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deer-flow/backend/tests/test_memory_staleness_review.py
Aari e32456d337
fix(memory): coerce stored confidence in the three remaining raw reads (#4034) 
* fix(memory): coerce stored confidence in the three remaining raw reads

`_coerce_source_confidence` exists because `memory.json` is user-editable and
written across versions: a `confidence` that is null, a str, a bool, out of
range, or non-finite still has to read back as a usable score. Consolidation
already routes every stored read through it, and #4023 did the same for the
max_facts trim. Three reads still take the field raw.

`_build_staleness_section` formats it with `f"{conf:.2f}"` — a str raises
ValueError, None raises TypeError. `_do_update_memory_sync`'s `except Exception`
swallows that into `return False`, aborting the whole memory-update cycle
permanently, since the offending fact is then never rewritten.

The staleness cap's `sort(key=lambda f: f.get("confidence", 0))` ranks the facts
it is about to delete. A str raises the same way; the values that don't raise
mis-rank instead. `true`/`inf` outrank a genuine 0.9 and push it into the removal
slot; an absent key ranks 0 and is deleted first; `nan` compares false against
everything, so which fact dies depends on where the corrupted one happens to sit
in the file.

`search_memory_facts` — the `memory_search` tool, added in #4023 — ranks results
the same raw way and then truncates to `limit`, so the same mis-ranking hands the
model the wrong facts, or fails the tool call outright on a str.

All three now read through the helper, so an unusable stored confidence ranks as
unknown (0.5): neither kept ahead of a real score nor evicted before one. The two
sorts run in opposite directions, and 0.5 is load-bearing in both.

* test(memory): anchor the confidence delta at every coerced read

The str-based tests raise on main, so they cannot go red for any stored
confidence that mis-ranks without raising. `true`/`false`/`inf` and an absent key
never reached the except handler at all: bool subclasses int, so `true` ranked
1.0; `inf` outranked every real score; an absent key ranked 0. Silent fact loss
in the staleness cap, wrong results out of `memory_search` — no log line either
way.

Parametrize both ranking sorts over the four non-raising inputs that fall to the
0.5 default, each pitted against a genuine neighbour chosen so the survivor
flips. The sorts run in opposite directions, so the one matrix covers eviction
from both ends.

`nan` is excluded from those: its old rank is undefined rather than pinned to an
end of the order, so one fixed input order happens to yield the correct survivor.
Its real property is order-independence, asserted across both fact orders.

The staleness prompt formatter is pinned by rendered value, not merely by not
raising: 1.5 → 1.00, -0.3 → 0.00, and inf/nan/true/None → 0.50, matching the
consolidation prompt that reads the same field through the same helper.
2026-07-14 07:40:49 +08:00

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"""Tests for the staleness review feature in the memory updater.
Covers:
- Candidate selection (age threshold, protected categories)
- Trigger conditions (min candidates, enabled flag)
- Prompt section formatting
- Staleness removal in _apply_updates (safety cap, observability)
- Normalization of staleFactsToRemove from LLM responses
- Integration with _prepare_update_prompt
"""
from datetime import UTC, datetime, timedelta
from unittest.mock import MagicMock, patch
import pytest
from deerflow.agents.memory.updater import (
MemoryUpdater,
_build_staleness_section,
_normalize_memory_update_data,
_parse_fact_datetime,
_select_stale_candidates,
)
from deerflow.config.memory_config import MemoryConfig
# ── Helpers ────────────────────────────────────────────────────────────────
_ABSENT = object()
"""Sentinel: the fact carries no ``confidence`` key at all."""
