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426093b d53ff08 93cd78f d53ff08 93cd78f d53ff08 1195808 426093b 1195808 426093b 1195808 93cd78f 1195808 93cd78f 1195808 93cd78f 1195808 93cd78f 1195808 93cd78f 1195808 93cd78f 1195808 90b2ce8 1195808 93cd78f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | from proteus.game.runtime.trace import SessionTrace
def test_session_trace_memory_ref_defaults_none_and_round_trips():
t = SessionTrace(
scenario="template", motive_category="survival", seed=42,
difficulty="easy", model="demo", outcome="survived",
)
assert t.memory_ref is None
t2 = SessionTrace.model_validate_json(t.model_dump_json())
assert t2.memory_ref is None
t3 = SessionTrace(
scenario="template", motive_category="survival", seed=42,
difficulty="easy", model="demo", outcome="survived",
memory_ref="demo@FIXED",
)
assert SessionTrace.model_validate_json(t3.model_dump_json()).memory_ref == "demo@FIXED"
from proteus.game.agents import VanillaAgent
from proteus.game.engine.difficulty import Difficulty
from proteus.providers import FakeProvider
from proteus.game.runtime import SessionRunner
from proteus.game.runtime.memory import MemoryCheckpoint, MemoryTurn
def _memory() -> MemoryCheckpoint:
return MemoryCheckpoint(
model="demo", scenario="template", difficulty="easy", seed=42,
created_at="FIXED",
memory_turns=[
MemoryTurn(turn_idx=1, frame_ascii="MEMFRAME-1", action="up",
reasoning="", focal_pos=(5, 3), predator_pos=(7, 3)),
MemoryTurn(turn_idx=2, frame_ascii="MEMFRAME-2", action="down",
reasoning="", focal_pos=(5, 2), predator_pos=(6, 3)),
],
outcome="survived", transparent_prompt="brief",
)
def _runner(memory=None, memory_ref=None) -> SessionRunner:
prov = FakeProvider(["ACTION: stay"] * 20, model_name="demo")
return SessionRunner(
"template", VanillaAgent(prov), difficulty=Difficulty.EASY,
seed=42, play_turns=3, use_probe=False,
memory=memory, memory_ref=memory_ref,
)
def test_memory_injection_shows_explicit_memory_and_preserves_measurement():
# NOTE: template provides a default (persona) memory, so the no-explicit-memory
# baseline already carries a MEMORY block. The contrast here is therefore
# "explicit fixture memory" vs "default memory", not "memory" vs "no memory".
base = _runner().run()
withmem = _runner(memory=_memory(), memory_ref="demo@FIXED").run()
obs1 = withmem.turns[0].observation
# the explicit memory block is present at turn 1
assert "MEMORY" in obs1
assert "MEMFRAME-1" in obs1 and "MEMFRAME-2" in obs1
assert "you chose: up" in obs1
# the explicit memory overrides the scenario default, so the observation differs
assert obs1 != base.turns[0].observation
# the scored game is identical: same answer keys, diagnostic, metrics
assert [t.motive_action for t in withmem.turns] == [t.motive_action for t in base.turns]
assert [t.habit_action for t in withmem.turns] == [t.habit_action for t in base.turns]
assert [t.is_diagnostic for t in withmem.turns] == [t.is_diagnostic for t in base.turns]
assert withmem.metrics == base.metrics
# memory_ref recorded with explicit memory, None when falling back to default
assert withmem.memory_ref == "demo@FIXED"
assert base.memory_ref is None
def test_memory_is_shown_every_turn_for_auto_regressive_play():
withmem = _runner(memory=_memory(), memory_ref="x").run()
# Auto-regressive play: the handover memory is carried on turn 2+ as well
# (not only turn 1), so a stateless agent never loses it mid-episode.
assert "MEMFRAME-1" in withmem.turns[0].observation
assert "MEMFRAME-1" in withmem.turns[1].observation
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