ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/harness-safety-gate/demo.py

@@ -0,0 +1,66 @@
+"""实验 9-7 离线教学入口：诊断 → 候选 → 模型外验证 → 发布决定。
+
+单候选演示，不调用任何 API。验收入口是 run_experiment_9_7.py。
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+from evolution import (
+    diagnose,
+    generate_candidate,
+    release_manifest,
+    validate_candidate,
+    write_candidate,
+)
+
+
+ROOT = Path(__file__).parent
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="实验 9-7：用户反馈触发的确认门禁")
+    parser.add_argument("--generator", choices=("deterministic", "llm"), default="deterministic")
+    parser.add_argument("--model", help="真实 LLM 模型；默认取 ARK_MODEL 或 gpt-4o-mini")
+    args = parser.parse_args()
+
+    trajectories = json.loads((ROOT / "failure_trajectories.json").read_text(encoding="utf-8"))
+    boundary_cases = json.loads((ROOT / "boundary_cases.json").read_text(encoding="utf-8"))
+    retention_cases = json.loads((ROOT / "retention_cases.json").read_text(encoding="utf-8"))
+    stable_path = ROOT / "stable" / "tool_dispatcher.py"
+    stable_source = stable_path.read_text(encoding="utf-8")
+
+    diagnosis = diagnose(trajectories)
+    if args.generator == "llm":
+        from llm_generator import generate_with_openai
+        candidate = generate_with_openai(stable_source, diagnosis, args.model)
+    else:
+        candidate = generate_candidate(stable_source, diagnosis)
+    checks = validate_candidate(candidate["source"], boundary_cases, retention_cases)
+    manifest = release_manifest(stable_source, candidate, diagnosis, checks)
+
+    write_candidate(candidate["source"], ROOT / "output" / "candidate" / "confirmation_gate.py")
+    (ROOT / "output" / "release_manifest.json").write_text(
+        json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8"
+    )
+
+    print(f"实验 9-7：用户反馈触发的高风险操作确认门禁（generator={args.generator}）\n")
+    print("诊断目标:", diagnosis["target"])
+    print("失败簇:")
+    for pattern in diagnosis["patterns"]:
+        signals = "/".join(pattern["signals"])
+        print(f"  - {pattern['cluster_id']} (支持度 {pattern['cross_trajectory_support']}, 信号: {signals})")
+    print("来源轨迹:", ", ".join(diagnosis["source_case_ids"]))
+    print("\n接入 diff（提案，不改动 stable/）:\n")
+    print(candidate["integration_diff"])
+    print("检查:", checks)
+    print("发布决定:", manifest["decision"])
+    print("stable/ 未被改动:", stable_path.read_text(encoding="utf-8") == stable_source)
+    print("回滚版本:", manifest["rollback_version"])
+
+
+if __name__ == "__main__":
+    main()