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	"""
	3D 模型优化服务 - HF Space 版本
	Gradio + HF Hub API \| 含用户建议反馈
	"""
	import os
	import json
	import uuid
	import time
	from datetime import datetime

	import gradio as gr
	from huggingface_hub import HfApi, list_repo_files

	from feedback_util import fetch_public_feedback, submit_feedback

	# === 预览配置 ===
	PREVIEW_FORMATS = [".glb", ".gltf", ".obj"]
	HF_RESOLVE_BASE = "https://huggingface.co/datasets"

	# === 配置 ===
	REPO_ID = "wangyiyi666/model-optimizer-queue"
	REPO_TYPE = "dataset"
	HF_TOKEN = os.environ.get("HF_TOKEN", "")
	SUPPORTED_FORMATS = [".glb", ".gltf", ".fbx", ".obj"]

	api = HfApi(token=HF_TOKEN)

	# === 文件列表缓存（避免重复调用 HF API，防止超时/限流） ===
	_files_cache = {"files": None, "ts": 0}
	_FILES_CACHE_SEC = 10 # 缓存 10 秒


	def _get_repo_files(force=False):
	"""获取仓库文件列表（带缓存 + 超时保护）"""
	global _files_cache
	now = time.time()
	if not force and _files_cache["files"] and (now - _files_cache["ts"]) < _FILES_CACHE_SEC:
	return _files_cache["files"]
	import concurrent.futures
	def _fetch():
	return list(list_repo_files(REPO_ID, repo_type=REPO_TYPE, token=HF_TOKEN))
	with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
	future = executor.submit(_fetch)
	try:
	files = future.result(timeout=30) # 最多等 30 秒
	except concurrent.futures.TimeoutError:
	if _files_cache["files"]:
	return _files_cache["files"] # 超时时返回旧缓存
	raise TimeoutError("HF API 响应超时，请稍后重试")
	_files_cache = {"files": files, "ts": now}
	return files


	def get_stats():
	"""获取任务统计数据"""
	try:
	files = _get_repo_files()
	inbox_models = [f for f in files if f.startswith("inbox/") and not f.endswith(".json") and not f.endswith(".gitkeep")]
	outbox_models = [f for f in files if f.startswith("outbox/") and not f.endswith(".json") and not f.endswith(".gitkeep")]
	total = len(inbox_models) + len(outbox_models)
	done = len(outbox_models)
	pending = len(inbox_models)
	return f"📦 上传总数: {total}  \|  ⏳ 待处理: {pending}  \|  ✅ 已回传: {done}"
	except Exception as e:
	return f"统计加载失败: {e}"


	def log(msg):
	timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
	print(f"[{timestamp}] [SPACE] {msg}")


	# === 场景描述选项定义 ===
	SCENE_TYPES = [
	"游戏 - 实时渲染角色/道具",
	"电商 - 3D 商品展示",
	"建筑/室内 - BIM 可视化",
	"数字人/虚拟主播",
	"Web/小程序 - 轻量 3D",
	"影视/离线渲染",
	"3D 打印",
	"其他 / 仅测试",
	]
	TARGET_PLATFORMS = [
	"移动端(iOS/Android)",
	"PC 端",
	"Web 浏览器",
	"VR/AR 头显",
	"游戏主机",
	"不确定",
	]
	FACE_BUDGETS = [
	"不确定，由优化师决定",
	"极轻量 (< 5K faces)",
	"轻量 (5K - 30K)",
	"中等 (30K - 100K)",
	"高精度 (100K - 500K)",
	"不限 / 尽量保留细节",
	]


	def upload_model(file, scene_type, target_platform, face_budget, scene_note, progress=gr.Progress()):
	"""处理用户上传的模型文件（含场景描述）"""
	if file is None:
	return "### ⚠️ 请先选择文件", ""

	# 校验必填项
	if not scene_type:
	return "### ⚠️ 请选择「使用场景」后再提交", ""
	if not target_platform or len(target_platform) == 0:
	return "### ⚠️ 请至少选择一个「目标平台」", ""

	filename = os.path.basename(file.name if hasattr(file, "name") else file)
	ext = os.path.splitext(filename)[1].lower()
	log(f"用户上传: {filename}")

	if ext not in SUPPORTED_FORMATS:
	log(f"格式不支持: {ext}")
	return f"### ❌ 不支持的格式: `{ext}`\n\n支持的格式: {', '.join(SUPPORTED_FORMATS)}", ""

	task_id = uuid.uuid4().hex
	target_name = f"{task_id}{ext}"

