feat: Enable lazy loading of examples in app.py

app.py

@@ -13,7 +13,7 @@ client = None
 job = None
 
 
-def infer(selected_space_index, prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
+def infer(selected_space, prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
     global job
     global client
 
@@ -21,16 +21,12 @@ def infer(selected_space_index, prompt, seed=42, randomize_seed=False, width=102
     max_attempts = len(flux_1_schell_spaces)
     attempts = 0
 
-    while client is None and attempts < max_attempts:
-        try:
-            selected_space = flux_1_schell_spaces[selected_space_index]
-            client = Client(selected_space)
-            print(f"Loaded custom model from {selected_space}")
-        except ValueError as e:
-            print(f"Failed to load custom model from {selected_space}: {e}")
-            selected_space_index = (selected_space_index + 1) % len(flux_1_schell_spaces)
-            client = None
-            attempts += 1
+    try:
+        client = Client(selected_space)
+        print(f"Loaded custom model from {selected_space}")
+    except ValueError as e:
+        print(f"Failed to load custom model from {selected_space}: {e}")
+        client = None
 
     if client is None:
         raise gr.Error("Failed to load client after trying all spaces.")
@@ -76,7 +72,7 @@ with gr.Blocks(css=css) as demo:
 12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
 [[blog](https://blackforestlabs.ai/2024/07/31/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
         """)
-        space = gr.Radio(flux_1_schell_spaces, label="HF Space")
+        space = gr.Radio(flux_1_schell_spaces, label="HF Space", value=flux_1_schell_spaces[0])
      
         
         with gr.Row():
@@ -144,7 +140,7 @@ with gr.Blocks(css=css) as demo:
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn = infer,
-        inputs = [selected_space_index, prompt, seed, randomize_seed, width, height, num_inference_steps],
+        inputs = [space, prompt, seed, randomize_seed, width, height, num_inference_steps],
         outputs = [selected_space_index, space, result, seed]
     )