annotate: address review feedback — bug fixes, docs/code drift, naming, cleanup

Bugs
  * validator: don't re-raise on unknown style. The second column_for_style
    lookup (used to route persistent vs event) now sits in try/except so an
    unknown style is recorded by _check_column_routing and skipped instead
    of crashing the whole validation pass.
  * general_vqa._target_cameras: when restrict_to_default_camera is set but
    the configured camera_key isn't one the provider exposes, warn and fall
    back to all cameras instead of returning a phantom key that KeyErrors
    deep in frame decode.
  * interjections: clamp interjection timestamps to frame_timestamps[0]
    rather than a hardcoded 0.0 (datasets can start at non-zero t).

Docs / code drift
  * annotation_pipeline.mdx: drop the phantom 'vocabulary discovery / phase
    0 / --vocabulary.* / canonical_vocabulary.json' section (none of it
    exists); describe the real describe->segment + coverage-stitch flow.
    Soften the src/lerobot/tools/ + TOOL_REGISTRY reference to 'not part of
    this PR' (matches tools.mdx, which already marks the runtime layer as
    not-yet-implemented). Fix the --push_to_hub/--new_repo_id wording. Note
    the default is now a single h200. Add a 'Contributing new modules'
    section inviting module / prompt / quality contributions.
  * executor docstring: six phases, no phantom phase 0.

run_hf_job.py
  * add the Apache 2.0 license header (was flagged repeatedly).
  * default to a single GPU: flavor=h200, parallel_servers=1, num_gpus=1
    (scale to h200x4 noted in the docstring).
  * pin the install to @main instead of the feature branch (won't break
    after merge).

Naming / cleanup
  * rename dest_repo_id -> new_repo_id across config / script / example /
    test to match the LeRobot dataset edit tools.
  * rename prompt templates module_N_*.txt -> descriptive (plan_*,
    interjections_*, vqa.txt) and update every load_prompt() call.
  * remove dead _messages_to_prompt (used only by the removed in-process
    backends).
  * declare _warned_decode_fail (frames) and _warned_no_camera (vqa) as
    real init=False dataclass fields instead of getattr monkey-patches.
  * scope bandit B607 to the two ffmpeg subprocess.run sites via
    '# nosec B607' and drop it from the global skip list.

Tests
  * fix stale canned-VLM markers ('ONE realistic interruption' ->
    'compact interjection', 'Update the memory' -> 'compressed semantic
    memory') and drop the dead 'concise hierarchical PLAN' plan responders
    (plan generation is deterministic now) in run_e2e_smoke,
    test_pipeline_recipe_render, test_modules.
  * run_e2e_smoke now asserts interjection + speech rows are produced so a
    stale marker can't silently pass again.
  * drop remaining 'PR 1' / 'PR 2' references from test comments / names.

Verified: tests/annotations + tests/datasets/test_language +
tests/scripts/test_lerobot_annotate (31 passed); make-style E2E smoke
(interjections=1 speech_atoms=2); pre-commit (ruff, mypy, bandit,
prettier) clean.

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

examples/annotations/run_hf_job.py

@@ -1,21 +1,37 @@
 #!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 """Launch ``lerobot-annotate`` on a Hugging Face job (vllm + Qwen3.6-27B VLM).
 
-Spawns one ``h200x4`` job that:
+Spawns one single-GPU ``h200`` job that:
 
-  1. installs this branch of ``lerobot`` plus the annotation extras,
-  2. boots four vllm servers (one per GPU) with Qwen3.6-27B (dense VLM),
+  1. installs ``lerobot`` plus the annotation extras,
+  2. boots one vllm server with Qwen3.6-27B (dense VLM),
   3. runs the plan / interjections / vqa modules across the dataset
      in free-form mode (each episode generates its own subtasks +
      memory),
-  4. uploads the annotated dataset to ``--dest_repo_id`` (when set)
+  4. uploads the annotated dataset to ``--new_repo_id`` (when set)
      or back to ``--repo_id``.
 
 Usage:
 
     HF_TOKEN=hf_... uv run python examples/annotations/run_hf_job.py
 
-Adjust ``CMD`` below to point at your own dataset / target hub repo.
+Adjust ``CMD`` (dataset, model, hub repo) and ``flavor`` below for your
+run. For larger datasets, scale to ``h200x4`` and raise
+``--vlm.parallel_servers`` / ``--vlm.num_gpus`` to match.
 """
 
 import os
@@ -29,7 +45,7 @@ if not token:
 CMD = (
     "apt-get update -qq && apt-get install -y -qq git ffmpeg && "
     "pip install --no-deps "
-    "'lerobot @ git+https://github.com/huggingface/lerobot.git@feat/language-annotation-pipeline' && "
+    "'lerobot @ git+https://github.com/huggingface/lerobot.git@main' && "
     "pip install --upgrade-strategy only-if-needed "
     "datasets pyarrow av jsonlines draccus gymnasium torchcodec mergedeep pyyaml-include toml typing-inspect "
     "openai && "
@@ -37,12 +53,12 @@ CMD = (
     "export VLLM_VIDEO_BACKEND=pyav && "
     "lerobot-annotate "
     "--repo_id=pepijn223/robocasa_pretrain_human300_v4 "
-    "--dest_repo_id=pepijn223/robocasa_pretrain_human300_v4_annotated5 "
+    "--new_repo_id=pepijn223/robocasa_pretrain_human300_v4_annotated5 "
     "--push_to_hub=true "
     "--vlm.backend=openai "
     "--vlm.model_id=Qwen/Qwen3.6-27B "
-    "--vlm.parallel_servers=4 "
-    "--vlm.num_gpus=4 "
+    "--vlm.parallel_servers=1 "
+    "--vlm.num_gpus=1 "
     '--vlm.serve_command="vllm serve Qwen/Qwen3.6-27B '
     "--tensor-parallel-size 1 --max-model-len 32768 "
     '--gpu-memory-utilization 0.8 --uvicorn-log-level warning --port {port}" '
@@ -111,7 +127,7 @@ CMD = (
 job = run_job(
     image="vllm/vllm-openai:latest",
     command=["bash", "-c", CMD],
-    flavor="h200x4",
+    flavor="h200",
     secrets={"HF_TOKEN": token},
     timeout="2h",
 )