Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
script: string
role: string
sender_id: string
now: int64
text: string
reply: string
status: string
tool_trace: list<item: struct<tool: string, role: string, gate: string, result: struct<minutes: double, quantile (... 116 chars omitted)
child 0, item: struct<tool: string, role: string, gate: string, result: struct<minutes: double, quantile: double, p (... 104 chars omitted)
child 0, tool: string
child 1, role: string
child 2, gate: string
child 3, result: struct<minutes: double, quantile: double, p90: double, party_id: string, position: int64, size: int6 (... 46 chars omitted)
child 0, minutes: double
child 1, quantile: double
child 2, p90: double
child 3, party_id: string
child 4, position: int64
child 5, size: int64
child 6, needs_high_chair: bool
child 7, request_id: string
backend: string
dwell_minutes: null
reservations: list<item: struct<party_id: string, time: double, size: int64, needs_high_chair: bool, hold_until: n (... 37 chars omitted)
child 0, item: struct<party_id: string, time: double, size: int64, needs_high_chair: bool, hold_until: null, arrive (... 25 chars omitted)
child 0, party_id: string
child 1, time: double
child 2, size: int64
child 3, needs_high_chair: bool
child 4, hold_until: null
child 5, arrived: bool
child 6, seated_at: null
seed: int64
parties: list<item: struct<party_id: string, size: int64, needs_high_chair: bool, joined_at: double, quoted_m (... 182 chars omitted)
child 0, item: struct<party_id: string, size: int64, needs_high_chair: bool, joined_at: double, quoted_minutes: nul (... 170 chars omitted)
child 0, party_id: string
child 1, size: int64
child 2, needs_high_chair: bool
child 3, joined_at: double
child 4, quoted_minutes: null
child 5, quoted_at: null
child 6, notified_at: null
child 7, patience_minutes: double
child 8, temperament: double
child 9, seated_at: null
child 10, table_ids: list<item: null>
child 0, item: null
child 11, walked_away_at: null
child 12, requotes: int64
to
{'seed': Value('int64'), 'parties': List({'party_id': Value('string'), 'size': Value('int64'), 'needs_high_chair': Value('bool'), 'joined_at': Value('float64'), 'quoted_minutes': Value('null'), 'quoted_at': Value('null'), 'notified_at': Value('null'), 'patience_minutes': Value('float64'), 'temperament': Value('float64'), 'seated_at': Value('null'), 'table_ids': List(Value('null')), 'walked_away_at': Value('null'), 'requotes': Value('int64')}), 'reservations': List({'party_id': Value('string'), 'time': Value('float64'), 'size': Value('int64'), 'needs_high_chair': Value('bool'), 'hold_until': Value('null'), 'arrived': Value('bool'), 'seated_at': Value('null')}), 'dwell_minutes': Json(decode=True)}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
script: string
role: string
sender_id: string
now: int64
text: string
reply: string
status: string
tool_trace: list<item: struct<tool: string, role: string, gate: string, result: struct<minutes: double, quantile (... 116 chars omitted)
child 0, item: struct<tool: string, role: string, gate: string, result: struct<minutes: double, quantile: double, p (... 104 chars omitted)
child 0, tool: string
child 1, role: string
child 2, gate: string
child 3, result: struct<minutes: double, quantile: double, p90: double, party_id: string, position: int64, size: int6 (... 46 chars omitted)
child 0, minutes: double
child 1, quantile: double
child 2, p90: double
child 3, party_id: string
child 4, position: int64
child 5, size: int64
child 6, needs_high_chair: bool
child 7, request_id: string
backend: string
dwell_minutes: null
reservations: list<item: struct<party_id: string, time: double, size: int64, needs_high_chair: bool, hold_until: n (... 37 chars omitted)
child 0, item: struct<party_id: string, time: double, size: int64, needs_high_chair: bool, hold_until: null, arrive (... 25 chars omitted)
child 0, party_id: string
child 1, time: double
child 2, size: int64
child 3, needs_high_chair: bool
child 4, hold_until: null
child 5, arrived: bool
child 6, seated_at: null
seed: int64
parties: list<item: struct<party_id: string, size: int64, needs_high_chair: bool, joined_at: double, quoted_m (... 182 chars omitted)
child 0, item: struct<party_id: string, size: int64, needs_high_chair: bool, joined_at: double, quoted_minutes: nul (... 170 chars omitted)
child 0, party_id: string
child 1, size: int64
child 2, needs_high_chair: bool
child 3, joined_at: double
child 4, quoted_minutes: null
child 5, quoted_at: null
child 6, notified_at: null
child 7, patience_minutes: double
child 8, temperament: double
child 9, seated_at: null
child 10, table_ids: list<item: null>
child 0, item: null
child 11, walked_away_at: null
child 12, requotes: int64
to
{'seed': Value('int64'), 'parties': List({'party_id': Value('string'), 'size': Value('int64'), 'needs_high_chair': Value('bool'), 'joined_at': Value('float64'), 'quoted_minutes': Value('null'), 'quoted_at': Value('null'), 'notified_at': Value('null'), 'patience_minutes': Value('float64'), 'temperament': Value('float64'), 'seated_at': Value('null'), 'table_ids': List(Value('null')), 'walked_away_at': Value('null'), 'requotes': Value('int64')}), 'reservations': List({'party_id': Value('string'), 'time': Value('float64'), 'size': Value('int64'), 'needs_high_chair': Value('bool'), 'hold_until': Value('null'), 'arrived': Value('bool'), 'seated_at': Value('null')}), 'dwell_minutes': Json(decode=True)}
because column names don't match
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 1379, 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 956, 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 1702, 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 1887, 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.
