feat(runtime): make the interactive runtime drive PI052 too

The runtime's text path was hard-wired to SmolVLA2: _build_text_batch
read policy.config.vlm_model_name (which PI052Config doesn't have) and
built a SmolVLM2 chat-template prompt. PI052/PaliGemma is not
chat-pretrained and trains on a flat `User: ... \nAssistant: ...`
prompt, so the runtime crashed or fed an out-of-distribution prefix.

- _build_text_batch now dispatches on policy.config.type: smolvla2 ->
  chat template (renamed _build_text_batch_chat); pi052 -> flat
  role-prefixed text via PI052TextTokenizerStep's own _format_messages /
  _strip_blocks / _flatten_say_tool_calls, so the inference prefix
  matches PI052 training exactly.
- Add a lerobot-pi052-runtime entry point (alias of the same main; the
  policy type is read from the checkpoint) so the command name isn't
  misleading. argparse prog now defaults to the invoked command name.

PI052's select_message / predict_action_chunk already work with the
runtime; this was the one SmolVLA2-only coupling.

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

pyproject.toml

@@ -308,7 +308,12 @@ lerobot-imgtransform-viz="lerobot.scripts.lerobot_imgtransform_viz:main"
 lerobot-edit-dataset="lerobot.scripts.lerobot_edit_dataset:main"
 lerobot-setup-can="lerobot.scripts.lerobot_setup_can:main"
 lerobot-annotate="lerobot.scripts.lerobot_annotate:main"
+# Interactive hierarchical-VLA runtime. The same entry point drives both
+# SmolVLA2 (SmolVLM2 backbone) and PI052 (PaliGemma backbone) — the
+# policy type is read from the checkpoint. ``lerobot-pi052-runtime`` is
+# an alias so the command name isn't misleading for PI052 users.
 lerobot-smolvla2-runtime="lerobot.scripts.lerobot_smolvla2_runtime:main"
+lerobot-pi052-runtime="lerobot.scripts.lerobot_smolvla2_runtime:main"
 
 # ---------------- Tool Configurations ----------------
 [tool.setuptools.package-data]