	try:
	progress(0.3, desc="正在上传模型文件...")
	file_path = file.name if hasattr(file, "name") else file
	api.upload_file(
	path_or_fileobj=file_path,
	path_in_repo=f"inbox/{target_name}",
	repo_id=REPO_ID,
	repo_type=REPO_TYPE,
	)

	progress(0.7, desc="正在创建任务...")
	name_no_ext = os.path.splitext(filename)[0]
	meta = json.dumps({
	"task_id": task_id,
	"filename": filename,
	"name_no_ext": name_no_ext,
	"scene_type": scene_type,
	"target_platform": target_platform if isinstance(target_platform, list) else [target_platform],
	"face_budget": face_budget or "不确定，由优化师决定",
	"scene_note": (scene_note or "").strip(),
	"status": "pending",
	"created": str(datetime.now()),
	}, ensure_ascii=False)
	api.upload_file(
	path_or_fileobj=meta.encode("utf-8"),
	path_in_repo=f"inbox/{task_id}.json",
	repo_id=REPO_ID,
	repo_type=REPO_TYPE,
	)

	progress(1.0, desc="上传完成!")
	log(f"上传成功: {target_name}, 任务ID: {task_id}")

	file_size = os.path.getsize(file_path)
	size_str = f"{file_size / 1024:.1f} KB" if file_size < 1024 * 1024 else f"{file_size / 1024 / 1024:.1f} MB"

	return (
	f"### ✅ 上传成功！\n\n"
	f"\| 项目 \| 信息 \|\n"
	f"\|------\|------\|\n"
	f"\| 📋 任务ID \| `{task_id}` \|\n"
	f"\| 📁 文件名 \| {filename} \|\n"
	f"\| 📦 文件大小 \| {size_str} \|\n"
	f"\| 🎯 使用场景 \| {scene_type} \|\n"
	f"\| 📱 目标平台 \| {', '.join(target_platform) if isinstance(target_platform, list) else target_platform} \|\n"
	f"\| ⏱️ 状态 \| 等待优化处理 \|\n\n"
	f"> ⚠️ 务必保存好任务ID，这是您下载优化结果的唯一凭证！"
	), task_id

	except Exception as e:
	log(f"上传失败: {e}")
	return f"### ❌ 上传失败\n\n```\n{str(e)}\n```", ""


	def _parse_glb_meshes(repo_path: str) -> list:
	"""从 GLB 文件头解析每个网格的三角面数，返回 [(mesh_name, tris), ...]（只下载 JSON chunk）"""
	import struct
	import requests as _req
	try:
	url = f"https://huggingface.co/datasets/{REPO_ID}/resolve/main/{repo_path}"
	headers = {"Range": "bytes=0-2097151"} # 前 2MB
	if HF_TOKEN:
	headers["Authorization"] = f"Bearer {HF_TOKEN}"
	resp = _req.get(url, headers=headers, timeout=15)
	data = resp.content
	if len(data) < 20:
	return []
	json_len = struct.unpack_from('<I', data, 12)[0]
	if json_len > len(data) - 20:
	del headers["Range"]
	resp = _req.get(url, headers=headers, timeout=60)
	data = resp.content
	json_len = struct.unpack_from('<I', data, 12)[0]
	json_bytes = data[20:20 + json_len]
	gltf = json.loads(json_bytes.decode('utf-8'))
	accessors = gltf.get('accessors', [])
	result = []
	for i, mesh in enumerate(gltf.get('meshes', [])):
	tris = 0
	for prim in mesh.get('primitives', []):
	if 'indices' in prim:
	tris += accessors[prim['indices']].get('count', 0) // 3
	elif 'attributes' in prim and 'POSITION' in prim['attributes']:
	tris += accessors[prim['attributes']['POSITION']].get('count', 0) // 3
	result.append((mesh.get('name') or f"mesh{i}", tris))
	return result
	except Exception as e:
	log(f"面数统计失败 {repo_path}: {e}")
	return []


	def _count_glb_faces(repo_path: str) -> int:
	"""GLB 总三角面数"""
	return sum(t for _, t in _parse_glb_meshes(repo_path))


	def _build_viewer_html(inbox_path: str \| None, outbox_path: str \| None) -> str:
	"""生成 <model-viewer> 双视口 HTML，含面数统计"""
	import random
	uid = random.randint(10000, 99999)