def _memory_config(**overrides: object) -> MemoryConfig:
config = MemoryConfig()
for key, value in overrides.items():
setattr(config, key, value)
return config
def _make_fact(
fact_id: str,
content: str = "test content",
category: str = "knowledge",
confidence: float = 0.9,
days_ago: int = 100,
) -> dict:
created = (datetime.now(UTC) - timedelta(days=days_ago)).isoformat().replace("+00:00", "Z")
return {
"id": fact_id,
"content": content,
"category": category,
"confidence": confidence,
"createdAt": created,
"source": "thread-test",
}
def _make_memory(facts: list[dict] | None = None) -> dict:
return {
"version": "1.0",
"lastUpdated": "",
"user": {
"workContext": {"summary": "", "updatedAt": ""},
"personalContext": {"summary": "", "updatedAt": ""},
"topOfMind": {"summary": "", "updatedAt": ""},
},
"history": {
"recentMonths": {"summary": "", "updatedAt": ""},
"earlierContext": {"summary": "", "updatedAt": ""},
"longTermBackground": {"summary": "", "updatedAt": ""},
},
"facts": facts or [],
}
# ── _parse_fact_datetime ──────────────────────────────────────────────────
class TestParseFactDatetime:
def test_z_suffix(self):
result = _parse_fact_datetime("2025-06-01T12:00:00Z")
assert result is not None
assert result.year == 2025
assert result.month == 6
def test_offset_format(self):
result = _parse_fact_datetime("2025-06-01T12:00:00+00:00")
assert result is not None
assert result.year == 2025
def test_empty_string(self):
assert _parse_fact_datetime("") is None
def test_invalid_format(self):
assert _parse_fact_datetime("not-a-date") is None
def test_naive_datetime_gets_utc(self):
"""Naive datetime (no tzinfo) should be treated as UTC, not cause TypeError."""
result = _parse_fact_datetime("2025-06-01T12:00:00")
assert result is not None
assert result.tzinfo is not None
assert result.utcoffset().total_seconds() == 0
# ── _select_stale_candidates ──────────────────────────────────────────────
class TestSelectStaleCandidates:
def test_old_facts_selected(self):
memory = _make_memory(
[
_make_fact("fact_old", days_ago=100),
_make_fact("fact_new", days_ago=10),
]
)
config = _memory_config(staleness_age_days=90)
candidates = _select_stale_candidates(memory, config)
assert len(candidates) == 1
assert candidates[0]["id"] == "fact_old"
def test_protected_category_excluded(self):
memory = _make_memory(
[
_make_fact("fact_correction", category="correction", days_ago=200),
_make_fact("fact_knowledge", category="knowledge", days_ago=200),
]
)
config = _memory_config(staleness_age_days=90, staleness_protected_categories=["correction"])
candidates = _select_stale_candidates(memory, config)
assert len(candidates) == 1
assert candidates[0]["id"] == "fact_knowledge"
def test_custom_protected_categories(self):
memory = _make_memory(
[
_make_fact("fact_goal", category="goal", days_ago=200),
]
)
config = _memory_config(staleness_age_days=90, staleness_protected_categories=["goal"])
candidates = _select_stale_candidates(memory, config)
assert len(candidates) == 0
def test_no_facts(self):
memory = _make_memory([])
config = _memory_config(staleness_age_days=90)
assert _select_stale_candidates(memory, config) == []
def test_all_recent(self):
memory = _make_memory(
[
_make_fact("fact_a", days_ago=10),
_make_fact("fact_b", days_ago=30),
]
)
config = _memory_config(staleness_age_days=90)
assert _select_stale_candidates(memory, config) == []
# ── Trigger conditions via _select_stale_candidates + config ─────────────
class TestStalenessTriggerConditions:
"""The old _should_run_staleness_review was removed; trigger logic is now
inlined in _prepare_update_prompt. We verify the gating conditions here
through _select_stale_candidates + config flags directly."""
