Update app.py

app.py

@@ -1,3 +1,193 @@
+import gradio as gr
 from gradio_client import Client
-client = Client("prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
-print(client.view_api())
+import random
+import os
+
+# API client for the external Space
+space_client = Client("prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
+
+LORA_STYLES = [
+    'Multiple-Angles',
+    'Photo-to-Anime',
+    'Anime-V2',
+    'Light-Migration',
+    'Upscaler',
+    'Style-Transfer',
+    'Manga-Tone',
+    'Anything2Real',
+    'Fal-Multiple-Angles',
+    'Polaroid-Photo',
+    'Unblur-Anything',
+    'Midnight-Noir-Eyes-Spotlight',
+    'Hyper-Realistic-Portrait',
+    'Ultra-Realistic-Portrait',
+    'Pixar-Inspired-3D',
+    'Noir-Comic-Book',
+    'Any-light',
+    'Studio-DeLight',
+    'Cinematic-FlatLog',
+]
+MAX_SEED = 2**31 - 1
+
+
+def encode_image_for_gallery(image_path):
+    """把本地文件路径转成 Gallery 期望的 dict 格式"""
+    if not image_path or not isinstance(image_path, str):
+        return None
+    if not os.path.exists(image_path):
+        print(f"文件不存在: {image_path}")
+        return None
+
+    return {
+        "image": {
+            "path": image_path,
+            "url": None,
+            "size": os.path.getsize(image_path),
+            "orig_name": os.path.basename(image_path),
+            "mime_type": None,
+            "is_stream": False,
+            "meta": {}
+        },
+        "caption": None
+    }
+
+
+def infer(
+    image,
+    prompt,
+    lora_adapter,
+    seed,
+    randomize_seed,
+    guidance_scale,
+    steps,
+    progress=gr.Progress(track_tqdm=True),
+):
+    images_input = []
+
+    if image is not None:
+        if isinstance(image, list):
+            for im in image:
+                obj = encode_image_for_gallery(im)
+                if obj:
+                    images_input.append(obj)
+                else:
+                    print(f"警告: 路径无效或无法读取: {im}")
+        else:
+            obj = encode_image_for_gallery(image)
+            if obj:
+                images_input.append(obj)
+            else:
+                print(f"警告: 路径无效或无法读取: {image}")
+
+    if len(images_input) == 0:
+        print("未检测到有效图片，请上传图片后再试。")
+        return None, seed
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+
+    print("[调用API] 输入参数：")
+    print(f"  images count: {len(images_input)}")
+    print(f"  prompt: {prompt}")
+    print(f"  lora_adapter: {lora_adapter}")
+    print(f"  seed: {seed}")
+    print(f"  randomize_seed: {randomize_seed}")
+    print(f"  guidance_scale: {guidance_scale}")
+    print(f"  steps: {steps}")
+
+    try:
+        result = space_client.predict(
+            images=images_input,
+            prompt=prompt,
+            lora_adapter=lora_adapter,
+            seed=float(seed),
+            randomize_seed=bool(randomize_seed),
+            guidance_scale=float(guidance_scale),
+            steps=float(steps),
+            api_name="/infer",
+        )
+
+        print(f"[调用API] 返回值: {result}")
+
+        # result 是 (image_dict, seed_float) 元组
+        image_info, seed_used = result
+
+        if isinstance(image_info, dict):
+            img_out = image_info.get("path") or image_info.get("url")
+            return img_out, int(seed_used)
+        else:
+            return image_info, int(seed_used)
+
+    except Exception as e:
+        import traceback
+        traceback.print_exc()
+        print(f"[调用API] 调用接口异常: {e}")
+        return None, seed
+
+
+css = """
+#col-container {
+    margin: 0 auto;
+    max-width: 640px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("# 图像编辑 Demo\n基于 prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
+
+        image = gr.Image(
+            label="上传图片",
+            sources=["upload"],
+            type="filepath",
+            elem_id="input-image"
+        )
+
+        prompt = gr.Text(
+            label="编辑描述（Prompt）",
+            placeholder="请输入图片编辑描述...",
+        )
+
+        lora_adapter = gr.Dropdown(
+            label="编辑风格（Style）",
+            choices=LORA_STYLES,
+            value="Photo-to-Anime"
+        )
+
+        run_button = gr.Button("执行编辑", variant="primary")
+
+        result = gr.Image(label="结果图片", show_label=True)
+
+        with gr.Accordion("高级设置", open=False):
+            seed = gr.Slider(
+                label="随机种子",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+            randomize_seed = gr.Checkbox(label="随机化种子", value=True)
+            guidance_scale = gr.Slider(
+                label="引导强度 (Guidance Scale)",
+                minimum=0.1,
+                maximum=10.0,
+                step=0.1,
+                value=1.0,
+            )
+            steps = gr.Slider(
+                label="推理步数 (Steps)",
+                minimum=1,
+                maximum=50,
+                step=1,
+                value=4,
+            )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
+        outputs=[result, seed],
+    )
+
+if __name__ == "__main__":
+    demo.launch(ssr_mode=False, share=True)