feat(memory): store + replay food_cells (paint under agents)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

proteus/grid/scenario.py

@@ -237,6 +237,13 @@ class Scenario(ABC):
         """
         return []
 
+    def food_cells(self) -> list[tuple[int, int]]:
+        """Static 1x1 food cells of the built world, for replay/observation.
+
+        Default: none. Scenarios with food override this (see ``memory_gen``).
+        """
+        return []
+
     def record_focal_move(self, action: str) -> None:
         """Record the focal's last committed move (no-op by default).
 

proteus/runtime/memory.py

@@ -70,6 +70,8 @@ class MemoryCheckpoint(BaseModel):
     Populated for scenarios whose observation is prose (no ASCII grid), so the
     web replay can paint walls it cannot recover from ``frame_ascii``. Empty for
     grid scenarios (their walls are already in each ``frame_ascii``)."""
+    food_cells: list[tuple[int, int]] = Field(default_factory=list)
+    """Static 1x1 food cells of the episode world (same rationale as wall_rects)."""
 
 
 def _safe(name: str) -> str:
@@ -164,6 +166,7 @@ def memory_frames(
     focal_idx = sym2idx.get("A", 1)
     predator_idx = sym2idx.get("B", 2)
     wall_idx = sym2idx.get("#", 3)
+    food_idx = sym2idx.get("F", 14)
     w, h = grid_size
     out: list[dict] = []
 
@@ -182,6 +185,9 @@ def memory_frames(
                 for y in range(max(0, ry0), min(h, ry1 + 1)):
                     for x in range(max(0, rx0), min(w, rx1 + 1)):
                         grid[y][x] = wall_idx
+            for (fx, fy) in checkpoint.food_cells:
+                if 0 <= fx < w and 0 <= fy < h:
+                    grid[fy][fx] = food_idx
             paint(grid, mt.predator_pos[0], mt.predator_pos[1], 5, predator_idx)
             paint(grid, mt.focal_pos[0], mt.focal_pos[1], 3, focal_idx)
         out.append({"turn_idx": mt.turn_idx, "action": mt.action, "grid": grid})

proteus/runtime/memory_gen.py

@@ -121,4 +121,5 @@ def generate_memory(
         transparent_prompt=brief,
         persona_weight_id=persona.persona_weight_id if persona else None,
         wall_rects=list(scenario.wall_rects()),
+        food_cells=list(scenario.food_cells()),
     )

tests/runtime/test_memory_frames.py

@@ -34,3 +34,27 @@ def test_prose_frame_paints_positions_and_walls():
     assert g[2][2] != 3                   # focal painted over its cells
     assert g[3][3] == 3                   # wall cell visible
     assert g[0][4] == 5                   # background elsewhere
+
+
+def test_prose_frame_paints_food_cells():
+    ck = _ck(
+        [MemoryTurn(turn_idx=1, frame_ascii="Open field 8x8. You are A ...",
+                    action="up", focal_pos=(0, 0), predator_pos=(6, 6))],
+        wall_rects=[(5, 1, 5, 1)],   # a clear cell (not under focal/predator/food)
+    )
+    ck.food_cells = [(4, 1), (1, 4)]
+    g = memory_frames(ck, legend=_GRID_LEGEND, grid_size=(8, 8))[0]["grid"]
+    assert g[1][4] == 14 and g[4][1] == 14   # food (idx 14) painted
+    assert g[1][5] == 3                       # wall still there
+    assert g[0][0] == 1                       # focal still on top
+
+
+def test_checkpoint_food_cells_roundtrips():
+    from proteus.runtime.memory import MemoryCheckpoint
+    ck = MemoryCheckpoint(
+        model="m", scenario="pack_evade", difficulty="easy", seed=1,
+        created_at="t", outcome="survived", transparent_prompt="x",
+        food_cells=[(3, 4)],
+    )
+    ck2 = MemoryCheckpoint.model_validate_json(ck.model_dump_json())
+    assert ck2.food_cells == [(3, 4)]