nemo_gym.task_data

Per-server task-data schemas.

A resources server ships a task_data.py module next to its app.py exporting a single symbol TaskData: either a Pydantic BaseModel subclass or a type (e.g. an Annotated[Union[...], Field(discriminator=...)] alias) accepted by pydantic.TypeAdapter. A self-contained agent (one that declares datasets but no resources_server reference) ships the same module under responses_api_agents/<implementation>/ and owns its rows’ schema; an agent WITH a reference uses that resources server’s schema instead. It describes the task-owned fields of that server’s dataset rows, written FLAT in the planned end-state shape: the fields as they will appear inside the unified task_data row key after the row-format migration. Framework-owned keys (see RESERVED_ROW_KEYS) are never part of TaskData, and neither is a verifier_metadata wrapper: rows that still carry one have its contents spliced up by normalize_task_fields before validation, so one flat schema validates both today’s rows and post-migration task_data contents. Fields that today’s wire reads EXCLUSIVELY from inside verifier_metadata should be annotated Field(..., json_schema_extra={"legacy_location": "verifier_metadata"}) — that reverse map is what the row-format migration and the dispatch compatibility shim consume, and validation flags rows that carry such a field only top-level (the server would not see it). Servers whose wire accepts both placements (e.g. via a before-validator that nests top-level fields itself) must not carry the marker.

This module is a dependency-light leaf: it may import only the standard library and Pydantic, and per-server task_data.py modules may import only the standard library, Pydantic, this module, and other servers’ task_data modules. That keeps schemas loadable by data tooling (collate, gym env schema, dataset import) without installing any server’s requirements.

Conventions for TaskData models:

• model_config = ConfigDict(extra="allow") by default. extra="forbid" is opt-in for servers that are already fail-closed. Pydantic’s default extra="ignore" is banned: silently dropping row fields is the existing bug class this system exists to catch.
• Required-ness mirrors the server’s wire contract (its verify/run request models), not what verify() happens to read. A field the wire requires stays required even if unread.
• Fields may carry json_schema_extra={"consumed_by": [...]} with values from {"verify", "metrics", "prompt", "provenance"}. These tags are purely informational: they document what reads a field for humans inspecting gym env schema output, and no tooling consumes them. Fields that are JSON-encoded strings on the wire stay typed str.

Module Contents

Classes

Functions

Data

LEGACY_METADATA_KEY

RESERVED_ROW_KEYS

TASK_DATA_EXPORT_NAME

TASK_DATA_MODULE_NAME

TASK_DATA_ROW_KEY

API

class nemo_gym.task_data.TaskDataSchemaError()

class nemo_gym.task_data.TaskDataValidationReport(
    server_name: str,
    dataset_fpath: str,
    rows: int = 0,
    error_rows: int = 0,
    errors: typing.List[str] = list(),
    unknown_keys: typing.Dict[str, int] = dict(),
    conflicting_keys: typing.Dict[str, int] = dict(),
    misplaced_keys: typing.Dict[str, int] = dict()
)

nemo_gym.task_data.TaskDataValidationReport.summary() -> str

class nemo_gym.task_data.TaskDataValidator(
    server_name: str,
    adapter: pydantic.TypeAdapter,
    dataset_fpath: str
)

nemo_gym.task_data.TaskDataValidator.validate_row(
    row_index: int,
    row: typing.Dict[str, typing.Any]
) -> None

nemo_gym.task_data.find_server_dir(
    server_name: str,
    base_folder: str = 'resources_servers'
) -> typing.Optional[pathlib.Path]

nemo_gym.task_data.legacy_metadata_fields(
    adapter: pydantic.TypeAdapter
) -> frozenset

nemo_gym.task_data.load_task_data_schema(
    server_dir: pathlib.Path
) -> typing.Optional[pydantic.TypeAdapter]

nemo_gym.task_data.normalize_task_fields(
    row: typing.Dict[str, typing.Any]
) -> tuple[typing.Dict[str, typing.Any], typing.List[str]]

nemo_gym.task_data.validate_jsonl_rows(
    server_name: str,
    adapter: pydantic.TypeAdapter,
    dataset_fpath: str,
    lines: typing.Iterable[str]
) -> nemo_gym.task_data.TaskDataValidationReport

nemo_gym.task_data.LEGACY_METADATA_KEY = 'verifier_metadata'

nemo_gym.task_data.RESERVED_ROW_KEYS = frozenset({'responses_create_params', 'agent_ref', 'task_source', '_ng_task_inde...

nemo_gym.task_data.TASK_DATA_EXPORT_NAME = 'TaskData'

nemo_gym.task_data.TASK_DATA_MODULE_NAME = 'task_data'

nemo_gym.task_data.TASK_DATA_ROW_KEY = 'task_data'