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<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>投票 - LLM Interview Hot 100</title>
<meta name="description" content="为 LLM 面试题目投票，帮助社区了解真实面试热度">
<link rel="icon" href="data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>🗳️</text></svg>">
<!-- Supabase JS -->
<script src="https://cdn.jsdelivr.net/npm/@supabase/supabase-js@2"></script>
<style>
:root {
--primary: #6366f1;
--primary-dark: #4f46e5;
--fire: #ef4444;
--success: #22c55e;
--bg: #f8fafc;
--bg-card: #ffffff;
--bg-hover: #f1f5f9;
--text: #1e293b;
--text-muted: #64748b;
--border: #e2e8f0;
--gradient: linear-gradient(135deg, #6366f1 0%, #8b5cf6 50%, #ec4899 100%);
}
* { box-sizing: border-box; margin: 0; padding: 0; }
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Noto Sans SC', sans-serif;
background: var(--bg);
color: var(--text);
line-height: 1.6;
min-height: 100vh;
}
/* Header */
.header {
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border-bottom: 1px solid var(--border);
padding: 15px 20px;
position: sticky;
top: 0;
z-index: 100;
box-shadow: 0 2px 10px rgba(0,0,0,0.05);
}
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max-width: 1200px;
margin: 0 auto;
display: flex;
justify-content: space-between;
align-items: center;
}
.logo-link {
display: flex;
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gap: 10px;
text-decoration: none;
color: var(--text);
font-weight: 700;
font-size: 1.2rem;
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.nav-links {
display: flex;
gap: 20px;
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color: var(--text-muted);
text-decoration: none;
transition: color 0.2s;
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.nav-links a:hover {
color: var(--text);
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/* Main */
.container {
max-width: 1200px;
margin: 0 auto;
padding: 30px 20px;
}
/* Stats Bar */
.stats-bar {
display: flex;
gap: 30px;
justify-content: center;
margin-bottom: 30px;
flex-wrap: wrap;
}
.stat-item {
background: var(--bg-card);
padding: 20px 30px;
border-radius: 12px;
text-align: center;
border: 1px solid var(--border);
box-shadow: 0 2px 10px rgba(0,0,0,0.05);
}
.stat-value {
font-size: 2rem;
font-weight: 700;
background: var(--gradient);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.stat-label {
color: var(--text-muted);
font-size: 0.9rem;
}
/* Leaderboard */
.leaderboard {
background: var(--bg-card);
border-radius: 16px;
padding: 25px;
margin-bottom: 30px;
border: 1px solid var(--border);
box-shadow: 0 2px 10px rgba(0,0,0,0.05);
}
.leaderboard h2 {
margin-bottom: 20px;
display: flex;
align-items: center;
gap: 10px;
}
.lb-list {
display: flex;
flex-direction: column;
gap: 10px;
}
.lb-item {
display: flex;
align-items: center;
padding: 12px 15px;
background: var(--bg);
border-radius: 10px;
transition: transform 0.2s;
}
.lb-item:hover {
transform: translateX(5px);
}
.lb-rank {
width: 35px;
height: 35px;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
font-weight: 700;
margin-right: 15px;
font-size: 0.9rem;
}
.lb-rank.gold { background: linear-gradient(135deg, #fbbf24, #f59e0b); color: #78350f; }
.lb-rank.silver { background: linear-gradient(135deg, #e2e8f0, #94a3b8); color: #334155; }
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.lb-rank.normal { background: var(--border); color: var(--text-muted); }
.lb-name {
flex: 1;
font-weight: 500;
}
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color: var(--text-muted);
font-size: 0.85rem;
margin-left: 10px;
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display: flex;
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gap: 10px;
margin-bottom: 20px;
flex-wrap: wrap;
}
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padding: 8px 16px;
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border: 1px solid var(--border);
background: var(--bg-card);
color: var(--text-muted);
cursor: pointer;
transition: all 0.2s;
font-size: 0.9rem;
}
.filter-btn:hover {
border-color: var(--primary);
color: var(--text);
