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Update app.py
Browse files
app.py
CHANGED
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@@ -7,8 +7,8 @@ import gradio as gr
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CSV_PATH = Path("leaderboard.csv")
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# Full breakdown columns
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"Model",
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"Score",
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"Completeness",
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@@ -26,19 +26,6 @@ FULL_COLS = [
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"Goal Decomposition",
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]
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# A compact "Arena-like" summary view (close to your Table 2)
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SUMMARY_COLS = [
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"Model",
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"Score",
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"Completeness",
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"Grounding",
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"Recovery Rate",
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"Flexibility",
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"Format",
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"Tool Calls",
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"Goal Decomposition",
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]
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PERCENT_COLS = {
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"Success Rate",
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"Recovery Rate",
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@@ -56,12 +43,12 @@ LABEL_MAP = {
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"Goal Decomposition": "Goal Decomp.",
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}
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ARENA_CSS = r"""
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/* ===== Force a clean "Arena-like" light theme with proper contrast ===== */
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:root { color-scheme: light; }
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html, body { background: #f6f7fb !important; }
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/*
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.gradio-container{
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max-width: 1200px !important;
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margin: 0 auto !important;
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@@ -70,10 +57,10 @@ html, body { background: #f6f7fb !important; }
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--body-background-fill: #f6f7fb !important;
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--body-background-fill-hover: #f6f7fb !important;
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--body-text-color: #0f172a !important;
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--body-text-color-subdued: #334155 !important;
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--block-background-fill: #ffffff !important;
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--block-background-fill-hover: #ffffff !important;
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--block-border-color: #e5e7eb !important;
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@@ -98,24 +85,7 @@ html, body { background: #f6f7fb !important; }
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--link-text-color-active: #1d4ed8 !important;
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}
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/*
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.gradio-container .prose, .gradio-container .prose *{
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color: #0f172a !important;
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}
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.gradio-container .prose p{
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color: #334155 !important;
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}
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/* Make inline code pill readable */
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.gradio-container code{
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background: #f1f5f9 !important;
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border: 1px solid #e2e8f0 !important;
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color: #0f172a !important;
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padding: 1px 6px;
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border-radius: 6px;
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}
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/* ===== Arena table card ===== */
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.arena-card{
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background: #ffffff;
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border: 1px solid #e5e7eb;
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@@ -127,33 +97,38 @@ html, body { background: #f6f7fb !important; }
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table.arena-table{
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width: 100%;
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min-width:
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border-collapse: separate;
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border-spacing: 0;
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font-size: 13px;
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color: #0f172a;
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}
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/*
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table.arena-table thead th{
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position: sticky;
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top: 0;
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z-index:
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background: #f8fafc;
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color: #334155 !important;
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font-weight: 650;
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text-align: left;
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padding: 10px 12px;
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border-bottom: 1px solid #e2e8f0;
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white-space: nowrap;
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}
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/* Body */
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table.arena-table tbody td{
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padding: 10px 12px;
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border-bottom: 1px solid #eef2f7;
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white-space: nowrap;
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color: #0f172a !important;
