task_id string | rollout_index int64 | status string | error string | wall_time_seconds float64 | created_at string | collection_id string | reward float64 | num_trajectories int64 | num_steps int64 | num_events int64 | events list |
|---|---|---|---|---|---|---|---|---|---|---|---|
textcraft_synth.val.12 | 0 | completed | null | 5.035912 | 2026-03-25T10:29:52.420551+00:00 | 067887f6-4a76-4f95-8d3e-7d90b8d7025c | 1 | 1 | 9 | 12 | [
{
"type": "trajectory_created",
"ts": 1774434587.421833,
"process_id": 875609,
"collection_id": "067887f6-4a76-4f95-8d3e-7d90b8d7025c",
"trajectory_id": "bab877d9-8056-436f-8f22-9edcf558e7bd",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.17 | 0 | completed | null | 12.14221 | 2026-03-25T10:57:41.516100+00:00 | 2d615a7a-6c43-424c-a991-f529e0b257d1 | 1 | 1 | 17 | 20 | [
{
"type": "trajectory_created",
"ts": 1774436249.4071295,
"process_id": 875609,
"collection_id": "2d615a7a-6c43-424c-a991-f529e0b257d1",
"trajectory_id": "6803baed-2a89-48b4-a340-fe3056714916",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.19 | 0 | completed | null | 3.511217 | 2026-03-25T08:35:24.984370+00:00 | 7f261017-bd3a-43af-9e4d-af3235701bfa | 1 | 1 | 7 | 10 | [
{
"type": "trajectory_created",
"ts": 1774427721.5132675,
"process_id": 875609,
"collection_id": "7f261017-bd3a-43af-9e4d-af3235701bfa",
"trajectory_id": "0f587002-9cbf-4d50-a9ea-8000d5fd9e29",
"step_index": null,
"reward": null,
"finish_message": null,
"error_message": null,
... |
textcraft_synth.val.23 | 0 | completed | null | 102.692845 | 2026-03-25T11:09:27.466335+00:00 | 09bb7a09-7d0e-4b1f-b2d1-7f3b0796c620 | 1 | 1 | 175 | 178 | [{"type":"trajectory_created","ts":1774436864.767658,"process_id":875609,"collection_id":"09bb7a09-7(...TRUNCATED) |
textcraft_synth.val.28 | 0 | completed | null | 5.39624 | 2026-03-25T10:57:29.338314+00:00 | 99f77b95-2b70-40ce-8a89-d2eba0e60f51 | 0 | 1 | 9 | 12 | [{"type":"trajectory_created","ts":1774436243.9822693,"process_id":875609,"collection_id":"99f77b95-(...TRUNCATED) |
textcraft_synth.val.31 | 0 | completed | null | 189.29721 | 2026-03-25T09:08:33.516829+00:00 | 4a346153-c6a7-4891-8d22-fa90793ef6e6 | 0 | 1 | 244 | 247 | [{"type":"trajectory_created","ts":1774429524.2277107,"process_id":875609,"collection_id":"4a346153-(...TRUNCATED) |
textcraft_synth.val.32 | 0 | completed | null | 17.135966 | 2026-03-25T09:31:10.857666+00:00 | 6657d53b-bec7-4397-919d-3397f41c63da | 1 | 1 | 33 | 36 | [{"type":"trajectory_created","ts":1774431053.7551427,"process_id":875609,"collection_id":"6657d53b-(...TRUNCATED) |
textcraft_synth.val.37 | 0 | completed | null | 172.486006 | 2026-03-25T07:57:04.386729+00:00 | 33182b1a-688a-4461-946c-e624f781cebb | 0 | 1 | 242 | 245 | [{"type":"trajectory_created","ts":1774425251.9097981,"process_id":875609,"collection_id":"33182b1a-(...TRUNCATED) |
textcraft_synth.val.45 | 0 | completed | null | 17.606253 | 2026-03-25T10:05:32.942579+00:00 | 482362b0-a9b7-4677-a214-d649f7f4adae | 1 | 1 | 35 | 38 | [{"type":"trajectory_created","ts":1774433115.3694298,"process_id":875609,"collection_id":"482362b0-(...TRUNCATED) |
textcraft_synth.val.51 | 0 | completed | null | 238.493026 | 2026-03-25T09:03:54.654858+00:00 | 356e1ad2-a9bc-48c5-8364-3423e65ac913 | 0 | 1 | 318 | 321 | [{"type":"trajectory_created","ts":1774429196.1806364,"process_id":875609,"collection_id":"356e1ad2-(...TRUNCATED) |
textcraft-synth-single-agent
TextCraft (synthetic) rollouts from a single (linear) Qwen3-4B agent. The agent was trained with a 40K context window; these rollouts were run without a context limit.
There is one row per rollout. The full event log for that rollout is in the events column.
import json
from datasets import load_dataset
ds = load_dataset("apurvaga/textcraft-synth-single-agent", split="train")
row = ds[0]
for e in row["events"]:
if e["type"] == "trajectory_step_added":
step = json.loads(e["step"]) # thought, code, output, error, reward, misc
Columns
| column | description |
|---|---|
task_id, rollout_index |
which task and rollout this row is |
status, error, wall_time_seconds, created_at |
from the rollout's metadata.json |
collection_id |
ID of the trajectory collection (root agent and its sub-agents) |
reward |
the root agent's final reward |
num_trajectories |
number of agents in the rollout (1 plus the number of sub-agents) |
num_steps, num_events |
step and event counts across all agents |
events |
the ordered event log (see below) |
Each entry in events has type, ts (Unix timestamp), process_id, collection_id, trajectory_id,
step_index, reward, finish_message, error_message, trajectory, task and step. Fields that don't
apply to an event type are null. trajectory, task, step and finish_message are JSON-encoded strings;
decode them with json.loads.
| event type | fields set |
|---|---|
trajectory_created |
trajectory (initial trajectory; parent_info is null for the root agent and set for sub-agents) |
trajectory_task_set |
task (goal, id, max_steps, misc) |
trajectory_step_added |
step_index, step (thought, code, output, error, reward, misc) |
trajectory_finished |
reward, finish_message, error_message |
Within a row, events interleaves events from the root agent and all of its sub-agents in time order. To get one agent's trajectory, filter by trajectory_id; each sub-agent's parent_info (in its trajectory_created event) links it to the agent that spawned it. Single-agent datasets have one trajectory per row. The task in trajectory_task_set is the
state at the start of the run (for TextCraft, task.misc.initial_inventory is the true starting inventory).
Viewing with platoon's visualization tool
The platoon viewer reads JSONL event logs. hf_to_events.py (in this repo) writes each row back out as
events_<task_id>_<collection_id>.jsonl, byte-for-byte identical to the original log:
pip install datasets
python hf_to_events.py apurvaga/textcraft-synth-single-agent ./events
uv run -m platoon.visualization.cli tail --dir ./events
tail loads every event at once, so you see the full trajectory trees immediately. To watch a single run play out step by step, use replay <file.jsonl> --delay 0.25 instead.
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