Update app.py

app.py

@@ -1,47 +1,116 @@
-import os
 import gradio as gr
-from huggingface_hub import login
-from zerogpu import ZeroGPU  # Import ZeroGPU
+import numpy as np
+import random
+import spaces
+import torch
+from diffusers import DiffusionPipeline
 
-# Initialize ZeroGPU
-zero_gpu = ZeroGPU()
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
 
-# Gradio demo definition
-def create_demo():
-    with gr.Blocks() as demo:
-        gr.Markdown("# Flex.1-alpha Text to Image Generation")
+# Changed model to Flex.1-alpha
+pipe = DiffusionPipeline.from_pretrained("ostris/Flex.1-alpha", torch_dtype=dtype).to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 2048
+
+@spaces.GPU()
+def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=20, progress=gr.Progress(track_tqdm=True)):
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator().manual_seed(seed)
+    image = pipe(
+            prompt=prompt, 
+            width=width,
+            height=height,
+            num_inference_steps=num_inference_steps, 
+            generator=generator,
+    ).images[0]
+    return image, seed
+ 
+examples = [
+    "a detailed portrait of a cyberpunk character",
+    "a serene landscape with mountains and lakes",
+    "a futuristic city at night with neon lights",
+]
+
+css="""
+#col-container {
+    margin: 0 auto;
+    max-width: 520px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(f"""# Flex.1-alpha
+A fine-tuned version of FLUX optimized for high-quality image generation
+        """)
         
         with gr.Row():
-            with gr.Column():
-                prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
-                negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What you don't want to see in the image...")
-                
-                with gr.Row():
-                    generate = gr.Button("Generate")
-                    clear = gr.Button("Clear")
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
             
-            with gr.Column():
-                result = gr.Image(label="Generated Image")
+            run_button = gr.Button("Run", scale=0)
         
-        def mock_generation(prompt, negative_prompt):
-            return None  # Return None as we can't generate images in zero GPU environment
+        result = gr.Image(label="Result", show_label=False)
         
-        generate.click(
-            fn=mock_generation,
-            inputs=[prompt, negative_prompt],
-            outputs=result
-        )
-        clear.click(lambda: ["", ""], outputs=[prompt, negative_prompt])
+        with gr.Accordion("Advanced Settings", open=False):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+            
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+            
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+                
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+            
+            with gr.Row():
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=20,  # Changed default to 20 as Flex might need more steps
+                )
         
-    return demo
-
-# Create and launch the demo
-if __name__ == "__main__":
-    demo = create_demo()
-    # Configure the launch settings for Spaces
-    demo.launch(
-        server_name="0.0.0.0",  # Required for Spaces
-        server_port=7860,       # Default Spaces port
-        share=False,            # Don't create a public link
-        enable_queue=True       # Enable queuing for better handling of multiple users
-    )
+        gr.Examples(
+            examples=examples,
+            fn=infer,
+            inputs=[prompt],
+            outputs=[result, seed],
+            cache_examples="lazy"
+        )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps],
+        outputs=[result, seed]
+    )
+
+demo.launch()