Update app.py

app.py

@@ -13,7 +13,7 @@ LORA_FACE_ADAPTER = "face_detail"
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 DTYPE = torch.float16 if DEVICE == "cuda" else torch.float32
 
-print("Chargement SDXL...")
+print("SDXL NSFW loading...")
 pipe = AutoPipelineForText2Image.from_pretrained(
     BASE_MODEL_ID,
     torch_dtype=DTYPE,
@@ -23,92 +23,76 @@ pipe = AutoPipelineForText2Image.from_pretrained(
 )
 pipe.to(DEVICE)
 
-# MONKEY PATCH NSFW : Force "toujours safe"
-def dummy_safety_checker(images, **kwargs):
+# MONKEY PATCH NSFW
+def dummy_checker(images, **kwargs):
     return images, [False] * len(images)
+pipe.safety_checker = dummy_checker
 
-pipe.safety_checker = dummy_safety_checker
 pipe.set_progress_bar_config(disable=True)
 
-print("Chargement LoRA face...")
+print("LoRA face...")
 pipe.load_lora_weights(LORA_FACE_REPO, adapter_name=LORA_FACE_ADAPTER)
 
 os.makedirs("outputs", exist_ok=True)
 
 @spaces.GPU()
-def generate(prompt, negative_prompt, seed, steps, guidance, width, height, face_enabled, face_weight, script_name):
-    if not prompt:
-        return None, "Prompt vide.", ""
-
+def generate(prompt, negative, seed, steps, guidance, width, height, face_weight, name):
     generator = torch.Generator(DEVICE).manual_seed(int(seed)) if seed >= 0 else torch.Generator(DEVICE)
 
-    adapters = [LORA_FACE_ADAPTER]
-    weights = [float(face_weight) if face_enabled else 0.0]
-    pipe.set_adapters(adapters, adapter_weights=weights)
-
-    try:
-        result = pipe(
-            prompt=prompt,
-            negative_prompt=negative_prompt or None,
-            num_inference_steps=int(steps),
-            guidance_scale=float(guidance),
-            width=int(width),
-            height=int(height),
-            generator=generator,
-        )
-    except Exception as e:
-        return None, f"Erreur: {e}", ""
-
-    image = result.images[0]
-    
+    pipe.set_adapters([LORA_FACE_ADAPTER], adapter_weights=[face_weight])
+
+    result = pipe(
+        prompt=prompt,
+        negative_prompt=negative or None,
+        num_inference_steps=int(steps),
+        guidance_scale=float(guidance),
+        width=int(width),
+        height=int(height),
+        generator=generator,
+    ).images[0]
+
     metadata = {
         "model": BASE_MODEL_ID,
-        "lora_face": LORA_FACE_REPO,
+        "lora": LORA_FACE_REPO,
         "prompt": prompt,
         "seed": int(seed),
         "steps": int(steps),
         "guidance": float(guidance),
     }
 
-    base_name = script_name.strip().replace(" ", "_") or "nsfw_sdxl"
-    img_path = f"outputs/{base_name}.png"
-    json_path = f"outputs/{base_name}.json"
+    safe_name = name.strip().replace(" ", "_") or "sdxl_nsfw"
+    img_path = f"outputs/{safe_name}.png"
+    json_path = f"outputs/{safe_name}.json"
 
     pnginfo = PngImagePlugin.PngInfo()
     pnginfo.add_text("params", json.dumps(metadata))
-    image.save(img_path, pnginfo=pnginfo)
+    result.save(img_path, pnginfo=pnginfo)
 
     with open(json_path, "w", encoding="utf-8") as f:
         json.dump(metadata, f, indent=2)
 
-    return image, json.dumps(metadata, indent=2), json_path
+    return result, json.dumps(metadata, indent=2), json_path  # ← chemin relatif OK pour gr.File
 
-with gr.Blocks(title="SDXL NSFW Unlocked") as demo:
-    gr.Markdown("## SDXL 1.0 NSFW ✅ + Face Detail LoRA")
+with gr.Blocks(title="🔥 SDXL NSFW Unlocked") as demo:
+    gr.Markdown("# SDXL 1.0 NSFW + Face Detail LoRA\n✅ Safety checker BYPASSED")
     
     with gr.Row():
-        with gr.Column():
-            prompt = gr.Textbox(
-                "Prompt NSFW", lines=4, 
-                value="masterpiece, best quality, 1girl, nude, detailed anatomy, realistic skin, sharp face, hourglass figure"
-            )
-            negative = gr.Textbox(
-                "Negative", value="blurry, deformed, ugly, lowres, extra limbs"
-            )
-            seed = gr.Number("Seed (-1=random)", value=-1)
-            steps = gr.Slider(20, 50, 35, step=1, label="Steps")
-            guidance = gr.Slider(5.0, 12.0, 7.5, step=0.1, label="Guidance")
-            w, h = 1024, 1024
-            width = gr.Slider(512, 1536, w, step=64, label="Width")
-            height = gr.Slider(512, 1536, h, step=64, label="Height")
-            
-            face_weight = gr.Slider(0.0, 1.2, 0.7, step=0.05, label="LoRA Face Weight")
+        with gr.Column(scale=1):
+            prompt = gr.Textbox("Prompt", lines=4, value="1girl nude, masterpiece, detailed anatomy, realistic skin, sharp face")
+            negative = gr.Textbox("Negative", value="blurry, deformed, ugly, low quality")
+            seed = gr.Number("Seed", value=-1)
+            steps = gr.Slider(20, 50, 35, step=1)
+            guidance = gr.Slider(5, 12, 7.5, step=0.1)
+            width = gr.Slider(512, 1536, 1024, step=64)
+            height = gr.Slider(512, 1536, 1024, step=64)
+            face_weight = gr.Slider(0, 1.2, 0.7, step=0.05, label="LoRA Weight")
+            filename = gr.Textbox("Filename", value="nsfw_test")
             
-            name = gr.Textbox("Nom fichier", value="nsfw_test")
-            gr.Button("🚀 Générer NSFW", variant="primary").click(
-                generate, 
-                [prompt, negative, seed, steps, guidance, width, height, True, face_weight, name],
-                [gr.Image("Image"), gr.Textbox("Metadata", lines=10), gr.File("JSON")]
+        with gr.Column(scale=1):
+            gr.Button("🚀 Generate NSFW", variant="primary", size="lg").click(
+                generate,
+                [prompt, negative, seed, steps, guidance, width, height, face_weight, filename],
+                [gr.Image(label="Generated Image"), gr.Textbox(label="Metadata JSON"), gr.File(label="Download JSON")]  # ← FIX ICI
             )
 
 if __name__ == "__main__":