def test_disabled_means_no_section(self):
memory = _make_memory([_make_fact(f"f{i}", days_ago=100) for i in range(5)])
config = _memory_config(staleness_review_enabled=False, staleness_age_days=90, staleness_min_candidates=3)
candidates = _select_stale_candidates(memory, config)
# Even though candidates exist, the caller checks enabled flag first
assert config.staleness_review_enabled is False
assert len(candidates) >= config.staleness_min_candidates
def test_below_min_candidates(self):
memory = _make_memory([_make_fact("fact_only", days_ago=100)])
config = _memory_config(staleness_review_enabled=True, staleness_age_days=90, staleness_min_candidates=3)
candidates = _select_stale_candidates(memory, config)
assert len(candidates) < config.staleness_min_candidates
def test_at_min_candidates(self):
memory = _make_memory([_make_fact(f"fact_{i}", days_ago=100) for i in range(3)])
config = _memory_config(staleness_review_enabled=True, staleness_age_days=90, staleness_min_candidates=3)
candidates = _select_stale_candidates(memory, config)
assert len(candidates) >= config.staleness_min_candidates
def test_above_min_candidates(self):
memory = _make_memory([_make_fact(f"fact_{i}", days_ago=100) for i in range(10)])
config = _memory_config(staleness_review_enabled=True, staleness_age_days=90, staleness_min_candidates=3)
candidates = _select_stale_candidates(memory, config)
assert len(candidates) >= config.staleness_min_candidates
# ── _build_staleness_section ──────────────────────────────────────────────
class TestBuildStalenessSection:
def test_empty_candidates(self):
assert _build_staleness_section([], 90) == ""
def test_includes_fact_details(self):
candidates = [
_make_fact("fact_vue", "User uses Vue.js", "knowledge", 0.95, days_ago=120),
]
section = _build_staleness_section(candidates, 90)
assert "fact_vue" in section
assert "User uses Vue.js" in section
assert "0.95" in section
assert "90 days" in section
def test_multiple_facts(self):
candidates = [
_make_fact("fact_a", "Fact A", "knowledge", 0.9, days_ago=100),
_make_fact("fact_b", "Fact B", "preference", 0.8, days_ago=150),
]
section = _build_staleness_section(candidates, 90)
assert "fact_a" in section
assert "fact_b" in section
assert "<stale_facts>" in section
def test_html_special_chars_in_content_are_escaped(self):
"""Fact content with XML tags or quotes is HTML-escaped so it cannot
break the surrounding prompt structure."""
candidates = [
_make_fact("fact_x", 'Like <b>bold</b> & "quotes"', "knowledge", 0.9, days_ago=100),
]
section = _build_staleness_section(candidates, 90)
assert "<b>" not in section
assert "&lt;b&gt;" in section
assert "&amp;" in section
assert "&quot;" in section
def test_closing_tag_in_content_is_escaped(self):
"""A closing </stale_facts> tag embedded in content must not prematurely
end the prompt XML block."""
candidates = [
_make_fact("fact_y", "</stale_facts><injected>bad</injected>", "knowledge", 0.8, days_ago=100),
]
section = _build_staleness_section(candidates, 90)
assert "</stale_facts><injected>" not in section
assert "&lt;/stale_facts&gt;" in section
def test_special_chars_in_category_are_escaped(self):
"""A category name with XML tags or quotes is HTML-escaped, consistent
with how category is handled in the consolidation section."""
candidates = [
_make_fact("fact_z", "content", 'pref<"erences>', 0.8, days_ago=100),
]
section = _build_staleness_section(candidates, 90)
assert 'pref<"erences>' not in section
assert "pref&lt;&quot;erences&gt;" in section
@pytest.mark.parametrize("stored_confidence", ["0.9", None, "high", ""])
def test_non_float_confidence_does_not_raise(self, stored_confidence):
"""A stored ``confidence`` that is not a float must not abort the update.
``memory.json`` is user-editable and written across versions, which is why
``_coerce_source_confidence`` exists. Formatting it raw raises ValueError on
a str and TypeError on None; ``_do_update_memory_sync``'s ``except Exception``
turns that into a silent ``return False`` that aborts the whole memory-update
cycle -- permanently, since the offending fact is then never rewritten.