}
.filter-btn.active {
background: var(--primary);
border-color: var(--primary);
color: white;
}
/* Topic List */
.category-section {
margin-bottom: 30px;
}
.category-header {
display: flex;
align-items: center;
gap: 10px;
padding: 15px 0;
border-bottom: 1px solid var(--border);
margin-bottom: 15px;
}
.category-header h3 {
font-size: 1.2rem;
}
.category-header a {
color: var(--primary);
font-size: 0.9rem;
text-decoration: none;
margin-left: auto;
}
.topic-grid {
display: flex;
flex-direction: column;
gap: 10px;
}
.topic-item {
display: flex;
align-items: center;
padding: 15px 20px;
background: var(--bg-card);
border-radius: 12px;
border: 1px solid var(--border);
transition: all 0.2s;
box-shadow: 0 1px 3px rgba(0,0,0,0.03);
}
.topic-item:hover {
border-color: var(--primary);
box-shadow: 0 4px 15px rgba(99,102,241,0.1);
}
.topic-number {
width: 30px;
color: var(--text-muted);
font-size: 0.9rem;
}
.topic-info {
flex: 1;
}
.topic-name {
font-weight: 600;
margin-bottom: 3px;
}
.topic-desc {
font-size: 0.85rem;
color: var(--text-muted);
}
.topic-votes {
display: flex;
align-items: center;
gap: 15px;
}
.vote-count {
display: flex;
align-items: center;
gap: 5px;
font-size: 0.95rem;
color: var(--fire);
min-width: 50px;
justify-content: flex-end;
}
.vote-btn {
padding: 8px 20px;
border-radius: 20px;
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font-size: 0.9rem;
font-weight: 600;
cursor: pointer;
transition: all 0.2s;
display: flex;
align-items: center;
gap: 6px;
}
.vote-btn.not-voted {
background: var(--primary);
color: white;
}
.vote-btn.not-voted:hover {
background: var(--primary-dark);
transform: scale(1.05);
}
.vote-btn.voted {
background: var(--success);
color: white;
}
.vote-btn.voted:hover {
background: #16a34a;
}
.vote-btn:disabled {
opacity: 0.6;
cursor: not-allowed;
}
/* Loading */
.loading {
text-align: center;
padding: 50px;
color: var(--text-muted);
}
.spinner {
width: 40px;
height: 40px;
border: 3px solid var(--border);
border-top-color: var(--primary);
border-radius: 50%;
animation: spin 1s linear infinite;
margin: 0 auto 15px;
}
@keyframes spin {
to { transform: rotate(360deg); }
}
/* Toast */
.toast {
position: fixed;
bottom: 30px;
left: 50%;
transform: translateX(-50%) translateY(100px);
background: var(--bg-card);
padding: 15px 25px;
border-radius: 10px;
border: 1px solid var(--border);
box-shadow: 0 10px 40px rgba(0,0,0,0.3);
transition: transform 0.3s ease;
z-index: 1000;
}
.toast.show {
transform: translateX(-50%) translateY(0);
}
/* Footer */
footer {
text-align: center;
padding: 40px 20px;
color: var(--text-muted);
border-top: 1px solid var(--border);
margin-top: 50px;
}
footer a {
color: var(--primary);
text-decoration: none;
}
/* Mobile */
@media (max-width: 768px) {
.topic-item {
flex-wrap: wrap;
}
.topic-info {
width: 100%;
margin-bottom: 10px;
}
.topic-votes {
width: 100%;
justify-content: space-between;
}
.lb-category {
display: none;
}
}
</style>
</head>
<body>
<!-- Header -->
<header class="header">
<div class="header-content">
<a href="index.html" class="logo-link">
🔥 LLM Hot 100
</a>
<nav class="nav-links">
<a href="index.html">首页</a>
<a href="https://github.com/cdhx/LLM-Code-Hot-100">GitHub</a>
</nav>
</div>
</header>
<div class="container">
<!-- Stats -->
<div class="stats-bar">
<div class="stat-item">
<div class="stat-value" id="total-votes">—</div>
<div class="stat-label">总投票数</div>
</div>
<div class="stat-item">
<div class="stat-value" id="total-topics">63</div>
<div class="stat-label">题目总数</div>
</div>
<div class="stat-item">
<div class="stat-value" id="your-votes">—</div>
<div class="stat-label">你已投票</div>
</div>
</div>
<!-- Leaderboard -->
<div class="leaderboard">
<h2>🏆 实时热度排行榜</h2>
<div class="lb-list" id="leaderboard">
<div class="loading">
<div class="spinner"></div>
加载中...
</div>
</div>
</div>
<!-- Filter -->
<div class="filter-bar" id="filter-bar">
<button class="filter-btn active" data-category="all">全部</button>
</div>
<!-- Topic List -->
<div id="topic-list">
<div class="loading">
<div class="spinner"></div>
加载题目列表...
