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>

src/lerobot/processor/render_messages_processor.py

@@ -69,7 +69,9 @@ class RenderMessagesStep(ProcessorStep):
             dataset_ctx=self.dataset_ctx,
         )
         if rendered is None:
-            return None
+            rendered = _fallback_low_level_render(complementary_data.get("task"))
+            if rendered is None:
+                return None
 
         new_transition = transition.copy()
         new_complementary_data = dict(new_transition.get(TransitionKey.COMPLEMENTARY_DATA) or {})
@@ -107,7 +109,9 @@ class RenderMessagesStep(ProcessorStep):
                 dataset_ctx=self.dataset_ctx,
             )
             if rendered is None:
-                continue
+                rendered = _fallback_low_level_render(_batch_value(complementary_data.get("task"), i))
+                if rendered is None:
+                    continue
             keep_indices.append(i)
             messages.append(rendered["messages"])
             message_streams.append(rendered["message_streams"])
@@ -178,3 +182,16 @@ def _select_value(value: Any, indices: list[int]) -> Any:
     if hasattr(value, "index_select") and hasattr(value, "new_tensor") and getattr(value, "ndim", 0) > 0:
         return value.index_select(0, value.new_tensor(indices).long())
     return value
+
+
+def _fallback_low_level_render(task: Any) -> dict[str, Any] | None:
+    """Keep action-only samples trainable when no recipe branch matches."""
+    if hasattr(task, "item"):
+        task = task.item()
+    if not isinstance(task, str) or not task:
+        return None
+    return {
+        "messages": [{"role": "user", "content": task}],
+        "message_streams": ["low_level"],
+        "target_message_indices": [],
+    }

tests/processor/test_render_messages_processor.py

@@ -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"] == [[], []]