infiniflow/ragflow · error · ValueError

{} not supported, should be 0 or positive integer

Error message

 {} not supported, should be 0 or positive integer

What it means

check_nonnegative_integer raises when a param is not an int type (note: it accepts the legacy name 'long') or is negative. Enforces counts, limits, and sizes that may be zero but not negative.

Source

Thrown at agent/component/base.py:266

                    raise ValueError("Please check runtime conf, {} = {} does not match user-parameter restriction".format(variable, value))

            elif variable in validation_json:
                self._validate_param(attr, validation_json)

    @staticmethod
    def check_string(param, description):
        if type(param).__name__ not in ["str"]:
            raise ValueError(description + " {} not supported, should be string type".format(param))

    @staticmethod
    def check_empty(param, description):
        if not param:
            raise ValueError(description + " does not support empty value.")

    @staticmethod
    def check_nonnegative_integer(param, description):
        if type(param).__name__ not in ["int", "long"] or param < 0:
            raise ValueError(description + " {} not supported, should be 0 or positive integer".format(param))

    @staticmethod
    def check_positive_integer(param, description):
        if type(param).__name__ not in ["int", "long"] or param <= 0:
            raise ValueError(description + " {} not supported, should be positive integer".format(param))

    @staticmethod
    def check_positive_number(param, description):
        if type(param).__name__ not in ["float", "int", "long"] or param <= 0:
            raise ValueError(description + " {} not supported, should be positive numeric".format(param))

    @staticmethod
    def check_nonnegative_number(param, description):
        if type(param).__name__ not in ["float", "int", "long"] or param < 0:
            raise ValueError(description + " {} not supported, should be non-negative numeric".format(param))

    @staticmethod
    def check_decimal_float(param, description):

View on GitHub (pinned to 554fb1133a)

Solutions

  1. Set the value to an int >= 0 (if 'unlimited' semantics are needed, use the component's documented max or a large int, not -1).
  2. Coerce types at the boundary: int(value) before it reaches the component.
  3. Fix UI inputs to emit proper numeric types.
  4. Check for float drift in computed configs and round/cast to int.

Example fix

# before
params = {"top_n": "5"}   # string -> fails
# before
params = {"top_n": -1}    # negative -> fails

# after
params = {"top_n": 5}
Defensive patterns

Strategy: type-guard

Validate before calling

def to_nonneg_int(v, field):
    if isinstance(v, bool) or not isinstance(v, int):
        raise ValueError(f'{field} must be int')
    if v < 0:
        raise ValueError(f'{field} must be >= 0')
    return v

Type guard

def is_nonneg_int(v) -> bool:
    return isinstance(v, int) and not isinstance(v, bool) and v >= 0

Try / catch

try:
    param.check()
except ValueError as e:
    if 'should be 0 or positive integer' in str(e):
        conf[field] = max(0, int(conf[field]))  # coerce then re-check
        param.update(conf); param.check()

Prevention

When it happens

Trigger: A component check() calling check_nonnegative_integer(param, description) where param is e.g. -1, a float like 1.5, or a string like "10" — top_n, retries, timeout counts, memory limits.

Common situations: Config forms returning strings for numeric inputs; passing -1 as a 'no limit' sentinel the validator does not accept; floats leaking in from computed values; YAML unquoted values parsing oddly.

Related errors

AI-assisted analysis of infiniflow/ragflow@554fb1133a (2026-08-15). Data as JSON: /api/errors/5ba348af4aff882f. Report an issue: GitHub.