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app.py

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+import gradio as gr
+from utils import generate_images_simulated
+
+# --- Constants ---
+ANYCODER_LINK = "https://huggingface.co/spaces/akhaliq/anycoder"
+MODEL_CHOICES = {
+    "Stable Diffusion v1.4 (CompVis)": "CompVis/stable-diffusion-v1-4",
+    "Stable Diffusion 2.1 Base (Manojb)": "Manojb/stable-diffusion-2-1-base"
+}
+DEFAULT_MODEL_KEY = list(MODEL_CHOICES.keys())[0]
+
+# --- Gradio Logic Wrapper ---
+def process_generation(prompt: str, negative_prompt: str, model_key: str, steps: float, guidance_scale: float, num_images: float):
+    """
+    Wrapper function to call the simulated generation logic, translating model key.
+    
+    Args:
+        prompt: The text prompt for generation.
+        negative_prompt: Text prompt to guide the model away from.
+        model_key: The user-friendly name of the selected model.
+        steps: Inference steps.
+        guidance_scale: CFG scale.
+        num_images: Number of images to generate (1-4).
+        
+    Returns:
+        A list of PIL Images for the Gradio Gallery.
+    """
+    model_name_id = MODEL_CHOICES[model_key]
+    
+    # Note: steps and guidance_scale are floats from the slider, cast to appropriate types
+    results = generate_images_simulated(
+        prompt=prompt, 
+        negative_prompt=negative_prompt, 
+        model_name=model_name_id, 
+        steps=int(steps), 
+        guidance_scale=guidance_scale, 
+        num_images=int(num_images)
+    )
+    return results
+
+# --- Gradio UI Definition ---
+with gr.Blocks(title="Stable Diffusion Model Comparison Demo") as demo:
+    
+    # Custom Header
+    gr.HTML(
+        f"""
+        <div style="text-align: center; max-width: 800px; margin: 0 auto;">
+            <h1>Stable Diffusion Model Comparison Demo</h1>
+            <p>Compare outputs from Stable Diffusion v1.4 and 2.1 Base. The application handles empty prompts by using a default prompt internally.</p>
+            <p>Built with <a href="{ANYCODER_LINK}" target="_blank" style="color: blue; text-decoration: underline;">anycoder</a></p>
+        </div>
+        """
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            # --- Inputs ---
+            prompt = gr.Textbox(
+                label="Prompt", 
+                placeholder="e.g., A photorealistic image of a vintage robot reading a book in a cozy library, cinematic lighting",
+                value="A majestic portrait of a futuristic cyborg cat, digital art, highly detailed",
+                lines=3
+            )
+            
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt (Optional)", 
+                placeholder="e.g., blurry, low quality, distorted, bad anatomy, text",
+                lines=2
+            )
+            
+            model_selector = gr.Radio(
+                label="Select Model",
+                choices=list(MODEL_CHOICES.keys()),
+                value=DEFAULT_MODEL_KEY,
+                interactive=True
+            )
+            
+            with gr.Accordion("Generation Parameters", open=True):
+                steps = gr.Slider(
+                    minimum=10, maximum=100, step=5, value=50, label="Inference Steps"
+                )
+                
+                guidance_scale = gr.Slider(
+                    minimum=1.0, maximum=15.0, step=0.5, value=7.5, label="Guidance Scale (CFG)"
+                )
+                
+                num_images = gr.Slider(
+                    minimum=1, maximum=4, step=1, value=4, label="Number of Images to Generate",
+                    info="Uploads up to 4 images."
+                )
+            
+            generate_btn = gr.Button("Generate Images", variant="primary")
+
+        with gr.Column(scale=3):
+            # --- Outputs ---
+            output_gallery = gr.Gallery(
+                label="Generated Images (512x512)", 
+                columns=2, 
+                rows=2, 
+                height="auto", 
+                preview=True
+            )
+            
+            gr.Examples(
+                examples=[
+                    ["A hyper-detailed oil painting of a lighthouse during a storm", "ugly, blurry, low resolution", DEFAULT_MODEL_KEY],
+                    ["", "text, watermark, poor rendering", "Stable Diffusion 2.1 Base (Manojb)"], # Empty prompt example
+                    ["A 1950s sci-fi movie poster featuring a giant insect attacking Paris", "modern, photorealistic, color photo", DEFAULT_MODEL_KEY]
+                ],
+                inputs=[prompt, negative_prompt, model_selector],
+                label="Examples (Note the second example uses an empty prompt)"
+            )
+
+    # --- Logic Binding ---
+    generate_btn.click(
+        fn=process_generation,
+        inputs=[prompt, negative_prompt, model_selector, steps, guidance_scale, num_images],
+        outputs=[output_gallery]
+    )
+    
+    # Run initial generation on load to populate the gallery immediately
+    demo.load(
+        fn=process_generation,
+        inputs=[prompt, negative_prompt, model_selector, steps, guidance_scale, num_images],
+        outputs=[output_gallery]
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+requests
+Pillow
+numpy