Update miniapp_leaderboard.py

miniapp_leaderboard.py

@@ -7,17 +7,14 @@ import uuid
 from urllib.parse import urlparse
 
 import gradio as gr
+import numpy as np
 import pandas as pd
 import requests
 from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.errors import RepositoryNotFoundError
 
-
 APP_NAME = "miniapp"
 
-# Space Secrets:
-# - HF_TOKEN: Hugging Face access token with WRITE access to the dataset repo
-# - LEADERBOARD_DATASET: dataset repo id like "ha251/miniapp-leaderboard"
 HF_TOKEN = os.environ.get("HF_TOKEN") or os.environ.get("TOKEN") or os.environ.get("HUGGINGFACE_TOKEN")
 LEADERBOARD_DATASET = (os.environ.get("LEADERBOARD_DATASET") or "").strip()
 MAX_ENTRIES = int(os.environ.get("MAX_ENTRIES", "500"))
@@ -53,6 +50,22 @@ NUMERIC_COLS = [
     "Lifestyle",
 ]
 
+# ✅ 展示顺序：Model 最左，Avg 第二列
+DISPLAY_ORDER = [
+    "Model name",
+    "Avg",
+    "Easy",
+    "Mid",
+    "Hard",
+    "Games",
+    "Science",
+    "Tools",
+    "Humanities",
+    "Viz",
+    "Lifestyle",
+]
+SORTABLE_COLS = DISPLAY_ORDER[:]
+
 IN_SPACES = bool(
     os.environ.get("SPACE_ID")
     or os.environ.get("SPACE_REPO_NAME")
@@ -144,44 +157,15 @@ def _load_entries_df() -> pd.DataFrame:
     for c in LEADERBOARD_COLUMNS:
         if c not in df.columns:
             df[c] = ""
+
     df = df[LEADERBOARD_COLUMNS]
     for c in NUMERIC_COLS:
         df[c] = pd.to_numeric(df[c], errors="coerce")
-    df = df.sort_values(by=["Submitted at"], ascending=False, kind="stable")
-    return df
-
-
-def _apply_search_and_sort(
-    df: pd.DataFrame,
-    search_text: str,
-    search_in: str,
-    sort_by: str,
-    sort_order: str,
-) -> pd.DataFrame:
-    search_text = (search_text or "").strip().lower()
-    if search_text:
-        if search_in == "Model name":
-            df = df[df["Model name"].astype(str).str.lower().str.contains(search_text, na=False)]
-        elif search_in == "Submitter":
-            df = df[df["Submitter"].astype(str).str.lower().str.contains(search_text, na=False)]
-        else:
-            mask = (
-                df["Model name"].astype(str).str.lower().str.contains(search_text, na=False)
-                | df["Submitter"].astype(str).str.lower().str.contains(search_text, na=False)
-            )
-            df = df[mask]
 
-    ascending = sort_order == "Ascending"
-    if sort_by in df.columns:
-        df = df.sort_values(by=[sort_by], ascending=ascending, kind="stable", na_position="last")
+    df = df.sort_values(by=["Submitted at"], ascending=False, kind="stable")
     return df
 
 
-def refresh(search_text: str, search_in: str, sort_by: str, sort_order: str):
-    df = _load_entries_df()
-    return _apply_search_and_sort(df, search_text, search_in, sort_by, sort_order)
-
-
 def _parse_hf_created_at(created_at: str) -> datetime.datetime | None:
     try:
         if created_at.endswith("Z"):
@@ -192,9 +176,6 @@ def _parse_hf_created_at(created_at: str) -> datetime.datetime | None:
 
 
 def _check_user_eligibility(username: str) -> tuple[bool, str]:
-    """
-    - Must be older than ~4 months (>= 120 days)
-    """
     try:
         r = requests.get(f"https://huggingface.co/api/users/{username}/overview", timeout=10)
         r.raise_for_status()
@@ -207,8 +188,7 @@ def _check_user_eligibility(username: str) -> tuple[bool, str]:
         now = datetime.datetime.now(datetime.timezone.utc)
         if dt.tzinfo is None:
             dt = dt.replace(tzinfo=datetime.timezone.utc)
-        age_days = (now - dt).days
-        if age_days < 120:
+        if (now - dt).days < 120:
             return False, "Account must be older than 4 months to submit."
         return True, ""
     except Exception:
@@ -226,76 +206,163 @@ def _submitted_today(username: str) -> bool:
     return any(str(v).startswith(today) for v in user_rows["Submitted at"].tolist())
 
