playgound with openai dependency 4

modules/constants.py

@@ -1,5 +1,6 @@
 # as in k-diffusion (sampling.py)
 MIN_SEED = 0
 MAX_SEED = 2**63 - 1
+MAX_IMAGE_SIZE = 1024
 
 AUTH_FILENAME = 'auth.json'

webui.py

@@ -115,6 +115,12 @@ if torch.cuda.is_available():
 else:
     power_device = "CPU"
 
+examples = [
+    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "An astronaut riding a green horse",
+    "A delicious ceviche cheesecake slice",
+]
+
 with shared.gradio_root:
     gr.Markdown(f"""# <center>zStudios Generative Media AI running on {power_device}</center>""")
     with gr.Tab("DALL-E"):
@@ -133,6 +139,88 @@ with shared.gradio_root:
         dalleText.submit(fn=inf.infer_dall_e, inputs=[dalleText, model, quality, size], outputs=output_image, api_name="infer_dall_e")
         dalleBtn.click(fn=inf.infer_dall_e, inputs=[dalleText, model, quality, size], outputs=output_image, api_name=False)
 
+    with gr.Tab("Stable Diffusion"):
+        with gr.Row():
+        
+            sdText = gr.Textbox(label="Prompt",
+                        placeholder="Enter your text and then click on the \"Run\" button, "
+                                    "or simply press the Enter key.")
+            
+            sdBtn = gr.Button("Run", scale=0)
+        
+        result = gr.Image(label="Image Output")
+
+        with gr.Accordion("Advanced Settings", open=False):
+            
+            negative_prompt = gr.Text(
+                label="Negative prompt",
+                max_lines=1,
+                placeholder="Enter a negative prompt",
+                visible=False,
+            )
+            
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=constants.MAX_SEED,
+                step=1,
+                value=0,
+            )
+            
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+            
+            with gr.Row():
+                
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=constants.MAX_IMAGE_SIZE,
+                    step=32,
+                    value=512,
+                )
+                
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=constants.MAX_IMAGE_SIZE,
+                    step=32,
+                    value=512,
+                )
+            
+            with gr.Row():
+                
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=0.0,
+                    maximum=10.0,
+                    step=0.1,
+                    value=0.0,
+                )
+                
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=12,
+                    step=1,
+                    value=2,
+                )
+        
+        gr.Examples(
+            examples = examples,
+            inputs = [sdText]
+        )
+
+        sdText.submit(
+            fn=inf.infer_stable_diffusion, 
+            inputs=[sdText, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps], 
+            outputs=result, 
+            api_name="infer_stable_diffusion")
+        sdBtn.click(
+            fn = inf.infer_stable_diffusion,
+            inputs = [sdText, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+            outputs = [result]
+        )
+
     with gr.Tab("Fooocus"):
         args = ini_args()
         if args.api_mode: