feat(ci): add health dashboard Space + benchmark metrics artifacts

- spaces/health-dashboard/app.py: Gradio Space that queries the GitHub
  Actions API directly (no extra datastore). Shows benchmark status
  badges, success-rate and duration trend charts, and embeds the latest
  rollout video per benchmark. Results cached 5 min in-memory; video
  files cached on disk by artifact ID so downloads only happen once.
- spaces/health-dashboard/requirements.txt + README.md: Space card with
  setup instructions for the GITHUB_RO_TOKEN secret (actions:read,
  metadata:read only).
- scripts/ci/parse_eval_metrics.py: runs on the CI host after each eval,
  reads eval_info.json written by lerobot-eval, extracts pc_success and
  n_episodes, and writes metrics.json to the artifacts dir.
- .github/workflows/benchmark_tests.yml: add "Parse … metrics" and
  "Upload … metrics" steps (if: always()) after each eval so the
  dashboard has data even when the eval fails.

The Space should be deployed as a private Space under the huggingface
org. Required secret: GITHUB_RO_TOKEN (fine-grained, read-only).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.github/workflows/benchmark_tests.yml

@@ -125,6 +125,15 @@ jobs:
                 --output_dir=/artifacts
             "
 
+      - name: Parse Libero eval metrics
+        if: always()
+        run: |
+          python scripts/ci/parse_eval_metrics.py \
+            --artifacts-dir /tmp/libero-artifacts \
+            --env libero \
+            --task libero_spatial \
+            --policy pepijn223/smolvla_libero
+
       - name: Upload Libero rollout video
         if: always()
         uses: actions/upload-artifact@v4
@@ -133,6 +142,14 @@ jobs:
           path: /tmp/libero-artifacts/videos/
           if-no-files-found: warn
 
+      - name: Upload Libero eval metrics
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: libero-metrics
+          path: /tmp/libero-artifacts/metrics.json
+          if-no-files-found: warn
+
   # ── METAWORLD ─────────────────────────────────────────────────────────────
   # Isolated image: lerobot[metaworld] only (metaworld==3.0.0, mujoco>=3 chain)
   metaworld-integration-test:
@@ -189,6 +206,15 @@ jobs:
                 --output_dir=/artifacts
             "
 
+      - name: Parse MetaWorld eval metrics
+        if: always()
+        run: |
+          python scripts/ci/parse_eval_metrics.py \
+            --artifacts-dir /tmp/metaworld-artifacts \
+            --env metaworld \
+            --task metaworld-push-v3 \
+            --policy pepijn223/smolvla_metaworld
+
       - name: Upload MetaWorld rollout video
         if: always()
         uses: actions/upload-artifact@v4
@@ -196,3 +222,11 @@ jobs:
           name: metaworld-rollout-video
           path: /tmp/metaworld-artifacts/videos/
           if-no-files-found: warn
+
+      - name: Upload MetaWorld eval metrics
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: metaworld-metrics
+          path: /tmp/metaworld-artifacts/metrics.json
+          if-no-files-found: warn

