invoke-ai/InvokeAI · error · UnsupportedWorkflowNodeError

call_saved_workflow generator node '{generator_node_data.get

Error message

call_saved_workflow generator node '{generator_node_data.get('id')}' is missing generator input

What it means

After confirming the node is otherwise well-formed, _resolve_generator_items looks for inputs.generator and requires it to be a mapping. A missing or non-mapping 'generator' input means the node has no generator configuration, so it raises this error naming the offending node id.

Source

Thrown at invokeai/app/services/session_processor/workflow_call_batch.py:410

        "integer_generator_linear_distribution",
        "integer_generator_random_distribution_uniform",
        "string_generator_dynamic_prompts_random",
    }:
        return int(value.get("count", 10))
    return None


def _resolve_generator_items(
    generator_node: Mapping[str, Any], services: Any, user_id: str | None, maximum_items: int
) -> list[Any]:
    generator_node_data = generator_node["data"]
    node_type = generator_node_data.get("type")
    inputs = generator_node_data.get("inputs")
    if not isinstance(node_type, str) or not _is_mapping(inputs):
        raise UnsupportedWorkflowNodeError("call_saved_workflow generator node is malformed")
    generator_input = inputs.get("generator")
    if not _is_mapping(generator_input):
        raise UnsupportedWorkflowNodeError(
            f"call_saved_workflow generator node '{generator_node_data.get('id')}' is missing generator input"
        )
    generator_value = generator_input.get("value")
    if not _is_mapping(generator_value):
        raise UnsupportedWorkflowNodeError(
            f"call_saved_workflow generator node '{generator_node_data.get('id')}' has invalid generator value"
        )
    declared_item_count = _get_declared_generator_item_count(generator_value)
    if declared_item_count is not None and declared_item_count > maximum_items:
        raise TooManySessionsError("call_saved_workflow exceeds remaining queue capacity for child workflow executions")
    if node_type == "integer_generator":
        return _resolve_integer_generator(generator_value)
    if node_type == "float_generator":
        return _resolve_float_generator(generator_value)
    if node_type == "string_generator":
        return _resolve_string_generator(generator_value)
    if node_type == "image_generator":
        return _resolve_image_generator(generator_value, services, user_id)

View on GitHub (pinned to 0b6a024f2f)

Solutions

  1. Add a valid mapping under data.inputs.generator of the generator node (with a 'value' mapping inside)
  2. Re-save the workflow from the InvokeAI UI to regenerate the correct input structure
  3. Delete and re-add the generator node to recreate its default inputs

Example fix

// before
{"data": {"type": "string_generator", "inputs": {"count": {"value": 5}}}}
// after
{"data": {"type": "string_generator", "inputs": {"generator": {"value": {"count": 5, "start": 0, "stop": 10, "step": 1}}}}}
Defensive patterns

Strategy: validation

Validate before calling

inputs = node["data"]["inputs"]
if not isinstance(inputs.get("generator"), dict):
    raise ValueError(f"generator node {node['data']['id']} lacks a mapping inputs.generator")

Type guard

def has_generator_input(node: dict) -> TypeGuard[dict]:
    return isinstance(node.get("data", {}).get("inputs", {}).get("generator"), Mapping)

Try / catch

try:
    build_batch_child_workflow_session_results(...)
except UnsupportedWorkflowNodeError as e:
    if "missing generator input" in str(e):
        fix_node_generator_input(extract_node_id(str(e)))

Prevention

When it happens

Trigger: An integer/float/string/image generator node whose data.inputs either omits the 'generator' key or stores a non-mapping (e.g. a plain value or list) at inputs.generator.

Common situations: Older workflow formats where generator config lived elsewhere; workflow JSON edited by scripts that wrote generator config at the wrong level; partially migrated saved workflows.

Understand the failure class

Background: "Missing required field" and "field is required" errors: why libraries reject payloads that omit mandatory fields — this error's family across 20 libraries.

Related errors

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/d8bee9953ddf0555. Report an issue: GitHub.