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Code ReferenceConfigConfig API

data_designer.config.run_config

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Module Contents

Classes

NameDescription
JinjaRenderingEngineTemplate renderer used by the engine for user-supplied Jinja templates.
ThrottleConfigAIMD throttle tuning parameters for adaptive concurrency control.
RunConfigRuntime configuration for dataset generation.

API

1class data_designer.config.run_config.JinjaRenderingEngine

Bases: data_designer.config.utils.type_helpers.StrEnum

Template renderer used by the engine for user-supplied Jinja templates.

Initialization:

Initialize self. See help(type(self)) for accurate signature.

1NATIVE = native
1SECURE = secure
1class data_designer.config.run_config.ThrottleConfig(
2 /,
3 **data: typing.Any
4)

Bases: data_designer.config.base.ConfigBase

AIMD throttle tuning parameters for adaptive concurrency control.

These knobs configure the ThrottleManager that wraps every outbound model HTTP request. The defaults are conservative and suitable for most workloads; override only when you understand the trade-offs.

Parameters:

reduce_factor

Multiplicative decrease factor applied to the per-domain concurrency limit on a 429 / rate-limit signal. Must be in (0, 1). Default is 0.75 (reduce by 25% on rate-limit).

additive_increase

Additive increase step applied after every success_window consecutive successes. Default is 1.

success_window

Number of consecutive successful releases before the additive increase is applied. Default is 25.

cooldown_seconds

Default cooldown duration (seconds) applied after a rate-limit when the provider does not include a Retry-After header. Default is 2.0.

ceiling_overshoot

Fraction above the observed rate-limit ceiling that additive increase is allowed to probe before capping. Default is 0.10 (10% overshoot).

rampup_seconds

Optional startup ramp duration. When greater than zero, each throttle domain starts at one concurrent request and linearly ramps to its configured peak over this many seconds. A 429 aborts the startup ramp and switches to normal AIMD recovery. Default is 0.0 (disabled).

Attributes:

reduce_factor

Multiplicative decrease factor applied to the per-domain concurrency limit on a 429 / rate-limit signal. Must be in (0, 1). Default is 0.75 (reduce by 25% on rate-limit).

additive_increase

Additive increase step applied after every success_window consecutive successes. Default is 1.

success_window

Number of consecutive successful releases before the additive increase is applied. Default is 25.

cooldown_seconds

Default cooldown duration (seconds) applied after a rate-limit when the provider does not include a Retry-After header. Default is 2.0.

ceiling_overshoot

Fraction above the observed rate-limit ceiling that additive increase is allowed to probe before capping. Default is 0.10 (10% overshoot).

rampup_seconds

Optional startup ramp duration. When greater than zero, each throttle domain starts at one concurrent request and linearly ramps to its configured peak over this many seconds. A 429 aborts the startup ramp and switches to normal AIMD recovery. Default is 0.0 (disabled).

Initialization:

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

1DEFAULT_REDUCE_FACTOR: typing.ClassVar[float] = 0.75
1DEFAULT_ADDITIVE_INCREASE: typing.ClassVar[int] = 1
1DEFAULT_SUCCESS_WINDOW: typing.ClassVar[int] = 25
1DEFAULT_COOLDOWN_SECONDS: typing.ClassVar[float] = 2.0
1DEFAULT_CEILING_OVERSHOOT: typing.ClassVar[float] = 0.1
1DEFAULT_RAMPUP_SECONDS: typing.ClassVar[float] = 0.0
1reduce_factor: float = Field(...)
1additive_increase: int = Field(...)
1success_window: int = Field(...)
1cooldown_seconds: float = Field(...)
1ceiling_overshoot: float = Field(...)
1rampup_seconds: float = Field(...)
1class data_designer.config.run_config.RunConfig(
2 /,
3 **data: typing.Any
4)

Bases: data_designer.config.base.ConfigBase

Runtime configuration for dataset generation.

Groups configuration options that control generation behavior but aren’t part of the dataset configuration itself.