"""
fact = _make_fact("fact_x", "Some fact", "knowledge", 0.9, days_ago=120)
fact["confidence"] = stored_confidence
section = _build_staleness_section([fact], 90)
assert "fact_x" in section
assert "Some fact" in section
@pytest.mark.parametrize(
("stored_confidence", "rendered"),
[
("0.9", "0.90"),
("high", "0.50"),
(None, "0.50"),
(True, "0.50"),
(1.5, "1.00"),
(-0.3, "0.00"),
(float("inf"), "0.50"),
(float("nan"), "0.50"),
],
)
def test_confidence_is_normalised_like_every_other_stored_read(self, stored_confidence, rendered):
"""Pins the mapping, not just the absence of a crash.
``0.5`` is this module's default for an unknown confidence
(``create_memory_fact``, ``_normalize_memory_update_fact``,
``_coerce_source_confidence``). Before this change the staleness prompt
rendered ``1.5`` as ``1.50``, ``inf`` as ``inf``, and a ``True`` as ``1.00``
-- disagreeing with the consolidation prompt, which reads the same field
through the same helper.
"""
fact = _make_fact("fact_x", "Some fact", "knowledge", 0.9, days_ago=120)
fact["confidence"] = stored_confidence
section = _build_staleness_section([fact], 90)
assert f"| {rendered} |" in section
def test_missing_confidence_key_renders_unknown_not_zero(self):
"""An absent key is *unknown* (0.50), not *worthless* (0.00).
The staleness cap removes the lowest-confidence facts first, so ranking an
unreadable confidence at 0.00 would make that fact the first one deleted.
"""
fact = _make_fact("fact_x", "Some fact", "knowledge", 0.9, days_ago=120)
del fact["confidence"]
assert "| 0.50 |" in _build_staleness_section([fact], 90)
# ── _apply_updates with staleness removals ─────────────────────────────────
class TestApplyUpdatesStaleness:
def test_stale_facts_removed(self):
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_keep", "User knows Python", days_ago=100),
_make_fact("fact_stale", "User uses Vue.js", days_ago=120),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_stale", "reason": "User switched to React"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=10),
):
result = updater._apply_updates(current_memory, update_data)
assert len(result["facts"]) == 1
assert result["facts"][0]["id"] == "fact_keep"
def test_stale_candidate_without_id_does_not_raise(self):
"""A legacy / hand-edited fact that lacks an ``id`` must not crash the
staleness apply path.
Regression: ``candidate_ids`` was built with a direct ``f["id"]``
access over ``_select_stale_candidates`` output, but every other fact
access in the module uses ``f.get("id")``. An aged, non-protected fact
with no ``id`` key (common in legacy / migrated ``memory.json``) is a
valid staleness candidate, so it reached ``f["id"]`` and raised
``KeyError: 'id'``, aborting the whole memory-update cycle.
"""
updater = MemoryUpdater()
aged = (datetime.now(UTC) - timedelta(days=120)).isoformat().replace("+00:00", "Z")
# An aged, non-protected fact deliberately missing the "id" key.
idless_fact = {"content": "User uses Vue.js", "category": "knowledge", "confidence": 0.8, "createdAt": aged}
current_memory = _make_memory([_make_fact("fact_keep", days_ago=100), idless_fact])
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_keep", "reason": "outdated"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=10),
):
# Must not raise KeyError: 'id'.
result = updater._apply_updates(current_memory, update_data)
# The id-less fact survives (it can never be targeted by the id-based
# removal set), and the id-based removal of fact_keep still applies.
contents = {f.get("content") for f in result["facts"]}
assert "User uses Vue.js" in contents
def test_safety_cap_limits_removals(self):
updater = MemoryUpdater()
# 5 stale facts, but cap is 2 → only 2 lowest-confidence should be removed
current_memory = _make_memory(
[
_make_fact("fact_high", confidence=0.95, days_ago=100),
_make_fact("fact_mid", confidence=0.80, days_ago=100),
_make_fact("fact_low1", confidence=0.70, days_ago=100),
_make_fact("fact_low2", confidence=0.65, days_ago=100),
_make_fact("fact_low3", confidence=0.60, days_ago=100),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_high", "reason": "outdated"},
{"id": "fact_mid", "reason": "outdated"},
{"id": "fact_low1", "reason": "outdated"},
{"id": "fact_low2", "reason": "outdated"},
{"id": "fact_low3", "reason": "outdated"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=2),
):
result = updater._apply_updates(current_memory, update_data)
# 5 - 2 = 3 facts remain; the 2 lowest-confidence removed
assert len(result["facts"]) == 3
remaining_ids = {f["id"] for f in result["facts"]}
assert "fact_high" in remaining_ids
assert "fact_mid" in remaining_ids
assert "fact_low1" in remaining_ids
def test_safety_cap_sort_survives_non_float_stored_confidence(self):
"""The cap's ranking sort reads stored confidence and must coerce it.
