review: dedupe regex, centralize column names, harden collate, more tests

* **#2 — dedupe `_PLACEHOLDER_RE`.** The same regex was compiled in
  `recipe.py` and `language_render.py`. Promote to module-level
  `PLACEHOLDER_RE` in `recipe.py` (its primary owner — declares
  template syntax) and import from `language_render.py`.
* **#3 — centralize language column names.** `io_utils.py` had
  hardcoded `{"language_persistent", "language_events"}` literals at
  two sites. Replace with `LANGUAGE_COLUMNS` import so a future column
  rename can't silently desync.
* **#4 — defensive collate preserved-keys.** `lerobot_collate_fn`
  silently filtered language fields from samples that didn't have
  them, which would hand downstream consumers a preserved list
  shorter than the tensor batch. Now: if any sample carries a key,
  every sample in the batch must carry it; otherwise raise a
  `ValueError` so the upstream rendering bug surfaces at the boundary.
* **#5 — `_scalar` rejects non-singleton lists.** Previously a zero-
  or multi-element list fell through and triggered confusing
  `float([])` errors downstream. Now raises `ValueError` with the
  actual length.
* **#6 — refactor `_extract_complementary_data`.** Replace 11 lines
  of `key = {... if ... else {}}` plus an 11-line splat dict with a
  single `_COMPLEMENTARY_KEYS` tuple iterated once.
* **#7 — document `EXTENDED_STYLES`.** Was an empty `set()` with no
  comment. Add a docstring explaining it's an intentional extension
  point: downstream modules append project-local styles before
  `column_for_style` is called.
* **#9 — `tools.mdx` notes the runtime layer is future work.** The
  page referenced `src/lerobot/tools/`, `registry.py`, and
  `get_tools(meta)` — none exist in this PR. Added a callout at the
  start of "How to add your own tool" plus a note on the
  implementations paragraph.
* **#10 — tests for YAML round-trip, malformed rows, blend
  validation.** `test_recipe.py` grew from 1 case to 12 covering:
  blend-or-messages exclusivity, target-turn requirement, blend
  emptiness, weight presence/positivity, nested-blend rejection,
  `from_dict` with nested blends, `from_yaml` / `load_recipe`
  agreement, top-level non-mapping rejection. Added a malformed-row
  test for `_normalize_rows` that asserts non-dict entries raise
  `TypeError`.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/configs/test_recipe.py

@@ -1,8 +1,22 @@
 #!/usr/bin/env python
 
+from pathlib import Path
+from textwrap import dedent
+
 import pytest
 
-from lerobot.configs.recipe import MessageTurn, TrainingRecipe
+from lerobot.configs.recipe import MessageTurn, TrainingRecipe, load_recipe
+
+
+def _minimal_message_turn(content: str = "${task}") -> MessageTurn:
+    return MessageTurn(role="user", content=content, stream="high_level")
+
+
+def _minimal_target_turn() -> MessageTurn:
+    return MessageTurn(role="assistant", content="ok", stream="high_level", target=True)
+
+
+# ── Message-recipe validation ────────────────────────────────────────
 
