Additional task settings

This page covers task configuration parameters that do not have their own dedicated page: naming and metadata, environment variables, and inline I/O thresholds.

For the full list of all task configuration parameters, see Configure tasks.

The name parameter on TaskEnvironment is required. It is combined with each task function name to form the fully-qualified task name. For example, if you define a TaskEnvironment with name="my_env" and a task function my_task, the fully-qualified task name is my_env.my_task.

The name must use snake_case or kebab-case and is immutable once set.

`short_name`

The short_name parameter on @env.task (and override()) overrides the display name of a task in the UI graph view. By default, the display name is the Python function name. Overriding short_name does not change the fully-qualified task name.

        
import flyte

env = flyte.TaskEnvironment(name="my_env")

@env.task(short_name="Train Model")
def train(data: list) -> dict:
    return {"accuracy": 0.95}

`description`

The description parameter on TaskEnvironment provides a description of the task environment (max 255 characters). It is used for organizational purposes and can be viewed in the UI.

`docs`

The docs parameter on @env.task accepts a Documentation object. If not set explicitly, the documentation is auto-extracted from the task function’s docstring.

        
    
import flyte
from flyte import Documentation

env = flyte.TaskEnvironment(name="my_env")

@env.task(docs=Documentation(description="Trains a model on the given dataset."))
def train(data: list) -> dict:
    """This docstring is used if docs is not set explicitly."""
    return {"accuracy": 0.95}

`report`

The report parameter on @env.task controls whether an HTML report is generated for the task. See Reports for details.

`links`

The links parameter on @env.task (and override()) attaches clickable URLs to tasks in the UI. Use links to connect tasks to external tools like experiment trackers, monitoring dashboards, or logging systems.

Links are defined by implementing the Link protocol. See Links for full details on creating and using links.

Environment variables

The env_vars parameter on TaskEnvironment injects plain-text environment variables into the task container. It accepts a Dict[str, str].

        
    
import flyte

env = flyte.TaskEnvironment(
    name="my_env",
    env_vars={
        "LOG_LEVEL": "DEBUG",
        "API_ENDPOINT": "https://api.example.com",
    },
)

@env.task
def my_task() -> str:
    import os
    return os.environ["API_ENDPOINT"]

Environment variables can be overridden at the task.override() invocation level (unless reusable is in effect).

Use env_vars for non-sensitive configuration values. For sensitive values like API keys and credentials, use secrets instead.

Inline I/O threshold

The max_inline_io_bytes parameter on @env.task (and override()) controls the maximum size for data passed directly in the task request and response (e.g., primitives, strings, dictionaries).

Data exceeding this threshold raises an InlineIOMaxBytesBreached error.

The default value is 10 MiB (10 * 1024 * 1024 bytes).

This setting does not affect flyte.io.File, flyte.io.Dir, or flyte.DataFrame, which are always offloaded to object storage regardless of size.

        
    
import flyte

env = flyte.TaskEnvironment(name="my_env")

# Allow up to 50 MiB of inline data
@env.task(max_inline_io_bytes=50 * 1024 * 1024)
def process_large_dict(data: dict) -> dict:
    return {k: v * 2 for k, v in data.items()}