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}
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table.arena-table tbody tr:nth-child(even){ background: #fbfdff; }
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@@ -163,8 +138,21 @@ table.arena-table th.num, table.arena-table td.num{
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text-align: right;
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font-variant-numeric: tabular-nums;
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}
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table.arena-table td.rank{ width: 52px; color: #64748b !important; }
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"""
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def _to_float(x):
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@@ -173,7 +161,6 @@ def _to_float(x):
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return float("nan")
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if isinstance(x, (int, float)) and not pd.isna(x):
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return float(x)
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s = str(x).strip()
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if not s:
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return float("nan")
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@@ -187,44 +174,37 @@ def _to_float(x):
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def load_df() -> pd.DataFrame:
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if not CSV_PATH.exists():
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return pd.DataFrame(columns=
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df = pd.read_csv(CSV_PATH)
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for c in
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if c not in df.columns:
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df[c] = ""
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return df[
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def format_cell(col: str, val) -> str:
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if val is None or (isinstance(val, float) and pd.isna(val)):
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return ""
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if col in PERCENT_COLS:
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return
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f = _to_float(val)
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if pd.isna(f):
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return
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return f"{f:.2f}"
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def prepare_df(query: str, sort_by: str, descending: bool
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df = load_df()
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# Search (Arena-style: by model name)
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if query:
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q = query.lower().strip()
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df = df[df["Model"].astype(str).str.lower().str.contains(q, na=False)]
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cols = SUMMARY_COLS if view == "Summary" else FULL_COLS
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# Sort
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if sort_by in df.columns:
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df = df.assign(_s=df[sort_by].map(_to_float))
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df = df.sort_values("_s", ascending=not descending, na_position="last").drop(columns=["_s"])
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# Rank
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df = df.reset_index(drop=True)
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df.insert(0, "Rank", range(1, len(df) + 1))
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return df[["Rank"] + cols]
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def render_table(df: pd.DataFrame) -> str:
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if df.empty:
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cols = list(df.columns)
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# Header
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ths = []
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for c in cols:
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label = LABEL_MAP.get(c, c)
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cls =
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if c == "Rank":
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cls
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else:
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cls += ["num"]
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ths.append(f"<th class=\"{' '.join(cls)}\">{html.escape(label)}</th>")
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# Body
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rows = []
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for _, row in df.iterrows():
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tds = []
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for c in cols:
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if c == "Rank":
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cls = "rank num"
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elif c == "Model":
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cls = "model"
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else:
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cls = "num"
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tds.append(f"<td class
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rows.append("<tr>" + "".join(tds) + "</tr>")
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return f"""
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</div>
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"""
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def update(
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return render_table(df)
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cols = SUMMARY_COLS if view == "Summary" else FULL_COLS
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return [c for c in cols if c not in ("Model",)]
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with gr.Blocks(title="ToolGym Leaderboard", css=ARENA_CSS) as demo:
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gr.Markdown("# 馃弳 ToolGym Leaderboard")
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gr.Markdown("
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with gr.Row():
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query = gr.Textbox(label="Search", placeholder="e.g., deepseek, gemini, qwen ...")
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with gr.Row():
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sort_by = gr.Dropdown(choices=sort_choices("Full breakdown"), value="Score", label="Sort by")
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descending = gr.Checkbox(value=True, label="Descending")
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table = gr.HTML()