``sort(key=lambda f: f.get("confidence", 0))`` compares a str against a
float and raises ``TypeError``, which the caller swallows into an aborted
update. Fixing only the prompt formatter would move this crash rather than
remove it, so the sort is pinned here too. ``"0.95"`` must rank like 0.95.
"""
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_str_high", confidence="0.95", days_ago=100),
_make_fact("fact_mid", confidence=0.80, days_ago=100),
_make_fact("fact_low", confidence=0.60, days_ago=100),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_str_high", "reason": "outdated"},
{"id": "fact_mid", "reason": "outdated"},
{"id": "fact_low", "reason": "outdated"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=1),
):
result = updater._apply_updates(current_memory, update_data)
# Only the single lowest-confidence fact is removed; the string "0.95"
# ranks as the highest and survives.
remaining_ids = {f["id"] for f in result["facts"]}
assert remaining_ids == {"fact_str_high", "fact_mid"}
@pytest.mark.parametrize(
("stored_confidence", "rival_confidence", "survivor"),
[
(_ABSENT, 0.1, "fact_x"),
(False, 0.1, "fact_x"),
(True, 0.9, "fact_rival"),
(float("inf"), 0.9, "fact_rival"),
],
)
def test_safety_cap_ranks_unusable_confidence_as_unknown(self, stored_confidence, rival_confidence, survivor):
"""The cap deletes the lowest-ranked fact, so a mis-ranked one deletes its neighbour.
Mirrors the max_facts trim's delta set with the sort reversed: here a
``true``/``inf`` fact ranked *above* a genuine 0.9 and pushed it into
the removal slot. None of these raised under the old key, so the
string-coercion test above passes unchanged for all four.
"""
fact_x = _make_fact("fact_x", days_ago=100)
if stored_confidence is _ABSENT:
del fact_x["confidence"]
else:
fact_x["confidence"] = stored_confidence
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_x", "reason": "outdated"},
{"id": "fact_rival", "reason": "outdated"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=1),
):
result = MemoryUpdater()._apply_updates(
_make_memory([fact_x, _make_fact("fact_rival", confidence=rival_confidence, days_ago=100)]),
update_data,
)
assert [f["id"] for f in result["facts"]] == [survivor]
def test_safety_cap_with_nan_confidence_is_order_independent(self):
"""Under the raw key the cap deleted either fact depending on their file order.
``nan`` compares false against every score, so ``sort`` leaves the pair
untouched: with the corrupted fact stored *second*, the genuine 0.9 one
landed in the removal slot instead.
"""
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_nan", "reason": "outdated"},
{"id": "fact_rival", "reason": "outdated"},
],
}
survivors = []
for nan_first in (True, False):
nan_fact = _make_fact("fact_nan", confidence=float("nan"), days_ago=100)
rival = _make_fact("fact_rival", confidence=0.9, days_ago=100)
facts = [nan_fact, rival] if nan_first else [rival, nan_fact]
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=1),
):
result = MemoryUpdater()._apply_updates(_make_memory(facts), update_data)
survivors.append(result["facts"][0]["id"])
assert survivors == ["fact_rival", "fact_rival"]
def test_empty_stale_removals_no_effect(self):
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_a", days_ago=100),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100),
):
result = updater._apply_updates(current_memory, update_data)
assert len(result["facts"]) == 1
def test_missing_stale_removals_key_no_effect(self):
"""When LLM doesn't return staleFactsToRemove, existing behavior is preserved."""
updater = MemoryUpdater()
current_memory = _make_memory([_make_fact("fact_a")])
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
# no staleFactsToRemove key
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100),
):
result = updater._apply_updates(current_memory, update_data)
assert len(result["facts"]) == 1
def test_contradiction_and_staleness_removals_combined(self):
"""Both factsToRemove and staleFactsToRemove work together."""
