@loopstack/prompt-example-workflow

A module for the Loopstack AI automation framework.

This module provides an example workflow demonstrating how to integrate an LLM using a simple prompt pattern.

Overview

The Prompt Example Workflow shows the most basic way to call an LLM in Loopstack—using a simple text prompt. It generates a haiku about a user-provided subject.

By using this workflow as a reference, you'll learn how to:

• Define workflow input arguments with default values
• Use the prompt parameter for simple LLM calls
• Interpolate arguments into prompts using template syntax
• Access tool results via the runtime object
• Display LLM responses as documents

This example is the ideal starting point for developers new to LLM integration in Loopstack.

Installation

See SETUP.md for installation and setup instructions.

How It Works

Key Concepts

1. Workflow Input

Define input parameters with default values using @Input:

@Input({
  schema: z.object({
    subject: z.string().default('coffee'),
  }),
})
args: {
  subject: string;
};

Configure the UI form in YAML:

ui:
  form:
    properties:
      subject:
        title: 'What should the haiku be about?'

2. Simple Prompt Pattern

Use the prompt parameter for straightforward LLM calls without conversation history. The tool call is given an id so its result can be referenced later:

- id: prompt
  from: start
  to: prompt_executed
  call:
    - id: llm_call
      tool: aiGenerateText
      args:
        llm:
          provider: openai
          model: gpt-4o
        prompt: Write a haiku about {{ args.subject }}

3. Accessing Results via Runtime

Instead of using assign to save results to workflow state, tool results are accessed through the runtime object. The path follows the pattern runtime.tools.<transitionId>.<toolCallId>.data:

- id: add_response
  from: prompt_executed
  to: end
  call:
    - tool: createDocument
      args:
        document: aiMessageDocument
        update:
          content: ${{ runtime.tools.prompt.llm_call.data }}

The TypeScript class declares the runtime types with the @Runtime() decorator:

@Runtime()
runtime: {
  tools: Record<'prompt', Record<'llm_call', ToolResult<AiMessageDocumentContentType>>>;
};

4. Argument Interpolation

Access workflow arguments in templates using args.<name>:

prompt: Write a haiku about {{ args.subject }}

Dependencies

This workflow uses the following Loopstack modules:

• @loopstack/core - Core framework functionality
• @loopstack/core-ui-module - Provides CreateDocument tool
• @loopstack/ai-module - Provides AiGenerateText tool and AiMessageDocument

About

Author: Jakob Klippel

License: Apache-2.0

Additional Resources

• Loopstack Documentation
• Getting Started with Loopstack
• Find more Loopstack examples in the Loopstack Registry