	def _viewer(label: str, repo_path: str \| None, viewer_id: str, show_lod: bool = False) -> str:
	if not repo_path:
	return ""
	ext = os.path.splitext(repo_path)[1].lower()
	if ext not in PREVIEW_FORMATS:
	return (
	f'<div style="flex:1;min-width:280px;">'
	f'<div style="font-weight:600;margin-bottom:8px;">{label}</div>'
	f'<div style="height:400px;background:#2E3340;border-radius:12px;display:flex;align-items:center;justify-content:center;color:#aaa;font-size:14px;">'
	f'\u26a0\ufe0f \u683c\u5f0f {ext.upper()} \u4e0d\u652f\u6301\u5728\u7ebf\u9884\u89c8</div></div>'
	)
	url = f"{HF_RESOLVE_BASE}/{REPO_ID}/resolve/main/{repo_path}"
	# 服务端计算面数（解析一次网格）
	meshes = _parse_glb_meshes(repo_path)
	faces = sum(t for _, t in meshes)
	if faces > 0:
	face_label = f"{faces/1000000:.1f}M" if faces >= 1000000 else f"{faces/1000:.1f}K" if faces >= 1000 else str(faces)
	stats_html = f'\u25b3 <b>{faces:,}</b> faces ({face_label})'
	if show_lod:
	import re
	lods = []
	for name, tris in meshes:
	m = re.search(r'LOD\s*(\d+)', name or '', re.I)
	if m:
	lods.append((int(m.group(1)), tris))
	if len(lods) >= 2:
	lods.sort(key=lambda x: x[0])
	parts = ' \u00b7 '.join(f'LOD{n}: {t:,}' for n, t in lods)
	stats_html = f'{parts}<br>\u5408计 {faces:,}'
	else:
	stats_html = ''
	return (
	f'<div style="flex:1;min-width:280px;">'
	f'<div style="font-weight:600;margin-bottom:8px;">{label}</div>'
	f'<model-viewer id="{viewer_id}" src="{url}" '
	f'camera-controls auto-rotate '
	f'shadow-intensity="0.7" exposure="1.0" environment-image="neutral" '
	f'style="width:100%;height:400px;background:#2E3340;border-radius:12px;"'
	f'></model-viewer>'
	f'<div style="margin-top:6px;padding:6px 12px;'
	f'background:rgba(12,15,28,0.6);border:1px solid rgba(100,180,255,0.12);'
	f'border-radius:8px;color:#80d4ff;font-size:13px;font-family:monospace;'
	f'text-align:center;min-height:24px;">{stats_html}</div>'
	f'</div>'
	)

	vid_in = f"mv-in-{uid}"
	vid_out = f"mv-out-{uid}"
	left = _viewer("📤 原始模型", inbox_path, vid_in)
	right = _viewer("✨ 优化后模型", outbox_path, vid_out, show_lod=True)
	if not left and not right:
	return ""
	return f'<div style="display:flex;gap:16px;flex-wrap:wrap;">{left}{right}</div>'


	def check_status(task_id):
	"""查询任务状态，同时返回模型预览"""
	hide_btn = gr.update(visible=False)
	no_preview = ""

	if not task_id or len(task_id.strip()) == 0:
	return "### ⚠️ 请输入任务ID", hide_btn, no_preview

	task_id = task_id.strip()
	log(f"查询: {task_id}")

	try:
	files = _get_repo_files(force=True)

	inbox_model_files = [
	f for f in files
	if f.startswith(f"inbox/{task_id}") and not f.endswith(".json")
	]
	outbox_matches = [
	f for f in files
	if f.startswith(f"outbox/{task_id}") and not f.endswith(".json")
	]

	if outbox_matches:
	result_path = outbox_matches[0]
	ext = os.path.splitext(result_path)[1].upper().lstrip(".")
	log(f"任务 {task_id} 已完成")

	viewer_html = _build_viewer_html(
	inbox_model_files[0] if inbox_model_files else None,
	result_path,
	)
	status_md = (
	f"### ✅ 优化完成！\n\n"
	f"\| 项目 \| 信息 \|\n"
	f"\|------\|------\|\n"
	f"\| 📋 任务ID \| `{task_id}` \|\n"
	f"\| 📄 输出格式 \| {ext} \|\n\n"
	f"> 👇 点击下方「下载模型」按钮获取优化后的文件"
	)
	return status_md, gr.update(visible=True), viewer_html

