update app

app.py

@@ -1,97 +1,3 @@
-import os
-
-os.environ.setdefault("PYTORCH_CUDA_ALLOC_CONF", "expandable_segments:True")
-
-import spaces
-import random
-import torch
-import gradio as gr
-from PIL import Image
-from diffusers import QwenImage21Pipeline
-
-MODEL_ID = os.environ.get("QWEN_IMAGE_MODEL", "Qwen/Qwen-Image-2.1")
-LORA_REPO = os.environ.get(
-    "UNCENSORED_LORA_REPO", "abenzerps/Qwen-Image-2.1-Uncensored-GGUF"
-)
-LORA_WEIGHT = os.environ.get(
-    LORA_REPO = "abenzerps/Qwen-Image-2.1-Uncensored-Quantized"
-LORA_WEIGHT = "qwen-image-2.1-uncensored-lora.safetensors"
-
-pipe.load_lora_weights(
-    LORA_REPO,
-    weight_name=LORA_WEIGHT
-)
-)
-
-SIZE_PRESETS = {
-    "1024x1024 (1:1)": (1024, 1024),
-    "1344x768 (16:9)": (1344, 768),
-    "768x1344 (9:16)": (768, 1344),
-    "1184x864 (4:3)": (1184, 864),
-    "864x1184 (3:4)": (864, 1184),
-}
-
-pipe = QwenImage21Pipeline.from_pretrained(MODEL_ID, torch_dtype=torch.bfloat16)
-pipe.load_lora_weights(LORA_REPO, weight_name=LORA_WEIGHT)
-pipe.to("cuda")
-pipe.vae.enable_tiling(
-    tile_sample_min_height=1024,
-    tile_sample_min_width=1024,
-    tile_sample_stride_height=768,
-    tile_sample_stride_width=768,
-)
-
-
-def _seed(seed: int, randomize_seed: bool) -> int:
-    if randomize_seed or seed is None or int(seed) < 0:
-        return random.randint(0, 2**32 - 1)
-    return int(seed)
-
-
-def _set_lora(scale: float) -> None:
-    try:
-        pipe.set_adapters(["default"], adapter_weights=[float(scale)])
-    except Exception:
-        pass
-
-
-def _as_pil(img) -> Image.Image:
-    if img is None:
-        raise gr.Error("Upload an image.")
-    if isinstance(img, Image.Image):
-        return img.convert("RGB")
-    return Image.fromarray(img).convert("RGB")
-
-
-@spaces.GPU(duration=120)
-def generate(
-    prompt: str,
-    size: str,
-    steps: int,
-    seed: int,
-    randomize_seed: bool,
-    lora_scale: float,
-) -> tuple:
-    """Text-to-image with Qwen-Image-2.1 + uncensored LoRA."""
-    if not prompt or not prompt.strip():
-        raise gr.Error("Enter a prompt.")
-    seed = _seed(seed, randomize_seed)
-    width, height = SIZE_PRESETS.get(size, (1024, 1024))
-    generator = torch.Generator("cuda").manual_seed(seed)
-    _set_lora(lora_scale)
-    image = pipe(
-        prompt=prompt.strip(),
-        width=width,
-        height=height,
-        num_inference_steps=int(steps),
-        true_cfg_scale=1.0,
-        generator=generator,
-    ).images[0]
-    return image, seed
-
-
-@spaces.GPU(duration=120)
-def edit(
     prompt: str,
     input_image,
     extra_images: list | None,
@@ -114,7 +20,7 @@ def edit(
     generator = torch.Generator("cuda").manual_seed(seed)
     _set_lora(lora_scale)
     w, h = images[0].size
-    # keep ~1K area so ZeroGPU large fits
+    # Keep the image area near 1 megapixel to reduce ZeroGPU memory use.
     scale = (1024 * 1024 / max(w * h, 1)) ** 0.5
     width = max(64, int(w * scale) // 32 * 32)
     height = max(64, int(h * scale) // 32 * 32)
@@ -133,12 +39,13 @@ def edit(
 with gr.Blocks(title="Qwen-Image-2.1 Uncensored") as demo:
     gr.Markdown(
         """
-# Qwen-Image-2.1 Uncensored — generate & edit
+# Qwen-Image-2.1 Uncensored: generate and edit
+
+[abenzerps/Qwen-Image-2.1-Uncensored-Quantized](https://huggingface.co/abenzerps/Qwen-Image-2.1-Uncensored-Quantized)
 
-[abenzerps/Qwen-Image-2.1-Uncensored-GGUF](https://huggingface.co/abenzerps/Qwen-Image-2.1-Uncensored-GGUF)
-via Diffusers + uncensored LoRA (not Comfy GGUF).
+Uses the Diffusers pipeline with the uncensored LoRA adapter.
 
-**Generate** = text-to-image. **Edit** = 1–10 refs (`image=` on the same pipeline).
+**Generate** creates an image from text. **Edit** accepts 1–10 reference images.
 
 **18+.** No safety filter.
 """
@@ -163,7 +70,7 @@ via Diffusers + uncensored LoRA (not Comfy GGUF).
                     g_out_seed = gr.Number(label="Used seed", precision=0)
             gr.Examples(
                 examples=[
-                    ["A neon shop sign that reads \"QWEN IMAGE 2.1\", rainy night"],
+                    ['A neon shop sign that reads "QWEN IMAGE 2.1", rainy night'],
                     ["Oil painting of a red fox in snow, soft morning light"],
                 ],
                 inputs=[g_prompt],