</div>
</div>
</div>
<!-- Toast -->
<div class="toast" id="toast"></div>
<!-- Footer -->
<footer>
<p><strong>#LLMHot100</strong> - LLM 时代的 Hot 100</p>
<p style="margin-top: 10px;">
<a href="index.html">返回首页</a> ·
<a href="https://github.com/cdhx/LLM-Code-Hot-100">GitHub</a>
</p>
</footer>
<script>
// ========== 配置 ==========
// 👇 替换为你的 Supabase 配置
const SUPABASE_URL = 'https://qxlhugrwofxnssqggbac.supabase.co';
const SUPABASE_ANON_KEY = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6InF4bGh1Z3J3b2Z4bnNzcWdnYmFjIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NzQ0Nzg4OTYsImV4cCI6MjA5MDA1NDg5Nn0.Y0SaWTANFQkd-V6JP_8i_7Mk0JIEWV4FeZmGUxot9qQ';
// 判断是否配置了 Supabase
const useSupabase = SUPABASE_URL !== 'YOUR_SUPABASE_URL' && SUPABASE_ANON_KEY !== 'YOUR_SUPABASE_ANON_KEY';
let supabaseClient = null;
if (useSupabase) {
supabaseClient = window.supabase.createClient(SUPABASE_URL, SUPABASE_ANON_KEY);
}
// ========== 题目数据 ==========
const topics = [
// 00-LLM 基础
{ id: 'gradient', name: '梯度与反向传播', desc: '链式法则手推，深度学习根基', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
{ id: 'linear-reg', name: '线性回归', desc: 'y = Wx + b，最简单的模型', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
{ id: 'logistic-reg', name: '逻辑回归', desc: 'sigmoid(Wx + b)，二分类基础', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
{ id: 'softmax-reg', name: 'Softmax 回归', desc: '多分类，LLM 输出层', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
{ id: 'mlp', name: 'MLP 多层感知机', desc: '万能近似器，FFN 的基础', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
{ id: 'activations', name: '激活函数', desc: 'ReLU/GELU/SiLU 及其梯度', category: 'LLM基础', doc: 'docs/00-llm-basics.md' },
// 01-Attention
{ id: 'sdpa', name: 'Scaled Dot-Product Attention', desc: 'softmax(QK^T/√d)V，一切的基础', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'mha', name: 'Multi-Head Attention', desc: '多头并行，不同子空间的注意力', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'causal-mask', name: 'Causal Mask', desc: '下三角掩码，防止看到未来', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'gqa', name: 'Grouped Query Attention', desc: 'Q头数 > KV头数，LLaMA2 主流', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'mqa', name: 'Multi-Query Attention', desc: '所有 Q 共享一组 KV', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'flash-attn', name: 'Flash Attention', desc: '分块计算，IO 感知，内存优化', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'kv-cache-attn', name: 'KV Cache', desc: '缓存历史 KV，避免重复计算', category: 'Attention', doc: 'docs/01-attention.md' },
{ id: 'cross-attn', name: 'Cross Attention', desc: 'Q 来自 decoder，KV 来自 encoder', category: 'Attention', doc: 'docs/01-attention.md' },
// 02-归一化
{ id: 'layernorm', name: 'Layer Normalization', desc: '沿特征维度归一化，Transformer 标配', category: '归一化', doc: 'docs/02-normalization.md' },
{ id: 'rmsnorm', name: 'RMS Normalization', desc: '去掉均值只除 RMS，LLaMA 用', category: '归一化', doc: 'docs/02-normalization.md' },
{ id: 'batchnorm', name: 'Batch Normalization', desc: '沿 batch 维度归一化，CNN 常用', category: '归一化', doc: 'docs/02-normalization.md' },
{ id: 'prenorm', name: 'Pre-Norm vs Post-Norm', desc: 'Pre-Norm 训练稳定，现代 LLM 主流', category: '归一化', doc: 'docs/02-normalization.md' },
// 03-位置编码
{ id: 'sinusoidal', name: 'Sinusoidal PE', desc: 'sin/cos 固定编码，原始 Transformer', category: '位置编码', doc: 'docs/03-position-encoding.md' },
{ id: 'learnable-pe', name: 'Learnable PE', desc: '可学习的嵌入，BERT/GPT', category: '位置编码', doc: 'docs/03-position-encoding.md' },
{ id: 'rope', name: 'RoPE 旋转位置编码', desc: '复数旋转，相对位置，LLM 主流', category: '位置编码', doc: 'docs/03-position-encoding.md' },