	inbox_all = [f for f in files if f.startswith(f"inbox/{task_id}")]
	if inbox_all:
	log(f"任务 {task_id} 仍在队列中")
	viewer_html = _build_viewer_html(
	inbox_model_files[0] if inbox_model_files else None,
	None,
	)
	status_md = (
	f"### ⏳ 处理中\n\n"
	f"任务 `{task_id}` 正在优化队列中，请稍后再查询。\n\n"
	f"> Worker 每 30秒检查一次新任务，优化完成后即可下载。"
	)
	return status_md, hide_btn, viewer_html

	log(f"任务 {task_id} 未找到")
	return f"### ❌ 未找到任务\n\n任务ID `{task_id}` 不存在，请检查是否输入正确。", hide_btn, no_preview

	except Exception as e:
	log(f"查询出错: {e}")
	return f"### ❌ 查询出错\n\n```\n{str(e)}\n```", hide_btn, no_preview


	def download_model(task_id):
	"""下载模型并记录取件事件"""
	if not task_id or len(task_id.strip()) == 0:
	return None, "### ⚠️ 请先查询任务ID"

	task_id = task_id.strip()
	log(f"用户下载: {task_id}")

	try:
	files = _get_repo_files()
	outbox_matches = [f for f in files if f.startswith(f"outbox/{task_id}") and not f.endswith(".json")]
	if not outbox_matches:
	return None, "### ❌ 未找到优化结果"

	result_path = outbox_matches[0]
	download_url = f"https://huggingface.co/datasets/{REPO_ID}/resolve/main/{result_path}"

	# 记录下载事件到 HF Dataset
	from datetime import datetime
	record = json.dumps({
	"task_id": task_id,
	"downloaded_at": datetime.now().isoformat(),
	"result_file": result_path,
	})
	try:
	api.upload_file(
	path_or_fileobj=record.encode(),
	path_in_repo=f"outbox/{task_id}.downloaded.json",
	repo_id=REPO_ID,
	repo_type=REPO_TYPE,
	)
	log(f"已记录下载: {task_id}")
	except Exception as e:
	log(f"记录下载失败(不影响下载): {e}")

	return (
	None,
	f"### ✅ 下载链接已生成\n\n"
	f"> 👇 [点击此处下载优化后的模型]({download_url})\n\n"
	f"下载记录已通知管理端"
	)

	except Exception as e:
	log(f"下载出错: {e}")
	return None, f"### ❌ 下载出错\n\n```\n{str(e)}\n```"


	def delete_task(task_id):
	"""删除任务（清理 inbox + outbox 文件）"""
	if not task_id or len(task_id.strip()) == 0:
	return "### ⚠️ 请输入任务ID"

	task_id = task_id.strip()
	log(f"删除任务: {task_id}")

	try:
	files = _get_repo_files(force=True)
	to_delete = [f for f in files if task_id in f and f != ".gitattributes"]

	if not to_delete:
	return f"### ❌ 未找到任务\n\n任务ID `{task_id}` 不存在。"

	deleted = []
	for filepath in to_delete:
	try:
	api.delete_file(filepath, REPO_ID, repo_type=REPO_TYPE)
	deleted.append(filepath)
	log(f"已删除: {filepath}")
	except Exception as e:
	log(f"删除失败 {filepath}: {e}")

	file_list = "\n".join([f"- `{f}`" for f in deleted])
	return f"### 🗑️ 删除成功\n\n已删除 {len(deleted)} 个文件：\n\n{file_list}"

	except Exception as e:
	log(f"删除出错: {e}")
	return f"### ❌ 删除出错\n\n```\n{str(e)}\n```"


	def render_public_feedback():
	items = fetch_public_feedback()
	if not items:
	return "<p style='color:#888;'>暂无公开反馈</p>"

	blocks = []
	for item in items:
	created = (item.get("created") or "")[:19]
	username = item.get("username") or "匿名"
	text = (item.get("text") or "").replace("\n", "<br>")
	img_note = ""
	if item.get("images"):
	img_note = f"<div style='color:#666;font-size:13px;margin-top:6px;'>附带 {len(item['images'])} 张图片</div>"
	blocks.append(
	f"<div style='border:1px solid #eee;border-radius:8px;padding:14px;margin-bottom:12px;background:#fafafa;'>"
	f"<div style='font-weight:600;'>{username} "
	f"<span style='color:#999;font-size:12px;'>{created}</span></div>"
	f"<div style='margin-top:8px;line-height:1.6;'>{text}</div>{img_note}</div>"
	)
	return "".join(blocks)


	def handle_feedback_submit(username, text, images, is_public):
	try:
	image_paths = []
	if images:
	if isinstance(images, list):
	image_paths = [item.name if hasattr(item, "name") else item for item in images]
	else:
	image_paths = [images.name if hasattr(images, "name") else images]
	meta = submit_feedback(username, text, image_paths, is_public)
	visibility = "已公开" if meta.get("is_public") else "仅管理员可见"
	return f"### ✅ 反馈提交成功\n\n\| 项目 \| 信息 \|\n\|------\|------\|\n\| 反馈ID \| `{meta['feedback_id']}` \|\n\| 展示范围 \| {visibility} \|"
	except Exception as e:
	log(f"反馈提交失败: {e}")
	return f"### ❌ 提交失败\n\n```\n{str(e)}\n```"


