mis2/Trajectory2Gym-30B-A3B
Text Generation • 4B • Updated • 30
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<properties: string, required: list<item: string>, type: string, $defs: struct<FlightInfo: struct<properties: struct<date: struct<description: string, title: string, type: string>, flight_number: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>, Passenger: struct<properties: struct<dob: struct<description: string, title: string, type: string>, first_name: struct<description: string, title: string, type: string>, last_name: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>, Payment: struct<properties: struct<amount: struct<description: string, title: string, type: string>, payment_id: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>>, title: string>
to
{'properties': Json(decode=True), 'required': List(Value('string')), 'type': Value('string')}
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2118, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2068, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2068, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<properties: string, required: list<item: string>, type: string, $defs: struct<FlightInfo: struct<properties: struct<date: struct<description: string, title: string, type: string>, flight_number: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>, Passenger: struct<properties: struct<dob: struct<description: string, title: string, type: string>, first_name: struct<description: string, title: string, type: string>, last_name: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>, Payment: struct<properties: struct<amount: struct<description: string, title: string, type: string>, payment_id: struct<description: string, title: string, type: string>>, required: list<item: string>, title: string, type: string>>, title: string>
to
{'properties': Json(decode=True), 'required': List(Value('string')), 'type': Value('string')}
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
assistant_turns int64 | context_assistant_turns int64 | domain string | enable_thinking bool | format string | messages list | source_corpus string | source_domain string | source_task_id string | split string | success bool | supervised_assistant_turn_indices list | supervised_assistant_turns int64 | task_id string | tools list | trace_hash string | trajectory_family_id string | trajectory_role string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [
{
"content": "# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline agent, you can help users book, modify, or cancel flight reservations.\n\n- Before taking any actions that update the booking database (booking, modifying flights, editing baggage, upgrading cabin class, or upd... | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7
] | 8 | tau1:airline:0:0e49f3257668 | [
{
"function": {
"description": "Book a reservation.",
"name": "book_reservation",
"parameters": {
"properties": {
"cabin": {
"enum": [
"basic_economy",
"economy",
"business"
],
"type": "string"
... | 0e49f32576688ec0d6605696bc319f416f69e57fe7a6a9476345ebd6a4b6cf43 | tau1:airline:0 | demonstration |
16 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [
{
"content": "# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline agent, you can help users book, modify, or cancel flight reservations.\n\n- Before taking any actions that update the booking database (booking, modifying flights, editing baggage, upgrading cabin class, or upd... | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
11,
13,
14,
15
] | 14 | tau1:airline:0:2f51136116fb | [
{
"function": {
"description": "Book a reservation.",
"name": "book_reservation",
"parameters": {
"properties": {
"cabin": {
"enum": [
"basic_economy",
"economy",
"business"
],
"type": "string"
... | 2f51136116fbe372f99d5f006d37dc265aac6d05f5bdf10eb346f9268994e19d | tau1:airline:0 | demonstration |
11 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [
{
"content": "# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline agent, you can help users book, modify, or cancel flight reservations.\n\n- Before taking any actions that update the booking database (booking, modifying flights, editing baggage, upgrading cabin class, or upd... | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] | 11 | tau1:airline:0:53a5c5aba865 | [
{
"function": {
"description": "Book a reservation.",
"name": "book_reservation",
"parameters": {
"properties": {
"cabin": {
"enum": [
"basic_economy",
"economy",
"business"
],
"type": "string"
... | 53a5c5aba865221d7f1c5ba214598f44dfd15ef82db109bb82c51ba4190c328c | tau1:airline:0 | demonstration |
20 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [
{
"content": "# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline agent, you can help users book, modify, or cancel flight reservations.\n\n- Before taking any actions that update the booking database (booking, modifying flights, editing baggage, upgrading cabin class, or upd... | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
14,
16,
17,
18,
19
] | 18 | tau1:airline:0:63ad4cfe9cd8 | [
{
"function": {
"description": "Book a reservation.",
"name": "book_reservation",
"parameters": {
"properties": {
"cabin": {
"enum": [
"basic_economy",
"economy",
"business"
],
"type": "string"
... | 63ad4cfe9cd8cfffc7dfdc28521867f1cb14bf33e2ae504fb3062ff22915e8af | tau1:airline:0 | demonstration |
11 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [
{
"content": "# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline agent, you can help users book, modify, or cancel flight reservations.\n\n- Before taking any actions that update the booking database (booking, modifying flights, editing baggage, upgrading cabin class, or upd... | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
8,
9,
10
] | 10 | tau1:airline:0:8871eb4ac5e1 | [
{
"function": {
"description": "Book a reservation.",