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_keep", days_ago=10),
_make_fact("fact_contradicted", days_ago=10),
_make_fact("fact_stale", days_ago=200),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": ["fact_contradicted"],
"staleFactsToRemove": [{"id": "fact_stale", "reason": "old"}],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(max_facts=100, staleness_max_removals_per_cycle=10),
):
result = updater._apply_updates(current_memory, update_data)
assert len(result["facts"]) == 1
assert result["facts"][0]["id"] == "fact_keep"
def test_protected_category_fact_refused_at_apply(self):
"""Regression: LLM hallucinating a correction-category fact id in
staleFactsToRemove must be silently rejected at the apply layer,
even though it appears in the serialized prompt JSON."""
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_stale", category="knowledge", days_ago=200),
_make_fact("fact_correction", category="correction", days_ago=200),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_stale", "reason": "outdated"},
{"id": "fact_correction", "reason": "LLM slip"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(
max_facts=100,
staleness_review_enabled=True,
staleness_age_days=90,
staleness_min_candidates=1,
staleness_max_removals_per_cycle=10,
staleness_protected_categories=["correction"],
),
):
result = updater._apply_updates(current_memory, update_data)
# fact_stale removed, fact_correction kept (protected)
assert len(result["facts"]) == 1
assert result["facts"][0]["id"] == "fact_correction"
def test_non_aged_fact_refused_at_apply(self):
"""Regression: LLM returning a fresh (non-aged) fact id in
staleFactsToRemove must be silently rejected."""
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_stale", days_ago=200),
_make_fact("fact_fresh", days_ago=10),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_stale", "reason": "outdated"},
{"id": "fact_fresh", "reason": "LLM hallucination"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(
max_facts=100,
staleness_review_enabled=True,
staleness_age_days=90,
staleness_min_candidates=1,
staleness_max_removals_per_cycle=10,
staleness_protected_categories=["correction"],
),
):
result = updater._apply_updates(current_memory, update_data)
# fact_stale removed, fact_fresh kept (not in candidate set)
assert len(result["facts"]) == 1
assert result["facts"][0]["id"] == "fact_fresh"
def test_guardrail_runs_when_staleness_review_disabled(self):
"""Regression: guardrail must reject invalid ids even when
staleness_review_enabled=False, so the protection is independent
of the feature flag and model behavior."""
updater = MemoryUpdater()
current_memory = _make_memory(
[
_make_fact("fact_stale", days_ago=200),
_make_fact("fact_fresh", days_ago=5),
]
)
update_data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_stale", "reason": "LLM hallucination"},
{"id": "fact_fresh", "reason": "LLM hallucination"},
],
}
with patch(
"deerflow.agents.memory.updater.get_memory_config",
return_value=_memory_config(
max_facts=100,
staleness_review_enabled=False,
staleness_age_days=90,
staleness_min_candidates=3,
staleness_max_removals_per_cycle=10,
staleness_protected_categories=["correction"],
),
):
result = updater._apply_updates(current_memory, update_data)
# Guardrail runs regardless of feature flag:
# fact_stale is a valid candidate (200 days old) → removed
# fact_fresh is not a candidate (5 days old) → kept
assert len(result["facts"]) == 1
assert result["facts"][0]["id"] == "fact_fresh"
# ── _normalize_memory_update_data with staleFactsToRemove ─────────────────
class TestNormalizeStaleFactsToRemove:
def test_valid_entries(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [
{"id": "fact_a", "reason": "User moved offices"},
{"id": "fact_b", "reason": "Tech stack changed"},
],
}
result = _normalize_memory_update_data(data)
assert len(result["staleFactsToRemove"]) == 2
