Update app.py

app.py

@@ -1,7 +1,66 @@
+import torch
+from diffusers import DiffusionPipeline
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load the base model and apply the LoRA weights for super realism
+def load_pipeline():
+    base_model = "black-forest-labs/FLUX.1-dev"
+    lora_repo = "strangerzonehf/Flux-Super-Realism-LoRA"
+    trigger_word = "Super Realism"  # Recommended trigger word
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+    # Load the base model
+    pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
+
+    # Load the LoRA weights into the pipeline
+    pipe.load_lora_weights(lora_repo)
+
+    # Use GPU if available
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    pipe.to(device)
+    return pipe
+
+# Instantiate the pipeline once on Space startup
+pipe = load_pipeline()
+
+# Define a function for image generation
+def generate_image(prompt, seed, width, height, guidance_scale, randomize_seed):
+    # If randomize_seed is selected, allow the model to generate a random seed
+    if randomize_seed:
+        seed = None
+
+    # Ensure the prompt includes realism trigger words if needed
+    if "realistic" not in prompt.lower() and "realism" not in prompt.lower():
+        prompt += " realistic, realism"
+
+    # Generate the image
+    output = pipe(
+        prompt=prompt,
+        seed=seed,
+        width=width,
+        height=height,
+        guidance_scale=guidance_scale
+    )
+    return output.images[0]
+
+# Set up Gradio interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.inputs.Textbox(lines=2, label="Prompt", placeholder="Enter your prompt, e.g., 'A tiny astronaut hatching from an egg on the moon, 4k, planet theme'"),
+        gr.inputs.Slider(0, 10000, step=1, default=0, label="Seed (0 for random)"),
+        gr.inputs.Slider(256, 1024, step=64, default=1024, label="Width"),
+        gr.inputs.Slider(256, 1024, step=64, default=1024, label="Height"),
+        gr.inputs.Slider(1, 20, step=0.5, default=6, label="Guidance Scale"),
+        gr.inputs.Checkbox(default=True, label="Randomize Seed")
+    ],
+    outputs=gr.outputs.Image(type="pil", label="Generated Image"),
+    title="Flux Super Realism LoRA Demo",
+    description=(
+        "This demo uses the Flux Super Realism LoRA model for ultra-realistic image generation. "
+        "You can use the trigger word 'Super Realism' (recommended) along with other realism-related words "
+        "to guide the generation process."
+    ),
+)
+
+if __name__ == "__main__":
+    iface.launch()