	# ---------- 读取流体背景脚本 ----------
	_fluid_js_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fluid_bg.js")
	_fluid_js = ""
	if os.path.exists(_fluid_js_path):
	with open(_fluid_js_path, encoding="utf-8") as _f:
	_fluid_js = _f.read()

	_head_html = (
	'<script type="module" src="https://unpkg.com/@google/model-viewer/dist/model-viewer.min.js"></script>'
	+ f'<script>{_fluid_js}</script>' if _fluid_js else
	'<script type="module" src="https://unpkg.com/@google/model-viewer/dist/model-viewer.min.js"></script>'
	)

	custom_css = """
	/* ===== dark glass-morphism theme ===== */
	body { background: #05060a !important; }
	body.fluid-off { background: #000 !important; }
	footer { display: none !important; }

	/* --- Gradio wrapper chain: ALL transparent so fluid canvas shows through --- */
	body > div,
	body > div > div,
	#root,
	.gradio-container > .main,
	.gradio-container > .wrap,
	.gradio-container > .contain,
	.app {
	background: transparent !important;
	background-color: transparent !important;
	}

	.gradio-container {
	position: relative; z-index: 5;
	max-width: 1200px !important;
	width: 88% !important;
	margin: 0 auto !important;
	padding: 28px 40px !important;
	background: transparent !important;
	border-radius: 18px !important;
	border: 1px solid transparent !important;
	margin-top: 20px !important;
	margin-bottom: 20px !important;
	transition: background 0.4s ease, border-color 0.4s ease, backdrop-filter 0.4s ease !important;
	}
	.gradio-container:focus-within {
	background: rgba(8, 10, 20, 0.75) !important;
	backdrop-filter: blur(20px) saturate(1.2) !important;
	-webkit-backdrop-filter: blur(20px) saturate(1.2) !important;
	border-color: rgba(100, 180, 255, 0.08) !important;
	}

	/* panels — glass morphism only on interaction blocks */
	.gr-panel, .gr-box, .gr-form, .gr-input-label,
	.gr-padded {
	background: rgba(12, 15, 28, 0.65) !important;
	border: 1px solid rgba(100, 180, 255, 0.10) !important;
	border-radius: 14px !important;
	backdrop-filter: blur(18px) saturate(1.3) !important;
	-webkit-backdrop-filter: blur(18px) saturate(1.3) !important;
	}
	/* Gradio 4.x structural wrappers — keep transparent */
	.gr-block, .gr-group, .gr-row, .block {
	background: transparent !important;
	background-color: transparent !important;
	}
	/* Svelte 内部包装器透明（排除 checkbox/radio 容器） */
	.gradio-container [class*="svelte"]:not([role="group"]):not(.wrap) {
	background: transparent !important;
	background-color: transparent !important;
	}
	.tabitem > div, .tab-content, .form, .block.padded {
	background: transparent !important;
	}
	/* checkbox / radio 组件保证可点击 */
	.gr-check-radio, .gr-checkbox-group,
	label:has(input[type="checkbox"]), label:has(input[type="radio"]) {
	pointer-events: auto !important;
	position: relative !important;
	z-index: 10 !important;
	}
	input[type="checkbox"], input[type="radio"] {
	pointer-events: auto !important;
	cursor: pointer !important;
	position: relative !important;
	z-index: 10 !important;
	}
	/* re-apply glass on input blocks */
	.gr-block.gr-box {
	background: rgba(12, 15, 28, 0.65) !important;
	}

	/* tabs */
	.tabs { background: transparent !important; }
	.tabitem { background: transparent !important; }
	.tab-nav { background: transparent !important; border-bottom: 1px solid rgba(100,180,255,0.12) !important; }
	.tab-nav button {
	color: rgba(180, 210, 255, 0.6) !important;
	background: transparent !important;
	border: none !important;
	font-weight: 500;
	}
	.tab-nav button.selected {
	color: #60c8ff !important;
	border-bottom: 2px solid #60c8ff !important;
	background: rgba(96, 200, 255, 0.06) !important;
	}