 
+# ---------- HTML Leaderboard ----------
+def _fmt_cell(v):
+    if v is None or (isinstance(v, float) and pd.isna(v)):
+        return ""
+    if isinstance(v, (int, float, np.number)):
+        return f"{float(v):.2f}"
+    return str(v)
+
+
+def _apply_search_and_sort(df: pd.DataFrame, search_text: str, sort_col: str, sort_dir: str) -> pd.DataFrame:
+    s = (search_text or "").strip().lower()
+    if s:
+        df = df[df["Model name"].astype(str).str.lower().str.contains(s, na=False)]
+
+    sort_col = sort_col if sort_col in df.columns else "Avg"
+    asc = sort_dir == "asc"
+    df = df.sort_values(by=[sort_col], ascending=asc, kind="stable", na_position="last")
+    return df
+
+
+def _render_leaderboard_html(df: pd.DataFrame, sort_col: str, sort_dir: str) -> str:
+    import html as _html
+
+    def th(label, col=None, align_left=False, cls=""):
+        if col:
+            arrow = ""
+            if col == sort_col:
+                arrow = " ▲" if sort_dir == "asc" else " ▼"
+            al = " left" if align_left else ""
+            return f'<th class="th clickable{al} {cls}" data-col="{_html.escape(col)}">{_html.escape(label)}{arrow}</th>'
+        al = " left" if align_left else ""
+        return f'<th class="th{al} {cls}">{_html.escape(label)}</th>'
+
+    trs = []
+    for _, r in df.iterrows():
+        tds = []
+        for c in DISPLAY_ORDER:
+            val = _fmt_cell(r.get(c, ""))
+            if c == "Model name":
+                tds.append(f'<td class="td model">{_html.escape(val)}</td>')
+            else:
+                tds.append(f'<td class="td num">{_html.escape(val)}</td>')
+        trs.append("<tr class='tr'>" + "".join(tds) + "</tr>")
+
+    # ✅ 三层表头：Model 最左，Avg 第二列
+    return f"""
+    <div class="table-wrap">
+      <div class="table-scroll">
+        <table class="table" id="lb_table">
+          <thead>
+            <tr class="r1">
+              {th("Model", "Model name", align_left=True, cls="model")}
+              {th("Avg. (%)", "Avg", cls="avg")}
+              <th class="th group" colspan="9">Pass Rate (%)</th>
+            </tr>
+            <tr class="r2">
+              <th class="th"></th>
+              <th class="th"></th>
+              <th class="th group" colspan="3">Difficulty</th>
+              <th class="th group" colspan="6">Domain</th>
+            </tr>
+            <tr class="r3">
+              <th class="th"></th>
+              <th class="th"></th>
+              {th("Easy", "Easy")}
+              {th("Mid", "Mid")}
+              {th("Hard", "Hard")}
+              {th("Games", "Games")}
+              {th("Science", "Science")}
+              {th("Tools", "Tools")}
+              {th("Humanities", "Humanities")}
+              {th("Viz.", "Viz")}
+              {th("Lifestyle", "Lifestyle")}
+            </tr>
+          </thead>
+          <tbody>
+            {''.join(trs)}
+          </tbody>
+        </table>
+      </div>
+    </div>
+    """
+
+
+def render_lb(search_text: str, sort_col: str, sort_dir: str) -> str:
+    df = _load_entries_df()
+    df = _apply_search_and_sort(df, search_text, sort_col, sort_dir)
+    return _render_leaderboard_html(df, sort_col, sort_dir)
+
+
+def toggle_sort(clicked_col: str, current_col: str, current_dir: str):
+    clicked_col = (clicked_col or "").strip()
+    if clicked_col not in SORTABLE_COLS:
+        return current_col, current_dir
+    if clicked_col == current_col:
+        return current_col, ("asc" if current_dir == "desc" else "desc")
+    return clicked_col, "desc"
+
+
+# ---------- Submit ----------
 def submit(
-    model_name: str,
     model_api: str,
     api_key: str,
-    avg: float,
-    easy: float,
-    mid: float,
-    hard: float,
-    games: float,
-    science: float,
-    tools: float,
-    humanities: float,
-    viz: float,
-    lifestyle: float,
     search_text: str,
-    search_in: str,
-    sort_by: str,
-    sort_order: str,
+    sort_col: str,
+    sort_dir: str,
     profile: gr.OAuthProfile | None,
 ):
-    # Login required to submit (in Spaces)
     if IN_SPACES and (profile is None or not getattr(profile, "username", None)):
-        return "You must log in to submit.", refresh(search_text, search_in, sort_by, sort_order)
+        return "You must log in to submit.", render_lb(search_text, sort_col, sort_dir)
 