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default = "Score" if "Score" in new_choices else (new_choices[0] if new_choices else "")
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df = prepare_df(q, default, desc, v)
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return gr.Dropdown.update(choices=new_choices, value=default), render_table(df)
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view.change(on_view_change, inputs=[view, query, descending], outputs=[sort_by, table])
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# Regular refresh
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query.change(update, inputs=[query, view, sort_by, descending], outputs=table)
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sort_by.change(update, inputs=[query, view, sort_by, descending], outputs=table)
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descending.change(update, inputs=[query, view, sort_by, descending], outputs=table)
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# Initial render
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demo.load(update, inputs=[query, view, sort_by, descending], outputs=table)
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if CSV_PATH.exists():
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ts = datetime.utcfromtimestamp(CSV_PATH.stat().st_mtime).strftime("%Y-%m-%d %H:%M UTC")
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else:
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gr.Markdown("<small>Source: <code>leaderboard.csv</code></small>")
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with gr.Accordion("Submit / Update", open=False):
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gr.Markdown(
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"- Open a PR
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"-
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)
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demo.launch()
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CSV_PATH = Path("leaderboard.csv")
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# Full breakdown columns (Appendix Table 6)
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COLS = [
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"Model",
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"Score",
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"Completeness",
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"Goal Decomposition",
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]
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PERCENT_COLS = {
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"Success Rate",
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"Recovery Rate",
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"Goal Decomposition": "Goal Decomp.",
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}
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# Light, Arena-like, high-contrast style (prevents "light bg + light text" issues)
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ARENA_CSS = r"""
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:root { color-scheme: light; }
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html, body { background: #f6f7fb !important; }
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/* Gradio theme tokens */
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.gradio-container{
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max-width: 1200px !important;
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margin: 0 auto !important;
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--body-background-fill: #f6f7fb !important;
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--body-background-fill-hover: #f6f7fb !important;
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--body-text-color: #0f172a !important;
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--body-text-color-subdued: #334155 !important;
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--block-background-fill: #ffffff !important;
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--block-background-fill-hover: #ffffff !important;
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--block-border-color: #e5e7eb !important;
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--link-text-color-active: #1d4ed8 !important;
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}
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/* Arena table card */
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.arena-card{
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background: #ffffff;
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border: 1px solid #e5e7eb;
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table.arena-table{
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width: 100%;
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min-width: 1300px; /* wide table, scrolls horizontally */
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border-collapse: separate;
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border-spacing: 0;
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font-size: 13px;
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color: #0f172a;
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}
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/* IMPORTANT: override any global "prose table" borders */
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table.arena-table th, table.arena-table td{
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border: none !important;
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overflow: visible !important;
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text-overflow: clip !important;
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}
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table.arena-table thead th{
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position: sticky;
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top: 0;
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z-index: 2;
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background: #f8fafc;
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color: #334155 !important;
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font-weight: 650;
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text-align: left;
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padding: 10px 12px;
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border-bottom: 1px solid #e2e8f0 !important;
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white-space: nowrap;
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}
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table.arena-table tbody td{
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padding: 10px 12px;
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border-bottom: 1px solid #eef2f7 !important;
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white-space: nowrap;
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color: #0f172a !important;
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}
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table.arena-table tbody tr:nth-child(even){ background: #fbfdff; }
