#!/usr/bin/env python3 """第一方 agent 行为回归 — live 评估 runner(手动/nightly,要真 LLM、花钱)。 用法: AGENTPAAS_API_KEY= python3 evals/run_evals.py [golden/xxx.yaml ...] 不传文件则跑 evals/golden/ 下全部。结果打印汇总 + 落 evals/last_report.json。 框架(打分逻辑)在 agentpaas.engine.agent_eval(已单测,进 CI);本 runner 只负责 把真实"跑 agent / 收产物 / judge"接进去。judge 复用 pipeline.default_judge。 """ from __future__ import annotations import glob import json import os import sys import time import urllib.request sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "agentpaas", "src")) sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "lambdagent", "src")) from agentpaas.engine.agent_eval import EvalTask, run_eval_task, summarize # noqa: E402 BASE = os.environ.get("AGENTPAAS_URL", "http://127.0.0.1:8000") KEY = os.environ.get("AGENTPAAS_API_KEY", "") def _api(method, path, body=None): url = f"{BASE}{path}" data = json.dumps(body).encode() if body is not None else None req = urllib.request.Request(url, data=data, method=method, headers={"Content-Type": "application/json", "Authorization": f"Bearer {KEY}"}) with urllib.request.urlopen(req, timeout=1800) as r: return json.loads(r.read()) def _resolve_agent_id(template: str) -> str: """按模板找一个已安装实例(取第一个 active)。""" agents = _api("GET", "/api/v1/agents").get("agents", []) for a in agents: if a.get("agent_template") == template and a.get("status", "active") == "active": return a["id"] raise RuntimeError(f"未找到模板 {template} 的已安装实例") def _run_fn(task: EvalTask) -> dict: aid = task.agent_id or _resolve_agent_id(task.agent_template) # 同步 /run:返回时已完成 res = _api("POST", f"/api/v1/agents/{aid}/run", {"input": task.input}) return { "output": res.get("output", ""), "steps": (res.get("usage") or {}).get("steps", res.get("steps", 0)), "cost_usd": res.get("cost_usd", 0.0), "workspace_path": res.get("workspace_path", ""), "_run_id": res.get("id", ""), "_agent_id": aid, } def _collect_fn(workspace_path: str) -> dict: # 直接读磁盘(workspace_path 是本机绝对路径) files = {} if not workspace_path or not os.path.isdir(workspace_path): return files skip = {"config.yml", "cost.json", "input.json", "manifest.json", "output.json", "trace.json"} for dp, _dn, fn in os.walk(workspace_path): for f in fn: if f in skip or f.startswith("."): continue full = os.path.join(dp, f) try: with open(full, encoding="utf-8", errors="ignore") as fh: files[os.path.relpath(full, workspace_path)] = fh.read() except Exception: pass return files def _judge_fn(req): from agentpaas.engine.pipeline import default_judge return default_judge(req) def _load_tasks(paths): import yaml tasks = [] for p in paths: spec = yaml.safe_load(open(p, encoding="utf-8")) tmpl = spec.get("agent_template", "") for t in spec.get("tasks", []): tasks.append(EvalTask( id=t["id"], agent_template=tmpl, agent_id=t.get("agent_id", ""), input=t.get("input", ""), must_produce=t.get("must_produce", []), rubric=t.get("rubric", ""), threshold=float(t.get("threshold", 0.6)))) return tasks def main(): if not KEY: print("✗ 需要 AGENTPAAS_API_KEY 环境变量(同前端用的那把)。"); return 2 paths = sys.argv[1:] or sorted(glob.glob(os.path.join(os.path.dirname(__file__), "golden", "*.yaml"))) tasks = _load_tasks(paths) print(f"跑 {len(tasks)} 个 golden 任务 @ {BASE}\n") results = [] for t in tasks: t0 = time.time() r = run_eval_task(t, run_fn=_run_fn, collect_artifacts_fn=_collect_fn, judge_fn=_judge_fn) results.append(r) flag = "✅" if r.passed else "❌" print(f"{flag} {t.id:24} files_ok={r.files_ok} judge={r.judge_score:.2f} " f"steps={r.steps} ${r.cost_usd:.3f} {int(time.time()-t0)}s" + (f" 缺:{r.missing_files}" if r.missing_files else "") + (f" err:{r.error[:60]}" if r.error else "")) s = summarize(results) print("\n=== 汇总 ===") print(json.dumps(s, ensure_ascii=False, indent=2)) out = os.path.join(os.path.dirname(__file__), "last_report.json") json.dump({"summary": s, "results": [r.__dict__ for r in results]}, open(out, "w", encoding="utf-8"), ensure_ascii=False, indent=2) print(f"\n报告已落:{out}") return 0 if s["passed"] == s["total"] else 1 if __name__ == "__main__": sys.exit(main())