 0 and 20) in 'Prior Guidance Scale' Slider component
+		4,	# float (numeric value between 4 and 12) in 'Decoder Inference Steps' Slider component
+		0,	# float (numeric value between 0 and 0) in 'Decoder Guidance Scale' Slider component
+		1,	# float (numeric value between 1 and 2) in 'Number of Images' Slider component
+		api_name="/run"
     )
     return result
 
@@ -22,15 +22,7 @@ demo = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Prompt"),
-        gr.Textbox(label="Negative prompt"),
-        gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1),
-        gr.Slider(label="Width", minimum=1024, maximum=1536, step=1),
-        gr.Slider(label="Height", minimum=1024, maximum=1536, step=1),
-        gr.Slider(label="Prior Inference Steps", minimum=10, maximum=30, step=1),
-        gr.Slider(label="Prior Guidance Scale", minimum=0, maximum=20, step=1),
-        gr.Slider(label="Decoder Inference Steps", minimum=4, maximum=12, step=1),
-        gr.Slider(label="Decoder Guidance Scale", minimum=0, maximum=0, step=1),
-        gr.Slider(label="Number of Images", minimum=1, maximum=2, step=1),
+        gr.Textbox(label="Negative prompt", value="bad quality, low quality"),
     ],
     outputs=["image"],
     theme = "soft"