Create app.py

app.py

@@ -0,0 +1,153 @@
+from contextlib import nullcontext
+from diffusers import EulerAncestralDiscreteScheduler, StableDiffusionXLPipeline
+import gradio as gr
+import spaces
+import torch
+
+# Listahan ng models (Hugging Face Repositories)
+MODELS = {
+    "Pony Diffusion V6 XL": (
+        "LyliaEngine/Pony_Diffusion_V6_XL",
+        "ponyDiffusionV6XL_v6StartWithThisOne.safetensors",
+    ),
+    "Illustrious-XL v0.1": (
+        "OnomaAIResearch/Illustrious-xl-early-release-v0",
+        "Illustrious-XL-v0.1.safetensors",
+    ),
+    "HolyMix Illustrious": (
+        "John6666/holy-mix-illustriousxl-vibrant-anime-checkpoint-v1-sdxl",
+        "holy-mix-illustriousxl-vibrant-anime-checkpoint-v1-sdxl.safetensors",
+    ),
+}
+
+current_model_name = None
+pipe = None
+
+
+def load_pipeline(model_choice):
+    global pipe, current_model_name
+    if pipe is None or current_model_name != model_choice:
+        repo_id, filename = MODELS[model_choice]
+        print(f"Loading {model_choice}...")
+
+        pipe = StableDiffusionXLPipeline.from_single_file(
+            f"https://huggingface.co/{repo_id}/resolve/main/{filename}",
+            torch_dtype=torch.float16,
+            use_safetensors=True,
+        )
+        pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(
+            pipe.scheduler.config
+        )
+        current_model_name = model_choice
+    return pipe
+
+
+# ZeroGPU: Inilalaan lamang ang Nvidia A100 habang tumatakbo ang function na ito
+@spaces.GPU(duration=45)
+def generate_image(
+    prompt, negative_prompt, model_choice, width, height, steps, cfg_scale, seed
+):
+    pipeline = load_pipeline(model_choice)
+    pipeline.to("cuda")
+
+    generator = None
+    if seed != -1:
+        generator = torch.Generator(device="cuda").manual_seed(seed)
+
+    # Siguraduhin ang kalidad para sa Anime / Pony tags
+    if "score_9" not in prompt and "Pony" in model_choice:
+        prompt = (
+            "score_9, score_8_up, score_7_up, source_anime, "
+            + prompt
+            + ", masterpiece, best quality"
+        )
+        negative_prompt = (
+            "score_4, score_5, score_6, ugly, deformed, blurry, bad anatomy, "
+            + negative_prompt
+        )
+
+    image = pipeline(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        width=width,
+        height=height,
+        num_inference_steps=steps,
+        guidance_scale=cfg_scale,
+        generator=generator,
+    ).images[0]
+
+    return image
+
+
+# Custom Netflix Dark CSS na tugma sa website mo
+custom_css = """
+body, .gradio-container { background-color: #141414 !important; color: #ffffff !important; }
+button.primary { background: linear-gradient(90deg, #E50914 0%, #b80710 100%) !important; border: none !important; color: white !important; font-weight: bold !important; }
+"""
+
+with gr.Blocks(css=custom_css, theme=gr.themes.Base()) as demo:
+    gr.Markdown(
+        """
+    # 👑 QUEENDOM STUDIO — ZeroGPU Backend
+    High-Performance SDXL, Pony, and Illustrious Generator powered by free dynamic Nvidia A100.
+    """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            model_dd = gr.Dropdown(
+                choices=list(MODELS.keys()),
+                value="Pony Diffusion V6 XL",
+                label="Checkpoint Model",
+            )
+            prompt_input = gr.Textbox(
+                label="Positive Prompt",
+                lines=3,
+                value="1girl, solo, silver hair, golden eyes, beautiful anime waifu",
+            )
+            neg_prompt_input = gr.Textbox(
+                label="Negative Prompt",
+                lines=2,
+                value="ugly, deformed, low quality",
+            )
+
+            with gr.Row():
+                width_slider = gr.Slider(
+                    512, 1216, value=832, step=64, label="Width"
+                )
+                height_slider = gr.Slider(
+                    512, 1216, value=1216, step=64, label="Height"
+                )
+
+            with gr.Row():
+                steps_slider = gr.Slider(
+                    15, 40, value=25, step=1, label="Steps"
+                )
+                cfg_slider = gr.Slider(
+                    3.0, 10.0, value=6.5, step=0.5, label="CFG Scale"
+                )
+
+            seed_input = gr.Number(value=-1, label="Seed (-1 for Random)")
+            generate_btn = gr.Button(
+                "✨ GENERATE ARTWORK", variant="primary", elem_classes=["primary"]
+            )
+
+        with gr.Column(scale=1):
+            output_img = gr.Image(label="Rendered Artwork", type="pil")
+
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[
+            prompt_input,
+            neg_prompt_input,
+            model_dd,
+            width_slider,
+            height_slider,
+            steps_slider,
+            cfg_slider,
+            seed_input,
+        ],
+        outputs=output_img,
+    )
+
+demo.queue().launch()