Input Data in Agent Catalyst Workflows

Agent Catalyst workflows can leverage input data in two main ways to process and generate meaningful outputs:

1. Static Data: Predefined and embedded directly in the workflow.

2. User Input: Dynamically provided by the user at runtime.

---

Static Data

Static data is defined in the workflow’s frontmatter metadata using the data field. These values are accessible throughout the workflow during execution.

Example: Static Data

yaml ---  
data:  
  quote: "The only limit to our realization of tomorrow is our doubts of today."  
  langs:  
    - Spanish  
    - Italian  
    - German  
    - French  
---  

<Loop  
  as="translations"  
  until={$.index === langs.length}  
  provide={{ langs, quote }}>  
  Translate "{quote}" into {langs[$.index]}.  
  <GenText as="translation" model="openai:gpt-4o" />  
</Loop>

• Accessing Data: Reference static data fields like quote or langs using {} syntax, e.g., {quote} or {langs}.

• Complex Structures: Data can include simple strings, nested objects, or arrays.

---

User Input

User inputs allow workflows to be reusable by prompting for specific input values during execution. Inputs are defined using the input field in the frontmatter metadata.

Example: User Input

yaml ---  
data:  
  langs:  
    - Spanish  
    - Italian  
    - German  
    - French  
input:  
  quote:  
    type: text  
    message: "Enter a quote you'd like to translate:"  
---  

<Loop  
  as="translations"  
  until={$.index === langs.length}  
  provide={{ langs, quote }}>  
  Translate "{quote}" into {langs[$.index]}.  
  <GenText as="translation" model="openai:gpt-4o" />  
</Loop>

• Dynamic Prompts: The user is prompted to input a quote during execution.

• Reusability: The workflow adapts to different inputs without modification.

---

Input Types

Agent Catalyst supports diverse input types for flexible user interaction. Inputs are specified as key-value pairs under the input field.

1. Text Input

Prompts the user for a single-line or multi-line text.

Field	Type	Description	Required
type	string	Must be "text".	✅
message	string	Prompt displayed to the user.	✅
multiline	boolean	Allows multi-line input (default: false).	❌

Example:

yaml quote:  
  type: text  
  message: "Enter your favorite quote:"  
  multiline: false  

2. Select Input

Prompts the user to choose from a list of options.

Field	Type	Description	Required
type	string	Must be "select".	✅
options	array	List of options (strings or objects).	✅

Example:

yaml language:  
  type: select  
  message: "Select a language for translation:"  
  options:  
    - Spanish  
    - French  
    - German  

3. File Input

Prompts the user to upload a file or specify a file path.

Field	Type	Description	Required
type	string	Must be "file".	✅
fileType	string	File type ("text" or "image").	✅

Example:

yaml upload:  
  type: file  
  fileType: text  
  message: "Upload a text file for processing:"  

4. Array Input

Prompts the user to enter multiple text values, which are returned as an array.

Field	Type	Description	Required
type	string	Must be "array".	✅
multiline	boolean	Allows multi-line input.	❌

Example:

yaml languages:  
  type: array  
  message: "Enter a list of languages for translation:"  
  multiline: true  

---

Variable Naming Rules

• Uniqueness: All variable names (from inputs or actions) must be unique within the workflow. Duplicate names will cause a compilation error.

• Nested Scopes: Variables can be reused within nested scopes (e.g., within <Loop /> or <Cond />).

Example of Block Scoping:

yaml <Loop  
  as="outer"  
  until={$.index === items.length}  
  provide={{ item: items[$.index] }}>  

  Item: {item.name}  

  <Loop  
    as="inner"  
    until={$.index === item.subitems.length}  
    provide={{ subitem: item.subitems[$.index] }}>  

    Subitem: {subitem.name}  

  </Loop>  
</Loop>

In this example:

• item and subitem are scoped to their respective loops.

• Parent variables must be explicitly passed using provide.

---