# Inputs ZBrain supports a wide array of input options to enhance data handling and processing capabilities. ### **How to Use Different Input Components in ZBrain Flow?** To use different input components, choose from a range of input options. * Json: Add JSON. * Long text: Add Long Text. * Number: Add a Number. * Read File: Read a file from the file system. * Text: Add Text. * Text List: Add Text List. #### **Additional Settings for Text Component** **Text Field:** You can enter or dynamically capture text, such as webhook responses or user inputs, to be used within your workflow. #### **Additional Settings for Text List Component** **Add Item**: Enables the addition of individual text entries to the list, facilitating the compilation of multiple discrete data points. #### **Additional Settings for Long Text List Component** **Text**: Enables entering long text input. #### **Additional Settings for Number Component** **Number:** Enables entering number input. #### **Additional Settings for JSON Input Component** This component allows you to input structured data in JSON format, enabling complex data manipulation and parameterization within your workflow. * **Json Field**: Enter or paste JSON data directly into this field to be used in the workflow. #### **Additional Settings for Reading File Input** This component allows you to input and read data from a file directly within your workflow. * **File**: Upload the file that you wish to read. This field accepts various file formats depending on your workflow requirements. * **Output Format**: Select the desired format for the output data after the file is read, such as text or Base64 format. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.zbrain.ai/zbrain-documentation/zbrain-builder/flows/flow-components/inputs.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.