| --- |
| license: apache-2.0 |
| tags: |
| - agents |
| - tool-use |
| - trajectories |
| - nethack |
| - minihack |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "episodes/**/*.json" |
| --- |
| |
| # Lantern episodes |
|
|
| Every episode played in [Lantern](https://huggingface.co/spaces/visproj/lantern): Beam (and later a distilled 1.7B student) exploring MiniHack dungeon levels through tool calls, with its full reasoning, plans, notes and lessons. |
|
|
| ## Layout |
|
|
| `episodes/{level}/{id}.json`, one file per episode, plus `journal.json` (the Space's current lessons per level). |
|
|
| Each episode has `id`, `task` (level), `seed`, `outcome` (`success`, `failure`, `timeout`, `budget`, `stalled`, `stopped`, `error`), `steps`, `use_lessons` (journal on/off), `source`, `model`, and `events`: |
|
|
| - `start`: goal, legal actions, the exact system prompt and tool schema, model, prompt version, and the journal lessons read before the run. |
| - `turn` (one per model call): the observation prompt, the model's reasoning, the tool calls it made (planned moves, moves actually done, whether the plan was cut short, the hero's position after every move), its notes, the resulting map, running token usage, and any advice a viewer sent. |
| - `lessons`: the lessons written after the run. |
| - `end`: outcome, steps, token usage. |
|
|
| ## Sources |
|
|
| - `bench`: the benchmark (tag `bench-v2`): 8 levels × 5 seeds × journal off/on, all with Beam and prompt version 2. These 80 episodes are the main data. |
| - `space`: live runs started by visitors to the Space. `coached: true` marks runs where the visitor sent advice, and that advice text is included. |
| - `student-eval`: the distilled student and the untrained base model on the benchmark seeds. |
|
|
| Episodes with `outcome` `error` (infrastructure failures, replayed afterwards) or `stopped` aren't results; leave them out when computing win rates. |
|
|
| ## Using it for training |
|
|
| To build supervised training rows, take winning episodes made with the current prompt version and skip coached runs. Each `turn` becomes one example: the system prompt from `start` plus that turn's observation as input, and the tool calls the model made as output. This is how [Lantern-1.7B](https://huggingface.co/visproj/lantern-1.7b) was trained. |
|
|
| ## Privacy |
|
|
| Visitors' IP addresses are never stored. Space episodes contain only the run itself and any advice text a visitor chose to send. |
|
|
| ## Limitations |
|
|
| - Small: 80 benchmark episodes, 5 seeds per level and condition. |
| - Beam's reasoning is included as returned by the provider; it isn't edited. |
| - Level goals include some strategy hints (see the Space README). |
|
|
| ## License |
|
|
| Apache-2.0. Episodes contain outputs generated by Beam 1.0 (Reflection, Apache-2.0) and Lantern-1.7B, on levels from MiniHack (Apache-2.0). |
|
|