Parameters:

disable_early_shutdown

If True, disables the executor’s early-shutdown behavior entirely. Generation will continue regardless of error rate, and the early-shutdown exception will never be raised. Error counts and summaries are still collected. Default is False.

shutdown_error_rate

Error rate threshold (0.0-1.0) that triggers early shutdown when early shutdown is enabled. Default is 0.5.

shutdown_error_window

Minimum number of completed tasks before error rate monitoring begins. Must be >= 1. Default is 10.

buffer_size

Number of records to process in each batch during dataset generation. A batch is processed end-to-end (column generation, post-batch processors, and writing the batch to artifact storage) before moving on to the next batch. Must be > 0. Default is 1000.

non_inference_max_parallel_workers

Maximum number of worker threads used for non-inference cell-by-cell generators. Must be >= 1. Default is 4.

max_conversation_restarts

Maximum number of full conversation restarts permitted when generation tasks call ModelFacade.generate(...). Must be >= 0. Default is 5.

max_conversation_correction_steps

Maximum number of correction rounds permitted within a single conversation when generation tasks call ModelFacade.generate(...). Must be >= 0. Default is 0.

async_trace

If True, collect per-task tracing data when using the async engine (DATA_DESIGNER_ASYNC_ENGINE=1). Has no effect on the sync path. Default is False.

progress_bar

If True, display sticky ANSI progress bars instead of periodic log lines during generation. Requires a TTY; falls back to log lines in non-TTY environments. Default is False.

progress_interval

How often (in seconds) the async progress reporter emits a consolidated log block. Must be > 0. Default is 5.0.

jinja_rendering_engine

Template renderer used for engine-side Jinja evaluation. native uses Jinja2’s built-in sandbox with the standard filter set and fewer Data Designer-specific restrictions. secure uses Data Designer’s hardened sandbox with additional AST, filter, and output guards. Default is secure.

throttle

AIMD throttle tuning parameters. See ThrottleConfig for details.

Attributes:

disable_early_shutdown

If True, disables the executor’s early-shutdown behavior entirely. Generation will continue regardless of error rate, and the early-shutdown exception will never be raised. Error counts and summaries are still collected. Default is False.

shutdown_error_rate

Error rate threshold (0.0-1.0) that triggers early shutdown when early shutdown is enabled. Default is 0.5.

shutdown_error_window

Minimum number of completed tasks before error rate monitoring begins. Must be >= 1. Default is 10.

buffer_size

Number of records to process in each batch during dataset generation. A batch is processed end-to-end (column generation, post-batch processors, and writing the batch to artifact storage) before moving on to the next batch. Must be > 0. Default is 1000.

non_inference_max_parallel_workers

Maximum number of worker threads used for non-inference cell-by-cell generators. Must be >= 1. Default is 4.

max_conversation_restarts

Maximum number of full conversation restarts permitted when generation tasks call ModelFacade.generate(...). Must be >= 0. Default is 5.

max_conversation_correction_steps

Maximum number of correction rounds permitted within a single conversation when generation tasks call ModelFacade.generate(...). Must be >= 0. Default is 0.

async_trace

If True, collect per-task tracing data when using the async engine (DATA_DESIGNER_ASYNC_ENGINE=1). Has no effect on the sync path. Default is False.

progress_bar

If True, display sticky ANSI progress bars instead of periodic log lines during generation. Requires a TTY; falls back to log lines in non-TTY environments. Default is False.

progress_interval

How often (in seconds) the async progress reporter emits a consolidated log block. Must be > 0. Default is 5.0.

jinja_rendering_engine

Template renderer used for engine-side Jinja evaluation. native uses Jinja2’s built-in sandbox with the standard filter set and fewer Data Designer-specific restrictions. secure uses Data Designer’s hardened sandbox with additional AST, filter, and output guards. Default is secure.

throttle

AIMD throttle tuning parameters. See ThrottleConfig for details.

Initialization:

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

1disable_early_shutdown: bool = False
1shutdown_error_rate: float = Field(...)
1shutdown_error_window: int = Field(...)
1buffer_size: int = Field(...)
1non_inference_max_parallel_workers: int = Field(...)
1max_conversation_restarts: int = Field(...)
1max_conversation_correction_steps: int = Field(...)
1async_trace: bool = False
1progress_bar: bool = False
1progress_interval: float = Field(...)
1jinja_rendering_engine: data_designer.config.run_config.JinjaRenderingEngine = Field(...)
1throttle: data_designer.config.run_config.ThrottleConfig = Field(...)
1normalize_shutdown_settings() -> typing_extensions.Self

Normalize shutdown settings for compatibility.