feat: add skip.when conditional column generation by nabinchha · Pull Request #502 · NVIDIA-NeMo/DataDesigner

nabinchha · 2026-04-07T17:36:01Z

Summary

Adds per-row conditional column generation via SkipConfig(when="..."). Columns can now be skipped based on a Jinja2 expression evaluated against the current row, with automatic downstream propagation and an opt-out mechanism. This avoids expensive LLM calls for rows that don't need a particular column (e.g., complaint analysis only for low-rated reviews).

Changes

Added

SkipConfig model on SingleColumnConfig — skip=SkipConfig(when="{{ expr }}") with configurable value and propagate_skip flag
skip_evaluator.py — NativeSandboxedEnvironment for safe expression evaluation with StrictUndefined, plus should_skip_by_propagation for upstream skip detection
skip_tracker.py — centralized __internal_skipped_columns metadata management on record dicts (apply, read, strip before DataFrame/parquet, round-trip preservation via restore IDs)
test_skip_config.py, test_skip_evaluator.py, test_skip_tracker.py — unit tests for config validation, expression evaluation, and tracker logic
Validation rules: SkipConfig rejected on sampler/seed-dataset columns, rejected with allow_resize, and self-referencing when expressions are caught
validate_skip_references in validation.py — checks skip.when column references exist, rejects skip on sampler/seed and allow_resize columns

Changed

Sequential engine (dataset_builder.py): _run_full_column_generator now splits into skip-aware and non-skip-aware paths; fan-out methods (_fan_out_with_threads, _fan_out_with_async) evaluate skip per-record, exclude skipped rows from generator input, and merge results back with skip metadata preserved. _column_can_skip fast-path short-circuits when no skip config or propagation applies. Skip metadata is preserved across replace_buffer via prepare_records_for_skip_metadata_round_trip / restore_skip_metadata restore-ID mechanism.
Async engine (async_scheduler.py): _run_cell returns (result, skipped) tuple; _run_batch pre-evaluates skip before building the batch DataFrame; skipped cells report as skipped in progress tracking
DAG (dag.py): skip.when column references added as dependency edges; refactored edge-building into shared _add_dependency_edges helper
ExecutionGraph (execution_graph.py): stores SkipConfig, propagate_skip, required_columns, and side_effects_by_producer per column with accessor methods (get_skip_config, should_propagate_skip, get_required_columns, get_side_effect_columns)
DatasetBatchManager and RowGroupBufferManager: strip __internal_skipped_columns metadata before DataFrame construction and parquet writes
Tutorial notebook (2-structured-outputs-and-jinja-expressions): added conditional generation section demonstrating all three skip patterns (expression gate, propagation, opt-out)
Architecture docs (dataset-builders.md): documented conditional generation subsystem
mkdocs.yml and notebook README: updated tutorial title to include "Conditional Generation"

Fixed

_run_full_column_generator now correctly preserves row ordering when merging skipped and generated records back together (8931b45)
_column_can_skip returns False for allow_resize=True columns to prevent row-count mismatches in the skip-aware merge path

Attention Areas

Reviewers: Please pay special attention to the following:

dataset_builder.py — The skip-aware split/merge in _run_full_column_generator_with_skip and the restore-ID mechanism in _run_full_column_generator_without_skip that preserves skip metadata across DataFrame round-trips
async_scheduler.py — _run_batch now pre-evaluates skip before building the batch DataFrame; _run_cell returns a (result, skipped) tuple
skip_evaluator.py — Fail-safe behavior (skip on evaluation error) is intentional to avoid wasting LLM calls on ambiguous rows
skip_tracker.py — The prepare_records_for_skip_metadata_round_trip / restore_skip_metadata pair uses hidden restore-ID columns to survive DataFrame round-trips where row order or count may change

Description updated with AI

Adds implementation plan for a `skip_when` field on `SingleColumnConfig` that enables conditional column generation. When the Jinja2 expression evaluates truthy, the cell is set to None and the generator is skipped. Skips auto-propagate through the DAG to downstream columns. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

…e propagation - Introduce SkipConfig(when, value) as nested model on SingleColumnConfig - Move propagate_skip to SingleColumnConfig as independent field, fixing bug where columns with no SkipConfig couldn't participate in propagation - Add full sync engine implementation (Steps 4a-4d) covering both _fan_out_with_threads and _run_full_column_generator dispatch paths - Add serialization boundary stripping for both DatasetBatchManager (sync) and RowGroupBufferManager (async) - Simplify architecture diagrams for readability - Update all references, design decisions, verification plan Made-with: Cursor