seed int64 | parties list | reservations list | dwell_minutes unknown |
|---|---|---|---|
0 | [
{
"party_id": "P001",
"size": 4,
"needs_high_chair": false,
"joined_at": 5,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 21.7532564633,
"temperament": 0.8158535541,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
... | [
{
"party_id": "R001",
"time": 15,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 55,
"size": 6,
"needs_high_chair": true,
"hold_until": null,
"arrived": false,
"seated_at": nul... | {
"P001": 86.3453652061,
"P002": 99.3919237451,
"P003": 104.3940392666,
"P004": 114.4985243472,
"P005": 53.7041444418,
"P006": 42.9461060332,
"P007": 52.3587885715,
"P008": 73.6391728903,
"P009": 139.0152456259,
"P010": 151.0712258444,
"P011": 122.2714197808,
"P012": 107.6233940412,
"P013": 13... |
1 | [
{
"party_id": "P001",
"size": 6,
"needs_high_chair": false,
"joined_at": 1,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 49.1419931578,
"temperament": 0.8277025938,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
... | [
{
"party_id": "R001",
"time": 15,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 75,
"size": 4,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": nu... | {
"P001": 126.1683880279,
"P002": 81.1313307621,
"P003": 81.5106200049,
"P004": 65.8146496669,
"P005": 111.5292314101,
"P006": 93.5934996277,
"P007": 52.0825777693,
"P008": 54.5677327786,
"P009": 45.2649914062,
"P010": 41.9569358061,
"P011": 85.2106947439,
"P012": 63.7852237575,
"P013": 116.66... |
2 | [
{
"party_id": "P001",
"size": 2,
"needs_high_chair": false,
"joined_at": 16,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 55.4634395579,
"temperament": 0.5110659736,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
... | [
{
"party_id": "R001",
"time": 75,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 95,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": nu... | {
"P001": 72.9728258154,
"P002": 89.260870033,
"P003": 79.8264822032,
"P004": 58.9242935638,
"P005": 60.723207464,
"P006": 69.4705772076,
"P007": 60.1357773647,
"P008": 45.0539624607,
"P009": 119.62660485480001,
"P010": 61.3755902307,
"P011": 147.4113854014,
"P012": 48.9826528887,
"P013": 37.6... |
3 | [
{
"party_id": "P001",
"size": 4,
"needs_high_chair": false,
"joined_at": 15,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 38.8031659349,
"temperament": 0.0014900835,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
... | [
{
"party_id": "R001",
"time": 15,
"size": 6,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 35,
"size": 4,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": nu... | {
"P001": 152.9426753011,
"P002": 60.6910644052,
"P003": 59.0264853705,
"P004": 69.0485828788,
"P005": 102.4496230757,
"P006": 66.8833028307,
"P007": 97.2585986008,
"P008": 84.6169510044,
"P009": 57.7011123361,
"P010": 58.6039919112,
"P011": 90.171194472,
"P012": 50.8491717537,
"P013": 78.1110... |
4 | [
{
"party_id": "P001",
"size": 8,
"needs_high_chair": true,
"joined_at": 0,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 15.7376432866,
"temperament": 0.3764865844,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
"... | [
{
"party_id": "R001",
"time": 15,
"size": 4,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 35,
"size": 2,
"needs_high_chair": true,
"hold_until": null,
"arrived": false,
"seated_at": nul... | {
"P001": 84.6585065671,
"P002": 55.0324775576,
"P003": 81.5184155413,
"P004": 114.1464825846,
"P005": 49.1638577334,
"P006": 76.3165235458,
"P007": 117.2777217229,
"P008": 133.5038535844,
"P009": 64.1561994415,
"P010": 99.6123702568,
"P011": 159.4543034834,
"P012": 113.2232125104,
"P013": 90.... |
5 | [
{
"party_id": "P001",
"size": 2,
"needs_high_chair": false,
"joined_at": 9,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 67.600305424,
"temperament": 0.8976776081,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
"... | [
{
"party_id": "R001",
