HumanSignal/label-studio · error · ValueError

Failed to create {transition_class.__name__}: {e}

Error message

Failed to create {transition_class.__name__}: {e}

What it means

create_transition_from_dict instantiates a transition class from a dict of data and re-raises any construction failure as ValueError with the class name and original error. It is a validation wrapper: the transition's __init__ rejected the supplied data.

Source

Thrown at label_studio/fsm/transition_utils.py:126

    """
    Create a transition instance from a dictionary of data.

    This handles Pydantic validation and provides clear error messages.

    Args:
        transition_class: The transition class to instantiate
        data: Dictionary of transition data

    Returns:
        Validated transition instance

    Raises:
        ValueError: If data validation fails
    """
    try:
        return transition_class(**data)
    except Exception as e:
        raise ValueError(f'Failed to create {transition_class.__name__}: {e}')


def get_transition_schema(transition_class: Type[BaseTransition]) -> Dict[str, Any]:
    """
    Get the JSON schema for a transition class.

    Useful for generating API documentation or frontend forms.

    Args:
        transition_class: The transition class

    Returns:
        JSON schema dictionary
    """
    return transition_class.model_json_schema()


def validate_transition_data(transition_class: Type[BaseTransition], data: Dict[str, Any]) -> Dict[str, List[str]]:

View on GitHub (pinned to 0b49e9b539)

Solutions

1. Read the chained message '{e}' to see which field failed validation.
2. Validate the payload against get_transition_schema(transition_class) before constructing.
3. Fix the data dict to include all required fields with correct types.
4. On the caller side, catch ValueError and return a 400-style validation error to the API client.

Example fix

// before
transition = create_transition_from_dict(StartTaskTransition, {"foo": 1})
// after
schema = get_transition_schema(StartTaskTransition)
validate_against_schema(schema, data)  # raises clear field errors first
transition = create_transition_from_dict(StartTaskTransition, {"task_id": 1, "assigned_user_id": 2})

schema = get_transition_schema(StartTaskTransition)
# validate payload against schema before construction
jsonschema.validate(instance=data, schema=schema)

def is_valid_transition_payload(cls, data: dict) -> bool:
    try:
        cls(**data)
        return True
    except Exception:
        return False

try:
    t = create_transition_from_dict(StartTaskTransition, data)
except ValueError as e:
    return Response({'detail': str(e)}, status=400)

When it happens

Trigger: Calling create_transition_from_dict(TransitionClass, data) where data is missing required fields, has wrong types, or fails pydantic-style validation in BaseTransition.__init__.

Common situations: Deserialized JSON payloads missing required keys; string/None values where ints or enums are expected; extra/unknown keys rejected by strict models; API clients sending malformed transition payloads.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

• transition_name: Unknown transition for this entity
• transition_name: Transition is auto-triggered and cannot be
• detail: {pydantic validation message}
• detail: {transition validation message}
• Transition validation failed for {self.transition_name}

AI-assisted analysis of HumanSignal/label-studio@0b49e9b539 (2026-08-29). Data as JSON: /api/errors/a4d18c42c7f3c971. Report an issue: GitHub.