Update app.py from anycoder

app.py

@@ -3,90 +3,154 @@ import torch
 from diffusers import DiffusionPipeline
 import random
 
-# --- Configuración del Modelo ---
+# --- Model Configuration ---
 model_id = "NewBie-AI/NewBie-image-Exp0.1"
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-print(f"Cargando modelo en: {device}...")
-
-# Cargamos el pipeline. 
-# Si usas GPU, usamos float16 para mayor velocidad y menos memoria.
-dtype = torch.float16 if device == "cuda" else torch.float32
+print(f"Loading model on: {device}...")
 
+# Load pipeline with proper error handling
 try:
     pipe = DiffusionPipeline.from_pretrained(
         model_id, 
-        torch_dtype=dtype,
+        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
         use_safetensors=True
     )
     pipe.to(device)
-    print("Modelo cargado exitosamente.")
+    print("Model loaded successfully.")
 except Exception as e:
-    print(f"Error cargando el modelo: {e}")
+    print(f"Error loading model: {e}")
 
-# --- Función de Generación ---
+# --- Generation Function ---
 def generate_image(prompt, negative_prompt, steps, guidance_scale, width, height, seed):
     if seed == -1:
         seed = random.randint(0, 2147483647)
     
-    # Configuramos el generador para reproducibilidad
-    generator = torch.Generator(device).manual_seed(int(seed))
+    # Configure generator for reproducibility
+    generator = torch.Generator(device).manual_seed(int(seed)))
     
-    print(f"Generando con semilla: {seed}")
+    print(f"Generating with seed: {seed}")
     
     try:
         image = pipe(
             prompt=prompt,
             negative_prompt=negative_prompt,
-            num_inference_steps=int(steps),
-            guidance_scale=guidance_scale,
-            width=int(width),
-            height=int(height),
+            num_inference_steps=int(steps)),
+            guidance_scale=float(guidance_scale)),
+            width=int(width)),
+            height=int(height)),
             generator=generator
         ).images[0]
         return image, seed
     except Exception as e:
-        return None, f"Error: {str(e)}"
+        return None, f"Error: {str(e)}")
 
-# --- Interfaz de Gradio ---
+# --- Gradio Interface ---
 css = """
 #col-container {max-width: 800px; margin-left: auto; margin-right: auto;}
 """
 
-with gr.Blocks(css=css) as demo:
+with gr.Blocks() as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"# 🎨 Generador de Imágenes: {model_id}")
-        gr.Markdown("Escribe un prompt para generar una imagen usando el modelo NewBie-AI.")
+        gr.Markdown(f"# 🎨 Image Generator: {model_id}")
+        gr.Markdown("Write a prompt to generate an image using the NewBie AI model.")
         
         with gr.Group():
-            prompt = gr.Textbox(label="Prompt (Descripción positiva)", placeholder="Un astronauta montando un caballo en marte, 4k, realista...", lines=2)
-            negative_prompt = gr.Textbox(label="Prompt Negativo (Lo que NO quieres)", placeholder="borroso, deforme, mala calidad, texto...", value="bad quality, worst quality, low resolution, blurry, distorted")
+            prompt = gr.Textbox(
+                label="Prompt (Positive description)", 
+                placeholder="An astronaut riding a horse on Mars, 4k, realistic...", 
+                lines=2
+            )
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt (What you DON'T want)", 
+                placeholder="blurry, deformed, bad quality, text...", 
+                value="bad quality, worst quality, low resolution, blurry, distorted"
+            )
             
         with gr.Row():
-            run_button = gr.Button("Generar Imagen", variant="primary", scale=1)
-        
+            with gr.Column():
+                width = gr.Slider(
+                    label="Width", 
+                    minimum=256, 
+                    maximum=1024, 
+                    step=64, 
+                    value=512
+            )
+            with gr.Column():
+                height = gr.Slider(
+                    label="Height", 
+                    minimum=256, 
+                    maximum=1024, 
+                    step=64, 
+                    value=512
+            )
+            
         with gr.Row():
-            result_image = gr.Image(label="Resultado", interactive=False)
-        
-        with gr.Accordion("Configuración Avanzada", open=False):
-            with gr.Row():
-                width = gr.Slider(label="Ancho", minimum=256, maximum=1024, step=64, value=512)
-                height = gr.Slider(label="Alto", minimum=256, maximum=1024, step=64, value=512)
+            with gr.Column():
+                steps = gr.Slider(
+                    label="Inference Steps", 
+                    minimum=10, 
+                    maximum=100, 
+                    step=1, 
+                    value=25
+            )
+            with gr.Column():
+                guidance_scale = gr.Slider(
+                    label="Guidance Scale (Prompt fidelity)", 
+                    minimum=1.0, 
+                    maximum=20.0, 
+                    step=0.5, 
+                    value=7.5
+            )
             
-            with gr.Row():
-                steps = gr.Slider(label="Pasos de Inferencia", minimum=10, maximum=100, step=1, value=25)
-                guidance_scale = gr.Slider(label="Guidance Scale (Fidelidad al prompt)", minimum=1, maximum=20, step=0.5, value=7.5)
+        with gr.Row():
+            seed = gr.Number(
+                    label="Seed (Use -1 for random)", 
+                    value=-1, 
+                    precision=0
+            )
             
-            seed = gr.Number(label="Semilla (Seed) - Usa -1 para aleatorio", value=-1, precision=0)
-            seed_output = gr.Number(label="Semilla utilizada", interactive=False)
+        with gr.Accordion("Advanced Configuration", open=False):
+                gr.Markdown("Adjust these parameters for finer control over image generation.")
+                
+        run_button = gr.Button("Generate Image", variant="primary")
+        result_image = gr.Image(label="Result", interactive=False)
+        seed_output = gr.Number(label="Seed used", interactive=False)
+        
+        clear_button = gr.Button("Clear", variant="secondary")
+        
+        # Examples
+        examples = gr.Examples(
+            examples=[
+                ["A beautiful sunset over mountains, digital art", "blurry, distorted", 25, 7.5, 512, 512, -1],
+                ["A futuristic city with flying cars, cyberpunk style", "low quality, pixelated", 30, 5.0, 768, 768, -1],
+                ["A magical forest with glowing mushrooms, fantasy", "text, watermark", 40, 3.0, 1024, 1024, -1]
+            ],
+            inputs=[prompt, negative_prompt, steps, guidance_scale, width, height, seed]
+        )
 
-    # Eventos
-    run_button.click(
-        fn=generate_image,
-        inputs=[prompt, negative_prompt, steps, guidance_scale, width, height, seed],
-        outputs=[result_image, seed_output]
-    )
+# Events
+run_button.click(
+    fn=generate_image,
+    inputs=[prompt, negative_prompt, steps, guidance_scale, width, height, seed],
+    outputs=[result_image, seed_output],
+    api_visibility="public"
+)
+
+def clear_all():
+    return None, -1
+
+clear_button.click(
+    fn=clear_all,
+    inputs=None,
+    outputs=[result_image, seed_output],
+    api_visibility="private"
+)
 
-# Lanzar la app
+# Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(
+        theme=gr.themes.Soft(primary_hue="indigo", secondary_hue="purple"),
+        css=css,
+        footer_links=[{"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"]
+)