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zsss0316 commited on 9 days ago

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@@ -1,118 +1,69 @@
-<!DOCTYPE html>
-<html lang="en">
 <head>
     <meta charset="UTF-8">
-    <title>Infernet Econometrics Benchmark Leaderboard</title>
     <style>
-        body {font-family: Arial; max-width:1100px; margin:30px auto; padding:0 20px;}
-        table {width:100%; border-collapse: collapse; margin:15px 0 40px;}
-        th,td {border:1px solid #ccc; padding:10px; text-align:left;}
-        th {background:#1f77b4; color:white;}
-        .tab{margin:8px 4px;padding:8px 16px;border:1px solid #999;background:#eee;cursor:pointer;}
-        .tab.active{background:#1f77b4;color:white;border-color:#1f77b4;}
-        .panel{display:none;}
-        .panel.show{display:block;}
     </style>
 </head>
 <body>
-<h1>🏆 Infernet Econometrics Benchmark Leaderboard</h1>
-<p><strong>CamoAiLab | HKU CAMO</strong><br>
-Dataset: <a href="https://huggingface.co/datasets/CamoAiLab/Infernet">CamoAiLab/Infernet</a>
-</p>
-<div>
-    <button class="tab active" onclick="switchTab(0)">1. Compilation Success Rate</button>
-    <button class="tab" onclick="switchTab(1)">2. Partial Replication Rate</button>
-    <button class="tab" onclick="switchTab(2)">3. Correct Coefficient Direction</button>
-</div>
-<div class="panel show" id="panel-compile"></div>
-<div class="panel" id="panel-rep"></div>
-<div class="panel" id="panel-dir"></div>
-<h3>📌 Metric Definition</h3>
-<ul>
-    <li><strong>Compilation Success:</strong> Generated code runs without runtime errors.</li>
-    <li><strong>Partial Replication:</strong> Partially reproduce target estimation results.</li>
-    <li><strong>Correct Coefficient Direction:</strong> Correct sign of estimated coefficients.</li>
-</ul>
-<script>
-const panels = document.querySelectorAll(".panel");
-const tabs = document.querySelectorAll(".tab");
-function switchTab(idx){
-    panels.forEach(p=>p.classList.remove("show"));
-    tabs.forEach(t=>t.classList.remove("active"));
-    panels[idx].classList.add("show");
-    tabs[idx].classList.add("active");
-}
-function parseCSV(text) {
-    text = text.replace(/\r\n/g,"\n").replace(/\r/g,"\n");
-    const lines = text.trim().split("\n").filter(line=>line.trim()!=='');
-    const headers = lines[0].split(",").map(h=>h.trim());
-    const rows = [];
-    for(let i=1;i<lines.length;i++){
-        const vals = lines[i].split(",").map(v=>v.trim());
-        const obj = {};
-        headers.forEach((h,idx)=>{
-            obj[h] = vals[idx];
-        });
-        rows.push(obj);
-    }
-    return rows;
-}
-function buildTable(title, data, sortKey){
-    const sorted = [...data].sort((a,b)=> Number(b[sortKey]) - Number(a[sortKey]));
-    let html = `<h3>${title}</h3><table><tr><th>Rank</th><th>Model</th><th>${sortKey}</th></tr>`;
-    sorted.forEach((row,i)=>{
-        html += `<tr>
-            <td>${i+1}</td>
-            <td>${row["Model ID"]}</td>
-            <td>${row[sortKey]}%</td>
-        </tr>`;
-    })
-    html += "</table>";
-    return html;
-}
-// 读取space本地csv，不再跨域访问dataset
-const csvUrl = "./results.csv";
-async function loadData(){
-    try {
-        const res = await fetch(csvUrl);
-        if(!res.ok) throw new Error(`HTTP ${res.status}`);
-        const csvText = await res.text();
-        const data = parseCSV(csvText);
-        if(data.length ===0){
-            document.body.insertAdjacentHTML("beforeend",`<p style="color:red">Warning: CSV parsed zero rows</p>`);
-            return;
-        }
-        document.getElementById("panel-compile").innerHTML = buildTable(
-            "Ranked by Code Compilation Success",
-            data,
-            "Compilation Success (%)"
-        );
-        document.getElementById("panel-rep").innerHTML = buildTable(
-            "Ranked by Partial Replication Rate",
-            data,
-            "Partial Replication (%)"
-        );
-        document.getElementById("panel-dir").innerHTML = buildTable(
-            "Ranked by Correct Coefficient Direction",
-            data,
-            "Correct Coefficient Direction (%)"
-        );
-    } catch(err){
-        console.error("load csv error",err);
-        document.body.insertAdjacentHTML("beforeend",`<p style='color:red'>Failed to load ranking data: ${err.message}</p>`);
-    }
-}
-loadData();
-</script>
 </body>
-</html>

+<html>
 <head>
     <meta charset="UTF-8">
+    <title>Infernet Leaderboard</title>
+    <!-- 加载 Gradio-lite 引擎 -->
+    <script type="module" src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
     <style>
+        body { background-color: #f9fafb; }
     </style>
 </head>
 <body>
+    <gradio-lite>
+        <!-- 这里编写您的 Python 代码 -->
+        <gradio-file name="app.py" entrypoint>
+import gradio as gr
+import pandas as pd
+import io
+# 1. 模拟数据（您也可以在此处直接修改数据 ）
+data_csv = """Model,Compilation %,Replication %,Direction %
+Econometrics-Agent (Ours),92.5,88.0,85.0
+GPT-4o,98.0,82.5,75.1
+Claude 3.5 Sonnet,96.2,80.4,72.8
+Llama-3-70B,85.0,65.0,60.5
+"""
+def load_data():
+    df = pd.read_csv(io.StringIO(data_csv))
+    df["Overall Score"] = df[["Compilation %", "Replication %", "Direction %"]].mean(axis=1).round(2)
+    return df.sort_values("Overall Score", ascending=False)
+# 2. 界面构建
+with gr.Blocks(title="Infernet Leaderboard") as demo:
+    gr.HTML("<h1 style='text-align: center; color: #1f2937;'>🏆 Infernet Econometrics Leaderboard</h1>")
+    gr.HTML("<p style='text-align: center; color: #6b7280;'>CamoAiLab | Free Browser-based Edition</p>")
+    with gr.Row():
+        df_init = load_data()
+        gr.Number(label="Total Models", value=len(df_init), interactive=False)
+        gr.Number(label="Best Overall (%)", value=df_init["Overall Score"].max(), interactive=False)
+    gr.Markdown("---")
+    with gr.Tabs():
+        with gr.TabItem("📊 Leaderboard"):
+            search = gr.Textbox(placeholder="🔍 Search model...", label=None, show_label=False)
+            table = gr.Dataframe(value=df_init, interactive=False)
+            def filter_table(query):
+                full_df = load_data()
+                if not query: return full_df
+                return full_df[full_df["Model"].str.contains(query, case=False)]
+            search.change(fn=filter_table, inputs=search, outputs=table)
+        with gr.TabItem("📖 Definitions"):
+            gr.Markdown("""
+            ### 计量经济学评测指标
+            - **Compilation %**: 代码运行成功率。
+            - **Replication %**: 统计结果复现率。
+            - **Direction %**: **核心指标**。系数正负号正确率。
+            """)
+demo.launch()
+        </gradio-file>
+    </gradio-lite>
 </body>
+</html>