{ id: 'alibi', name: 'ALiBi', desc: 'attention 加线性偏置，长度外推好', category: '位置编码', doc: 'docs/03-position-encoding.md' },
// 04-采样
{ id: 'greedy', name: 'Greedy Decoding', desc: '每步选 argmax，确定性输出', category: '采样策略', doc: 'docs/04-sampling.md' },
{ id: 'temperature', name: 'Temperature Sampling', desc: 'logits/T 控制随机性', category: '采样策略', doc: 'docs/04-sampling.md' },
{ id: 'topk', name: 'Top-k Sampling', desc: '只从 top-k 中采样', category: '采样策略', doc: 'docs/04-sampling.md' },
{ id: 'topp', name: 'Top-p Sampling', desc: '累积概率达到 p 后截断', category: '采样策略', doc: 'docs/04-sampling.md' },
{ id: 'beam', name: 'Beam Search', desc: '保留 k 个最优序列', category: '采样策略', doc: 'docs/04-sampling.md' },
// 05-损失函数
{ id: 'ce-loss', name: 'Cross Entropy Loss', desc: '-log(p_true)，分类标配', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'lm-loss', name: 'Language Model Loss', desc: 'CE 的自回归版，next token prediction', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'kl-div', name: 'KL Divergence', desc: '分布差异度量，蒸馏/RLHF 用', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'mse-loss', name: 'MSE Loss', desc: '(y-ŷ)²，回归任务', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'focal-loss', name: 'Focal Loss', desc: '降低易分类样本权重', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'sft-loss', name: 'SFT Loss', desc: '带 mask 的 CE，只算 response', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'rm-loss', name: 'Reward Model Loss', desc: '-log σ(r_w - r_l)，偏好学习', category: '损失函数', doc: 'docs/05-loss-functions.md' },
{ id: 'contrastive', name: 'Contrastive Loss', desc: '正样本近，负样本远', category: '损失函数', doc: 'docs/05-loss-functions.md' },
// 06-优化器
{ id: 'sgd', name: 'SGD', desc: '最基础 w -= lr * grad', category: '优化器', doc: 'docs/06-optimizers.md' },
{ id: 'momentum', name: 'SGD + Momentum', desc: '加动量，加速收敛', category: '优化器', doc: 'docs/06-optimizers.md' },
{ id: 'adam', name: 'Adam', desc: '自适应学习率，一阶+二阶矩', category: '优化器', doc: 'docs/06-optimizers.md' },
{ id: 'adamw', name: 'AdamW', desc: '解耦权重衰减，LLM 标配', category: '优化器', doc: 'docs/06-optimizers.md' },
{ id: 'lr-schedule', name: '学习率调度', desc: 'Warmup + Cosine/Linear decay', category: '优化器', doc: 'docs/06-optimizers.md' },
// 07-强化学习
{ id: 'reinforce', name: 'REINFORCE', desc: '策略梯度基础 ∇log π × R', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'gae', name: 'GAE', desc: '优势估计，平衡偏差方差', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'ppo', name: 'PPO', desc: 'clip 限制更新幅度，RLHF 核心', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'ppo-clip', name: 'PPO-Clip', desc: 'ratio clip 版本', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'dpo', name: 'DPO', desc: '直接偏好优化，无需 RM', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'grpo', name: 'GRPO', desc: '组相对策略优化，DeepSeek 用', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'kl-penalty', name: 'KL 惩罚', desc: '防止偏离参考策略太远', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
{ id: 'reward-shaping', name: 'Reward Shaping', desc: '奖励工程，稀疏 → 稠密', category: '强化学习', doc: 'docs/07-reinforcement-learning.md' },
// 08-高效训练
{ id: 'lora', name: 'LoRA', desc: '低秩分解 W + BA', category: '高效训练', doc: 'docs/08-efficient-training.md' },
{ id: 'qlora', name: 'QLoRA', desc: 'LoRA + 4bit 量化', category: '高效训练', doc: 'docs/08-efficient-training.md' },
{ id: 'grad-ckpt', name: 'Gradient Checkpointing', desc: '时间换空间，重计算激活值', category: '高效训练', doc: 'docs/08-efficient-training.md' },
{ id: 'mixed-precision', name: 'Mixed Precision', desc: '降低显存，加速计算', category: '高效训练', doc: 'docs/08-efficient-training.md' },
