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b71e10da6b
PR 2 used to write a top-level ``tools`` column on every parquet shard holding the JSON schema for the ``say`` tool, broadcast identically across every row. That extends PR 1's schema for no real information gain — the schema is a fixed code constant, parquet's RLE/dict encoding collapses it on disk anyway, and HF/TRL chat-template consumers can just import the constant directly. PR 2 should fill in PR 1's existing schema, not add to it. So: - ``writer.py``: stop emitting the ``tools`` column. Strip any legacy ``tools`` column from older shards on rerun so the schema converges to v3.1. ``SAY_TOOL_SCHEMA`` stays as a public constant (now joined by ``DEFAULT_TOOLS = [SAY_TOOL_SCHEMA]``); chat-template policies and the visualizer import them directly. - ``test_writer.py``: replace the "tools column present" assertion with one that explicitly checks the column is absent, plus a new test asserting the constant's shape. - ``test_pipeline_recipe_render.py``: drop the tools-column read; assert it's not present in the rewritten parquet. - ``annotation_pipeline.mdx``: update the writer description to note the parquet stays small and the schema lives as a code constant. If multi-tool-set support ever becomes real (datasets with different tool inventories), the right home is ``meta/info.json["tools"]`` — adding it later is non-breaking; ripping out a parquet column already shipped is not. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
299 lines
11 KiB
Python
299 lines
11 KiB
Python
#!/usr/bin/env python
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# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Writer correctness tests."""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pyarrow.parquet as pq
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import pytest
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from lerobot.annotations.steerable_pipeline.reader import iter_episodes
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from lerobot.annotations.steerable_pipeline.staging import EpisodeStaging
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from lerobot.annotations.steerable_pipeline.writer import (
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LanguageColumnsWriter,
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speech_atom,
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)
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def _stage_episode(
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staging_dir: Path,
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episode_index: int,
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*,
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module_1: list[dict] | None = None,
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module_2: list[dict] | None = None,
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module_3: list[dict] | None = None,
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) -> None:
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staging = EpisodeStaging(staging_dir, episode_index)
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if module_1 is not None:
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staging.write("module_1", module_1)
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if module_2 is not None:
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staging.write("module_2", module_2)
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if module_3 is not None:
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staging.write("module_3", module_3)
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def test_writer_persistence_identity(fixture_dataset_root: Path, tmp_path: Path) -> None:
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"""Every frame in an episode has a byte-identical persistent list."""
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staging_dir = tmp_path / "stage"
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_stage_episode(
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staging_dir,
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0,
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module_1=[
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{
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"role": "assistant",
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"content": "grasp the sponge",
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"style": "subtask",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": "1. wipe\n2. dry",
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"style": "plan",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": "wiped the counter",
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"style": "memory",
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"timestamp": 0.5,
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"tool_calls": None,
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},
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],
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)
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records = list(iter_episodes(fixture_dataset_root))
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LanguageColumnsWriter().write_all(records, staging_dir, fixture_dataset_root)
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table = pq.read_table(fixture_dataset_root / "data" / "chunk-000" / "file-000.parquet")
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persistent = table.column("language_persistent").to_pylist()
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first = persistent[0]
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assert first # non-empty
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for row in persistent:
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assert row == first, "persistent slice must be byte-identical across all frames"
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def test_writer_events_exact_timestamp(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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_stage_episode(
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staging_dir,
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0,
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module_2=[
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speech_atom(0.0, "Got it."),
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{
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"role": "user",
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"content": "skip the dishes",
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"style": "interjection",
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"timestamp": 0.5,
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"tool_calls": None,
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},
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speech_atom(0.5, "Skipping the dishes."),
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],
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)
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records = list(iter_episodes(fixture_dataset_root))
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LanguageColumnsWriter().write_all(records, staging_dir, fixture_dataset_root)
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table = pq.read_table(fixture_dataset_root / "data" / "chunk-000" / "file-000.parquet")
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timestamps = table.column("timestamp").to_pylist()
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events = table.column("language_events").to_pylist()
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for ts, ev in zip(timestamps, events, strict=True):
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if abs(ts - 0.0) < 1e-9:
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assert any(r["role"] == "assistant" and r.get("style") is None for r in ev), ev
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elif abs(ts - 0.5) < 1e-9:
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assert any(r.get("style") == "interjection" for r in ev), ev
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assert any(r.get("style") is None for r in ev), ev
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else:
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assert ev == []
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def test_writer_column_routing(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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_stage_episode(
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staging_dir,
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0,
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module_1=[
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{
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"role": "assistant",
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"content": "do X",
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"style": "subtask",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": "1. do X",
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"style": "plan",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": "did X",
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"style": "memory",
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"timestamp": 0.3,
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"tool_calls": None,
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},
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],
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module_2=[
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speech_atom(0.0, "OK"),
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{
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"role": "user",
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"content": "wait",
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"style": "interjection",
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"timestamp": 0.2,
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"tool_calls": None,
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},
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speech_atom(0.2, "Waiting"),