     submitter = (getattr(profile, "username", None) if profile is not None else "local") or "anonymous"
 
-    model_name = (model_name or "").strip()
     model_api = (model_api or "").strip()
     api_key = (api_key or "").strip()
 
-    if not model_name:
-        return "Model name is required.", refresh(search_text, search_in, sort_by, sort_order)
     if not model_api:
-        return "Model API URL is required.", refresh(search_text, search_in, sort_by, sort_order)
+        return "Model API URL is required.", render_lb(search_text, sort_col, sort_dir)
     if not _is_valid_http_url(model_api):
-        return "Model API must be a valid http(s) URL.", refresh(search_text, search_in, sort_by, sort_order)
+        return "Model API must be a valid http(s) URL.", render_lb(search_text, sort_col, sort_dir)
     if not api_key:
-        return "API key is required.", refresh(search_text, search_in, sort_by, sort_order)
+        return "API key is required.", render_lb(search_text, sort_col, sort_dir)
 
     ok, msg = _ensure_dataset_readable()
     if not ok:
-        return msg, refresh(search_text, search_in, sort_by, sort_order)
+        return msg, render_lb(search_text, sort_col, sort_dir)
 
     if IN_SPACES:
         ok, msg = _check_user_eligibility(submitter)
         if not ok:
-            return msg, refresh(search_text, search_in, sort_by, sort_order)
+            return msg, render_lb(search_text, sort_col, sort_dir)
 
     if _submitted_today(submitter):
-        return "You have already submitted today. Please try again tomorrow.", refresh(search_text, search_in, sort_by, sort_order)
+        return "You have already submitted today. Please try again tomorrow.", render_lb(search_text, sort_col, sort_dir)
 
     now = datetime.datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
     nonce = uuid.uuid4().hex[:8]
-    safe_model = _slug(model_name)
     safe_user = _slug(submitter)
+
+    host = urlparse(model_api).netloc or "unknown"
+    model_name = host
+
+    safe_model = _slug(model_name)
     path_in_repo = f"{ENTRIES_PREFIX}{now[:10]}/{now}-{safe_user}-{safe_model}-{nonce}.json"
 
-    # NOTE: api_key is collected but NOT stored.
     payload = {
         "Model name": model_name,
-        "Avg": avg,
-        "Easy": easy,
-        "Mid": mid,
-        "Hard": hard,
-        "Games": games,
-        "Science": science,
-        "Tools": tools,
-        "Humanities": humanities,
-        "Viz": viz,
-        "Lifestyle": lifestyle,
+        "Avg": None,
+        "Easy": None,
+        "Mid": None,
+        "Hard": None,
+        "Games": None,
+        "Science": None,
+        "Tools": None,
+        "Humanities": None,
+        "Viz": None,
+        "Lifestyle": None,
         "Submitted at": now,
         "Submitter": submitter,
         "Model API": model_api,
@@ -312,417 +379,181 @@ def submit(
         token=HF_TOKEN,
     )
 
