| --- |
| pretty_name: OpenVisTool-42K |
| license: other |
| task_categories: |
| - image-text-to-text |
| language: |
| - en |
| tags: |
| - multimodal |
| - tool-use |
| - agentic-vision |
| - visual-reasoning |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/*.jsonl |
| --- |
| |
| # OpenVisTool-42K |
|
|
| OpenVisTool-42K contains 42,048 outcome-valid, tool-use-gain-filtered visual |
| tool-use trajectories across Chart, GUI Grounding, Table, Web-to-HTML, and |
| Visual Search. Each example preserves the teacher's reasoning, function calls, |
| tool observations, and final answer in the ms-swift agent format. All trajectories were synthesized using Qwen3.5-Plus |
| as the teacher model. The teacher generated the reasoning traces, function |
| calls, and final answers, while tool observations were obtained by executing |
| the corresponding tools. This dataset accompanies [OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories](https://arxiv.org/abs/2608.08557). |
|
|
| ## Record schema |
|
|
| Every line is one JSON object: |
|
|
| ```json |
| { |
| "id": "chart-00000000", |
| "domain": "Chart", |
| "tools": "[{\"type\":\"function\",...}]", |
| "messages": [ |
| {"role": "system", "content": "..."}, |
| {"role": "user", "content": "<image>\n..."}, |
| {"role": "assistant", "content": "<think>...</think>"}, |
| {"role": "tool_call", "content": "{\"name\":\"crop\",...}"}, |
| {"role": "tool_response", "content": "<image>\n..."} |
| ], |
| "images": ["images/chart/ab/ab...ef.jpg"] |
| } |
| ``` |
|
|
| - `id`: stable ID derived from the row index in the published domain shard. |
| - `domain`: one of `Chart`, `GUI Grounding`, `Table`, `Web-to-HTML`, or |
| `Visual Search`. |
| - `tools`: a JSON-encoded string containing the function schemas expected by |
| ms-swift. A decoded copy is available as `metadata/tools.json`. |
| - `messages`: ordered agent messages. Roles are `system`, `user`, `assistant`, |
| `tool_call`, and `tool_response`. |
| - `images`: paths relative to the snapshot root. Entries align, in order, with |
| every `<image>` token across `messages`. Duplicate entries are intentional |
| when the same image is viewed more than once. |
|
|
| Paths such as `/mnt/data/example.png` inside messages are runtime paths in the |
| agent's sandbox. They are not paths to the downloaded snapshot and should not |
| be rewritten during training. |
|
|
| ## Source composition and provenance |
|
|
| Only source images and queries were used as task input; pre-existing source |
| reasoning traces were not used as supervision. The teacher-generated |
| trajectories were selected by outcome validity and measured tool-use gain. |
|
|
| | Domain | Source dataset | Records | License | |
| |---|---|---:|---| |
| | Chart | [ChartVerse-SFT-600K](https://huggingface.co/datasets/opendatalab/ChartVerse-SFT-600K) | 13,537 | Apache 2.0 | |
| | GUI Grounding | [AgentNet](https://huggingface.co/datasets/xlangai/AgentNet) | 1,170 | MIT | |
| | GUI Grounding | [OS-Atlas](https://huggingface.co/datasets/OS-Copilot/OS-Atlas-data) | 6,279 | Apache 2.0 | |
| | GUI Grounding | [UGround](https://huggingface.co/datasets/osunlp/UGround-V1-Data) | 3,517 | CC BY-NC-SA 4.0 | |
| | Table | [CoSyn-400K](https://huggingface.co/datasets/allenai/CoSyn-400K) | 4,645 | ODC-BY 1.0 | |
| | Table | [TABLET-Small](https://huggingface.co/datasets/alonsoapp/TABLET-Small) | 285 | CC BY 4.0 | |
| | Visual Search | [DeepEyesV2-RL](https://huggingface.co/datasets/honglyhly/DeepEyesV2_RL) | 738 | Not specified | |
| | Visual Search | [Vero-600K](https://huggingface.co/datasets/zlab-princeton/Vero-600k) | 1,203 | Apache 2.0 | |
| | Web-to-HTML | [VinciCoder-1.6M-SFT](https://huggingface.co/datasets/DocTron-Hub/VinciCoder-1.6M-SFT) | 10,674 | Not specified | |
|
|
| Licenses are those declared by the upstream dataset cards. Source-specific |
| terms continue to apply where an upstream dataset aggregates other datasets. |
|
|
| Tool-produced crops, masks, bounding-box visualizations, and HTML renderings |
| are packaged alongside original inputs because they are observations in the |
| training trajectories. These derivatives remain subject to any applicable |
| terms of the original image corpus. |
|
|