assert result["staleFactsToRemove"][0]["id"] == "fact_a"
assert result["staleFactsToRemove"][1]["reason"] == "Tech stack changed"
def test_missing_key(self):
data = {"user": {}, "history": {}, "newFacts": [], "factsToRemove": []}
result = _normalize_memory_update_data(data)
assert result["staleFactsToRemove"] == []
def test_non_list_ignored(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": "not a list",
}
result = _normalize_memory_update_data(data)
assert result["staleFactsToRemove"] == []
def test_non_dict_entries_skipped(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": ["just a string", 42, {"id": "fact_ok", "reason": "valid"}],
}
result = _normalize_memory_update_data(data)
assert len(result["staleFactsToRemove"]) == 1
assert result["staleFactsToRemove"][0]["id"] == "fact_ok"
def test_empty_id_skipped(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [{"id": "", "reason": "no id"}],
}
result = _normalize_memory_update_data(data)
assert result["staleFactsToRemove"] == []
def test_non_string_reason_defaulted(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [{"id": "fact_a", "reason": 123}],
}
result = _normalize_memory_update_data(data)
assert result["staleFactsToRemove"][0]["reason"] == ""
def test_missing_reason_defaulted(self):
data = {
"user": {},
"history": {},
"newFacts": [],
"factsToRemove": [],
"staleFactsToRemove": [{"id": "fact_a"}],
}
result = _normalize_memory_update_data(data)
assert result["staleFactsToRemove"][0]["reason"] == ""
# ── Integration: _prepare_update_prompt ────────────────────────────────────
class TestPrepareUpdatePromptStaleness:
def test_staleness_section_included_when_triggered(self):
updater = MemoryUpdater()
old_facts = [_make_fact(f"fact_{i}", days_ago=100) for i in range(5)]
memory = _make_memory(old_facts)
msg = MagicMock()
msg.type = "human"
msg.content = "Hello, I'm using React now"
config = _memory_config(
enabled=True,
staleness_review_enabled=True,
staleness_age_days=90,
staleness_min_candidates=3,
)
with (
patch("deerflow.agents.memory.updater.get_memory_config", return_value=config),
patch("deerflow.agents.memory.updater.get_memory_data", return_value=memory),
):
result = updater._prepare_update_prompt(
messages=[msg],
agent_name=None,
correction_detected=False,
reinforcement_detected=False,
)
assert result is not None
_, prompt = result
assert "Staleness Review" in prompt
assert "<stale_facts>" in prompt
def test_staleness_section_omitted_when_not_triggered(self):
updater = MemoryUpdater()
memory = _make_memory([]) # no facts at all
msg = MagicMock()
msg.type = "human"
msg.content = "Hello"
config = _memory_config(
enabled=True,
staleness_review_enabled=True,
staleness_age_days=90,
staleness_min_candidates=3,
)
with (
patch("deerflow.agents.memory.updater.get_memory_config", return_value=config),
patch("deerflow.agents.memory.updater.get_memory_data", return_value=memory),
):
result = updater._prepare_update_prompt(
messages=[msg],
agent_name=None,
correction_detected=False,
reinforcement_detected=False,
)
assert result is not None
_, prompt = result
assert "Staleness Review" not in prompt
assert "<stale_facts>" not in prompt
def test_staleness_section_omitted_when_disabled(self):
updater = MemoryUpdater()
old_facts = [_make_fact(f"fact_{i}", days_ago=200) for i in range(10)]
memory = _make_memory(old_facts)
msg = MagicMock()
msg.type = "human"
msg.content = "Hello"
config = _memory_config(
enabled=True,
staleness_review_enabled=False,
)
with (
patch("deerflow.agents.memory.updater.get_memory_config", return_value=config),
patch("deerflow.agents.memory.updater.get_memory_data", return_value=memory),
):
result = updater._prepare_update_prompt(
messages=[msg],
agent_name=None,
correction_detected=False,
reinforcement_detected=False,
)
assert result is not None
_, prompt = result
assert "Staleness Review" not in prompt
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