from unittest.mock import patch

from deerflow.agents.memory.thread_updater import ThreadMemoryUpdater


def test_scrub_sensitive_tolerates_non_numeric_confidence():
    updater = ThreadMemoryUpdater()
    cleaned = updater._scrub_sensitive(
        {
            "user": {},
            "history": {},
            "facts": [
                {"content": "Uses React", "category": "knowledge", "confidence": "high"},
                {"content": "Uses TypeScript", "category": "knowledge", "confidence": None},
            ],
        },
        "thread-test",
    )

    assert len(cleaned["facts"]) == 2
    assert cleaned["facts"][0]["confidence"] == 0.5
    assert cleaned["facts"][1]["confidence"] == 0.5


def test_update_memory_repairs_model_json_with_unescaped_inner_quotes():
    class _Storage:
        def __init__(self):
            self.saved = None

        def load(self, _thread_id):
            return None

        def save(self, _thread_id, data, expected_version=None):
            self.saved = {
                "thread_id": _thread_id,
                "data": data,
                "expected_version": expected_version,
            }
            return True

    fake_storage = _Storage()
    fake_model = type(
        "M",
        (),
        {
            "invoke": lambda self, prompt: type(
                "R",
                (),
                {
                    "content": """
{
  "user": {
    "topOfMind": {
      "summary": "反感“作为 AI"这种句式，认为回答不用寒暄直接说重点。",
      "updatedAt": "2026-06-11T07:13:11Z"
    }
  },
  "history": {},
  "facts": [
    {
      "content": "偏好直接回答，不喜欢“作为 AI"式开场",
      "category": "preference",
      "confidence": 0.92
    }
  ]
}
""".strip()
                },
            )()
        },
    )()
    messages = [type("Msg", (), {"type": "human", "content": "请直接回答重点，不要寒暄。"})()]

    with (
        patch("deerflow.agents.memory.thread_updater.get_thread_memory_storage", return_value=fake_storage),
        patch.object(ThreadMemoryUpdater, "_get_model", return_value=fake_model),
    ):
        result = ThreadMemoryUpdater().update_memory(messages, "thread-test")

    assert result is True
    assert fake_storage.saved is not None
    assert fake_storage.saved["expected_version"] == 0
    assert fake_storage.saved["data"]["user"]["topOfMind"]["summary"].startswith("反感“作为 AI")
    assert fake_storage.saved["data"]["facts"][0]["content"].startswith("偏好直接回答")