refactor(runtime): remove gibberish filtering

src/lerobot/policies/pi052/modeling_pi052.py

@@ -1751,8 +1751,6 @@ class PI052Policy(PreTrainedPolicy):
         return out
 
     def _generate_low_level_subtask(self, obs_i: dict[str, Tensor], task: str, i: int) -> str:
-        from lerobot.runtime.adapter import looks_like_gibberish as _looks_like_gibberish  # noqa: PLC0415
-
         from .inference.pi052_adapter import _generate_with_policy  # noqa: PLC0415
 
         msg = ""
@@ -1767,7 +1765,7 @@ class PI052Policy(PreTrainedPolicy):
         self.last_subtasks_raw[i] = msg or ""
 
         # Feed the generated subtask verbatim, matching low-level training.
-        if msg and not _looks_like_gibberish(msg):
+        if msg:
             subtask = " ".join(msg.strip().split())
             self._last_good_subtasks[i] = subtask
             self.last_subtasks[i] = subtask
@@ -1779,8 +1777,6 @@ class PI052Policy(PreTrainedPolicy):
         debug = getattr(self, "_last_select_message_debug", "") or ""
         if not task:
             reason = "No task string was available in the batch."
-        elif msg:
-            reason = f"Rejected generated subtask: {msg!r}"
         else:
             reason = f"Empty generated subtask. {debug}".strip()
         if self._last_good_subtasks[i]:

src/lerobot/runtime/adapter.py

@@ -43,11 +43,10 @@ class GenerationConfig:
 
 @dataclass
 class LanguageDiagnostics:
-    """Runtime-panel rejection and repeat counters keyed by text kind."""
+    """Runtime-panel generation counters keyed by text kind."""
 
     last_raw: dict[str, str] = field(default_factory=dict)
     empty: dict[str, int] = field(default_factory=dict)
-    gibberish: dict[str, int] = field(default_factory=dict)
     repeat: int = 0
 
     def _bump(self, table: dict[str, int], kind: str) -> int:
@@ -96,9 +95,9 @@ class BaseLanguageAdapter(ABC):
             state.set_context("plan", plan, label="plan")
 
     def plan_from_text(self, text: str) -> str:
-        """Strip ``<say>`` speech markers and reject gibberish plans."""
+        """Strip ``<say>`` speech markers from a generated plan."""
         plan, _speech = split_plan_and_say(text)
-        return "" if looks_like_gibberish(plan) else plan
+        return plan
 
     def _regenerate_context(self, observation: dict[str, Any] | None, state: RuntimeState) -> None:
         """Default hierarchy: regenerate the subtask, then memory when it changes.
@@ -127,7 +126,7 @@ class BaseLanguageAdapter(ABC):
     def _generate_filtered(
         self, kind: str, observation: dict[str, Any] | None, state: RuntimeState
     ) -> str | None:
-        """Generate one ``kind``, record diagnostics, drop empty / gibberish output."""
+        """Generate one ``kind``, record diagnostics, and drop empty output."""
         text = self.generate_text(kind, observation, state)
         self.diag.last_raw[kind] = text or ""
         if not text:
@@ -135,11 +134,6 @@ class BaseLanguageAdapter(ABC):
             if count == 1 or count % 5 == 0:
                 state.log(f"  [info] {kind} gen returned empty (x{count})")
             return None
-        if looks_like_gibberish(text):
-            count = self.diag._bump(self.diag.gibberish, kind)
-            if count == 1 or count % 30 == 0:
-                state.log(f"  [info] {kind} gen rejected (gibberish x{count}): {text[:60]!r}")
-            return None
         return text
 
 
@@ -159,29 +153,6 @@ class DirectTaskPolicyAdapter(BaseLanguageAdapter):
         return ""
 