- Explain why propagation must not use get_upstream_columns() once skip.when adds DAG edges; add _required_columns and get_required_columns() to the execution graph plan - Point async _run_cell at get_required_columns for parity with sync - Clarify DropSkippedRowsProcessorConfig vs stripping __skipped__ for DataFrames; tighten resolved-questions wording - Extend DAG/graph verification with gating_col regression case Refs #479 Made-with: Cursor

- Document new skip_provenance.py (key constant, read/write/strip API) - Point sync builder, async scheduler, and batch buffers at shared helpers - Strip metadata before every DataFrame from buffer dicts, including FULL_COLUMN active subsets - Split §3 into skip_evaluator vs skip_provenance; extend verification Refs #479 Made-with: Cursor

Drop legacy skip_when naming in headings and #362 cross-reference. Refs #479 Made-with: Cursor

…ng, caller-owns-deserialization - SkipConfig._validate_when_syntax now checks find_undeclared_variables is non-empty, rejecting expressions without {{ }} delimiters that would silently skip every row - evaluate_skip_when centralizes try/except so both sync and async engines get identical fail-safe behavior on eval errors - evaluate_skip_when takes a single pre-deserialized record; caller runs deserialize_json_values once and passes to both skip eval and generator (no double deserialization, no redundant parameter) - Update _should_skip_cell, async _run_cell, Files Modified table, and verification section accordingly Refs #479 Made-with: Cursor

Document _side_effects_by_producer inverse map and get_side_effect_columns() accessor on ExecutionGraph, needed by _write_skip_to_record / apply_skip_to_record to clear __trace, __reasoning_content, etc. on skip. Added to both Step 2b metadata section and Files Modified table. The __skipped__ leak into active_df (greptile's other P1) was already fixed in 7046378 via strip_skip_metadata_from_records. Refs #479 Made-with: Cursor

…479-skip-conditional-gen-implementation

Introduce SkipConfig on SingleColumnConfig to gate column generation with a Jinja2 expression. Columns can be skipped by expression or by upstream propagation (propagate_skip flag). - SkipConfig: Pydantic model with config-time syntax/delimiter/variable validation and cached column extraction from the Jinja2 AST - skip_evaluator: runtime expression evaluation via NativeSandboxedEnvironment with fail-safe error handling (skip on expected failures) - skip_provenance: centralized __skipped__ record tracking shared by sync builder, async scheduler, and buffer managers - DAG/ExecutionGraph: skip.columns wired as dependency edges in both topological sort and static execution graph - Validation: validate_skip_references checks reference existence, sampler/seed scope, and allow_resize conflicts - Sync builder: cell-by-cell and full-column skip with merge-back - Async scheduler: cell and batch skip with live-buffer provenance Made-with: Cursor

…ementation

- Add skip evaluation to _fan_out_with_async (was missing, causing skipped rows to still be sent to the LLM) - Preserve __skipped__ provenance on non-skipped records after full-column generation so multi-hop propagation works - Use single live-buffer reference in _run_batch skip loop for consistency with _run_cell - Move Template import to TYPE_CHECKING and reorder import blocks - Replace O(n²) sum() with itertools.chain in dag.py - Add set_required_columns/set_propagate_skip/set_skip_config setters to ExecutionGraph for symmetry with existing API Made-with: Cursor

Add a new recipe demonstrating skip.when patterns (expression gate, propagation, opt-out) with a customer support ticket pipeline. Also extract _should_skip_record in async_scheduler, remove the redundant propagate_skip param from should_skip_by_propagation, and pass a precomputed all_side_effects set through the DAG sort. Made-with: Cursor

Return False when the graph has not been initialized instead of raising, since skip logic cannot apply before generators are set up. Made-with: Cursor

…ementation

greptile-apps · 2026-04-07T18:19:36Z

Greptile Summary

This PR adds per-row conditional column generation via SkipConfig(when="..."), covering three paths (expression gate, upstream propagation, opt-out via propagate_skip=False) across both the sync and async engines. The core design — inline __internal_skipped_columns metadata on record dicts, restore-ID round-trip preservation, NativeSandboxedEnvironment for safe evaluation, and DAG edges for skip dependencies — is sound and well-tested.

Confidence Score: 4/5

Safe to merge with two minor issues worth addressing: a no-op redundant call and a positional-merge gap in the skip-aware full-column path.