"time": 15,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 35,
"size": 2,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": nu... | {
"P001": 35.4505963472,
"P002": 58.5550455382,
"P003": 71.448786378,
"P004": 118.3471957315,
"P005": 75.1980093507,
"P006": 90.5133756755,
"P007": 56.8982062124,
"P008": 52.0736543393,
"P009": 93.7385702028,
"P010": 75.6592316472,
"P011": 77.1066290203,
"P012": 111.7555460882,
"P013": 48.4047... |
6 | [
{
"party_id": "P001",
"size": 4,
"needs_high_chair": false,
"joined_at": 4,
"quoted_minutes": null,
"quoted_at": null,
"notified_at": null,
"patience_minutes": 52.4606141507,
"temperament": 0.1229723749,
"seated_at": null,
"table_ids": [],
"walked_away_at": null,
... | [
{
"party_id": "R001",
"time": 15,
"size": 4,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": null
},
{
"party_id": "R002",
"time": 35,
"size": 4,
"needs_high_chair": false,
"hold_until": null,
"arrived": false,
"seated_at": nu... | {
"P001": 94.901085244,
"P002": 168.3743989673,
"P003": 69.9193328555,
"P004": 70.8286346552,
"P005": 132.4815624989,
"P006": 80.9202378531,
"P007": 41.5322862858,
"P008": 88.2123929799,
"P009": 46.7127051643,
"P010": 75.3533038913,
"P011": 75.8339996652,
"P012": 39.3340142379,
"P013": 51.3377... |
7 | [{"party_id":"P001","size":2,"needs_high_chair":false,"joined_at":1.0,"quoted_minutes":null,"quoted_(...TRUNCATED) | [{"party_id":"R001","time":15.0,"size":2,"needs_high_chair":false,"hold_until":null,"arrived":false,(...TRUNCATED) | {"P001":103.9035022926,"P002":52.5109433975,"P003":62.5079097984,"P004":141.0230371672,"P005":79.115(...TRUNCATED) |
8 | [{"party_id":"P001","size":4,"needs_high_chair":false,"joined_at":1.0,"quoted_minutes":null,"quoted_(...TRUNCATED) | [{"party_id":"R001","time":15.0,"size":6,"needs_high_chair":false,"hold_until":null,"arrived":false,(...TRUNCATED) | {"P001":119.3689750526,"P002":61.5611929966,"P003":110.0083229778,"P004":104.0679569776,"P005":77.96(...TRUNCATED) |
9 | [{"party_id":"P001","size":4,"needs_high_chair":false,"joined_at":0.0,"quoted_minutes":null,"quoted_(...TRUNCATED) | [{"party_id":"R001","time":15.0,"size":6,"needs_high_chair":false,"hold_until":null,"arrived":false,(...TRUNCATED) | {"P001":100.1066221824,"P002":157.1501729302,"P003":56.5407050197,"P004":104.5685805815,"P005":104.8(...TRUNCATED) |
End of preview.
AI Host — Generated Friday Nights
Simulated Friday-night demand for a 20-table independent restaurant, plus StubLLM transcripts of five scripted "talking guests" run through the AI Host conversation loop. Generated by the AI Host simulator for the Meta Global AI Developer Hackathon. This is synthetic data. No real guests, restaurants, or personal information are included.
Files
nights.jsonl— 200 seeded nights, one per line:{seed, parties[], reservations[], dwell_minutes{}}. Parties carry size, high-chair need, arrival minute, patience, and temperament. Dwell minutes are the hidden time-at-table drawn from the policy's lognormal priors.talking_guest_transcripts.jsonl— 11 turns from five scripts (ask the wait, high chair, complaint after a late quote, argue, no-show late reservation) with the agent reply, status, and full tool trace.
Generation
Parties arrive by a Poisson process over a 17:00–22:00 service with an
evening peak curve. Party sizes follow 2/4/6/8 at 0.45/0.35/0.15/0.05.
Time-at-table is lognormal by party size. The generator is deterministic
per seed (sim/guests.py in the AI Host repo), so any night can be
reproduced exactly and replayed under different host policies (FIFO
baseline vs Monte Carlo quoting) for scoring.
Intended use
Evaluating wait-quote calibration, broken-promise rates, queue fairness, and agent conversation behavior for restaurant host work. Not intended as real-world demand data: arrival rates and dwell priors are illustrative policy inputs, not measurements from a live restaurant.
Regenerate
python -m eval.generate_dataset --nights 200
- Downloads last month
- 39