Update app.py

app.py

@@ -1,11 +1,31 @@
+import torch
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 import gradio as gr
 
-with gr.Blocks(fill_height=True) as demo:
-    with gr.Sidebar():
-        gr.Markdown("# Inference Provider")
-        gr.Markdown("This Space showcases the WolfAether21/NSFW-STABLE-DIFFUSION-LORA model, served by the hf-inference API. Sign in with your Hugging Face account to use this API.")
-        share=True
-        button = gr.LoginButton("Sign in")
-    gr.load("models/WolfAether21/NSFW-STABLE-DIFFUSION-LORA", accept_token=button, provider="hf-inference")
-    
+# Basismodell laden
+base_model = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.float16).to("cuda")
+
+# Optional: NSFW-Filter deaktivieren
+pipe.safety_checker = lambda images, **kwargs: (images, False)
+
+# LoRA laden (Beispiel: LoRA-Dateien lokal gespeichert)
+pipe.load_lora_weights("path/to/lora_weights")
+
+# LoRA aktivieren (nur nötig bei manchen Implementierungen)
+pipe.fuse_lora()
+
+def generate(prompt):
+    image = pipe(prompt).images[0]
+    return image
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        gr.Markdown("## NSFW Uncensored + LoRA Stable Diffusion")
+    prompt = gr.Textbox(label="Prompt", placeholder="Eingabe z.B. 'a nude portrait in oil painting style'")
+    output = gr.Image()
+    btn = gr.Button("Generate")
+
+    btn.click(fn=generate, inputs=prompt, outputs=output)
+
 demo.launch()