"name": "book_reservation",
"parameters": {
"properties": {
"cabin": {
"enum": [
"basic_economy",
"economy",
"business"
],
"type": "string"
... | 8871eb4ac5e1a1c476bd731f7fd995e8efcf54afbe6f1776a0d7340094e3ac58 | tau1:airline:0 | demonstration |
11 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [{"content":"# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline(...TRUNCATED) | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
] | 11 | tau1:airline:0:a277699b3d4f | [{"function":{"description":"Book a reservation.","name":"book_reservation","parameters":{"propertie(...TRUNCATED) | a277699b3d4f82d057edb1bd09903212bc5bc1f4da037370abe7087d173e0556 | tau1:airline:0 | demonstration |
16 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [{"content":"# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline(...TRUNCATED) | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
11,
13,
14,
15
] | 14 | tau1:airline:0:adf5c9e02762 | [{"function":{"description":"Book a reservation.","name":"book_reservation","parameters":{"propertie(...TRUNCATED) | adf5c9e027629a91302331b29a3845af0e62b0352ae1716bdd05f9ca3cf1a532 | tau1:airline:0 | demonstration |
20 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [{"content":"# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline(...TRUNCATED) | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
14,
16,
17,
18,
19
] | 18 | tau1:airline:0:ae0f702b2cdc | [{"function":{"description":"Book a reservation.","name":"book_reservation","parameters":{"propertie(...TRUNCATED) | ae0f702b2cdcec24731ca2b22d1fb620e8fa2a1b6af588c1c2c94a02a60748e3 | tau1:airline:0 | demonstration |
11 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [{"content":"# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline(...TRUNCATED) | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
8,
9,
10
] | 10 | tau1:airline:0:b1cfc956562e | [{"function":{"description":"Book a reservation.","name":"book_reservation","parameters":{"propertie(...TRUNCATED) | b1cfc956562ed0260e7b23b3e2dac3ad92f147efd68f372df18cfac71320f7f7 | tau1:airline:0 | demonstration |
8 | 0 | tau1/airline | false | trajectory2gym_sft_v0 | [{"content":"# Airline Agent Policy\n\nThe current time is 2024-05-15 15:00:00 EST.\n\nAs an airline(...TRUNCATED) | tau1 | airline | tau1:airline:0 | train | true | [
0,
1,
2,
3,
4,
5,
6,
7
] | 8 | tau1:airline:0:be0ecfc5c134 | [{"function":{"description":"Book a reservation.","name":"book_reservation","parameters":{"propertie(...TRUNCATED) | be0ecfc5c134278c8a28f7cc59ae738c8fe106b31bc40555666ff99f8c07f9ab | tau1:airline:0 | demonstration |
End of preview.
Trajectory2Gym: decision-grounded candidate interactions
This release contains 34,772 complete, policy-visible candidate interactions for tool-use post-training, stored in seven compressed JSONL shards. These are semantic parents, not rendered children or a final scale-specific training view.
| Source | Interactions |
|---|---|
| bfcl | 17282 |
| tau1 | 11411 |
| tau2 | 6079 |
Model checkpoints
Download the five corresponding Trajectory2Gym paper checkpoints:
| Scale | Model repository |
|---|---|
| 1.7B | Trajectory2Gym-1.7B |
| 4B | Trajectory2Gym-4B |
| 8B | Trajectory2Gym-8B |
| 14B | Trajectory2Gym-14B |
| 30B-A3B | Trajectory2Gym-30B-A3B |
Each model repository contains native tokenizers, chat templates, model cards, licenses, and release checksums. The candidate corpus below is not the rendered scale-specific training data; the 30B-A3B model uses an expanded corpus.
Record format
Records preserve native messages, tool definitions, supervised assistant-turn indices, context-turn counts, and stable source identities. The supervision mask selects assistant decisions; user/tool messages and masked failed actions can remain visible context.
Operational source paths and non-allowlisted top-level collection metadata are omitted. Dialogue content, native tool arguments, tool definitions, and supervision indices were checked against every original record, including nested dictionary ordering.
Loading
Native tool schemas and argument values are heterogeneous. Use a JSONL reader rather than assuming all records can be inferred as one flat Arrow schema.
import gzip, json
from huggingface_hub import hf_hub_download
path = hf_hub_download('mis2/Trajectory2gym', 'data/train-00000.jsonl.gz', repo_type='dataset')
with gzip.open(path, 'rt', encoding='utf-8') as f:
for line in f:
interaction = json.loads(line)
# interaction['messages'], interaction['supervised_assistant_turn_indices']
Scope and provenance
The source is the frozen training-side candidate corpus. Tau1 Airline uses the disclosed seen-task construction/evaluation scope. Tau2 construction uses its official train partition. This release does not assert template-level separation, and it is not the current upstream benchmark test distribution. The 30B-A3B study uses an expanded corpus, not this common pool alone.
Source input SHA-256: a65a690aeb21a8e28c1865607dff93a10cbb1c311c5a7beacf0e58ed3eb94e23
See provenance.json and RELEASE_MANIFEST.json for the transformation and file hashes. Exported bytes differ from the historical source file. Native reset states and all execution certificates are not included, so these files are not a standalone environment replay package.
Content checks
Credential patterns, internal-host strings, and operational paths were checked. Benchmark-native simulated address literals and a generic path placeholder were retained through an exact-value-hash review bound to the source hash; see NATIVE_LITERAL_REVIEW.json. That review is not an independent human PII audit. Native fixture entities are retained to preserve observation-to-action dependencies.
License and attribution
Released under Apache-2.0 with the upstream MIT and Apache-2.0 notices preserved. See LICENSE, THIRD_PARTY_NOTICES.md, and licenses/.
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