scripts/ci/parse_eval_metrics.py

@@ -0,0 +1,113 @@
+#!/usr/bin/env python3
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Parse lerobot-eval output into a small metrics.json artifact.
+
+Reads eval_info.json written by lerobot-eval --output_dir and extracts the
+key metrics needed by the health dashboard. Handles both single-task and
+multi-task eval output formats.
+
+Usage:
+    python scripts/ci/parse_eval_metrics.py \\
+        --artifacts-dir /tmp/libero-artifacts \\
+        --env libero \\
+        --task libero_spatial \\
+        --policy pepijn223/smolvla_libero
+
+Writes <artifacts-dir>/metrics.json. The CI workflow then uploads this file
+as a GitHub Actions artifact named "<env>-metrics".
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import math
+import sys
+from pathlib import Path
+
+
+def _extract_pc_success(info: dict) -> tuple[float | None, int | None]:
+    """Extract (pc_success, n_episodes) from eval_info.json.
+
+    Handles two output shapes:
+      - Single-task: {"aggregated": {"pc_success": 80.0, ...}}
+      - Multi-task:  {"overall": {"pc_success": 80.0, "n_episodes": 5, ...}}
+    """
+    # Single-task path
+    if "aggregated" in info:
+        agg = info["aggregated"]
+        pc = agg.get("pc_success")
+        n = agg.get("n_episodes")  # may be absent in older format
+        if pc is not None and not math.isnan(pc):
+            return float(pc), int(n) if n is not None else None
+
+    # Multi-task path
+    if "overall" in info:
+        overall = info["overall"]
+        pc = overall.get("pc_success")
+        n = overall.get("n_episodes")
+        if pc is not None and not math.isnan(pc):
+            return float(pc), int(n) if n is not None else None
+
+    return None, None
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
+    )
+    parser.add_argument("--artifacts-dir", required=True, help="Path to the mounted artifacts volume")
+    parser.add_argument("--env", required=True, help="Environment name (e.g. libero)")
+    parser.add_argument("--task", required=True, help="Task name (e.g. libero_spatial)")
+    parser.add_argument("--policy", required=True, help="Policy hub path (e.g. pepijn223/smolvla_libero)")
+    args = parser.parse_args()
+
+    artifacts_dir = Path(args.artifacts_dir)
+    eval_info_path = artifacts_dir / "eval_info.json"
+
+    pc_success: float | None = None
+    n_episodes: int | None = None
+
+    if eval_info_path.exists():
+        try:
+            info = json.loads(eval_info_path.read_text())
+            pc_success, n_episodes = _extract_pc_success(info)
+        except (json.JSONDecodeError, KeyError, TypeError) as exc:
+            print(f"[parse_eval_metrics] Warning: could not parse eval_info.json: {exc}", file=sys.stderr)
+    else:
+        print(
+            f"[parse_eval_metrics] Warning: {eval_info_path} not found — eval may have failed.",
+            file=sys.stderr,
+        )
+
+    metrics = {
+        "env": args.env,
+        "task": args.task,
+        "policy": args.policy,
+        "pc_success": pc_success,
+        "n_episodes": n_episodes,
+    }
+
+    out_path = artifacts_dir / "metrics.json"
+    out_path.write_text(json.dumps(metrics, indent=2))
+    print(f"[parse_eval_metrics] Written: {out_path}")
+    print(json.dumps(metrics, indent=2))
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

spaces/health-dashboard/README.md

@@ -0,0 +1,27 @@
+---
+title: LeRobot Health Dashboard
+emoji: 🤖
+colorFrom: yellow
+colorTo: orange
+sdk: gradio
+sdk_version: 5.29.0
+app_file: app.py
+pinned: true
+license: apache-2.0
+short_description: Live CI health for the LeRobot main branch
+---
+
+# LeRobot Health Dashboard
+
+Internal dashboard for monitoring the health of the `main` branch — benchmark smoke-test
+success rates, CI job durations, and latest rollout videos, all pulled live from the
+GitHub Actions API.
+
+## Required secret
+
+Add `GITHUB_RO_TOKEN` in the Space settings with a fine-grained GitHub token scoped to:
+
+- **Repository**: `huggingface/lerobot`
+- **Permissions**: `Actions` → Read-only, `Metadata` → Read-only
+
+The token is never exposed in the UI or logs.

