feat(bench): multi-language capability benchmark + model picker

Add bench-lang.py + bench/ package: a third benchmark axis answering
"which open-source model is best for my workflow?" across Python,
JavaScript, Go, Rust and Bash.

- MultiPL-E (Go/Rust/JS/Bash) + original HumanEval (Python), loaded via
  the HF datasets-server REST API with on-disk cache — no datasets/
  pyarrow dependency.
- Completions go straight to Ollama /api/generate with raw=True so
  instruct models continue the code instead of replying with prose.
- Code runs in rootless, network-less podman (safe default) with a
  host-toolchain fallback; pass@1/pass@k via the HumanEval estimator.
- run/score separation: results persist to a scorecard JSON, then
  `pick --workflow ops` re-ranks without re-running any model.
- Extensible: a new language is one Lang entry; a new workflow is one
  block in workflows.json.

Also fix a --runs grant-persistence bug in bench-sandbox.py: the grant
leaked across runs, invalidating the L0-nogrant refusal test on runs 2+.
Each run now revokes the ACL and starts ungranted.

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

hh/scripts/bench/runtime.py

@@ -0,0 +1,112 @@
+"""Execution backends for model-generated code.
+
+Two interchangeable runtimes implement ``run(lang, source, timeout) -> Exec``:
+
+  • PodmanRuntime  — rootless, network-disabled, per-language image. The safe
+    default: a 1.5B model's Rust is run in a throwaway container, not on the host.
+  • LocalRuntime   — a throwaway temp dir using the host toolchain. Zero setup,
+    no isolation; the fallback when podman is unavailable.
+
+The harness only ever sees the Exec result, so swapping runtimes never touches
+grading logic.
+"""
+
+from __future__ import annotations
+
+import shutil
+import subprocess
+import tempfile
+from dataclasses import dataclass
+from pathlib import Path
+
+from .langs import Lang
+
+
+@dataclass
+class Exec:
+    ok: bool                 # exit 0 and not skipped/timed-out == tests passed
+    rc: int | None
+    out: str
+    note: str = ""           # "timeout" | "image-missing" | error tail
+
+
+class LocalRuntime:
+    """Run in a temp dir with the host toolchain. No isolation — fallback only."""
+
+    name = "local"
+
+    def available(self, lang: Lang) -> bool:
+        tool = lang.run.split()[0]
+        return shutil.which(tool) is not None
+
+    def run(self, lang: Lang, source: str, timeout: float) -> Exec:
+        work = Path(tempfile.mkdtemp(prefix="hh-bench-"))
+        try:
+            (work / lang.filename).write_text(source)
+            try:
+                p = subprocess.run(["bash", "-c", lang.run], cwd=work,
+                                   capture_output=True, text=True, timeout=timeout)
+            except subprocess.TimeoutExpired:
+                return Exec(False, None, "", "timeout")
+            out = (p.stdout + p.stderr)
+            return Exec(p.returncode == 0, p.returncode, out,
+                        "" if p.returncode == 0 else out.strip()[-160:])
+        finally:
+            shutil.rmtree(work, ignore_errors=True)
+
+
+class PodmanRuntime:
+    """Run inside a rootless, network-less podman container per language."""
+
+    name = "podman"
+
+    def __init__(self, podman: str = "podman"):
+        self.podman = podman
+
+    def available(self, lang: Lang) -> bool:
+        return shutil.which(self.podman) is not None
+
+    def ensure_image(self, lang: Lang) -> bool:
+        """Pull the language image if absent. Returns False if it can't be had."""
+        have = subprocess.run([self.podman, "image", "exists", lang.image])
+        if have.returncode == 0:
+            return True
+        pull = subprocess.run([self.podman, "pull", lang.image],
+                              capture_output=True, text=True)
+        return pull.returncode == 0
+
+    def run(self, lang: Lang, source: str, timeout: float) -> Exec:
+        if not self.ensure_image(lang):
+            return Exec(False, None, "", f"image-missing: {lang.image}")
+        work = Path(tempfile.mkdtemp(prefix="hh-bench-"))
+        try:
+            (work / lang.filename).write_text(source)
+            cmd = [
+                self.podman, "run", "--rm",
+                "--network=none",          # model code never touches the network
+                "--memory=512m", "--pids-limit=128",
+                "-v", f"{work}:/w:Z", "-w", "/w",
+                lang.image, "sh", "-c", lang.run,
+            ]
+            try:
+                p = subprocess.run(cmd, capture_output=True, text=True,
+                                   timeout=timeout)
+            except subprocess.TimeoutExpired:
+                return Exec(False, None, "", "timeout")
+            out = (p.stdout + p.stderr)
+            return Exec(p.returncode == 0, p.returncode, out,
+                        "" if p.returncode == 0 else out.strip()[-160:])
+        finally:
+            shutil.rmtree(work, ignore_errors=True)
+
+
+def get_runtime(kind: str = "auto", lang: Lang | None = None):
+    """Pick a runtime. 'auto' prefers podman, falls back to local."""
+    if kind == "podman":
+        return PodmanRuntime()
+    if kind == "local":
+        return LocalRuntime()
+    pod = PodmanRuntime()
+    if pod.available(lang) if lang else shutil.which("podman"):
+        return pod
+    return LocalRuntime()