	/* inputs */
	input, textarea, .gr-input {
	background: rgba(15, 20, 40, 0.7) !important;
	border: 1px solid rgba(100, 180, 255, 0.15) !important;
	color: #d0e0ff !important;
	border-radius: 10px !important;
	}
	input:focus, textarea:focus {
	border-color: rgba(96, 200, 255, 0.5) !important;
	box-shadow: 0 0 12px rgba(96, 200, 255, 0.15) !important;
	}

	/* dropdown 下拉框组件 — 全部透明/暗色 */
	[data-testid="dropdown"], .gr-dropdown,
	[role="listbox"], ul[role="listbox"] {
	background: rgba(15, 20, 40, 0.95) !important;
	border: 1px solid rgba(100, 180, 255, 0.15) !important;
	border-radius: 10px !important;
	}
	[data-testid="dropdown"] > , .gr-dropdown > ,
	[data-testid="dropdown"] button,
	.gr-dropdown button,
	.wrap-inner, .secondary-wrap, .icon-wrap {
	background: transparent !important;
	background-color: transparent !important;
	}
	/* 下拉框输入区域透明 */
	[data-testid="dropdown"] input,
	.gr-dropdown input {
	background: transparent !important;
	background-color: transparent !important;
	}
	/* 下拉框外层包装器透明 */
	.gradio-container .wrap,
	.gradio-container div[data-testid] > div {
	background: transparent !important;
	background-color: transparent !important;
	}
	[role="option"], [role="listbox"] li {
	background: rgba(15, 20, 40, 0.95) !important;
	color: #d0e0ff !important;
	}
	[role="option"]:hover, [role="listbox"] li:hover {
	background: rgba(96, 200, 255, 0.15) !important;
	}
	[role="option"][aria-selected="true"] {
	background: rgba(96, 200, 255, 0.2) !important;
	color: #80d4ff !important;
	}

	/* buttons — 只针对 Gradio 功能按钮，排除内部组件小按钮 */
	.gr-button, button.primary, button.secondary, button.lg, button.sm, button.stop {
	min-height: 46px !important;
	padding: 10px 24px !important;
	font-size: 16px !important;
	font-weight: 500 !important;
	border-radius: 12px !important;
	transition: all 0.3s ease !important;
	}
	button.primary, button.lg.primary {
	background: linear-gradient(135deg, rgba(60,140,255,0.75), rgba(100,80,220,0.75)) !important;
	border: 1px solid rgba(100, 180, 255, 0.3) !important;
	color: #fff !important;
	backdrop-filter: blur(8px) !important;
	font-size: 17px !important;
	min-height: 52px !important;
	padding: 12px 28px !important;
	}
	button.primary:hover {
	background: linear-gradient(135deg, rgba(80,160,255,0.9), rgba(120,100,240,0.9)) !important;
	box-shadow: 0 0 24px rgba(96, 200, 255, 0.3) !important;
	transform: translateY(-1px);
	}
	button.secondary, button.stop {
	background: rgba(20, 25, 50, 0.6) !important;
	border: 1px solid rgba(100, 180, 255, 0.18) !important;
	color: #a0c0e8 !important;
	backdrop-filter: blur(8px) !important;
	font-size: 16px !important;
	min-height: 48px !important;
	}
	button.sm {
	background: rgba(20, 25, 50, 0.5) !important;
	border: 1px solid rgba(100, 180, 255, 0.12) !important;
	color: #80b0e0 !important;
	font-size: 14px !important;
	min-height: 38px !important;
	padding: 6px 16px !important;
	}
	/* 文件组件内部的 X 删除按钮 — 保持小尺寸 */
	.file-preview button, .upload-container button, button.remove-file {
	min-height: unset !important;
	padding: 2px 6px !important;
	font-size: 12px !important;
	border-radius: 50% !important;
	min-width: unset !important;
	width: 24px !important;
	height: 24px !important;
	backdrop-filter: none !important;
	}

