Update app.py

app.py

@@ -158,6 +158,57 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
         seed = random.randint(0, MAX_SEED)
     return seed
 
+@spaces.GPU(duration=60)
+def generate_30(
+    model_choice: str,
+    prompt: str,
+    negative_prompt: str = "",
+    use_negative_prompt: bool = False,
+    style_selection: str = "",
+    seed: int = 1,
+    width: int = 768,
+    height: int = 768,
+    guidance_scale: float = 4,
+    num_inference_steps: int = 125,
+    randomize_seed: bool = False,
+    use_resolution_binning: bool = True, 
+    num_images: int = 1,  
+    progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
+):
+    global models
+    pipe = models[model_choice]
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator(device='cuda').manual_seed(seed)
+    prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
+    options = {
+        "prompt": [prompt] * num_images,
+        "negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
+        "width": width,
+        "height": height,
+        "guidance_scale": guidance_scale,
+        "num_inference_steps": num_inference_steps,
+        "generator": generator,
+        "output_type": "pil",
+    }
+    if use_resolution_binning:
+        options["use_resolution_binning"] = True
+    images = []
+    pipe.scheduler.set_timesteps(num_inference_steps,device)
+    #with torch.no_grad():
+    for i in range(0, num_images, BATCH_SIZE):
+        batch_options = options.copy()
+        batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
+        if "negative_prompt" in batch_options:
+            batch_options["negative_prompt"] = options["negative_prompt"][i:i+BATCH_SIZE]
+        images.extend(pipe(**batch_options).images)
+    sd_image_path = f"rv50_{seed}.png"
+    images[0].save(sd_image_path,optimize=False,compress_level=0)
+    upload_to_ftp(sd_image_path)    
+    image_paths = [save_image(img) for img in images]
+    torch.cuda.empty_cache()
+    gc.collect()
+    return image_paths, seed
+
 @spaces.GPU(duration=60)
 def generate_60(
     model_choice: str,
@@ -284,8 +335,9 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
             placeholder="Enter your prompt",
             container=False,
         )
-        run_button_60 = gr.Button("Run_60", scale=0)
-        run_button_90 = gr.Button("Run_90", scale=0)
+        run_button_30 = gr.Button("Run 30 Seconds", scale=0)
+        run_button_60 = gr.Button("Run 60 Seconds", scale=0)
+        run_button_90 = gr.Button("Run 90 Seconds", scale=0)
     result = gr.Gallery(label="Result", columns=1, show_label=False) 
 
     with gr.Row():
@@ -373,6 +425,29 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
         api_name=False,
     )
     
+    gr.on(
+        triggers=[
+            run_button_30.click,
+        ],
+      #  api_name="generate",  # Add this line
+        fn=generate_30,
+        inputs=[
+            model_choice,
+            prompt,
+            negative_prompt,
+            use_negative_prompt,
+            style_selection,
+            seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+            randomize_seed, 
+            num_images, 
+        ],
+        outputs=[result, seed],
+    )
+    
     gr.on(
         triggers=[
             run_button_60.click,