 
-def looks_like_gibberish(text: str) -> bool:
-    """Heuristic filter for malformed / collapsed LM-head output."""
-    if not text or not text.strip():
-        return True
-    stripped = text.strip()
-    alpha = sum(1 for c in stripped if c.isalpha())
-    if alpha < max(3, len(stripped) // 8):
-        return True
-    if stripped.startswith('":') and stripped.count('"') > stripped.count(" "):
-        return True
-    if len(set(stripped)) <= 2 and len(stripped) > 4:
-        return True
-    cleaned = stripped.replace("\n", " ").replace(":", " ")
-    for marker in ("Assistant", "User", "Ass "):
-        if marker in cleaned and len(cleaned.split()) < 4:
-            return True
-    tokens = [t for t in cleaned.split() if any(c.isalpha() for c in t)]
-    unique_alpha = {t.lower() for t in tokens}
-    if len(unique_alpha) < 3 and len(stripped) < 80:
-        return True
-    return len(tokens) >= 8 and len(unique_alpha) <= max(3, len(tokens) // 10)
-
-
 def split_plan_and_say(text: str) -> tuple[str, str]:
     """Split ``plan <say>speech</say>`` into ``(plan, speech)``."""
     if not text:

src/lerobot/runtime/cli.py

@@ -660,24 +660,19 @@ def _make_state_panel_renderer(
         dispatched = int(st.get("actions_dispatched") or 0)
         console.print(f"  [dim]queued actions: {queue_len}    dispatched: {dispatched}[/]")
 
-        # Surface repeated or rejected generations as overfitting diagnostics.
+        # Surface repeated or empty generations as overfitting diagnostics.
         diag = getattr(runtime.policy_adapter, "diag", None)
         if diag is not None:
             raw_subtask = diag.last_raw.get("subtask")
             sub_rep = int(diag.repeat)
-            sub_gib = int(diag.gibberish.get("subtask", 0))
             sub_empty = int(diag.empty.get("subtask", 0))
-            if raw_subtask is not None or sub_rep or sub_gib or sub_empty:
+            if raw_subtask is not None or sub_rep or sub_empty:
                 raw_display = (raw_subtask or "(empty)")[:80]
-                color = "yellow" if (sub_rep >= 3 or sub_gib >= 3 or sub_empty >= 3) else "dim"
+                color = "yellow" if (sub_rep >= 3 or sub_empty >= 3) else "dim"
                 console.print(
-                    f"  [{color}]subtask diag    repeat:{sub_rep}  "
-                    f"gibberish:{sub_gib}  empty:{sub_empty}  "
+                    f"  [{color}]subtask diag    repeat:{sub_rep}  empty:{sub_empty}  "
                     f"last_raw: {raw_display!r}[/]"
                 )
-            mem_gib = int(diag.gibberish.get("memory", 0))
-            if mem_gib:
-                console.print(f"  [dim]gen rejects     memory:{mem_gib}[/]")
         console.rule(style="cyan")
         # Show recent generation warnings and speech oldest-first.
         if scrollback:

tests/runtime/test_adapter.py

@@ -17,7 +17,6 @@ from lerobot.runtime.adapter import (
     BaseLanguageAdapter,
     DirectTaskPolicyAdapter,
     GenerationConfig,
-    looks_like_gibberish,
 )
 
 
@@ -49,15 +48,15 @@ def test_cascade_sets_subtask_then_memory():
     assert adapter.calls == ["subtask", "memory"]
 
 
-def test_gibberish_subtask_is_rejected_and_counted():
-    adapter = ScriptedAdapter({"subtask": [":::: ::"], "memory": ["should not run"]})
+def test_nonempty_generation_is_used_verbatim():
+    adapter = ScriptedAdapter({"subtask": [":::: ::"], "memory": ["memory"]})
     state = RuntimeState(task="clean")
 
     adapter.update_language_state(None, state)
 
-    assert "subtask" not in state.language_context
-    assert adapter.diag.gibberish.get("subtask") == 1
-    assert adapter.calls == ["subtask"]  # memory never generated when subtask is rejected
+    assert state.language_context["subtask"] == ":::: ::"
+    assert state.language_context["memory"] == "memory"
+    assert adapter.calls == ["subtask", "memory"]
 
 
 def test_throttle_regenerates_every_n_chunks():
@@ -87,12 +86,6 @@ def test_handle_interjection_sets_plan_and_strips_say():
     assert state.language_context["plan"] == "turn to the left now"
 
 
-def test_looks_like_gibberish_basic():
-    assert looks_like_gibberish("")
-    assert looks_like_gibberish(":::: ::")
-    assert not looks_like_gibberish("pick up the red cube")
-
-
 def test_direct_task_adapter_delegates_action_chunk():
     class Policy:
         def predict_action_chunk(self, observation):