spaces/health-dashboard/app.py

@@ -0,0 +1,488 @@
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""LeRobot CI Health Dashboard.
+
+Pulls live data from the GitHub Actions API — no separate data store needed.
+Benchmark smoke-test results (success rate, duration) come from a small
+metrics.json artifact that each benchmark CI job uploads.
+
+Required Space secret: GITHUB_RO_TOKEN
+  Fine-grained token for huggingface/lerobot with Actions=read, Metadata=read.
+"""
+
+from __future__ import annotations
+
+import io
+import json
+import os
+import threading
+import time
+import zipfile
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+import gradio as gr
+import plotly.graph_objects as go
+import requests  # type: ignore[import-untyped]
+
+# ── Config ────────────────────────────────────────────────────────────────────
+
+REPO = "huggingface/lerobot"
+GH_TOKEN = os.environ.get("GITHUB_RO_TOKEN", "")
+
+CACHE_DIR = Path("/tmp/dashboard-cache")  # nosec B108 — only writable path in HF Spaces
+CACHE_DIR.mkdir(parents=True, exist_ok=True)
+
+API_CACHE_TTL = 300  # 5 min — avoids hammering GitHub on every page load
+
+# Maps CI job name fragment → display info.
+# "artifact" is the actions/upload-artifact name for the rollout video.
+# "metrics_artifact" is the artifact name for metrics.json.
+BENCHMARKS: dict[str, dict[str, str]] = {
+    "libero-integration-test": {
+        "label": "LIBERO",
+        "video_artifact": "libero-rollout-video",
+        "metrics_artifact": "libero-metrics",
+    },
+    "metaworld-integration-test": {
+        "label": "MetaWorld",
+        "video_artifact": "metaworld-rollout-video",
+        "metrics_artifact": "metaworld-metrics",
+    },
+}
+
+WORKFLOW_LABELS: dict[str, str] = {
+    "Benchmark Integration Tests": "Benchmarks",
+    "Fast Tests": "Fast Tests",
+    "Full Tests": "Full Tests",
+    "Quality": "Quality",
+    "Security": "Security",
+}
+
+# ── GitHub API helpers ────────────────────────────────────────────────────────
+
+_api_cache: dict[str, tuple[Any, float]] = {}
+_api_lock = threading.Lock()
+
+
+def _gh_get(path: str, **kwargs: Any) -> Any:
+    """Authenticated GitHub API GET with in-memory TTL cache."""
+    key = path + str(kwargs)
+    with _api_lock:
+        if key in _api_cache:
+            val, ts = _api_cache[key]
+            if time.monotonic() - ts < API_CACHE_TTL:
+                return val
+
+    headers: dict[str, str] = {"Accept": "application/vnd.github+json", "X-GitHub-Api-Version": "2022-11-28"}
+    if GH_TOKEN:
+        headers["Authorization"] = f"Bearer {GH_TOKEN}"
+
+    url = f"https://api.github.com{path}"
+    resp = requests.get(url, headers=headers, timeout=20, **kwargs)
+    resp.raise_for_status()
+    data = resp.json()
+
+    with _api_lock:
+        _api_cache[key] = (data, time.monotonic())
+    return data
+
+
+def _gh_download(url: str) -> bytes:
+    """Download a URL with auth (follows redirects, e.g. artifact zip → S3)."""
+    headers: dict[str, str] = {}
+    if GH_TOKEN:
+        headers["Authorization"] = f"Bearer {GH_TOKEN}"
+    resp = requests.get(url, headers=headers, allow_redirects=True, timeout=120)
+    resp.raise_for_status()
+    return resp.content
+
+
+# ── Data fetchers ─────────────────────────────────────────────────────────────
+
+
+def fetch_recent_runs(branch: str, n: int = 40) -> list[dict]:
+    data = _gh_get(f"/repos/{REPO}/actions/runs", params={"branch": branch, "per_page": n})
+    return data.get("workflow_runs", [])
+
+
+def fetch_jobs(run_id: int) -> list[dict]:
+    # Jobs are immutable once a run completes — cache forever (use long TTL via completed_at check).
+    data = _gh_get(f"/repos/{REPO}/actions/runs/{run_id}/jobs", params={"per_page": 100})
+    return data.get("jobs", [])
+
+
+def fetch_artifacts(run_id: int) -> list[dict]:
+    data = _gh_get(f"/repos/{REPO}/actions/runs/{run_id}/artifacts", params={"per_page": 100})
+    return data.get("artifacts", [])
+
+
+def download_metrics_json(artifact_id: int) -> dict | None:
+    """Download and parse metrics.json from a zip artifact. Caches to disk."""
+    cache_path = CACHE_DIR / f"metrics_{artifact_id}.json"
+    if cache_path.exists():
+        try:
+            return json.loads(cache_path.read_text())
+        except json.JSONDecodeError:
+            cache_path.unlink(missing_ok=True)
+
+    try:
+        raw = _gh_download(f"https://api.github.com/repos/{REPO}/actions/artifacts/{artifact_id}/zip")
+        with zipfile.ZipFile(io.BytesIO(raw)) as zf:
+            if "metrics.json" in zf.namelist():
+                data = json.loads(zf.read("metrics.json"))
+                cache_path.write_text(json.dumps(data))
+                return data
+    except Exception as exc:
+        print(f"[dashboard] Could not fetch metrics artifact {artifact_id}: {exc}")
+    return None
+
+
+def download_video(artifact_id: int, label: str) -> Path | None:
+    """Download the first .mp4 from a zip artifact. Caches to disk."""
+    cache_path = CACHE_DIR / f"video_{artifact_id}.mp4"
+    if cache_path.exists():
+        return cache_path
+
+    try:
+        raw = _gh_download(f"https://api.github.com/repos/{REPO}/actions/artifacts/{artifact_id}/zip")
+        with zipfile.ZipFile(io.BytesIO(raw)) as zf:
+            mp4s = [n for n in zf.namelist() if n.endswith(".mp4")]
+            if mp4s:
+                cache_path.write_bytes(zf.read(mp4s[0]))
+                return cache_path
+    except Exception as exc:
+        print(f"[dashboard] Could not fetch video artifact {artifact_id} ({label}): {exc}")
+    return None
+
+
+# ── Data aggregation ──────────────────────────────────────────────────────────
+
+
+def _job_duration_minutes(job: dict) -> float | None:
+    started = job.get("started_at")
+    completed = job.get("completed_at")
+    if not started or not completed:
+        return None
+    fmt = "%Y-%m-%dT%H:%M:%SZ"
+    try:
+        delta = datetime.strptime(completed, fmt) - datetime.strptime(started, fmt)
+        return delta.total_seconds() / 60
+    except ValueError:
+        return None
+
+
+def aggregate(branch: str) -> dict:
+    """Pull GitHub data and reshape into what the UI needs."""
+    runs = fetch_recent_runs(branch, n=40)
+
+    # Per-benchmark history (ordered newest-first from the API)
+    bench_history: dict[str, list[dict]] = {k: [] for k in BENCHMARKS}
+
+    # Per-workflow latest status + last few runs for the summary table
+    workflow_latest: dict[str, dict] = {}
+
+    for run in runs:
+        wf_name = run["name"]
+        conclusion = run["conclusion"]  # "success" | "failure" | "cancelled" | None
+        created_at = run["created_at"]
+        run_id = run["id"]
+        run_url = run["html_url"]
+
+        # Track latest status per workflow
+        if wf_name not in workflow_latest:
+            workflow_latest[wf_name] = {
+                "conclusion": conclusion,
+                "created_at": created_at,
+                "run_url": run_url,
+            }
+
+        if wf_name != "Benchmark Integration Tests":
+            continue
+
+        # Drill into jobs for this benchmark run
+        jobs = fetch_jobs(run_id)
+        artifacts = fetch_artifacts(run_id)
+        art_by_name = {a["name"]: a for a in artifacts if not a.get("expired")}
+
+        for job in jobs:
+            job_name = job["name"]  # e.g. "Libero — build image + 1-episode eval"
+            matched_key = next(
+                (k for k in BENCHMARKS if k in job_name.lower().replace(" ", "-")),
+                None,
+            )
+            if matched_key is None:
+                continue
+
+            info = BENCHMARKS[matched_key]
+            metrics: dict | None = None
+            if info["metrics_artifact"] in art_by_name:
+                metrics = download_metrics_json(art_by_name[info["metrics_artifact"]]["id"])
+
+            bench_history[matched_key].append(
+                {
+                    "run_id": run_id,
+                    "run_url": run_url,
+                    "created_at": created_at,
+                    "conclusion": job["conclusion"],
+                    "duration_min": _job_duration_minutes(job),
+                    "pc_success": metrics.get("pc_success") if metrics else None,
+                    "n_episodes": metrics.get("n_episodes") if metrics else None,
+                    "video_artifact_id": art_by_name.get(info["video_artifact"], {}).get("id"),
+                }
+            )
+
+    return {
+        "bench_history": bench_history,
+        "workflow_latest": workflow_latest,