{ id: 'grad-accum', name: 'Gradient Accumulation', desc: '小 batch 模拟大 batch', category: '高效训练', doc: 'docs/08-efficient-training.md' },
// 09-推理优化
{ id: 'kv-cache', name: 'KV Cache (推理)', desc: '缓存历史 KV，加速自回归', category: '推理优化', doc: 'docs/09-inference-optimization.md' },
{ id: 'paged-attn', name: 'Paged Attention', desc: '分页管理 KV，vLLM 核心', category: '推理优化', doc: 'docs/09-inference-optimization.md' },
{ id: 'spec-decode', name: 'Speculative Decoding', desc: '小模型猜测 + 大模型验证', category: '推理优化', doc: 'docs/09-inference-optimization.md' },
{ id: 'cont-batch', name: 'Continuous Batching', desc: '动态 batch，提高吞吐', category: '推理优化', doc: 'docs/09-inference-optimization.md' },
{ id: 'quantization', name: 'Quantization', desc: '量化推理，显存减半+', category: '推理优化', doc: 'docs/09-inference-optimization.md' },
// 10-架构
{ id: 'encoder-only', name: 'Encoder-Only (BERT)', desc: '双向注意力，理解任务', category: 'Transformer架构', doc: 'docs/10-transformer-architecture.md' },
{ id: 'decoder-only', name: 'Decoder-Only (GPT)', desc: '因果注意力，生成任务，LLM 主流', category: 'Transformer架构', doc: 'docs/10-transformer-architecture.md' },
{ id: 'enc-dec', name: 'Encoder-Decoder (T5)', desc: '序列到序列，翻译/摘要', category: 'Transformer架构', doc: 'docs/10-transformer-architecture.md' },
{ id: 'ffn', name: 'FFN', desc: '两层 MLP，中间扩展 4x', category: 'Transformer架构', doc: 'docs/10-transformer-architecture.md' },
{ id: 'swiglu', name: 'SwiGLU', desc: '门控 FFN，LLaMA 用', category: 'Transformer架构', doc: 'docs/10-transformer-architecture.md' },
];
const categories = [...new Set(topics.map(t => t.category))];
// ========== 状态 ==========
let votes = {}; // { topicId: voteCount }
let userVotes = []; // 用户投过票的 topicId 列表
let currentFilter = 'all';
// ========== 用户ID ==========
function getUserId() {
let id = localStorage.getItem('llm-hot-100-user-id');
if (!id) {
id = 'user_' + Math.random().toString(36).substr(2, 9);
localStorage.setItem('llm-hot-100-user-id', id);
}
return id;
}
const userId = getUserId();
// ========== 数据加载 ==========
async function loadVotes() {
// 先从 localStorage 加载，确保页面立即有数据
loadFromLocalStorage();
render();
// 如果配置了 Supabase，尝试同步数据
if (useSupabase) {
try {
// 获取所有投票计数
const { data: voteCounts } = await supabaseClient
.from('votes')
.select('topic_id');
if (voteCounts) {
votes = {};
voteCounts.forEach(v => {
votes[v.topic_id] = (votes[v.topic_id] || 0) + 1;
});
}
// 获取用户投票
const { data: userVoteData } = await supabaseClient
.from('votes')
.select('topic_id')
.eq('user_id', userId);
userVotes = userVoteData ? userVoteData.map(v => v.topic_id) : [];
render();
} catch (e) {
console.error('Supabase error:', e);
// 失败时保持 localStorage 数据
}
}
}
function loadFromLocalStorage() {
votes = JSON.parse(localStorage.getItem('llm-hot-100-votes') || '{}');
userVotes = JSON.parse(localStorage.getItem('llm-hot-100-user-votes') || '[]');
}
function saveToLocalStorage() {
localStorage.setItem('llm-hot-100-votes', JSON.stringify(votes));
localStorage.setItem('llm-hot-100-user-votes', JSON.stringify(userVotes));
}
// ========== 投票 ==========
async function vote(topicId) {
const isVoted = userVotes.includes(topicId);
if (useSupabase) {
try {
if (isVoted) {
await supabaseClient
.from('votes')
.delete()
.eq('user_id', userId)
.eq('topic_id', topicId);
userVotes = userVotes.filter(id => id !== topicId);
votes[topicId] = Math.max(0, (votes[topicId] || 0) - 1);
} else {
await supabaseClient
.from('votes')
.insert({ user_id: userId, topic_id: topicId });
userVotes.push(topicId);