No P0/P1 correctness bugs found. The two P2 findings are: (1) _merge_skipped_and_generated aligns generator output positionally while its sibling _run_full_column_generator_without_skip uses restore IDs — a subtle inconsistency that could misassign results if a generator reorders rows without allow_resize=True; (2) update_record in the fan-out skip paths is a no-op since iter_current_batch yields live buffer references. Neither blocks merge but both are worth addressing.

dataset_builder.py — specifically _merge_skipped_and_generated (positional merge) and _fan_out_with_threads/_fan_out_with_async (redundant update_record).

Important Files Changed

Filename	Overview
packages/data-designer-config/src/data_designer/config/base.py	Adds `SkipConfig` model with Jinja2 syntax validation, `columns` cached_property for AST-based variable extraction, and `propagate_skip` field on `SingleColumnConfig`; model validator correctly blocks self-references, sampler/seed columns, and allow_resize combinations.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/skip_evaluator.py	New file implementing `NativeSandboxedEnvironment` (correct MRO combining sandbox + native-type output), `evaluate_skip_when` with fail-safe semantics, and `should_skip_column_for_record` unified decision function; LRU-cached template compilation is a sound optimization.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/skip_tracker.py	New file implementing the `__internal_skipped_columns` metadata lifecycle (apply, strip for DataFrame, restore via hidden ID columns); restore-ID mechanism correctly handles row reordering and allow_resize cases with proper bijection validation.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/dataset_builder.py	Splits `_run_full_column_generator` into skip-aware and non-skip-aware paths; fan-out methods gain per-row skip evaluation; key issue: `_merge_skipped_and_generated` uses positional merge (no restore IDs) while the sibling without-skip path is reorder-safe, and `update_record` in fan-out skip paths is a no-op.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/async_scheduler.py	`_run_cell` and `_run_batch` gain skip-aware paths; cell skip writes directly to live buffer references (correct), batch skip pre-evaluates before building the DataFrame; `result_idx` alignment with `pre_skipped` rows is handled correctly.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/execution_graph.py	Stores `SkipConfig`, `propagate_skip`, `required_columns`, and `side_effects_by_producer` per column with clean accessor methods; `set_required_columns` correctly stores producer-resolved dependencies only.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/dag.py	Refactors edge-building into `_add_dependency_edges` helper and correctly adds skip.when column references as DAG edges; `all_side_effects` pre-computation avoids repeated flattening.
packages/data-designer-engine/src/data_designer/engine/validation.py	Adds `validate_skip_references` covering reference existence, sampler/seed scope, and allow_resize conflicts; the sampler/seed and allow_resize checks are defense-in-depth (model validators fire first) which is acceptable.
packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/dataset_batch_manager.py	Correctly strips skip metadata from `get_current_batch(as_dataframe=True)` and the parquet write path; `iter_current_batch` intentionally yields live buffer references (enabling in-place mutation by skip writers).
packages/data-designer-config/src/data_designer/config/column_configs.py	Adds `_coerce_skip_value_to_dtype` validator on `ExpressionColumnConfig` that mutates `skip.value` via Pydantic's non-frozen attribute assignment; bool/int subclass edge case (`isinstance(True, int)` is True) is minor and unlikely to matter in practice.

Flowchart

%%{init: {'theme': 'neutral'}}%%
flowchart TD
    A["_run_full_column_generator(generator)"] --> B{column_name != None\nAND _column_can_skip?}
    B -- "No (MultiColumnConfig\nor allow_resize=True)" --> C["_run_full_column_generator_without_skip"]
    B -- Yes --> D["_run_full_column_generator_with_skip"]

    C --> C1["prepare_records_for_skip_metadata_round_trip\n(injects restore IDs if skip metadata present)"]
    C1 --> C2["generator.generate(full_df)"]
    C2 --> C3["restore_skip_metadata via restore IDs\n(reorder-safe)"]
    C3 --> C4["batch_manager.replace_buffer"]

    D --> D1["Iterate all records\nevaluate _should_skip_cell per row"]
    D1 --> D2{any row skipped?}
    D2 -- No --> C
    D2 -- Yes --> D3["_merge_skipped_and_generated\n(positional merge — assumes generator\npreserves row order)"]
    D3 --> D4["generator.generate(active_rows_only)"]
    D4 --> D5["Merge: skipped rows keep record ref\nactive rows use gen_result + copy prior_skipped"]
    D5 --> D6["batch_manager.replace_buffer"]

    style D3 fill:#fff3cd,stroke:#856404

Prompt To Fix All With AI

This is a comment left during a code review.
Path: packages/data-designer-engine/src/data_designer/engine/dataset_builders/dataset_builder.py
Line: 615-641

Comment:
**Positional merge in skip path diverges from restore-ID safety in no-skip path**

`_merge_skipped_and_generated` aligns generator output with `records_with_skip_status` by position (`next(result_iter)`). `_run_full_column_generator_without_skip` — the sibling path for the same generator — now uses restore IDs to handle row reordering across the DataFrame round-trip. The skip path gets no such safety net: if a FULL_COLUMN generator returns rows in a different order than it received them (e.g., a sorting step inside the generator) without `allow_resize=True`, the active-row results are silently assigned to the wrong rows.