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text-align: right;
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font-variant-numeric: tabular-nums;
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}
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table.arena-table td.model{ font-weight: 650; }
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table.arena-table td.rank{ width: 52px; color: #64748b !important; }
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/* optional: keep Model column visible while horizontal scrolling */
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table.arena-table thead th:first-child,
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table.arena-table tbody td:first-child{
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position: sticky;
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left: 0;
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z-index: 3;
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background: #f8fafc;
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}
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table.arena-table tbody td:first-child{
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background: #ffffff;
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}
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"""
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def _to_float(x):
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return float("nan")
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if isinstance(x, (int, float)) and not pd.isna(x):
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return float(x)
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s = str(x).strip()
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if not s:
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return float("nan")
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def load_df() -> pd.DataFrame:
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if not CSV_PATH.exists():
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return pd.DataFrame(columns=COLS)
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df = pd.read_csv(CSV_PATH)
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for c in COLS:
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if c not in df.columns:
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df[c] = ""
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return df[COLS]
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def format_cell(col: str, val) -> str:
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if val is None or (isinstance(val, float) and pd.isna(val)):
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return ""
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s = str(val).strip()
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if col in PERCENT_COLS:
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return s
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f = _to_float(val)
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if pd.isna(f):
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return s
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return f"{f:.2f}"
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def prepare_df(query: str, sort_by: str, descending: bool) -> pd.DataFrame:
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df = load_df()
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if query:
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q = query.lower().strip()
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df = df[df["Model"].astype(str).str.lower().str.contains(q, na=False)]
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if sort_by in df.columns:
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df = df.assign(_s=df[sort_by].map(_to_float))
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df = df.sort_values("_s", ascending=not descending, na_position="last").drop(columns=["_s"])
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df = df.reset_index(drop=True)
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df.insert(0, "Rank", range(1, len(df) + 1))
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return df
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def render_table(df: pd.DataFrame) -> str:
|
| 210 |
if df.empty:
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|
| 212 |
|
| 213 |
cols = list(df.columns)
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| 214 |
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|
| 215 |
ths = []
|
| 216 |
for c in cols:
|
| 217 |
label = LABEL_MAP.get(c, c)
|
| 218 |
+
cls = "num" if c not in ("Model",) else ""
|
| 219 |
if c == "Rank":
|
| 220 |
+
cls = "rank num"
|
| 221 |
+
ths.append(f"<th class='{cls}'>{html.escape(label)}</th>")
|
| 222 |
+
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|
| 223 |
rows = []
|
| 224 |
for _, row in df.iterrows():
|
| 225 |
tds = []
|
| 226 |
for c in cols:
|
| 227 |
if c == "Rank":
|
| 228 |
cls = "rank num"
|
| 229 |
+
val = row[c]
|
| 230 |
elif c == "Model":
|
| 231 |
cls = "model"
|
| 232 |
+
val = row[c]
|
| 233 |
else:
|
| 234 |
cls = "num"
|
| 235 |
+
val = format_cell(c, row[c])
|
| 236 |
+
tds.append(f"<td class='{cls}'>{html.escape(str(val))}</td>")
|
| 237 |
rows.append("<tr>" + "".join(tds) + "</tr>")
|
| 238 |
|
| 239 |
return f"""
|
|
|
|
| 247 |
</div>
|
| 248 |
"""
|
| 249 |
|
| 250 |
+
def update(q: str, s: str, d: bool) -> str:
|
| 251 |
+
return render_table(prepare_df(q, s, d))
|
|
|
|
| 252 |
|
| 253 |
+
SORT_CHOICES = [c for c in COLS if c != "Model"]
|
|
|
|
|
|
|
| 254 |
|
| 255 |
with gr.Blocks(title="ToolGym Leaderboard", css=ARENA_CSS) as demo:
|
| 256 |
gr.Markdown("# 馃弳 ToolGym Leaderboard")
|
| 257 |
+
gr.Markdown("Full leaderboard breakdown. Update by editing `leaderboard.csv` via PR.")
|
| 258 |
|
| 259 |
with gr.Row():
|
| 260 |
query = gr.Textbox(label="Search", placeholder="e.g., deepseek, gemini, qwen ...")
|
| 261 |
+
sort_by = gr.Dropdown(label="Sort by", choices=SORT_CHOICES, value="Score")
|
|
|
|
|
|
|
|
|
|
| 262 |
descending = gr.Checkbox(value=True, label="Descending")
|
| 263 |
|
| 264 |
table = gr.HTML()
|
| 265 |
|
| 266 |
+
query.change(update, inputs=[query, sort_by, descending], outputs=table)
|
| 267 |
+
sort_by.change(update, inputs=[query, sort_by, descending], outputs=table)
|
| 268 |
+
descending.change(update, inputs=[query, sort_by, descending], outputs=table)
|
| 269 |
+
demo.load(update, inputs=[query, sort_by, descending], outputs=table)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 270 |
|
| 271 |
+
ts = ""
|
| 272 |
if CSV_PATH.exists():
|
| 273 |
ts = datetime.utcfromtimestamp(CSV_PATH.stat().st_mtime).strftime("%Y-%m-%d %H:%M UTC")
|
| 274 |
+
gr.Markdown(f"<small>Source: <code>leaderboard.csv</code>{(' 路 Last updated: ' + ts) if ts else ''}</small>")
|
|
|
|
|
|
|
| 275 |
|
| 276 |
with gr.Accordion("Submit / Update", open=False):
|
| 277 |
gr.Markdown(
|
| 278 |
+
"- Open a PR editing `leaderboard.csv`.\n"
|
| 279 |
+
"- Include: model name, evaluation setting/commit hash, and the metrics.\n"
|
| 280 |
)
|
| 281 |
|
| 282 |
demo.launch()
|