votes[topicId] = (votes[topicId] || 0) + 1;
}
} catch (e) {
console.error('Vote error:', e);
showToast('投票失败，请重试');
return;
}
} else {
// localStorage 模式
if (isVoted) {
userVotes = userVotes.filter(id => id !== topicId);
votes[topicId] = Math.max(0, (votes[topicId] || 0) - 1);
} else {
userVotes.push(topicId);
votes[topicId] = (votes[topicId] || 0) + 1;
}
saveToLocalStorage();
}
showToast(isVoted ? '已取消投票' : '投票成功！感谢参与 🎉');
render();
}
// ========== 渲染 ==========
function render() {
renderStats();
renderLeaderboard();
renderFilters();
renderTopics();
}
function renderStats() {
const totalVotes = Object.values(votes).reduce((a, b) => a + b, 0);
document.getElementById('total-votes').textContent = totalVotes;
document.getElementById('total-topics').textContent = topics.length;
document.getElementById('your-votes').textContent = userVotes.length;
}
function renderLeaderboard() {
const sorted = [...topics]
.map(t => ({ ...t, votes: votes[t.id] || 0 }))
.sort((a, b) => b.votes - a.votes)
.slice(0, 10);
const html = sorted.map((t, i) => {
const rankClass = i === 0 ? 'gold' : i === 1 ? 'silver' : i === 2 ? 'bronze' : 'normal';
const rankText = i < 3 ? ['🥇', '🥈', '🥉'][i] : (i + 1);
return `
<div class="lb-item">
<div class="lb-rank ${rankClass}">${rankText}</div>
<div class="lb-name">${t.name}<span class="lb-category">${t.category}</span></div>
<div class="lb-votes">🔥 ${t.votes}</div>
</div>
`;
}).join('');
document.getElementById('leaderboard').innerHTML = html;
}
function renderFilters() {
const html = `
<button class="filter-btn ${currentFilter === 'all' ? 'active' : ''}" data-category="all">全部</button>
${categories.map(cat => `
<button class="filter-btn ${currentFilter === cat ? 'active' : ''}" data-category="${cat}">${cat}</button>
`).join('')}
`;
document.getElementById('filter-bar').innerHTML = html;
// 绑定事件
document.querySelectorAll('.filter-btn').forEach(btn => {
btn.addEventListener('click', () => {
currentFilter = btn.dataset.category;
render();
});
});
}
function renderTopics() {
const filtered = currentFilter === 'all'
? topics
: topics.filter(t => t.category === currentFilter);
// 按分类分组
const grouped = {};
filtered.forEach(t => {
if (!grouped[t.category]) grouped[t.category] = [];
grouped[t.category].push(t);
});
let html = '';
let num = 1;
Object.entries(grouped).forEach(([category, catTopics]) => {
html += `
<div class="category-section">
<div class="category-header">
<h3>${category}</h3>
<a href="${catTopics[0].doc}" target="_blank">查看文档 →</a>
</div>
<div class="topic-grid">
${catTopics.map(t => {
const isVoted = userVotes.includes(t.id);
const voteCount = votes[t.id] || 0;
return `
<div class="topic-item">
<div class="topic-number">${num++}</div>
<div class="topic-info">
<div class="topic-name">${t.name}</div>
<div class="topic-desc">${t.desc}</div>
</div>
<div class="topic-votes">
<div class="vote-count">🔥 ${voteCount}</div>
<button class="vote-btn ${isVoted ? 'voted' : 'not-voted'}" onclick="vote('${t.id}')">
${isVoted ? '✓ 已投票' : '👍 投票'}
</button>
</div>
</div>
`;
}).join('')}
</div>
</div>
`;
});
document.getElementById('topic-list').innerHTML = html;
}
// ========== Toast ==========
function showToast(message) {
const toast = document.getElementById('toast');
toast.textContent = message;
toast.classList.add('show');
setTimeout(() => toast.classList.remove('show'), 2500);
}
// ========== 初始化 ==========
async function init() {
await loadVotes();
render();
if (!useSupabase) {
showToast('📦 本地模式运行中（配置 Supabase 后可同步数据）');
}
}
init();
</script>
</body>
</html>