The `_run_full_column_generator_without_skip` path already demonstrates how to handle this correctly with `prepare_records_for_skip_metadata_round_trip` / `restore_skip_metadata`. The same restore-ID mechanism could be applied to `active_records` in `_merge_skipped_and_generated` to keep both paths equally robust.

How can I resolve this? If you propose a fix, please make it concise.

---

This is a comment left during a code review.
Path: packages/data-designer-engine/src/data_designer/engine/dataset_builders/dataset_builder.py
Line: 775-789

Comment:
**`update_record` call is a no-op after in-place mutation**

`iter_current_batch()` yields direct references to `self._buffer[i]` (via `enumerate(self._buffer)`). `_write_skip_to_record(column_name, record)` mutates that dict in-place, so `self._buffer[i]` already reflects the skip metadata before `update_record` is called. The subsequent `self.batch_manager.update_record(i, record)` executes `self._buffer[i] = record`, which just re-assigns the same reference — a no-op. Same pattern appears in `_fan_out_with_async` at the corresponding location.

How can I resolve this? If you propose a fix, please make it concise.

_{Reviews (11): Last reviewed commit: "fix: make expression jinja validator pri..." | Re-trigger Greptile}

nabinchha · 2026-04-08T15:47:57Z

Both P1s from Greptile's review are addressed in 1affce9:

P1: Skip metadata erased by non-skip-aware replace_buffer calls

Added restore_skip_metadata() helper in skip_tracker.py that re-attaches __internal_skipped_columns after df.to_dict(orient="records") strips it. Applied in all replace_buffer paths (MultiColumnConfig, non-skip-aware, has_skipped=False fallthrough). Refactored _run_full_column_generator into three focused methods to eliminate the duplication.

P1: allow_resize=True columns enter skip branch via propagation

_column_can_skip now returns False for allow_resize=True columns, so they never enter the skip-aware merge path (option (a) — the column runs the normal generation path regardless of upstream skips).

Tests added:

test_skip_metadata_preserved_across_non_skip_aware_full_column — interleaved independent FULL_COLUMN between skip-setting and propagating columns
test_skip_metadata_preserved_when_no_rows_skipped_for_current_column — has_skipped=False fallthrough preserves sibling metadata
test_allow_resize_column_not_blocked_by_upstream_skip — 1:N generator with skippable upstream
Unit tests for restore_skip_metadata in test_skip_tracker.py

…ementation

github-actions · 2026-04-09T15:43:15Z

Docs preview: https://c435f332.dd-docs-preview.pages.dev

Notebook tutorials are placeholder-only in previews.

andreatgretel · 2026-04-10T13:22:16Z

the skip integration tests in test_dataset_builder.py all run through the sync engine. might be good to add at least one that flips DATA_DESIGNER_ASYNC_ENGINE=1 to exercise the async _run_cell / _run_batch skip paths, since the buffer management model is different

- Extract shared skip decision logic (_should_skip_cell / _should_skip_record) into should_skip_column_for_record() in skip_evaluator.py so both sync and async engines call the same function (andreatgretel review comment) - Extend SkipConfig self-reference validation to cover side-effect columns (e.g. review__trace on the review column) — previously only checked self.name, now checks self.name | self.side_effect_columns - Add async engine integration tests for skip paths: cell-by-cell with propagation and full-column batch skip (exercises _run_cell / _run_batch) - Fix test_allow_resize_column_not_blocked_by_upstream_skip to use default propagate_skip=True so it actually exercises the allow_resize guard - Move get_skipped_column_names from skip_tracker to skip_evaluator (sole production consumer) Made-with: Cursor

nabinchha · 2026-04-10T16:40:50Z

Done in bf6332e — added two async engine skip tests in test_async_scheduler.py: test_scheduler_skip_cell_by_cell_with_propagation (exercises _run_cell skip + downstream propagation) and test_scheduler_skip_full_column_batch (exercises _run_batch skip with active/skipped row splitting). Both use a buffer manager so the skip metadata write-back path is covered.