 
 def test_message_recipe_validates_unknown_binding():
@@ -10,6 +24,134 @@ def test_message_recipe_validates_unknown_binding():
         TrainingRecipe(
             messages=[
                 MessageTurn(role="user", content="${missing}", stream="high_level"),
-                MessageTurn(role="assistant", content="ok", stream="high_level", target=True),
+                _minimal_target_turn(),
             ]
         )
+
+
+def test_message_recipe_requires_at_least_one_target():
+    with pytest.raises(ValueError, match="target"):
+        TrainingRecipe(
+            messages=[
+                _minimal_message_turn(),
+                MessageTurn(role="assistant", content="no target", stream="high_level"),
+            ]
+        )
+
+
+def test_recipe_rejects_both_messages_and_blend():
+    with pytest.raises(ValueError, match="only one"):
+        TrainingRecipe(
+            messages=[_minimal_message_turn(), _minimal_target_turn()],
+            blend={"a": TrainingRecipe(weight=1.0, messages=[_minimal_target_turn()])},
+        )
+
+
+def test_recipe_rejects_neither_messages_nor_blend():
+    with pytest.raises(ValueError, match="must set one"):
+        TrainingRecipe()
+
+
+# ── Blend validation ─────────────────────────────────────────────────
+
+
+def test_blend_must_be_non_empty():
+    with pytest.raises(ValueError, match="at least one component"):
+        TrainingRecipe(blend={})
+
+
+def test_blend_component_must_define_weight():
+    with pytest.raises(ValueError, match="weight"):
+        TrainingRecipe(blend={"a": TrainingRecipe(messages=[_minimal_target_turn()])})
+
+
+def test_blend_component_weight_must_be_positive():
+    with pytest.raises(ValueError, match="positive weight"):
+        TrainingRecipe(blend={"a": TrainingRecipe(weight=0.0, messages=[_minimal_target_turn()])})
+
+
+def test_blend_component_must_define_messages():
+    # A bare TrainingRecipe(weight=1.0) would itself raise; build it without
+    # going through __post_init__ to exercise the blend-level validator.
+    bad = TrainingRecipe.__new__(TrainingRecipe)
+    bad.messages = None
+    bad.bindings = None
+    bad.blend = None
+    bad.weight = 1.0
+    with pytest.raises(ValueError, match="must define messages"):
+        TrainingRecipe(blend={"a": bad})
+
+
+def test_blend_components_cannot_themselves_define_a_blend():
+    inner = TrainingRecipe(blend={"x": TrainingRecipe(weight=1.0, messages=[_minimal_target_turn()])})
+    # Force-bypass the inner component's normal validation so the test
+    # exercises the outer blend's "no nested blends" rule directly.
+    nested = TrainingRecipe.__new__(TrainingRecipe)
+    nested.messages = None
+    nested.bindings = None
+    nested.blend = inner.blend
+    nested.weight = 1.0
+    with pytest.raises(ValueError, match="cannot itself define a blend"):
+        TrainingRecipe(blend={"outer": nested})
+
+
+# ── from_dict / from_yaml round-trips ────────────────────────────────
+
+
+def test_from_dict_with_nested_blend():
+    recipe = TrainingRecipe.from_dict(
+        {
+            "blend": {
+                "a": {
+                    "weight": 1.0,
+                    "messages": [
+                        {"role": "user", "content": "${task}", "stream": "high_level"},
+                        {"role": "assistant", "content": "a", "stream": "high_level", "target": True},
+                    ],
+                },
+                "b": {
+                    "weight": 2.0,
+                    "messages": [
+                        {"role": "user", "content": "${task}", "stream": "high_level"},
+                        {"role": "assistant", "content": "b", "stream": "high_level", "target": True},
+                    ],
+                },
+            }
+        }
+    )
+    assert recipe.blend is not None
+    assert set(recipe.blend) == {"a", "b"}
+    assert recipe.blend["b"].weight == 2.0
+    # Inner messages were promoted to MessageTurn instances.
+    assert isinstance(recipe.blend["a"].messages[0], MessageTurn)
+
+
+def test_from_yaml_round_trips_through_load_recipe(tmp_path: Path):
+    yaml_text = dedent(
+        """
+        bindings:
+          custom: "active_at(t, style=subtask)"
+        messages:
+          - {role: user, content: "${task}: ${custom}", stream: high_level}
+          - {role: assistant, content: "ok", stream: high_level, target: true}
+        """
+    ).strip()
+    path = tmp_path / "recipe.yaml"
+    path.write_text(yaml_text)
+
+    via_classmethod = TrainingRecipe.from_yaml(path)
+    via_helper = load_recipe(path)
+
+    assert via_classmethod.bindings == {"custom": "active_at(t, style=subtask)"}
+    assert via_classmethod.messages[1].target is True
+    # ``load_recipe`` is just a wrapper, but assert the two paths agree
+    # on the structural result so a future divergence is caught here.
+    assert via_helper.bindings == via_classmethod.bindings
+    assert len(via_helper.messages) == len(via_classmethod.messages)
+
+
+def test_from_yaml_rejects_non_mapping(tmp_path: Path):
+    path = tmp_path / "bad.yaml"
+    path.write_text("- just\n- a\n- list\n")
+    with pytest.raises(ValueError, match="mapping at the top level"):
+        TrainingRecipe.from_yaml(path)

tests/datasets/test_language_render.py

@@ -342,6 +342,29 @@ def test_resolve_task_explicit_override_beats_rephrasings():
     assert rendered["messages"][0]["content"] == "explicit override wins"
 
 
+def test_render_sample_rejects_non_dict_language_rows():
+    """``_normalize_rows`` must surface malformed inputs as TypeError.
+
+    A pipeline that hands the renderer a non-dict (e.g. a stray string)
+    is a real upstream bug — silent skipping would let it propagate.
+    """
+    recipe = TrainingRecipe(
+        messages=[
+            MessageTurn(role="user", content="${task}", stream="high_level"),
+            MessageTurn(role="assistant", content="ok", stream="high_level", target=True),
+        ]
+    )
+    with pytest.raises(TypeError, match="must be dictionaries"):
+        render_sample(
+            recipe=recipe,
+            persistent=["not a dict"],
+            events=[],
+            t=0.0,
+            sample_idx=0,
+            task="x",
+        )
+
+
 def test_low_level_branch_renders_active_subtask():
     low_level = TrainingRecipe(
         blend={