-    return "Submitted successfully.", refresh(search_text, search_in, sort_by, sort_order)
-
+    return "Submitted successfully.", render_lb(search_text, sort_col, sort_dir)
+
+
+# ✅ 强制覆盖成浅灰线：用 !important，避免被主题样式覆盖成黑线
+CSS = r"""
+.gradio-container { max-width: 100% !important; }
+#page { padding: 16px; }
+
+#topbar { display:flex; align-items:center; justify-content:space-between; gap:12px; margin-bottom: 10px; }
+#titleline { font-weight: 700; font-size: 18px; }
+#searchbox { width: 280px; }
+#searchbox label { display:none !important; }
+#searchbox textarea, #searchbox input {
+  height: 34px !important;
+  border-radius: 8px !important;
+  border: 1px solid #e5e7eb !important;
+  background: #fff !important;
+  box-shadow: none !important;
+}
+#searchbox textarea::placeholder, #searchbox input::placeholder { color: #9ca3af; }
+
+/* table container */
+.table-wrap{
+  width: 100%;
+  border: 1px solid #e5e7eb !important;
+  border-radius: 8px;
+  background: #fff;
+}
+.table-scroll{ width: 100%; overflow-x: auto; }
+table.table{
+  width: 100%;
+  border-collapse: separate;
+  border-spacing: 0;
+  min-width: 1100px;
+}
+
+/* header */
+th.th{
+  font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial !important;
+  font-weight: 600;
+  font-size: 13px;
+  color: #111827;
+  padding: 10px 12px;
+  text-align: center;
+  background: #f9fafb;
+  border-bottom: 1px solid #e5e7eb !important;
+  border-right: 1px solid #e5e7eb !important;
+  white-space: nowrap;
+}
+thead tr.r3 th.th { background: #ffffff; }
+th.th.left{ text-align:left; }
+th.group{ color:#374151; font-weight:600; }
+th.th:last-child{ border-right: none !important; }
+
+/* body */
+td.td{
+  font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial !important;
+  font-size: 13px;
+  color: #111827;
+  padding: 10px 12px;
+  border-bottom: 1px solid #f0f1f3 !important;
+  border-right: 1px solid #f0f1f3 !important;
+  background: #fff;
+}
+td.td:last-child{ border-right: none !important; }
+td.num{ text-align:right; }
+td.model{ text-align:left; min-width: 280px; }
+tr.tr:hover td.td{ background: #fafafa; }
+
+/* clickable sort */
+th.clickable{ cursor:pointer; user-select:none; }
+th.clickable:hover{ background:#f3f4f6; }
+
+/* submit */
+#submit_card{
+  width: 100%;
+  border: 1px solid #e5e7eb !important;
+  border-radius: 8px;
+  padding: 12px;
+  background: #fff;
+  margin-top: 14px;
+}
+#submit_card .hint{
+  margin: 0 0 10px 0;
+  color: #6b7280;
+  font-size: 13px;
+}
+"""
 