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],
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module_3=[
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{
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"role": "user",
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"content": "where is the cup?",
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"style": "vqa",
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"timestamp": 0.4,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": json.dumps(
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{"detections": [{"label": "cup", "bbox_format": "xyxy", "bbox": [1, 2, 3, 4]}]},
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sort_keys=True,
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),
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"style": "vqa",
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"timestamp": 0.4,
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"tool_calls": None,
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},
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],
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)
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records = list(iter_episodes(fixture_dataset_root))
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LanguageColumnsWriter().write_all(records, staging_dir, fixture_dataset_root)
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table = pq.read_table(fixture_dataset_root / "data" / "chunk-000" / "file-000.parquet")
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persistent = table.column("language_persistent").to_pylist()[0]
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persistent_styles = {r["style"] for r in persistent}
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assert persistent_styles == {"subtask", "plan", "memory"}
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all_events = [r for ev in table.column("language_events").to_pylist() for r in ev]
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event_styles = {r.get("style") for r in all_events}
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assert event_styles == {None, "interjection", "vqa"}
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def test_writer_drops_subtask_index_idempotent(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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_stage_episode(
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staging_dir,
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0,
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module_1=[
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{
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"role": "assistant",
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"content": "do X",
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"style": "subtask",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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],
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)
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records = list(iter_episodes(fixture_dataset_root))
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writer = LanguageColumnsWriter()
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writer.write_all(records, staging_dir, fixture_dataset_root)
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path = fixture_dataset_root / "data" / "chunk-000" / "file-000.parquet"
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table_a = pq.read_table(path)
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assert "subtask_index" not in table_a.column_names
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assert "language_persistent" in table_a.column_names
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assert "language_events" in table_a.column_names
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# The writer no longer emits a dataset-level ``tools`` column; the
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# ``say`` tool schema lives as a code constant (``SAY_TOOL_SCHEMA``)
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# so the parquet stays small and PR 2 doesn't extend PR 1's schema.
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assert "tools" not in table_a.column_names
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# second pass — must produce identical bytes for the language columns
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records_again = list(iter_episodes(fixture_dataset_root))
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writer.write_all(records_again, staging_dir, fixture_dataset_root)
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table_b = pq.read_table(path)
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assert (
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table_a.column("language_persistent").to_pylist() == table_b.column("language_persistent").to_pylist()
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)
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assert table_a.column("language_events").to_pylist() == table_b.column("language_events").to_pylist()
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def test_writer_normalize_rejects_misrouted_persistent_style() -> None:
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"""``_normalize_persistent_row`` must reject any non-persistent style."""
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from lerobot.annotations.steerable_pipeline.writer import _normalize_persistent_row
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with pytest.raises(ValueError, match="non-persistent style"):
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_normalize_persistent_row(
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{"role": "assistant", "content": "oops", "style": "vqa", "timestamp": 0.0, "tool_calls": None}
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)
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def test_writer_normalize_rejects_misrouted_event_style() -> None:
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"""``_normalize_event_row`` must reject any persistent style."""
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from lerobot.annotations.steerable_pipeline.writer import _normalize_event_row
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with pytest.raises(ValueError):
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_normalize_event_row({"role": "assistant", "content": "oops", "style": "subtask", "tool_calls": None})
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def test_say_tool_schema_constant_is_well_formed() -> None:
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"""``SAY_TOOL_SCHEMA`` (and ``DEFAULT_TOOLS``) replace the parquet
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``tools`` column — chat-template consumers import them directly.
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"""
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from lerobot.annotations.steerable_pipeline.writer import (
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DEFAULT_TOOLS,
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SAY_TOOL_SCHEMA,
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)
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assert DEFAULT_TOOLS == [SAY_TOOL_SCHEMA]
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assert SAY_TOOL_SCHEMA["function"]["name"] == "say"
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params = SAY_TOOL_SCHEMA["function"]["parameters"]
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assert params["properties"]["text"]["type"] == "string"
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assert params["required"] == ["text"]
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def test_writer_does_not_add_tools_column(fixture_dataset_root: Path, tmp_path: Path) -> None:
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"""Re-running on a parquet that already has a legacy ``tools`` column
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must drop it cleanly so reruns converge to the v3.1 schema.
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"""
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staging_dir = tmp_path / "stage"
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_stage_episode(
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staging_dir,
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0,
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module_1=[
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{"role": "assistant", "content": "x", "style": "subtask", "timestamp": 0.0, "tool_calls": None}
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],
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)
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records = list(iter_episodes(fixture_dataset_root))
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LanguageColumnsWriter().write_all(records, staging_dir, fixture_dataset_root)
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table = pq.read_table(fixture_dataset_root / "data" / "chunk-000" / "file-000.parquet")
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assert "tools" not in table.column_names
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def test_speech_atom_shape_matches_plan_spec() -> None:
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atom = speech_atom(2.5, "I'm cleaning up!")
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assert atom["role"] == "assistant"
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assert atom["style"] is None
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assert atom["content"] is None
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assert atom["timestamp"] == 2.5
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assert isinstance(atom["tool_calls"], list)
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call = atom["tool_calls"][0]
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assert call["type"] == "function"
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assert call["function"]["name"] == "say"
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assert call["function"]["arguments"]["text"] == "I'm cleaning up!"
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