fix(rl): enhance intervention handling in actor and learner

(cherry picked from commit ef8bfffbd7)

src/lerobot/rl/actor.py

@@ -337,7 +337,7 @@ def act_with_policy(
 
         # Check for intervention from transition info
         intervention_info = new_transition[TransitionKey.INFO]
-        is_intervention = intervention_info.get(TeleopEvents.IS_INTERVENTION, False)
+        is_intervention = bool(intervention_info.get(TeleopEvents.IS_INTERVENTION, False))
         if is_intervention:
             episode_intervention = True
             episode_intervention_steps += 1
@@ -346,7 +346,10 @@ def act_with_policy(
             "discrete_penalty": torch.tensor(
                 [new_transition[TransitionKey.COMPLEMENTARY_DATA].get("discrete_penalty", 0.0)]
             ),
-            "is_intervention": is_intervention,
+            # Forward the intervention flag so the learner can route this transition
+            # into the offline replay buffer (see `process_transitions` in learner.py).
+            # Use the plain string key so the payload survives torch.load(weights_only=True).
+            TeleopEvents.IS_INTERVENTION.value: is_intervention,
         }
         # Create transition for learner (convert to old format)
         list_transition_to_send_to_learner.append(

src/lerobot/rl/learner.py

@@ -937,7 +937,7 @@ def process_transitions(
 
             # Add to offline buffer if it's an intervention
             if dataset_repo_id is not None and transition.get("complementary_info", {}).get(
-                TeleopEvents.IS_INTERVENTION
+                TeleopEvents.IS_INTERVENTION.value
             ):
                 offline_replay_buffer.add(**transition)