Update app.py

app.py

@@ -22,6 +22,14 @@ def load_pipeline(model_id):
 # Initialize with default model
 pipe = load_pipeline("CompVis/stable-diffusion-v1-4")
 
+available_models = [
+    "CompVis/stable-diffusion-v1-4",
+    "runwayml/stable-diffusion-v1-5",
+    "stabilityai/stable-diffusion-2-1",
+    "prompthero/openjourney",
+    "stabilityai/sdxl-base-0.9"
+]
+
 def infer(
     model_id,
     prompt,
@@ -73,76 +81,68 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template with Model Selection")
 
-        model_id = gr.Text(
-            label="Model ID",
-            show_label=True,
-            placeholder="Enter HuggingFace model ID (e.g., CompVis/stable-diffusion-v1-4)",
+        model_id = gr.Dropdown(
+            label="Model Selection",
+            choices=available_models,
             value="CompVis/stable-diffusion-v1-4",
         )
 
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+        prompt = gr.Text(
+            label="Prompt",
+            show_label=True,
+            max_lines=1,
+            placeholder="Enter your prompt",
+        )
 
-            run_button = gr.Button("Run", scale=0, variant="primary")
+        negative_prompt = gr.Text(
+            label="Negative prompt",
+            max_lines=1,
+            placeholder="Enter a negative prompt",
+        )
 
-        result = gr.Image(label="Result", show_label=False)
+        seed = gr.Slider(
+            label="Seed",
+            minimum=0,
+            maximum=MAX_SEED,
+            step=1,
+            value=42,
+        )
 
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
+        guidance_scale = gr.Slider(
+            label="Guidance scale",
+            minimum=0.0,
+            maximum=20.0,
+            step=0.1,
+            value=7.0,
+        )
+
+        num_inference_steps = gr.Slider(
+            label="Number of inference steps",
+            minimum=1,
+            maximum=100,
+            step=1,
+            value=20,
+        )
+
+        with gr.Row():
+            width = gr.Slider(
+                label="Width",
+                minimum=256,
+                maximum=MAX_IMAGE_SIZE,
+                step=32,
+                value=512,
             )
 
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=42,
+            height = gr.Slider(
+                label="Height",
+                minimum=256,
+                maximum=MAX_IMAGE_SIZE,
+                step=32,
+                value=512,
             )
 
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=False)
-
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=20.0,
-                    step=0.1,
-                    value=7.0,
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=100,
-                    step=1,
-                    value=20,
-                )
+        run_button = gr.Button("Run", scale=0, variant="primary")
+        result = gr.Image(label="Result", show_label=False)
 
         gr.Examples(examples=examples, inputs=[prompt])
 
@@ -154,11 +154,10 @@ with gr.Blocks(css=css) as demo:
             prompt,
             negative_prompt,
             seed,
-            randomize_seed,
-            width,
-            height,
             guidance_scale,
             num_inference_steps,
+            width,
+            height,
         ],
         outputs=[result, seed],
     )