Update app.py

app.py

@@ -90,44 +90,45 @@ examples = [
 with gr.Blocks(theme=theme, css=css) as app:
     # Add a title to the app
     gr.HTML("<center><h1>FLUX.1-Dev</h1></center>")
-    
-    # Container for all the UI elements
-    with gr.Column(elem_id="app-container"):
-        # Add a text input for the main prompt
-        with gr.Row():
-            with gr.Column(elem_id="prompt-container"):
+    with gr.Tabs() as tabs:
+        with gr.TabItem("✍️ Text to Image 🖼", visible=True):
+            # Container for all the UI elements
+            with gr.Column(elem_id="app-container"):
+                # Add a text input for the main prompt
                 with gr.Row():
-                    text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
+                    with gr.Column(elem_id="prompt-container"):
+                        with gr.Row():
+                            text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
+                        
+                        # Accordion for advanced settings
+                        with gr.Row():
+                            with gr.Accordion("Advanced Settings", open=False):
+                                negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
+                                with gr.Row():
+                                    width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
+                                    height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
+                                steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
+                                cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
+                                strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
+                                seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) # Setting the seed to -1 will make it random
+                                method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "LMS Karras", "PLMS", "UniPC", "UniPC BH2"])
+                            
+                # Add a button to trigger the image generation
+                with gr.Row():
+                    text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
                 
-                # Accordion for advanced settings
+                # Image output area to display the generated image
                 with gr.Row():
-                    with gr.Accordion("Advanced Settings", open=False):
-                        negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
-                        with gr.Row():
-                            width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
-                            height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
-                        steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
-                        cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
-                        strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
-                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) # Setting the seed to -1 will make it random
-                        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
-
-        # Add a button to trigger the image generation
-        with gr.Row():
-            text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
-        
-        # Image output area to display the generated image
-        with gr.Row():
-            image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
-
-        with gr.Row():        
-            gr.Examples(
-                examples = examples,    
-                inputs = [text_prompt],    
-            )            
+                    image_output = gr.Image(type="pil", label="Image Output", share=False, elem_id="gallery")
         
-        # Bind the button to the query function with the added width and height inputs
-        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
+                with gr.Row():        
+                    gr.Examples(
+                        examples = examples,    
+                        inputs = [text_prompt],    
+                    )            
+                
+                # Bind the button to the query function with the added width and height inputs
+                text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
 
 app.queue(default_concurrency_limit=200, max_size=200)  # <-- Sets up a queue with default parameters
 if __name__ == "__main__":