Booth AI


Implements a filtering mechanism that assesses data against user-defined conditions to determine its eligibility for further processing. This node is capable of applying a variety of filters based on numerical values, existence checks, and boolean evaluations, among others. It's essential for refining datasets, ensuring that only entries meeting specific criteria advance in the workflow, which is particularly beneficial for maintaining data integrity and relevance. Inputs: - condition_type: Defines the filter's nature, guiding what condition it applies (e.g., numerical comparison, emptiness check). - condition: The detailed specification of the condition, relevant to its type, optionally used for more complex checks. - value: The piece of data subjected to filtering. - condition_value: The benchmark for comparison or evaluation against the input value. - output_blank_value: Flags whether to emit a blank output for inputs failing the condition check. Output: - filtered_output: Yields either the verified input data or a blank value based on the condition fulfillment and configuration.

Condition Type
The type of condition to apply for filtering.
Output Blank Value
Indicates if a blank value should be returned for non-matching data.
The output string