Update sc1/score_clawbenchpro.sh

sc1/score_clawbenchpro.sh

@@ -2,6 +2,7 @@
 # ClawBenchPro base100/hard100 后处理评分。
 # 可选在本机启动 OpenAI-compatible vLLM Judge，然后调用每题自带 verifier。
 
+set -Eeo pipefail
 set -x
 
 SCRIPT_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
@@ -62,6 +63,106 @@ fi
 
 mkdir -p "${SCORE_OUTPUT_ROOT}" "$(dirname "${JUDGE_LOG}")"
 
+# 只把完整通过磁盘审计的 checkpoint 交给评分器。残缺模型不能用部分题目
+# 计算均分；它们由推理续跑脚本补齐后，再次运行本脚本即可自动纳入评分。
+MODELS=$(python3 - "${INFERENCE_ROOT}" "${BASE_TASKS}/benchmark_manifest.json" "${MODELS}" <<'PY'
+import json
+import sys
+from pathlib import Path
+
+inference_root = Path(sys.argv[1])
+manifest_path = Path(sys.argv[2])
+requested_raw = sys.argv[3]
+requested = {item.strip() for item in requested_raw.split(",") if item.strip()} or None
+
+try:
+    manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
+    task_ids = {str(item["task_id"]) for item in manifest["tasks"]}
+except Exception as exc:
+    print(
+        f"ERROR: failed to load benchmark manifest {manifest_path}: {type(exc).__name__}: {exc}",
+        file=sys.stderr,
+    )
+    raise SystemExit(2)
+
+def load_json(path: Path):
+    try:
+        value = json.loads(path.read_text(encoding="utf-8"))
+    except Exception:
+        return None
+    return value if isinstance(value, dict) else None
+
+complete = []
+discovered_names = set()
+for model_dir in sorted(path for path in inference_root.iterdir() if path.is_dir()):
+    if not (model_dir / "step_1").is_dir():
+        continue
+    model_name = model_dir.name
+    discovered_names.add(model_name)
+    if requested is not None and model_name not in requested:
+        continue
+
+    result_dirs = sorted(
+        path for path in (model_dir / "step_1").glob("data_*_sample_*") if path.is_dir()
+    )
+    discovered_task_ids = {
+        path.name.rsplit("_sample_", 1)[0]
+        for path in result_dirs
+        if "_sample_" in path.name
+    }
+    missing = sorted(task_ids - discovered_task_ids)
+    extra = sorted(discovered_task_ids - task_ids)
+    issues = []
+    if missing:
+        issues.append(f"missing_tasks={len(missing)} first={missing[:5]}")
+    if extra:
+        issues.append(f"extra_tasks={len(extra)} first={extra[:5]}")
+
+    for result_dir in result_dirs:
+        if not (result_dir / "workspace_after").is_dir():
+            issues.append(f"missing_workspace={result_dir.name}")
+        metadata = load_json(result_dir / "nanoclaw_metadata.json")
+        if metadata is None:
+            issues.append(f"invalid_metadata={result_dir.name}")
+        elif metadata.get("status") != "ready":
+            issues.append(f"metadata_status={metadata.get('status')}:{result_dir.name}")
+        if load_json(result_dir / "conversation_history.json") is None:
+            issues.append(f"invalid_conversation={result_dir.name}")
+        if load_json(result_dir / "trajectory.json") is None:
+            issues.append(f"invalid_trajectory={result_dir.name}")
+        if len(issues) >= 20:
+            break
+
+    if issues:
+        print(
+            f"[score_skip_incomplete] model={model_name} issues={len(issues)} "
+            f"preview={' | '.join(issues[:8])}",
+            file=sys.stderr,
+        )
+        continue
+
+    complete.append(model_name)
+    print(
+        f"[score_include_complete] model={model_name} tasks={len(task_ids)} samples={len(result_dirs)}",
+        file=sys.stderr,
+    )
+
+if requested is not None:
+    unknown = sorted(requested - discovered_names)
+    if unknown:
+        print(f"ERROR: requested model directories not found: {unknown}", file=sys.stderr)
+        raise SystemExit(2)
+
+print(",".join(complete))
+PY
+)
+export MODELS
+if [ -z "${MODELS}" ]; then
+    echo "NO_COMPLETE_MODELS_TO_SCORE: incomplete checkpoints must finish inference before scoring."
+    exit 0
+fi
+echo "COMPLETE_MODELS_TO_SCORE=${MODELS}"
+
 # Triton/vLLM 在 Judge 初始化 KV cache 前会通过 tempfile 创建 hivmc
 # 探测文件。训练环境安装脚本历史上默认使用 /cache/ray_tmp，但该目录在
 # 某些独立评分节点上不存在、不可写或已耗尽配额。评分任务使用独立临时
@@ -122,7 +223,7 @@ trap cleanup EXIT INT TERM
 
 check_judge() {
     python3 -c 'import json,sys,urllib.request; req=urllib.request.Request(sys.argv[1].rstrip("/")+"/models",headers={"Authorization":"Bearer "+sys.argv[2]}); data=json.load(urllib.request.urlopen(req,timeout=10)); ids={str(x.get("id")) for x in data.get("data",[])}; raise SystemExit(0 if sys.argv[3] in ids else 1)' \
-        "${JUDGE_BASE_URL}" "${JUDGE_API_KEY}" "${JUDGE_SERVED_MODEL_NAME}"
+        "${JUDGE_BASE_URL}" "${JUDGE_API_KEY}" "${JUDGE_SERVED_MODEL_NAME}" 2>/dev/null
 }
 
 if [ "${JUDGE_ENABLED}" = "1" ]; then
@@ -195,7 +296,12 @@ score_args=(
 if [ "${FAIL_ON_ERROR}" = "1" ]; then
     score_args+=(--fail-on-error)
 fi
-"${score_args[@]}"
+score_rc=0
+"${score_args[@]}" || score_rc=$?
+if [ "${score_rc}" -ne 0 ]; then
+    echo "ERROR: ClawBenchPro scoring failed with exit code ${score_rc}." >&2
+    exit "${score_rc}"
+fi
 
 echo "Scoring completed:"
 echo "  ${SCORE_OUTPUT_ROOT}/summary.json"