fix(processor): fallback to task message when recipe misses

Keep action-only samples trainable by rendering the task as a low-level user message when no recipe branch matches. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-20 02:59:50 +00:00 · 2026-05-19 15:31:24 +00:00
parent 15f79b5e5e
commit e425dfd624
2 changed files with 86 additions and 2 deletions
@@ -54,3 +54,70 @@ def test_render_messages_step_renders_and_drops_raw_language():
    assert data["messages"][-1]["content"] == "reach carefully"
    assert data["message_streams"] == ["high_level", "low_level"]
    assert data["target_message_indices"] == [1]
+
+
+def test_render_messages_step_falls_back_to_low_level_task_when_recipe_misses():
+    recipe = TrainingRecipe(
+        messages=[
+            MessageTurn(
+                role="assistant",
+                content="${subtask}",
+                stream="high_level",
+                target=True,
+                if_present="subtask",
+            ),
+        ]
+    )
+    transition = create_transition(
+        complementary_data={
+            "task": "pick the cube",
+            "timestamp": torch.tensor(0.0),
+            "index": torch.tensor(7),
+            "language_persistent": [],
+            "language_events": [{"style": "unmatched", "timestamp": 0.0}],
+        }
+    )
+
+    out = RenderMessagesStep(recipe)(transition)
+    data = out[TransitionKey.COMPLEMENTARY_DATA]
+
+    assert data["messages"] == [{"role": "user", "content": "pick the cube"}]
+    assert data["message_streams"] == ["low_level"]
+    assert data["target_message_indices"] == []
+
+
+def test_render_messages_step_falls_back_per_sample_in_batched_language():
+    recipe = TrainingRecipe(
+        messages=[
+            MessageTurn(
+                role="assistant",
+                content="${subtask}",
+                stream="high_level",
+                target=True,
+                if_present="subtask",
+            ),
+        ]
+    )
+    transition = create_transition(
+        action=torch.arange(4).reshape(2, 2),
+        complementary_data={
+            "task": ["pick the cube", "open the drawer"],
+            "timestamp": torch.tensor([0.0, 1.0]),
+            "index": torch.tensor([7, 8]),
+            "language_persistent": [[], []],
+            "language_events": [
+                [{"style": "unmatched", "timestamp": 0.0}],
+                [{"style": "unmatched", "timestamp": 1.0}],
+            ],
+        },
+    )
+
+    out = RenderMessagesStep(recipe)(transition)
+    data = out[TransitionKey.COMPLEMENTARY_DATA]
+
+    assert data["messages"] == [
+        [{"role": "user", "content": "pick the cube"}],
+        [{"role": "user", "content": "open the drawer"}],
+    ]
+    assert data["message_streams"] == [["low_level"], ["low_level"]]
+    assert data["target_message_indices"] == [[], []]