ORCFLO Documentation

Overview

The Input component can define what data your workflow expects and creates a user-friendly interface for providing that data.

Whether you're building a simple text processing workflow or a complex multi-step automation, the Input component ensures your workflow receives the data it needs in a structured, validated format.

Input Types

Choose the appropriate input type based on the data you need to collect.

Type	Description	Use Case
Text	Single-line text input	Names, titles, keywords
Long Text	Multi-line textarea	Articles, descriptions, code
Number	Numeric input with constraints	Counts, limits, quantities
Boolean	True/false toggle	Feature flags, options
Select	Dropdown with predefined options	Categories, modes
File	File upload	Documents, images, data files

Configuration

Configure each input field with these settings.

Variable Name

The identifier used to reference this input throughout your workflow. Use descriptive, snake_case names for clarity.

Good Variable Names

customer_email
article_content
word_count
include_summary

Display Label

Human-readable label shown to users when they run the workflow. Make it clear what data is expected.

Description

Help text that appears below the input field. Use this to provide examples or clarify expectations.

Default Value

Pre-populate the input with a sensible default. Users can override this when running the workflow.

Required

Toggle whether this input must be provided. Required inputs prevent the workflow from running if left empty.

Using Variables

Input data is automatically passed to connected nodes in your workflow. When you connect an Input node to an AI Model node, the input values are provided as context for the AI to process.

Example: Blog Post Generator

Input Configuration:

json

{
  "topic": { "type": "text", "label": "Blog Topic" },
  "tone": { "type": "select", "options": ["professional", "casual", "technical"] },
  "word_count": { "type": "number", "default": 800 }
}

AI Model task instructions:

text

Write a blog post about the provided topic.
Use the specified tone throughout the article.
Target the requested word count.

Automatic Data Flow

Input values are automatically available to downstream nodes. Simply connect your Input node to the next step in your workflow.

Attaching Files

Input steps can include files from your file library, making them available to all downstream steps in your workflow. This is useful for providing reference documents, images, or data files that the workflow will use.

How to Add Files

Open Configuration

Click the "Configure" button on your Input step node.

Find Files Section

Scroll to the "Files" section in the configuration modal.

Select from Library

Click "Add Files" to browse your file library and select files to attach.

File Display

Attached files appear on the Input node card itself, showing up to 2 files with a "+N more" indicator if additional files are attached. This gives you a quick visual reference of what files are included in the input.

Files Flow Downstream

Files attached to an Input step are automatically available to all connected downstream steps. You don't need to re-attach them to each step - they flow through the workflow just like the task content.

Validation

Add validation rules to ensure inputs meet your requirements.

Input Type	Validation Options
Text	Min/max length, pattern matching (regex), email/URL format
Number	Min/max value, integer only, step increment
File	Accepted file types, maximum file size

Use Cases

Common input configurations for different workflows.

Content generation: topic, tone, length, audience
Data processing: file upload, format selection, filters
Email automation: recipient, subject, template variables
API integrations: endpoint, parameters, authentication
Report generation: date range, metrics selection, format
Translation: source text, target language, formality
Code generation: requirements, language, framework
Customer support: ticket content, priority, category

Best Practices

Use descriptive variable names: Clear names like customer_email are easier to understand than just email.
Provide helpful descriptions: Include examples or format expectations to guide users.
Set sensible defaults: Pre-populate common values to speed up workflow execution.
Only require what's necessary: Make fields optional when the workflow can function without them.

Input Order Matters

Inputs are displayed to users in the order they're defined. Put the most important inputs first for a better user experience.

Key Takeaways

Input components define what data your workflow needs to run
Choose the appropriate input type (text, number, file, etc.) for each field
Use clear variable names and helpful descriptions
Input data flows automatically to connected downstream nodes
Add validation to ensure data quality before processing

Input Component