dbt-labs/dbt-core · error

is_uniform: config.model is required

Error message

is_uniform: config.model is required: {e}

What it means

Raised in `is_uniform` when `config.get_attr("model")` fails because the config argument has no `model` attribute. `is_uniform` needs config.model to determine whether the model targets a Uniform catalog, so a config missing this attribute is an InvalidArgument error.

Solutions

  1. Provide a config object that includes a `model` attribute referencing the model node
  2. Prefer the model's real config object (model.config) in callers
  3. Guard with `config.get('model') is defined` / `is not none` before invoking
  4. Check the suffix of the message for the underlying attribute error

Example fix

// before (Jinja)
{% if is_uniform({'materialized': 'view'}) %}...{% endif %}
// after
{% if is_uniform(model.config) %}...{% endif %}
Defensive patterns

Strategy: validation

Validate before calling

{% if config is not mapping or config.get('model') is none %}
  {{ exceptions.raise_compiler_error("is_uniform requires config with a model attribute") }}
{% endif %}

Try / catch

{% set cfg = config if (config is mapping and config.get('model')) else model.config %}
{% if is_uniform(cfg) %}...{% endif %}

Prevention

When it happens

Trigger: Calling `is_uniform(config)` with a dict or object lacking `model`, or with an unrelated config-like object; also when config.model was renamed or omitted by the calling macro.

Common situations: Custom macros probing uniform support with hand-built config dicts; passing a partial config in tests; internal changes to where the model reference lives on config.

Understand the failure class

Background: "is required", "must be set", "missing required field": configuration validation errors across open-source libraries — this error's family across 36 libraries.

Related errors

AI-assisted analysis of dbt-labs/dbt-core@0267ce9170 (2026-09-07). Data as JSON: /api/errors/a3181a3311681f83. Report an issue: GitHub.

Appendix: source

Thrown at crates/dbt-adapter/src/adapter/mod.rs:2962

    /// https://github.com/databricks/dbt-databricks/blob/bfcb5c7c7714e97e67023119f674d2938b04acb0/dbt/adapters/databricks/impl.py#L256C6-L256C7
    ///
    /// ```python
    /// def is_uniform(self, config: BaseConfig) -> bool:
    /// ```
    #[tracing::instrument(skip(self, state), level = "trace")]
    pub fn is_uniform(&self, state: &State, args: &[Value]) -> Result<Value, minijinja::Error> {
        match &self.inner {
            Typed { adapter, .. } => {
                if adapter.adapter_type() != AdapterType::Databricks {
                    unimplemented!("is_uniform is only supported in Databricks")
                }

                let iter = ArgsIter::new("is_uniform", &["config"], args);
                let config_val = iter.next_arg::<&Value>()?;
                iter.finish()?;

                let model_val = config_val.get_attr("model").map_err(|e| {
                    minijinja::Error::new(
                        minijinja::ErrorKind::InvalidArgument,
                        format!("is_uniform: config.model is required: {e}"),
                    )
                })?;
                let config = minijinja_value_to_typed_struct::<ModelConfig>(config_val.clone())
                    .map_err(|e| {
                        minijinja::Error::new(
                            minijinja::ErrorKind::SerdeDeserializeError,
                            e.to_string(),
                        )
                    })?;
                let node = minijinja_value_to_typed_struct::<InternalDbtNodeWrapper>(model_val)
                    .map_err(|e| {
                        minijinja::Error::new(
                            minijinja::ErrorKind::SerdeDeserializeError,
                            e.to_string(),
                        )
                    })?;

View on GitHub (pinned to 0267ce9170)