+        "fetched_at": datetime.now(UTC).isoformat(),
+    }
+
+
+# ── UI helpers ────────────────────────────────────────────────────────────────
+
+_STATUS_STYLE = {
+    "success": ("✓ passing", "#16a34a"),
+    "failure": ("✗ failing", "#dc2626"),
+    "cancelled": ("⚠ cancelled", "#d97706"),
+    None: ("◌ pending", "#6b7280"),
+}
+
+
+def _badge(conclusion: str | None) -> str:
+    label, color = _STATUS_STYLE.get(conclusion, ("? unknown", "#6b7280"))
+    return (
+        f'<span style="background:{color};color:#fff;padding:1px 9px;border-radius:12px;'
+        f'font-size:12px;font-weight:600;font-family:monospace">{label}</span>'
+    )
+
+
+def _fmt_date(iso: str | None) -> str:
+    if not iso:
+        return "—"
+    return iso[:10]
+
+
+def render_status_table(data: dict) -> str:
+    bench_history = data["bench_history"]
+    workflow_latest = data["workflow_latest"]
+
+    rows = []
+
+    # ── Benchmark rows ──────────────────────────────────────────────
+    for key, info in BENCHMARKS.items():
+        history = bench_history.get(key, [])
+        if history:
+            latest = history[0]
+            badge = _badge(latest["conclusion"])
+            date = _fmt_date(latest["created_at"])
+            pc = latest.get("pc_success")
+            sr_str = f"{pc:.1f}%" if pc is not None else "—"
+            n_ep = latest.get("n_episodes") or "—"
+            link = f'<a href="{latest["run_url"]}" target="_blank">#{latest["run_id"]}</a>'
+        else:
+            badge = _badge(None)
+            date = sr_str = n_ep = link = "—"
+
+        rows.append(
+            f"<tr>"
+            f"<td><b>{info['label']}</b></td>"
+            f"<td>{badge}</td>"
+            f"<td>{date}</td>"
+            f"<td>{sr_str}</td>"
+            f"<td>{n_ep}</td>"
+            f"<td>{link}</td>"
+            f"</tr>"
+        )
+
+    # ── Other workflow rows ─────────────────────────────────────────
+    for wf_name, label in WORKFLOW_LABELS.items():
+        if wf_name == "Benchmark Integration Tests":
+            continue  # already shown above
+        latest_run = workflow_latest.get(wf_name)
+        if latest_run:
+            badge = _badge(latest_run["conclusion"])
+            date = _fmt_date(latest_run["created_at"])
+            link = f'<a href="{latest_run["run_url"]}" target="_blank">run</a>'
+        else:
+            badge = _badge(None)
+            date = link = "—"
+
+        rows.append(
+            f"<tr>"
+            f"<td><b>{label}</b></td>"
+            f"<td>{badge}</td>"
+            f"<td>{date}</td>"
+            f"<td>—</td><td>—</td>"
+            f"<td>{link}</td>"
+            f"</tr>"
+        )
+
+    header = (
+        "<tr style='border-bottom:1px solid #e5e7eb'>"
+        "<th align='left' style='padding:6px 12px'>Job</th>"
+        "<th align='left' style='padding:6px 12px'>Status</th>"
+        "<th align='left' style='padding:6px 12px'>Last run</th>"
+        "<th align='left' style='padding:6px 12px'>Success rate</th>"
+        "<th align='left' style='padding:6px 12px'>Episodes</th>"
+        "<th align='left' style='padding:6px 12px'>Link</th>"
+        "</tr>"
+    )
+    table_rows = "\n".join(rows)
+    return (
+        "<table style='width:100%;border-collapse:collapse;font-family:sans-serif;font-size:14px'>"
+        f"{header}{table_rows}"
+        "</table>"
+    )
+
+
+def render_success_rate_chart(data: dict) -> go.Figure:
+    fig = go.Figure()
+    for key, info in BENCHMARKS.items():
+        history = [e for e in data["bench_history"].get(key, []) if e.get("pc_success") is not None]
+        if history:
+            fig.add_trace(
+                go.Scatter(
+                    x=[e["created_at"][:10] for e in history],
+                    y=[e["pc_success"] for e in history],
+                    mode="lines+markers",
+                    name=info["label"],
+                    line={"width": 2},
+                    marker={"size": 6},
+                )
+            )
+    fig.update_layout(
+        title="Benchmark Success Rate (%) over time",
+        yaxis={"title": "Success rate (%)", "range": [0, 105]},
+        xaxis={"title": ""},
+        height=320,
+        margin={"l": 50, "r": 20, "t": 40, "b": 40},
+        legend={"orientation": "h", "y": -0.15},