	/* text colors & sizing */
	.gr-markdown, .gr-markdown , .prose, .prose {
	color: #c8daf0 !important;
	font-size: 15px !important;
	line-height: 1.6 !important;
	}
	.gr-markdown h1, .gr-markdown h2, .gr-markdown h3 {
	color: #e0f0ff !important;
	}
	.gr-markdown h1 { font-size: 22px !important; }
	.gr-markdown h2 { font-size: 19px !important; }
	.gr-markdown h3 { font-size: 17px !important; }
	.gr-markdown strong { color: #80d4ff !important; }
	.gr-markdown a { color: #60c8ff !important; }
	label, .gr-input-label span {
	color: #90b8dc !important;
	font-size: 14px !important;
	}
	input, textarea {
	font-size: 14px !important;
	}


	/* title section */
	.main-title { text-align: center; margin-bottom: 0.5em; }
	.main-title h1 {
	color: #e8f4ff !important;
	text-shadow: 0 0 30px rgba(96,200,255,0.2);
	font-size: 28px !important;
	}
	.sub-title {
	color: rgba(180, 210, 255, 0.6) !important;
	font-size: 15px !important;
	margin-bottom: 1.5em;
	text-align: center;
	}
	.format-badge {
	display: inline-block;
	background: rgba(96, 200, 255, 0.12);
	color: #60c8ff;
	padding: 5px 16px; border-radius: 16px; margin: 3px;
	font-size: 13px; font-weight: 500;
	border: 1px solid rgba(96, 200, 255, 0.18);
	backdrop-filter: blur(6px);
	}

	/* tab nav text */
	.tab-nav button {
	font-size: 14px !important;
	}

	/* file upload */
	.file-preview, .upload-area, [data-testid="file"] {
	background: rgba(12, 15, 28, 0.5) !important;
	border: 1px dashed rgba(100, 180, 255, 0.2) !important;
	border-radius: 12px !important;
	}

	/* checkbox — 增大并显示明确勾选 */
	.gr-check-radio input[type=checkbox],
	input[type=checkbox] {
	accent-color: #60c8ff !important;
	width: 18px !important;
	height: 18px !important;
	cursor: pointer !important;
	border: 2px solid rgba(100, 180, 255, 0.4) !important;
	border-radius: 4px !important;
	appearance: auto !important;
	-webkit-appearance: checkbox !important;
	}
	input[type=checkbox]:checked {
	background: #60c8ff !important;
	border-color: #60c8ff !important;
	}
	/* 选中项 label 高亮 */
	label:has(input[type=checkbox]:checked) {
	color: #80d4ff !important;
	font-weight: 600 !important;
	}

	/* scrollbar */
	::-webkit-scrollbar { width: 6px; }
	::-webkit-scrollbar-track { background: rgba(5,6,10,0.4); }
	::-webkit-scrollbar-thumb { background: rgba(96,200,255,0.2); border-radius: 3px; }

	/* stats row */
	.stats-row {
	background: rgba(12, 15, 28, 0.55) !important;
	border: 1px solid rgba(100, 180, 255, 0.10) !important;
	border-radius: 12px !important;
	backdrop-filter: blur(14px) !important;
	padding: 8px 16px;
	}

	/* model preview containers */
	model-viewer {
	border: 1px solid rgba(100, 180, 255, 0.12) !important;
	}
	"""

	with gr.Blocks(
	title="3D 模型优化服务",
	theme=gr.themes.Soft(primary_hue="blue", secondary_hue="slate"),
	css=custom_css,
	head=_head_html,
	) as demo:
	gr.HTML("""
	<div class="main-title"><h1>🛠️ 3D 模型优化服务</h1></div>
	<div class="sub-title">上传 3D 模型 · 自动优化处理 · 完成后下载</div>
	<div style="text-align:center;margin-bottom:1.5em;">
	<span class="format-badge">GLB</span><span class="format-badge">GLTF</span>
	<span class="format-badge">FBX</span><span class="format-badge">OBJ</span>
	<span style="margin:0 8px;color:rgba(150,200,255,0.4);">→</span>
	<span class="format-badge">GLB 输出</span>
	</div>
	<p style="text-align:center;color:rgba(255,180,100,0.85);">⚠️ 测试阶段，请优先上传 GLB 格式文件</p>
	""")

	with gr.Row():
	stats_display = gr.Markdown(value=get_stats())
	refresh_stats_btn = gr.Button("🔄 刷新统计", size="sm", scale=0)
	refresh_stats_btn.click(get_stats, outputs=[stats_display])