 with gr.Blocks(title=f"{APP_NAME} leaderboard") as demo:
-    # Layout: Overview -> Leaderboard -> Submission instructions
-    gr.Markdown(
-        f"## {APP_NAME} leaderboard\n\n"
-        "### Overview\n"
-        "_Placeholder overview text. Replace this with your benchmark description, rules, and links._\n\n"
-        "### Leaderboard\n"
-        "_The leaderboard below supports sorting and searching._\n\n"
-        "### Submission\n"
-        "_Placeholder submission instructions. Requires login. One submission per user per day. "
-        "Account must be older than 4 months._\n"
-    )
-
-    with gr.Row():
-        with gr.Column(scale=3):
+    with gr.Column(elem_id="page"):
+        with gr.Row(elem_id="topbar"):
+            gr.Markdown(f"<div id='titleline'>{APP_NAME} leaderboard</div>")
             with gr.Row():
-                search_text = gr.Textbox(label="Search", placeholder="Model name or submitter")
-                search_in = gr.Dropdown(
-                    label="Search in",
-                    choices=["Both", "Model name", "Submitter"],
-                    value="Both",
+                search_text = gr.Textbox(
+                    elem_id="searchbox",
+                    placeholder="Search model…",
+                    show_label=False,
+                    container=False,
+                    scale=1,
                 )
-            with gr.Row():
-                sort_by = gr.Dropdown(label="Sort by", choices=LEADERBOARD_COLUMNS, value="Avg")
-                sort_order = gr.Radio(label="Order", choices=["Descending", "Ascending"], value="Descending")
-                refresh_btn = gr.Button("Refresh")
-
-            leaderboard = gr.Dataframe(
-                label="Leaderboard",
-                value=_load_entries_df(),
-                interactive=False,
-                wrap=True,
-            )
-
-        with gr.Column(scale=2):
-            with gr.Accordion("Submit (login required)", open=True):
-                model_name = gr.Textbox(label="Model name (required)")
-                model_api = gr.Textbox(label="Model API (required)", placeholder="https://...")
-                api_key = gr.Textbox(label="API key (required)", type="password", placeholder="Will not be stored")
-
-                with gr.Row():
-                    avg = gr.Number(label="Avg", value=0)
-                    easy = gr.Number(label="Easy", value=0)
-                    mid = gr.Number(label="Mid", value=0)
-                    hard = gr.Number(label="Hard", value=0)
-
-                with gr.Row():
-                    games = gr.Number(label="Games", value=0)
-                    science = gr.Number(label="Science", value=0)
-                    tools = gr.Number(label="Tools", value=0)
-
-                with gr.Row():
-                    humanities = gr.Number(label="Humanities", value=0)
-                    viz = gr.Number(label="Viz", value=0)
-                    lifestyle = gr.Number(label="Lifestyle", value=0)
-
-                with gr.Row():
-                    gr.LoginButton()
-                    submit_btn = gr.Button("Submit", variant="primary")
-                status = gr.Markdown()
-
-    refresh_btn.click(refresh, inputs=[search_text, search_in, sort_by, sort_order], outputs=[leaderboard])
-    submit_btn.click(
-        submit,
-        inputs=[
-            model_name,
-            model_api,
-            api_key,
-            avg,
-            easy,
-            mid,
-            hard,
-            games,
-            science,
-            tools,
-            humanities,
-            viz,
-            lifestyle,
-            search_text,
-            search_in,
-            sort_by,
-            sort_order,
-        ],
-        outputs=[status, leaderboard],
-    )
-
-demo.launch()
-
-import datetime
-import io
-import json
-import os
-import re
-import uuid
-from urllib.parse import urlparse
-
-import gradio as gr
-import pandas as pd
-from huggingface_hub import HfApi, hf_hub_download
-
-
-APP_NAME = "miniapp"
-
-# 在 Space 里通过 Secrets 配置：
-# - HF_TOKEN: 具有写 dataset 权限的 token（Settings -> Variables and secrets -> Secrets）
-# - LEADERBOARD_DATASET: 形如 "your-username/miniapp-leaderboard"（repo_type=dataset）
-HF_TOKEN = os.environ.get("HF_TOKEN") or os.environ.get("TOKEN") or os.environ.get("HUGGINGFACE_TOKEN")
-LEADERBOARD_DATASET = os.environ.get("LEADERBOARD_DATASET", "").strip()
-# Owner 审核口令（放到 Space Secrets；不要放到公开 Variables）
-OWNER_REVIEW_TOKEN = os.environ.get("OWNER_REVIEW_TOKEN", "").strip()
-
-# 判断是否运行在 Hugging Face Spaces
-IN_SPACES = bool(
-    os.environ.get("SPACE_ID")
-    or os.environ.get("SPACE_REPO_NAME")
-    or os.environ.get("SPACE_AUTHOR_NAME")
-    or os.environ.get("system", "") == "spaces"
-)
-
-MAX_ENTRIES = int(os.environ.get("MAX_ENTRIES", "200"))
-
-PENDING_PREFIX = "pending/"
-APPROVED_PREFIX = "approved/"
-
-
-def _is_valid_http_url(url: str) -> bool:
-    try:
-        parsed = urlparse(url)
-        return parsed.scheme in ("http", "https") and bool(parsed.netloc)
-    except Exception:
-        return False
-
-
-def _slug(s: str, max_len: int = 60) -> str:
-    s = (s or "").strip().lower()
-    s = re.sub(r"[^a-z0-9]+", "-", s)
-    s = re.sub(r"-{2,}", "-", s).strip("-")
-    return (s[:max_len] or "model")
-
-
-def _api() -> HfApi:
-    return HfApi(token=HF_TOKEN)
-
-
-def _ensure_dataset_repo():
-    if not HF_TOKEN:
-        raise RuntimeError("未配置 HF_TOKEN（Space Secrets）。")
-    if not LEADERBOARD_DATASET:
-        raise RuntimeError("未配置 LEADERBOARD_DATASET（例如：your-username/miniapp-leaderboard）。")
-    api = _api()
-    try:
-        api.repo_info(repo_id=LEADERBOARD_DATASET, repo_type="dataset")
-    except Exception:
-        # 不存在则创建（public dataset；你也可以手动创建并设为 private）
-        api.create_repo(repo_id=LEADERBOARD_DATASET, repo_type="dataset", private=False, exist_ok=True)
-
-
-def _empty_df() -> pd.DataFrame:
-    return pd.DataFrame(columns=["submitted_at", "username", "model_name", "model_api", "notes"])
-
-
-def _list_json_files(prefix: str) -> list[str]:
-    if not HF_TOKEN or not LEADERBOARD_DATASET:
-        return []
-
-    api = _api()
-    try:
-        files = api.list_repo_files(repo_id=LEADERBOARD_DATASET, repo_type="dataset")
-    except Exception:
-        return []
-
-    return sorted(
-        [f for f in files if f.startswith(prefix) and f.endswith(".json")],
-        reverse=True,
-    )[:MAX_ENTRIES]
-
-
-def _load_entries_df(prefix: str, include_filename: bool) -> pd.DataFrame:
-    files = _list_json_files(prefix)
-    rows = []
-    for filename in files:
-        try:
-            path = hf_hub_download(
-                repo_id=LEADERBOARD_DATASET,
-                repo_type="dataset",
-                filename=filename,
-                token=HF_TOKEN,
-            )
-            with open(path, "r", encoding="utf-8") as fp:
-                row = json.load(fp)
-                if include_filename:
-                    row["_filename"] = filename
-                rows.append(row)
-        except Exception:
-            continue
-
-    if not rows:
-        df = _empty_df()
-        if include_filename:
-            df["_filename"] = []
-        return df
-
-    df = pd.DataFrame(rows)
-    for col in ["submitted_at", "username", "model_name", "model_api", "notes"]:
-        if col not in df.columns:
-            df[col] = ""
-    cols = ["submitted_at", "username", "model_name", "model_api", "notes"]
-    if include_filename:
-        if "_filename" not in df.columns:
-            df["_filename"] = ""
-        cols = cols + ["_filename"]
-    df = df[cols]
-    df = df.sort_values(by=["submitted_at"], ascending=False, kind="stable")
-    return df
-
-
-def refresh():
-    return _load_entries_df(APPROVED_PREFIX, include_filename=False)
-
-
-def refresh_pending():
-    df = _load_entries_df(PENDING_PREFIX, include_filename=True)
-    choices = list(df["_filename"]) if "_filename" in df.columns else []
-    return df, gr.update(choices=choices, value=choices[0] if choices else None)
-
-
-def submit(model_name: str, model_api: str, notes: str, username: str | None):
-    model_name = (model_name or "").strip()
-    model_api = (model_api or "").strip()
-    notes = (notes or "").strip()
-    username = (username or "").strip() or ("local" if not IN_SPACES else "anonymous")
-
-    if not model_name:
-        return "请填写 **模型名称**。", refresh()
-    if not model_api:
-        return "请填写 **模型 API**。", refresh()
-    if not _is_valid_http_url(model_api):
-        return "**模型 API** 需要是合法的 `http(s)://...` URL。", refresh()
-
-    if not HF_TOKEN:
-        return "Space 未配置 **HF_TOKEN**（Secrets），无法写入排行榜。", refresh()
-    if not LEADERBOARD_DATASET:
-        return "Space 未配置 **LEADERBOARD_DATASET**（例如：`your-username/miniapp-leaderboard`）。", refresh()
-
-    _ensure_dataset_repo()
-    api = _api()
-
-    now = datetime.datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
-    safe_model = _slug(model_name)
-    safe_user = _slug(username)
-    nonce = uuid.uuid4().hex[:8]
-    path_in_repo = f"{PENDING_PREFIX}{now[:10]}/{now}-{safe_user}-{safe_model}-{nonce}.json"
-
-    payload = {
-        "submitted_at": now,
-        "username": username,
-        "model_name": model_name,
-        "model_api": model_api,
-        "notes": notes,
-    }
-    data = (json.dumps(payload, ensure_ascii=False, indent=2) + "\n").encode("utf-8")
-    bio = io.BytesIO(data)
-
-    api.upload_file(
-        repo_id=LEADERBOARD_DATASET,
-        repo_type="dataset",
-        path_or_fileobj=bio,
-        path_in_repo=path_in_repo,
-        commit_message=f"miniapp: submit(pending) {username}/{model_name}",
-        token=HF_TOKEN,
-    )
-
-    return "已提交，等待 owner 审核后才会上榜。", refresh()
-
-
-def approve(pending_filename: str | None, review_token: str | None):
-    pending_filename = (pending_filename or "").strip()
-    review_token = (review_token or "").strip()
-
-    if not pending_filename:
-        df, dd = refresh_pending()
-        return "请选择一条待审核提交。", df, dd, refresh()
-
-    if not OWNER_REVIEW_TOKEN:
-        df, dd = refresh_pending()
-        return "Space 未配置 **OWNER_REVIEW_TOKEN**（Secrets），无法启用审核。", df, dd, refresh()
+                refresh_btn = gr.Button("Refresh", scale=0)
+
+        sort_col = gr.State("Avg")
+        sort_dir = gr.State("desc")
+
+        lb_html = gr.HTML(value=render_lb("", "Avg", "desc"))
+
+        clicked_col = gr.Textbox(visible=False, elem_id="clicked_col")
+
+        gr.HTML(
+            """
+<script>
+(function(){
+  function bindClicks(){
+    const table = document.getElementById("lb_table");
+    const hidden = document.getElementById("clicked_col");
+    if(!table || !hidden) return;
+
+    table.querySelectorAll("th.clickable").forEach(th=>{
+      th.onclick = () => {
+        const col = th.getAttribute("data-col") || "";
+        hidden.value = col;
+        hidden.dispatchEvent(new Event("input", {bubbles:true}));
+        hidden.dispatchEvent(new Event("change", {bubbles:true}));
+      };
+    });
+  }
+
+  const obs = new MutationObserver(()=>bindClicks());
+  obs.observe(document.body, {subtree:true, childList:true});
+  setTimeout(bindClicks, 250);
+})();
+</script>
+"""
+        )
 