+    )
+    return fig
+
+
+def render_duration_chart(data: dict) -> go.Figure:
+    fig = go.Figure()
+    for key, info in BENCHMARKS.items():
+        history = [e for e in data["bench_history"].get(key, []) if e.get("duration_min") is not None]
+        if history:
+            fig.add_trace(
+                go.Bar(
+                    x=[e["created_at"][:10] for e in history],
+                    y=[round(e["duration_min"], 1) for e in history],
+                    name=info["label"],
+                    opacity=0.85,
+                )
+            )
+    fig.update_layout(
+        title="Benchmark CI Duration (minutes)",
+        yaxis={"title": "Duration (min)"},
+        xaxis={"title": ""},
+        barmode="group",
+        height=320,
+        margin={"l": 50, "r": 20, "t": 40, "b": 40},
+        legend={"orientation": "h", "y": -0.15},
+    )
+    return fig
+
+
+def fetch_latest_videos(data: dict) -> dict[str, str | None]:
+    """Return {bench_key: local_mp4_path_or_None} for the latest successful run of each benchmark."""
+    results: dict[str, str | None] = {}
+    for key, info in BENCHMARKS.items():
+        history = data["bench_history"].get(key, [])
+        path = None
+        for entry in history:
+            art_id = entry.get("video_artifact_id")
+            if art_id:
+                downloaded = download_video(art_id, info["label"])
+                if downloaded:
+                    path = str(downloaded)
+                    break
+        results[key] = path
+    return results
+
+
+# ── Gradio app ────────────────────────────────────────────────────────────────
+
+
+def refresh(branch: str) -> tuple:
+    if not GH_TOKEN:
+        err = "<p style='color:red'><b>GITHUB_RO_TOKEN secret not set.</b> Add it in Space settings.</p>"
+        return err, go.Figure(), go.Figure(), None, None, "Error: no token"
+
+    try:
+        data = aggregate(branch)
+    except requests.HTTPError as exc:
+        err = f"<p style='color:red'>GitHub API error: {exc}</p>"
+        return err, go.Figure(), go.Figure(), None, None, str(exc)
+
+    status_html = render_status_table(data)
+    sr_chart = render_success_rate_chart(data)
+    dur_chart = render_duration_chart(data)
+    videos = fetch_latest_videos(data)
+
+    updated = datetime.now(UTC).strftime("Last updated: %Y-%m-%d %H:%M UTC")
+
+    bench_keys = list(BENCHMARKS.keys())
+    video_0 = videos.get(bench_keys[0]) if len(bench_keys) > 0 else None
+    video_1 = videos.get(bench_keys[1]) if len(bench_keys) > 1 else None
+
+    return status_html, sr_chart, dur_chart, video_0, video_1, updated
+
+
+with gr.Blocks(title="LeRobot Health Dashboard", theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        "# 🤖 LeRobot — CI Health Dashboard\n"
+        "Live view of benchmark smoke tests, CI job health, and latest rollout videos. "
+        "Data pulled from the GitHub Actions API."
+    )
+
+    with gr.Row():
+        branch_dd = gr.Dropdown(
+            choices=["main", "feat/benchmark-ci"],
+            value="main",
+            label="Branch",
+            scale=1,
+        )
+        refresh_btn = gr.Button("Refresh", variant="primary", scale=0)
+        updated_md = gr.Markdown("Click Refresh or wait for auto-load.", scale=3)
+
+    gr.Markdown("## Status")
+    status_html = gr.HTML()
+
+    with gr.Row():
+        sr_plot = gr.Plot(label="Success Rate Trend")
+        dur_plot = gr.Plot(label="Duration Trend")
+
+    gr.Markdown("## Latest Rollout Videos")
+    bench_labels = [v["label"] for v in BENCHMARKS.values()]
+    with gr.Row():
+        video_0 = gr.Video(
+            label=bench_labels[0] if len(bench_labels) > 0 else "Benchmark 0", interactive=False
+        )
+        video_1 = gr.Video(
+            label=bench_labels[1] if len(bench_labels) > 1 else "Benchmark 1", interactive=False
+        )
+
+    outputs = [status_html, sr_plot, dur_plot, video_0, video_1, updated_md]
+
+    refresh_btn.click(fn=refresh, inputs=[branch_dd], outputs=outputs)
+    demo.load(fn=refresh, inputs=[branch_dd], outputs=outputs)
+
+if __name__ == "__main__":
+    demo.launch()

spaces/health-dashboard/requirements.txt

@@ -0,0 +1,4 @@
+gradio>=5.0.0,<6.0.0
+plotly>=5.18.0
+pandas>=2.0.0
+requests>=2.31.0