	with gr.Tabs():
	with gr.Tab("📤 上传模型", id="upload"):
	with gr.Row(equal_height=True):
	with gr.Column(scale=1):
	file_input = gr.File(
	label="选择 3D 模型文件",
	file_types=[".glb", ".gltf", ".fbx", ".obj"],
	type="filepath",
	height=150,
	)
	gr.Markdown("#### 📝 场景描述（必填）", elem_classes=["scene-title"])
	scene_type_input = gr.Dropdown(
	label="使用场景",
	choices=SCENE_TYPES,
	value=None,
	info="选择模型的使用场景，便于针对性优化",
	)
	target_platform_input = gr.CheckboxGroup(
	label="目标平台（可多选）",
	choices=TARGET_PLATFORMS,
	value=[],
	info="模型最终运行的平台",
	)
	face_budget_input = gr.Dropdown(
	label="期望面数范围（可选）",
	choices=FACE_BUDGETS,
	value="不确定，由优化师决定",
	)
	scene_note_input = gr.Textbox(
	label="补充说明（可选）",
	placeholder="如：需要保留骨骼动画、关注面部精度、单场景有多个同类模型...",
	lines=2,
	max_lines=4,
	)
	upload_btn = gr.Button("🚀 提交优化", variant="primary", size="lg")
	with gr.Column(scale=1):
	upload_result = gr.Markdown(
	value="### 📋 等待上传\n\n选择文件并填写场景描述后点击「提交优化」按钮。",
	label="处理结果",
	)
	task_id_output = gr.Textbox(label="📋 任务ID（复制保存）", interactive=False)

	upload_btn.click(
	upload_model,
	inputs=[file_input, scene_type_input, target_platform_input, face_budget_input, scene_note_input],
	outputs=[upload_result, task_id_output],
	)

	with gr.Tab("🔍 查询结果", id="query"):
	with gr.Row(equal_height=True):
	with gr.Column(scale=1):
	task_id_input = gr.Textbox(label="输入任务ID", placeholder="粘贴完整任务ID", max_lines=1)
	with gr.Row():
	check_btn = gr.Button("🔍 查询状态", variant="primary", size="lg")
	delete_btn = gr.Button("🗑️ 删除任务", variant="stop", size="lg")
	download_btn = gr.Button("📥 下载模型", variant="secondary", size="lg", visible=False)
	with gr.Column(scale=1):
	status_result = gr.Markdown(
	value="### 📋 等待查询\n\n输入任务ID后点击「查询状态」按钮。",
	label="任务状态",
	)

	gr.Markdown("### 👁️ 模型预览")
	model_preview_html = gr.HTML(value="")

	check_btn.click(
	check_status,
	inputs=[task_id_input],
	outputs=[status_result, download_btn, model_preview_html],
	)
	delete_btn.click(delete_task, inputs=[task_id_input], outputs=[status_result])
	download_btn.click(download_model, inputs=[task_id_input], outputs=[download_btn, status_result])

	with gr.Tab("💬 提交反馈", id="feedback"):
	gr.Markdown("欢迎提交使用建议或问题反馈，可附带截图。管理员会在本地管理面板查看全部反馈。")
	feedback_username = gr.Textbox(label="用户名 / 昵称", placeholder="可选，默认匿名")
	feedback_text = gr.Textbox(label="反馈内容", lines=6, placeholder="请描述您的建议或遇到的问题...")
	feedback_images = gr.File(
	label="截图 / 图片（可选，可多选）",
	file_count="multiple",
	file_types=["image"],
	type="filepath",
	)
	feedback_public = gr.Checkbox(
	label="允许对外公开展示（勾选后其他用户可在「公开反馈」页看到文字内容）",
	value=False,
	)
	feedback_submit_btn = gr.Button("提交反馈", variant="primary")
	feedback_result = gr.Markdown()
	feedback_submit_btn.click(
	handle_feedback_submit,
	inputs=[feedback_username, feedback_text, feedback_images, feedback_public],
	outputs=[feedback_result],
	)

	with gr.Tab("📣 公开反馈", id="public_feedback"):
	refresh_public_btn = gr.Button("🔄 刷新公开反馈")
	public_feedback_html = gr.HTML(value=render_public_feedback())
	refresh_public_btn.click(lambda: render_public_feedback(), outputs=[public_feedback_html])

	gr.HTML("<p style='text-align:center;color:rgba(150,180,220,0.35);margin-top:1em;font-size:0.8em;'>Fluid effect inspired by <a href=\"https://github.com/PavelDoGreat/WebGL-Fluid-Simulation\" target=\"_blank\" style=\"color:rgba(96,200,255,0.4);text-decoration:none;\">WebGL-Fluid-Simulation</a></p>")


	if __name__ == "__main__":
	log("Gradio 前端启动")
	demo.launch()