"""多轮 Harness² 改进批量跑（sweep，接线层 CLI）。 读一个 JSON manifest，顺序跑多轮 run_improvement_via_tasks：所有轮 共享同一个 library_root（已入库的经验会被后续轮读到，即上游 sweep 的 library restore 语义）；单轮失败只记入报告、不中断后续轮 （dead 隔离）；最后写 sweep-report.json 并汇总打印。 这会创建真实任务、花真实模型配额——所以默认只打印计划，不建 任务：先跑一遍不带 --yes 看计划，确认无误后，再带 --yes 重跑。 密钥不走命令行参数（ps 可见）：用环境变量 CODEX_API_KEY。 manifest 形状： { "runs": [ {"run_tag": "sw1", "task_id": "ledger-1", "prompt": "Sum every signed amount in ledger.csv.", "base_harness_dir": "./base-harness", "source_dir": "./task-source", "domain": "accounting", "k": 1, "mode": "parallel", "budget": 5, "max_sessions": null, "model": null, "role_models": null, "effort": null, "approval": null, "environment_id": null, "executor": null, "no_time_limit": false, "timeout": 3600} ] } prompt 也可用 prompt_file（相对 manifest 所在目录）；base_harness_dir 与 source_dir 同样相对 manifest 目录解析（绝对路径原样用）。 """ import argparse import json import os import sys import tempfile from pathlib import Path sys.path.insert(0, str(Path(__file__).resolve().parents[1])) from cloud.harness2 import read_tree # noqa: E402 from cloud.harness2_tasks import ( # noqa: E402 HttpTaskClient, preflight_checks, run_sweep, validate_run_tag, ) def _flatten(root: Path) -> dict[str, bytes]: out: dict[str, bytes] = {} if not root or not root.is_dir(): return out for p in sorted(root.rglob("*")): if p.is_file() and not p.is_symlink() and "__pycache__" not in p.parts: out[str(p.relative_to(root))] = p.read_bytes() return out def _resolve(manifest_dir: Path, value): if not value: return value p = Path(value) return p if p.is_absolute() else manifest_dir / p def main(): ap = argparse.ArgumentParser() ap.add_argument("--manifest", required=True, help="JSON manifest 路径") ap.add_argument("--base-url", required=True, help="控制面地址") ap.add_argument("--project-id", required=True) ap.add_argument("--output", default="", help="sweep 工作根目录（默认临时目录）") ap.add_argument("--library-root", default="", help="共享经验库根目录（空 = 各轮不入库）") ap.add_argument("--yes", action="store_true", help="确认创建真实任务并消费配额") args = ap.parse_args() manifest_path = Path(args.manifest) try: manifest = json.loads(manifest_path.read_text(encoding="utf-8")) except (OSError, ValueError) as exc: print(f"manifest 读不到或不是合法 JSON：{exc}", file=sys.stderr) return 2 runs = manifest.get("runs") if not isinstance(runs, list) or not runs: print("manifest 里 runs 必须是非空列表", file=sys.stderr) return 2 manifest_dir = manifest_path.resolve().parent specs = [] seen_tags = set() for i, raw in enumerate(runs): if not isinstance(raw, dict): print(f"runs[{i}] 不是对象", file=sys.stderr) return 2 tag = raw.get("run_tag", "") try: if not tag: raise ValueError("每轮必须给 run_tag") validate_run_tag(tag) except ValueError as exc: print(f"runs[{i}] run_tag 非法：{exc}", file=sys.stderr) return 2 if tag in seen_tags: print(f"runs[{i}] run_tag 重复：{tag}", file=sys.stderr) return 2 seen_tags.add(tag) prompt = raw.get("prompt", "") if raw.get("prompt_file"): try: prompt = _resolve(manifest_dir, raw["prompt_file"]).read_text( encoding="utf-8") except OSError as exc: print(f"runs[{i}] prompt_file 读不到：{exc}", file=sys.stderr) return 2 base_dir = _resolve(manifest_dir, raw.get("base_harness_dir", "")) errors, warnings = preflight_checks( base_harness_dir=base_dir, source_dir=_resolve(manifest_dir, raw.get("source_dir")) or None, prompt=prompt, run_tag=tag, base_url=args.base_url) for e in errors: print(f"FAIL runs[{i}] {tag}: {e}", file=sys.stderr) for w in warnings: print(f"WARN runs[{i}] {tag}: {w}") if errors: return 2 source_dir = _resolve(manifest_dir, raw.get("source_dir")) specs.append({ "run_tag": tag, "task_id": raw.get("task_id", f"h2-task-{tag}"), "prompt": prompt, "base_harness": read_tree(base_dir), "source_files": _flatten(source_dir) if source_dir else None, "domain": raw.get("domain", "general"), "k": raw.get("k", 1), "mode": raw.get("mode", "parallel"), "budget_usd": raw.get("budget"), "max_sessions": raw.get("max_sessions"), "model": raw.get("model"), "role_models": raw.get("role_models"), "effort": raw.get("effort"), "approval": raw.get("approval"), "environment_id": raw.get("environment_id"), "executor": raw.get("executor"), "no_time_limit": bool(raw.get("no_time_limit", False)), "timeout_seconds": raw.get("timeout", 3600), }) print(f"计划：项目 {args.project_id}，共 {len(specs)} 轮，" f"tags={sorted(seen_tags)}，" f"共享 library={'是' if args.library_root else '否（不入库）'}") if not args.yes: print("未带 --yes：只打印计划，不创建任何任务。确认无误后加 --yes 重跑。") return 0 api_key = os.environ.get("CODEX_API_KEY") if not api_key: print("缺少 CODEX_API_KEY 环境变量（密钥不接受命令行参数）", file=sys.stderr) return 2 work_root = Path(args.output) if args.output else Path( tempfile.mkdtemp(prefix="h2sweep-")) client = HttpTaskClient(args.base_url, api_key) report = run_sweep( client, project_id=args.project_id, runs=specs, work_root=work_root, library_root=Path(args.library_root) if args.library_root else None) report_path = work_root / "sweep-report.json" report_path.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8") for entry in report["runs"]: status = "ok" if entry["ok"] else f"FAIL {entry['error']}" print(f"{entry['run_tag']}: {status} " f"chosen={entry['chosen_label']} " f"cost={entry['total_cost_usd']}") totals = report["totals"] print(f"汇总：{totals['n_ok']}/{totals['n_runs']} 轮成功，" f"总成本 {totals['total_cost_usd']}，报告 {report_path}") return 0 if totals["n_ok"] == totals["n_runs"] else 1 if __name__ == "__main__": raise SystemExit(main())