-    if review_token != OWNER_REVIEW_TOKEN:
-        df, dd = refresh_pending()
-        return "审核口令不正确。", df, dd, refresh()
+        search_text.change(render_lb, inputs=[search_text, sort_col, sort_dir], outputs=[lb_html])
+        refresh_btn.click(render_lb, inputs=[search_text, sort_col, sort_dir], outputs=[lb_html])
 
-    if not HF_TOKEN or not LEADERBOARD_DATASET:
-        df, dd = refresh_pending()
-        return "Space 未配置 HF 写入权限，无法审核。", df, dd, refresh()
+        def _on_click(col, cur_col, cur_dir, s):
+            new_col, new_dir = toggle_sort(col, cur_col, cur_dir)
+            return new_col, new_dir, render_lb(s, new_col, new_dir)
 
-    api = _api()
-    try:
-        local_path = hf_hub_download(
-            repo_id=LEADERBOARD_DATASET,
-            repo_type="dataset",
-            filename=pending_filename,
-            token=HF_TOKEN,
+        clicked_col.change(
+            _on_click,
+            inputs=[clicked_col, sort_col, sort_dir, search_text],
+            outputs=[sort_col, sort_dir, lb_html],
         )
-        with open(local_path, "r", encoding="utf-8") as fp:
-            payload = json.load(fp)
-    except Exception as e:
-        df, dd = refresh_pending()
-        return f"读取待审核文件失败：{e}", df, dd, refresh()
-
-    # 将文件复制到 approved 目录（保留原提交时间等字段）
-    base = pending_filename[len(PENDING_PREFIX) :] if pending_filename.startswith(PENDING_PREFIX) else pending_filename
-    approved_filename = f"{APPROVED_PREFIX}{base}"
-    data = (json.dumps(payload, ensure_ascii=False, indent=2) + "\n").encode("utf-8")
-    bio = io.BytesIO(data)
 
-    try:
-        api.upload_file(
-            repo_id=LEADERBOARD_DATASET,
-            repo_type="dataset",
-            path_or_fileobj=bio,
-            path_in_repo=approved_filename,
-            commit_message=f"miniapp: approve {payload.get('username','')}/{payload.get('model_name','')}",
-            token=HF_TOKEN,
-        )
-        # 删除 pending 原文件（真正“上榜前审核”）
-        api.delete_file(
-            repo_id=LEADERBOARD_DATASET,
-            repo_type="dataset",
-            path_in_repo=pending_filename,
-            commit_message=f"miniapp: remove pending {pending_filename}",
-            token=HF_TOKEN,
+        gr.HTML(
+            """
+<div id="submit_card">
+  <div class="hint">
+    <b>Submission</b> — Submit <b>Model API URL</b> and <b>API key</b> only.
+    Requires login (Spaces). One submission per user per day. Account must be older than 4 months.
+    API key will <b>not</b> be stored.
+  </div>
+</div>
+"""
         )
-    except Exception as e:
-        df, dd = refresh_pending()
-        return f"审核写入失败：{e}", df, dd, refresh()
 
