Update app.py

app.py

@@ -1,94 +1,44 @@
-import gradio as gr
 import torch
-import random
-import numpy as np
-from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
+from diffusers import StableDiffusionXLPipeline
 from huggingface_hub import hf_hub_download
+import gradio as gr
 
-# --- 設定 ---
-device = "cuda" if torch.cuda.is_available() else "cpu"
-torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 2048
-
-# --- safetensors ファイルの正しい取得 ---
+# モデルを Hugging Face からダウンロード
 model_path = hf_hub_download(
     repo_id="cocoat/cocoamix",
     filename="recocoamixXL3_coamixXL3.safetensors"
 )
 
-# --- パイプライン読み込み ---
-pipe = StableDiffusionXLPipeline.from_single_file(
-    "https://huggingface.co/cocoat/cocoamix/resolve/main/recocoamixXL3_coamixXL3.safetensors",
-    torch_dtype=torch_dtype,
-    use_safetensors=True
-).to(device)
-
-pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(
-    pipe.scheduler.config,
-    use_karras_sigmas=True
-)
-
-# 生成履歴
-history = []
-
-def infer(
-    prompt, negative_prompt, seed, randomize_seed,
-    width, height, cfg_scale, num_inference_steps,
-    progress=gr.Progress(track_tqdm=True)
-):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    gen = torch.Generator(device=device).manual_seed(seed)
-    pipe.scheduler.set_timesteps(num_inference_steps)
+# パイプラインを safetensors 単一ファイルからロード
+pipe = StableDiffusionXLPipeline.from_single_file(model_path, torch_dtype=torch.float16)
+pipe.to("cuda")  # CUDAに載せる（必要に応じて"cpu"に変更可）
 
-    def _callback(pipeline, step_idx, timestep, callback_kwargs):
-        progress(step_idx / num_inference_steps,
-                 desc=f"Step {step_idx}/{num_inference_steps}")
-        return callback_kwargs
-
-    out = pipe(
+# 生成関数
+def generate(prompt, negative_prompt, steps, cfg_scale, seed):
+    generator = torch.manual_seed(seed) if seed else None
+    image = pipe(
         prompt=prompt,
-        negative_prompt=negative_prompt or None,
+        negative_prompt=negative_prompt,
+        num_inference_steps=steps,
         guidance_scale=cfg_scale,
-        num_inference_steps=num_inference_steps,
-        width=width, height=height,
-        generator=gen,
-        callback_on_step_end=_callback
-    )
-    img = out.images[0]
-    history.insert(0, img)
-    progress(1.0, desc="Done!")
-    return img, seed, history
-
-css = "#col-container{margin:auto; max-width:720px}"
-examples = [["1girl, cocoart, masterpiece", "", 0, True, 1024, 1024, 5, 23]]
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown("## recocoamixXL3 demo")
-        prompt = gr.Textbox(lines=1, placeholder="Prompt…")
-        run = gr.Button("Generate")
-        img_out = gr.Image()
-        seed_out = gr.Textbox(label="Seed", interactive=False)
-        history_gallery = gr.Gallery(label="生成履歴", columns=4, height=200)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            neg = gr.Textbox(lines=1, placeholder="Negative prompt")
-            seed_sl = gr.Slider(0, MAX_SEED, step=1, value=0, label="Seed")
-            rand = gr.Checkbox(True, label="Randomize seed")
-            width = gr.Slider(256, MAX_IMAGE_SIZE, step=32, value=1024, label="Width")
-            height = gr.Slider(256, MAX_IMAGE_SIZE, step=32, value=1024, label="Height")
-            cfg = gr.Slider(1.0, 30.0, step=0.1, value=5, label="CFG Scale")
-            steps = gr.Slider(1, 50, step=1, value=23, label="Steps")
-
-        gr.Examples(examples, [prompt, neg, seed_sl, rand, width, height, cfg, steps])
-
-    run.click(
-        fn=infer,
-        inputs=[prompt, neg, seed_sl, rand, width, height, cfg, steps],
-        outputs=[img_out, seed_out, history_gallery]
-    )
+        generator=generator,
+    ).images[0]
+    return image
+
+# Gradio インターフェース
+demo = gr.Interface(
+    fn=generate,
+    inputs=[
+        gr.Textbox(label="Prompt"),
+        gr.Textbox(label="Negative Prompt"),
+        gr.Slider(minimum=10, maximum=50, value=30, label="Steps"),
+        gr.Slider(minimum=1.0, maximum=15.0, value=7.5, label="CFG Scale"),
+        gr.Number(value=42, label="Seed (空でランダム)")
+    ],
+    outputs=gr.Image(type="pil"),
+    title="recocoamixXL3_coamixXL3 Generator",
+    description="Hugging Faceから直接読み込んだSDXLベースモデルで画像を生成します。"
+)
 
-demo.queue()
+# 公開用（必要に応じて share=True）
 demo.launch(share=True)