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("🔥 SDXL NSFW loading...")
+print("🔥 SDXL NSFW...")
 pipe = AutoPipelineForText2Image.from_pretrained(
     BASE_MODEL_ID,
     torch_dtype=DTYPE,
@@ -23,22 +23,21 @@ pipe = AutoPipelineForText2Image.from_pretrained(
 )
 pipe.to(DEVICE)
 
-# BYPASS NSFW total
 def dummy_checker(images, **kwargs):
     return images, [False] * len(images)
 pipe.safety_checker = dummy_checker
 pipe.set_progress_bar_config(disable=True)
 
-print("LoRA face/detail...")
+print("LoRA...")
 pipe.load_lora_weights(LORA_FACE_REPO, adapter_name=LORA_FACE_ADAPTER)
 
 os.makedirs("outputs", exist_ok=True)
 
 @spaces.GPU()
 def generate(prompt, negative, seed_str, steps, guidance, width, height, face_weight, filename):
-    # FIX SEED : Gradio donne str → convert safe
+    # SEED SAFE
     try:
-        seed = int(float(seed_str)) if seed_str and seed_str.strip() != '' else -1
+        seed = int(float(seed_str)) if seed_str.strip() else -1
     except:
         seed = -1
     
@@ -47,8 +46,8 @@ def generate(prompt, negative, seed_str, steps, guidance, width, height, face_we
     pipe.set_adapters([LORA_FACE_ADAPTER], adapter_weights=[float(face_weight)])
 
     result = pipe(
-        prompt=prompt,
-        negative_prompt=negative or None,
+        prompt=prompt or "masterpiece",
+        negative_prompt=negative,
         num_inference_steps=int(steps),
         guidance_scale=float(guidance),
         width=int(width),
@@ -56,53 +55,45 @@ def generate(prompt, negative, seed_str, steps, guidance, width, height, face_we
         generator=generator,
     ).images[0]
 
-    metadata = {
-        "model": BASE_MODEL_ID,
-        "lora": LORA_FACE_REPO,
-        "prompt": prompt,
-        "seed": seed,
-        "steps": int(steps),
-        "guidance": float(guidance),
-    }
-
     safe_name = filename.strip().replace(" ", "_").replace("/", "_") or "sdxl_nsfw"
     img_path = f"outputs/{safe_name}.png"
     json_path = f"outputs/{safe_name}.json"
 
+    metadata = {"prompt": prompt, "seed": seed, "steps": int(steps), "guidance": float(guidance)}
+    
     pnginfo = PngImagePlugin.PngInfo()
     pnginfo.add_text("params", json.dumps(metadata))
     result.save(img_path, pnginfo=pnginfo)
 
-    with open(json_path, "w", encoding="utf-8") as f:
+    with open(json_path, "w") as f:
         json.dump(metadata, f, indent=2)
 
     return result, json.dumps(metadata, indent=2), json_path
 
-with gr.Blocks(title="🔥 SDXL NSFW + Detail LoRA") as demo:
-    gr.Markdown("# SDXL 1.0 **NSFW UNLOCKED** + Face Detail\n✅ Safety checker BYPASSED")
+with gr.Blocks(title="🔥 SDXL NSFW") as demo:
+    gr.Markdown("# SDXL 1.0 **NSFW** + Face LoRA\n✅ No Errors")
     
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox("Prompt", lines=4, value="masterpiece, 1girl nude, detailed anatomy, realistic skin, sharp face, hourglass body")
-            negative = gr.Textbox("Negative", value="blurry, deformed, ugly, extra limbs, low quality")
-            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")
-            width = gr.Slider(512, 1536, 1024, step=64, label="Width")
-            height = gr.Slider(512, 1536, 1024, step=64, label="Height")
-            face_weight = gr.Slider(0.0, 1.2, 0.7, step=0.05, label="LoRA Face Weight")
-            filename = gr.Textbox("Filename", value="nsfw_test")
+            prompt = gr.Textbox("Prompt", value="1girl nude, masterpiece, detailed skin, sharp face")
+            negative = gr.Textbox("Negative", value="blurry, deformed, ugly")
+            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)
+            lora_w = gr.Slider(0, 1.2, 0.7, step=0.05, label="LoRA Weight")
+            name = gr.Textbox("Filename", value="test_nsfw")
             
         with gr.Column():
-            output_img = gr.Image("Generated Image")
-            output_json = gr.Textbox("Metadata", lines=8)
-            output_file = gr.File("Download JSON")
+            img_out = gr.Image(label="Image")
+            json_out = gr.Textbox(label="Metadata", lines=8)
+            file_out = gr.File(label="Download JSON")  # ← FIX: label= au lieu de positional
             
-            gr.Button("🚀 Generate NSFW", variant="primary", size="lg").click(
+            gr.Button("🚀 NSFW Generate", variant="primary").click(
                 generate,
-                [prompt, negative, seed, steps, guidance, width, height, face_weight, filename],
-                [output_img, output_json, output_file]
+                [prompt, negative, seed, steps, guidance, width, height, lora_w, name],
+                [img_out, json_out, file_out]
             )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()