Update app.py

app.py

@@ -136,10 +136,10 @@ if torch.cuda.is_available():
         pipe3.enable_model_cpu_offload()
     else:
         pipe3.to(device)
-        print("Loaded Animagine XL 4.0 on Device!")
+        print("Loaded RealVisXL_V3.0_Turbo on Device!")
     if USE_TORCH_COMPILE:
         pipe3.unet = torch.compile(pipe3.unet, mode="reduce-overhead", fullgraph=True)
-        print("Model Animagine XL 4.0 Compiled!")
+        print("Model RealVisXL_V3.0_Turbo Compiled!")
 else:
     pipe = StableDiffusionXLPipeline.from_pretrained(
         "SG161222/RealVisXL_V5.0_Lightning",
@@ -235,8 +235,8 @@ def generate(
         
         selected_pipe = models.get(model_choice, pipe)
         images = selected_pipe(**options).images
+        yield "⚡ Generating image ███████▒▒▒ 69%"
         image_path = save_image(images[0])
-        yield "Generating image ..."
         yield gr.Image(image_path)
         return
 
@@ -272,7 +272,7 @@ def generate(
         thread.start()
 
         buffer = ""
-        yield "Thinking..."
+        yield "💭 Thinking..."
         for new_text in streamer:
             buffer += new_text
             buffer = buffer.replace("<|im_end|>", "")
@@ -340,9 +340,9 @@ demo = gr.ChatInterface(
     ],
     examples=[
         ["@tts1 Who is Nikola Tesla, and why did he die?"],
-        ['@lightningv5 "Chocolate dripping from a donut against a yellow background, in the style of brocore, hyper-realistic"'],
-        ['@lightningv4 "A serene landscape with mountains"'],
-        ['@turbov3 "Abstract art, colorful and vibrant"'],
+        ['@lightningv5 Chocolate dripping from a donut against a yellow background, in the style of brocore, hyper-realistic'],
+        ['@lightningv4 A serene landscape with mountains'],
+        ['@turbov3 Abstract art, colorful and vibrant'],
         ["Write a Python function to check if a number is prime."],
         ["@tts2 What causes rainbows to form?"],
     ],
@@ -351,9 +351,10 @@ demo = gr.ChatInterface(
     description=DESCRIPTION,
     css=css,
     fill_height=True,
-    textbox=gr.MultimodalTextbox(label="Query Input", file_types=["image"], file_count="multiple"),
+    textbox=gr.MultimodalTextbox(label="Query Input", file_types=["image"], file_count="multiple", placeholder="use the tags @lightningv5 @lightningv4 @turbov3 for image gen !"),
     stop_btn="Stop Generation",
     multimodal=True,
+    
 )
 
 if __name__ == "__main__":