---
pretty_name: MAGAR-Bench (Test inputs)
license: cc-by-nc-4.0
task_categories:
- visual-question-answering
tags:
- multimodal
- gui-agents
- 3d-mechanical-assembly
- minimal-rework
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: test
    path: test.jsonl
---

# MAGAR-Bench — Test inputs

This repository distributes only the public Test inputs of MAGAR-Bench:
**1,000 samples, six assembly families, and 1,140 unique PNG files**.
The paper's full benchmark contains 4,000 samples (3,000 Train and 1,000 Test);
the Train split is not included in this release.

| Task family | Test samples |
|---|---:|
| Assembly Decision | 238 |
| Atomic Action | 662 |
| Minimal Rework | 100 |
| Total | 1,000 |

The six Test families are `gearbox_structure`, `luban_12_pillars`,
`parametric_box_lock_01`, `parametric_tower_lock_10`,
`spherical_interlocking_structure`, and `triangle_dovetail_structure`.
They are disjoint from the original Train families.

## Contents

All upload files are at the repository root; there is no need to drag thousands
of image files into the web uploader.

| File | Purpose |
|---|---|
| `test.jsonl` | 1,000 Test inputs; no assistant messages or reference answers |
| `images.zip` | Exactly the 1,140 PNG files referenced by Test; paths start with `images/` |
| `image_manifest.json` | SHA-256 and byte size of each archived image |
| `schema.json`, `task_contract.md` | Input fields and model output contracts |
| `release_manifest.json` | Release version, counts, source hash and export changes |
| `load_test.py` | Standard-library loader with validated image extraction |
| `verify_release.py` | Record, archive, boundary and checksum validation |
| `LICENSE`, `ASSET_LICENSE.md` | License scope and image/Unity rights status |
| `MANIFEST.sha256` | Checksums of the shipped files |

## Load a downloaded repository

Python 3.11 or newer is required; no third-party packages are needed:

```bash
python verify_release.py
python load_test.py
```

The loader extracts the image archive into a temporary cache outside the
repository and resolves each record's image paths. To choose a persistent
cache location:

```bash
python load_test.py --extract-dir ../magar_test_image_cache
```

From Python, with this repository on the module search path:

```python
from load_test import load_test

records = load_test()
sample = records[0]
messages = sample["messages"]  # public user prompt, in original order
image_paths = sample["images"]  # absolute paths to extracted PNG files
```

Alternatively, read the table using Hugging Face Datasets:

```python
from datasets import load_dataset
ds = load_dataset("json", data_files={"test": "test.jsonl"})
```

This last example loads only the table. It does not download/extract the image
archive. Image paths in `test.jsonl` are relative to the archive extraction
directory. The Dataset Viewer is configured for the Test table; image path
strings are not embedded Image features and do not provide inline image
previews. Extract `images.zip` before using the PNG files locally.

## Evaluation boundary

Reference answers, locked Test gold, training records, human-evaluation
records, LLM-as-Judge outputs and experimental results are not included.
`verify_release.py` checks release integrity; it is not a benchmark scorer.
This package alone cannot compute answer-based benchmark scores; scoring
requires the separately maintained private references and evaluator.

Use the user messages and images as model inputs. Metadata is for indexing and
analysis. Predict one JSON object per sample according to `task_contract.md`.

## Version and provenance

Release `magar-bench-test-inputs-v1` is a separately versioned public export
of the frozen hardened-v3 Test inputs. Sample IDs, row order, user messages,
image order and image bytes are preserved. It is not a new benchmark split.

Metadata is reduced to the allowlist in `schema.json`. The export removes
semantic high-level task IDs, internal provenance paths, reviewer fields and
construction/audit flags. Removed-field counts are recorded in
`release_manifest.json`. This is an explicit export change; the original
frozen source files remain unchanged.

Some legacy Assembly Decision prompts mention `high_level_task_id` before a
later explicit vocabulary clause excludes it. The three output keys in
`task_contract.md` and that later clause are authoritative. We preserve the
original user messages and document this inconsistency rather than silently
rewriting the frozen prompts.

## License and attribution

Dataset content and cleared images use CC BY-NC 4.0; original Python helpers
use Apache-2.0. See `LICENSE` and `ASSET_LICENSE.md`. Asset ownership and
third-party redistribution clearance are not established by an integrity
check. The inherited maintainer asset attestation remains pending.

The associated manuscript is **MAGAG Multimodal Agents for GUI-Based 3D
Mechanical Assembly and Minimal Rework**. A verified author list and public
paper identifier were not available during this export; no arXiv identifier
or author citation is asserted here.