Update app.py

app.py

@@ -1,153 +1,148 @@
-from contextlib import nullcontext
-from diffusers import EulerAncestralDiscreteScheduler, StableDiffusionXLPipeline
-import gradio as gr
-import spaces
+import spaces  # <-- DAPAT ITO ANG PINAKAUNANG LINYA BAGO ANG LAHAT!
+
+import gc
 import torch
+import gradio as gr
+from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
 
-# Listahan ng models (Hugging Face Repositories)
+# =========================================================================
+# LAHAT NG 8 CHECKPOINT MODELS MULA SA HUGGING FACE
+# =========================================================================
 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",
-    ),
+    "SpatterXL v1.7 (Illustrious x Pony)": {
+        "type": "pretrained",
+        "path": "John6666/spatterxl-illustriousxl-ponyxl-v15-sdxl"
+    },
+    "Solmeleon-XL (NoobAI x Illustrious)": {
+        "type": "pretrained",
+        "path": "John6666/solmeleon-illustriousxl-v10-sdxl"
+    },
+    "HoneyMix PonyXL (High Contrast Anime)": {
+        "type": "pretrained",
+        "path": "John6666/honey-mix-xl-high-contrast-anime-checkpoint-v1-sdxl"
+    },
+    "Pony Diffusion V6 XL (Waifu & NSFW)": {
+        "type": "single_file",
+        "path": "https://huggingface.co/LyliaEngine/Pony_Diffusion_V6_XL/resolve/main/ponyDiffusionV6XL_v6StartWithThisOne.safetensors"
+    },
+    "Illustrious-XL v0.1 (Official Base)": {
+        "type": "single_file",
+        "path": "https://huggingface.co/OnomaAIResearch/Illustrious-xl-early-release-v0/resolve/main/Illustrious-XL-v0.1.safetensors"
+    },
+    "Hoseki LustrousMix (Vibrant Anime)": {
+        "type": "single_file",
+        "path": "https://huggingface.co/LyliaEngine/hosekiLustrousmixAnima_animaV10/resolve/main/hosekiLustrousmixAnima_animaV10.safetensors"
+    },
+    "Initium-XL (NoobAI Epsilon 1.1)": {
+        "type": "single_file",
+        "path": "https://huggingface.co/John6666/initium-finetune-noobaiepsilon11-v10-sdxl/resolve/main/initium-finetune-noobaiepsilon11-v10-sdxl.safetensors"
+    },
+    "Tryptophan-666 (Illustrious x Pony XL)": {
+        "type": "single_file",
+        "path": "https://huggingface.co/John6666/tryptophan-666-illustrious-xl-pony-compatable-v1666-sdxl/resolve/main/tryptophan-666-illustrious-xl-pony-compatable-v1666-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
-        )
+        if pipe is not None:
+            del pipe
+            gc.collect()
+            torch.cuda.empty_cache()
+
+        cfg = MODELS[model_choice]
+        print(f"Loading checkpoint: {model_choice}...")
+        
+        if cfg["type"] == "pretrained":
+            pipe = StableDiffusionXLPipeline.from_pretrained(
+                cfg["path"],
+                torch_dtype=torch.float16,
+                use_safetensors=True
+            )
+        else:
+            pipe = StableDiffusionXLPipeline.from_single_file(
+                cfg["path"],
+                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
+# ZeroGPU: Dynamic Nvidia A100 GPU Allocation
 @spaces.GPU(duration=45)
-def generate_image(
-    prompt, negative_prompt, model_choice, width, height, steps, cfg_scale, seed
-):
+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
-        )
+        generator = torch.Generator(device="cuda").manual_seed(int(seed))
+        
+    is_pony_family = any(k in model_choice for k in ["Pony", "Spatter", "Honey", "Tryptophan", "Initium"])
+    if is_pony_family and "score_9" not in prompt:
+        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
+    elif "masterpiece" not in prompt:
+        prompt = "masterpiece, best quality, very aesthetic, " + prompt
+        negative_prompt = "ugly, deformed, blurry, bad hands, low quality, " + negative_prompt
 
     image = pipeline(
         prompt=prompt,
         negative_prompt=negative_prompt,
-        width=width,
-        height=height,
-        num_inference_steps=steps,
-        guidance_scale=cfg_scale,
-        generator=generator,
+        width=int(width),
+        height=int(height),
+        num_inference_steps=int(steps),
+        guidance_scale=float(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
+    gr.Markdown("""
+    # 👑 QUEENDOM STUDIO — ZeroGPU Backend (8 Models)
     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",
+                value="SpatterXL v1.7 (Illustrious x Pony)",
+                label="Select 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",
-            )
-
+            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, blurry, bad anatomy")
+            
             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"
-                )
-
+                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"
-                )
-
+                steps_slider = gr.Slider(15, 40, value=26, step=1, label="Steps")
+                cfg_slider = gr.Slider(3.0, 10.0, value=6.0, 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"]
-            )
-
+            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,
+        inputs=[prompt_input, neg_prompt_input, model_dd, width_slider, height_slider, steps_slider, cfg_slider, seed_input],
+        outputs=output_img
     )
 
 demo.queue().launch()