| --- |
| dataset_info: |
| features: |
| - name: messages |
| list: |
| - name: content |
| dtype: string |
| - name: role |
| dtype: string |
| - name: ground_truth |
| dtype: string |
| - name: dataset |
| dtype: string |
| - name: env_config |
| struct: |
| - name: env_name |
| dtype: string |
| - name: image |
| dtype: string |
| - name: task_id |
| dtype: string |
| - name: source |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 21182796 |
| num_examples: 4567 |
| download_size: 20865488 |
| dataset_size: 21182796 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - tmax |
| - terminal |
| - agents |
| - reinforcement-learning |
| --- |
| |
| # SETA-Env for tmax |
|
|
| **Images require building:** the dataset conversion and complete task archive are published. 0 task image(s) were published during preparation; the remaining images are intentionally left for the included resumable build script. No build job is running for this release. Only tasks with available images can run immediately. See `image-build-status.json` for the publication-time snapshot. |
|
|
| All **4,567** task directories from [camel-ai/SETA-Env](https://huggingface.co/datasets/camel-ai/SETA-Env), pinned to `3c3bc8975b05826bf41769bd6b2da76ad1b6dd42`, converted to tmax's `swerl_vanillux_sandbox` format. |
|
|
| The train split uses the same `messages`, `ground_truth`, `dataset`, `env_config`, and `source` schema as the other `hamishivi/agent-task-*` datasets. Messages use the tmax Vanillux templates; `dataset` is `passthrough`. Task IDs are prefixed with `seta_env__` to avoid collisions when combining task archives. `task-manifest.json` maps them back to original paths. |
|
|
| `task-data.tar.gz` contains a directory per task with all original task files preserved byte-for-byte, plus `image.txt`. Instructions, verifiers, build contexts, metadata, and reference solutions are retained. The tmax loader exposes only environment seed files and defers tests until submission; reference solutions are not mounted into the agent sandbox. |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| from huggingface_hub import hf_hub_download |
| |
| train = load_dataset("hamishivi/agent-task-seta-env", split="train") |
| archive = hf_hub_download("hamishivi/agent-task-seta-env", "task-data.tar.gz", repo_type="dataset") |
| ``` |
|
|
| Extract the archive and set the sandbox `task_data_dir` to the directory containing the task directories. Every row specifies its image explicitly. Task resource requirements and verifier timeouts remain in the original `task.toml`; configure the training harness accordingly. |
|
|
| ## Images |
|
|
| Images use `hamishi740/agent-task-seta-env:<source-environment-hash>` and target Linux AMD64. See `task-manifest.json` for build status. |
|
|
| ## Validation and attribution |
|
|
| All rows passed schema and Parquet round-trip checks, and every archived task file was checked against the downloaded source bytes. See `validation.json`. This does not constitute an evaluation of every task or a full training run. |
|
|
| The upstream license is apache-2.0. Consult the upstream dataset card for citation and provenance. tmax Vanillux prompts are adapted from mini-swe-agent (MIT). |
|
|
| ## Resume image builds |
|
|
| Requires Docker Buildx and a Docker Hub login with write access to the `hamishi740` target repositories. The script skips tags already published, retains per-image logs, and can be rerun after failures. |
|
|
| ```sh |
| mkdir -p tasks |
| tar -xzf task-data.tar.gz -C tasks |
| python build_dataset_images.py --task-data-dir tasks --manifest task-manifest.json --workers 8 --timeout 1800 |
| ``` |
|
|
| To use another Docker Hub namespace, update the image references consistently in the manifest, training records, and task `image.txt` files before building. |
|
|
| Runtime smoke tests were not run for SETA because image builds were deferred. Structural, schema, and archive checks passed for all tasks. |
|
|
| ## Apptainer images |
|
|
| The current Apptainer pool and unified download manifest are maintained in [TMaxxx/agent-task-seta-env](https://huggingface.co/datasets/TMaxxx/agent-task-seta-env). New SIF uploads go to TMaxxx; earlier images remain available here. Use the downloader and manifest in the linked repository to retrieve all available images with tmax-compatible filenames. |
|
|