…ementation

andreatgretel · 2026-04-13T17:30:03Z

+# |---|---|---|
+# | **Expression gate** | `skip=dd.SkipConfig(when="...")` | Skip this column when the Jinja2 expression is truthy |
+# | **Skip propagation** (default) | Downstream column depends on a skipped column | Automatically skipped too (`propagate_skip=True` by default) |
+# | **Propagation opt-out** | `propagate_skip=False` on the downstream column | Always generates, even if an upstream was skipped |


nice examples. small nit: "Always generates" might be a touch too strong - if the column's own skip.when references an upstream value that got skipped (now None), the evaluator's fail-safe kicks in and skips the row anyway. maybe "generates even when upstream columns were skipped" would be more accurate?

andreatgretel

looking good, approving with nits. I think greptile's comment about allow_resize columns entering the skip branch via propagation is still open and worth addressing before merge.

- test_skip_evaluator: parametrized should_skip_column_for_record covering propagation, expression gates, short-circuiting, and disabled propagation - test_execution_graph: skip metadata accessors (get_skip_config, should_propagate_skip, get_required_columns, get_side_effect_columns, resolve_side_effect, skip.when DAG edges) - test_dataset_builder: chained transitive propagation (4 levels), two independent skip gates, custom skip.value, row count preservation Made-with: Cursor

…ementation

…ip-conditional-gen-implementation Made-with: Cursor # Conflicts: # packages/data-designer-engine/src/data_designer/engine/dataset_builders/async_scheduler.py # packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/execution_graph.py

Rename assert_expression_valid_jinja to _assert_expression_valid_jinja to match the private naming convention used by other model validators. Made-with: Cursor

nabinchha and others added 21 commits March 30, 2026 14:19

plan: remove HopChain example from skip_when plan

3f415c7

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

plan: replace HopChain example with generic product review example

6ee4c70

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

plan: add open questions on skip sentinel value and row filtering

14ab39b

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Merge branch 'main' into nmulepati/feat/479-skip-when-plan

b481e73

updates

2219cd6

plan: align doc title with SkipConfig / skip.when

a157a7f

Drop legacy skip_when naming in headings and #362 cross-reference. Refs #479 Made-with: Cursor

Merge branch 'nmulepati/feat/479-skip-when-plan' into nmulepati/feat/…

d9e3f2d

…479-skip-conditional-gen-implementation

Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

8ceb76e

…ementation

updates

2c6cb3d

fixes

875b4bc

remove recipe > inject conditional gen into existing tutorial

c1aa139

regen colab notebooks

569fb16

nabinchha requested a review from a team as a code owner April 7, 2026 17:36

nabinchha added 6 commits April 7, 2026 11:48

fix: handle missing execution graph in _column_can_skip

8fceabe

Return False when the graph has not been initialized instead of raising, since skip logic cannot apply before generators are set up. Made-with: Cursor

Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

cbe76a4

…ementation

parametrize some tests

634901e

public before private

4948fe2

slight refactor for readability

4d04842

parametrize some tests

a5b905e

greptile-apps bot reviewed Apr 7, 2026

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Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

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…ementation

nabinchha mentioned this pull request Apr 8, 2026

refactor: unify duplicate DAG construction (dag.py + ExecutionGraph) #511

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Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

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andreatgretel reviewed Apr 10, 2026

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Comment thread packages/data-designer-engine/src/data_designer/engine/dataset_builders/dataset_builder.py

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Comment thread packages/data-designer-engine/src/data_designer/engine/dataset_builders/utils/skip_evaluator.py

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nabinchha requested a review from andreatgretel April 10, 2026 16:44

nabinchha added 3 commits April 10, 2026 10:45

Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

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…ementation

address cr feedback

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Fix issue with full column generating messing up order of skipped rows

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nabinchha dismissed andreatgretel’s stale review via 4bc63b8 April 13, 2026 19:46

nabinchha requested a review from andreatgretel April 13, 2026 20:33

Merge branch 'main' into nmulepati/feat/479-skip-conditional-gen-impl…

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nabinchha added 2 commits April 14, 2026 15:30

fix: make expression jinja validator private

efbd5fe

Rename assert_expression_valid_jinja to _assert_expression_valid_jinja to match the private naming convention used by other model validators. Made-with: Cursor

nabinchha dismissed stale reviews from johnnygreco and andreatgretel via efbd5fe April 14, 2026 21:32

andreatgretel approved these changes Apr 14, 2026

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nabinchha merged commit a9af365 into main Apr 15, 2026
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nabinchha deleted the nmulepati/feat/479-skip-conditional-gen-implementation branch April 15, 2026 15:31

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feat: add skip.when conditional column generation#502

feat: add skip.when conditional column generation#502
nabinchha merged 44 commits intomainfrom
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