-    pending_df, pending_dd = refresh_pending()
-    approved_df = refresh()
-    return "已通过审核并更新榜单。", pending_df, pending_dd, approved_df
-
-
-with gr.Blocks(title=f"{APP_NAME} leaderboard") as demo:
-    gr.Markdown(
-        f"## {APP_NAME} leaderboard\n\n"
-        "用户提交信息后会进入 **pending（待审核）**；owner 审核通过后才会进入 **approved（上榜）**。\n\n"
-        f"- 当前 `LEADERBOARD_DATASET`: `{LEADERBOARD_DATASET or '(未配置)'}`\n"
-    )
-
-    with gr.Row():
-        with gr.Column(scale=2):
-            model_name = gr.Textbox(label="模型名称（必填）", placeholder="例如：my-agent-v1")
-            model_api = gr.Textbox(
-                label="模型 API（必填）",
-                placeholder="例如：https://api.example.com/v1/chat/completions",
-            )
-            notes = gr.Textbox(label="备注（可选）", lines=4)
-            username = gr.Textbox(
-                label="用户名（可选）",
-                placeholder="建议填你的 HF 用户名（也可留空）",
-                value="" if IN_SPACES else "local",
-            )
-            submit_btn = gr.Button("提交", variant="primary")
+        with gr.Column():
+            with gr.Row():
+                model_api = gr.Textbox(label="Model API URL", placeholder="https://...", scale=3)
+                api_key = gr.Textbox(label="API key", type="password", placeholder="Will not be stored", scale=2)
+            with gr.Row():
+                gr.LoginButton()
+                submit_btn = gr.Button("Submit", variant="primary")
             status = gr.Markdown()
-        with gr.Column(scale=3):
-            leaderboard = gr.Dataframe(
-                label="Leaderboard（按提交时间倒序）",
-                value=_load_entries_df(APPROVED_PREFIX, include_filename=False),
-                interactive=False,
-                wrap=True,
-            )
-            refresh_btn = gr.Button("刷新")
-
-    submit_btn.click(
-        submit,
-        inputs=[model_name, model_api, notes, username],
-        outputs=[status, leaderboard],
-    )
-    refresh_btn.click(refresh, inputs=[], outputs=[leaderboard])
 
-    with gr.Accordion("Owner 审核（测试 demo）", open=False):
-        gr.Markdown(
-            "需要在 Space Secrets 中配置 `OWNER_REVIEW_TOKEN`。只有输入正确口令，才允许把 pending 放入榜单。"
+        submit_btn.click(
+            submit,
+            inputs=[model_api, api_key, search_text, sort_col, sort_dir],
+            outputs=[status, lb_html],
         )
-        review_token = gr.Textbox(label="审核口令", type="password", placeholder="OWNER_REVIEW_TOKEN")
-        pending_refresh_btn = gr.Button("刷新待审核列表")
-        pending_df = gr.Dataframe(
-            label="待审核（pending）",
-            value=_load_entries_df(PENDING_PREFIX, include_filename=True),
-            interactive=False,
-            wrap=True,
-        )
-        pending_pick = gr.Dropdown(
-            label="选择要通过的提交（文件）",
-            choices=_list_json_files(PENDING_PREFIX),
-        )
-        approve_btn = gr.Button("通过审核并上榜", variant="primary")
-        approve_status = gr.Markdown()
-
-        pending_refresh_btn.click(
-            refresh_pending,
-            inputs=[],
-            outputs=[pending_df, pending_pick],
-        )
-        approve_btn.click(
-            approve,
-            inputs=[pending_pick, review_token],
-            outputs=[approve_status, pending_df, pending_pick, leaderboard],
-        )
-
-demo.launch()
 
+demo.launch(css=CSS, ssr_mode=False)