translation/source/documents/course/04-workflows/19-creating-conditional-steps.md

Creating Conditional Steps

Let's create two processing steps for different types of content: one for short and simple content, and one for everything else.

Assessment Step

First, create a step that analyzes content to determine which path to take:

const assessContentStep = createStep({
  id: "assess-content",
  description: "Assesses content to determine processing path",
  inputSchema: z.object({
    content: z.string(),
    type: z.enum(["article", "blog", "social"]).default("article"),
  }),
  outputSchema: z.object({
    content: z.string(),
    type: z.enum(["article", "blog", "social"]).default("article"),
    wordCount: z.number(),
    complexity: z.enum(["simple", "moderate", "complex"]),
    category: z.enum(["short", "medium", "long"]),
  }),
  execute: async ({ inputData }) => {
    const { content, type } = inputData;
    const words = content.trim().split(/\s+/);
    const wordCount = words.length;

    // Determine category by length
    let category: "short" | "medium" | "long" = "short";
    if (wordCount >= 50) category = "medium";
    if (wordCount >= 200) category = "long";

    // Determine complexity by average word length
    const avgWordLength =
      words.reduce((sum, word) => sum + word.length, 0) / wordCount;
    let complexity: "simple" | "moderate" | "complex" = "simple";
    if (avgWordLength > 5) complexity = "moderate";
    if (avgWordLength > 7) complexity = "complex";

    console.log(`📋 Assessment: ${category} content, ${complexity} complexity`);

    return {
      content,
      type,
      wordCount,
      complexity,
      category,
    };
  },
});

Quick Processing Step

For short, simple content:

const quickProcessingStep = createStep({
  id: "quick-processing",
  description: "Quick processing for short and simple content",
  inputSchema: z.object({
    content: z.string(),
    type: z.enum(["article", "blog", "social"]).default("article"),
    wordCount: z.number(),
    complexity: z.enum(["simple", "moderate", "complex"]),
    category: z.enum(["short", "medium", "long"]),
  }),
  outputSchema: z.object({
    processedContent: z.string(),
    processingType: z.string(),
    recommendations: z.array(z.string()),
  }),
  execute: async ({ inputData }) => {
    console.log("⚡ Quick processing for short and simple content...");

    return {
      processedContent: inputData.content,
      processingType: "quick",
      recommendations: [
        "Content is concise",
        "Consider expanding for more detail",
      ],
    };
  },
});

General Processing Step

For all other content (not short and simple):

const generalProcessingStep = createStep({
  id: "general-processing",
  description: "General processing for all other content",
  inputSchema: z.object({
    content: z.string(),
    type: z.enum(["article", "blog", "social"]).default("article"),
    wordCount: z.number(),
    complexity: z.enum(["simple", "moderate", "complex"]),
    category: z.enum(["short", "medium", "long"]),
  }),
  outputSchema: z.object({
    processedContent: z.string(),
    processingType: z.string(),
    recommendations: z.array(z.string()),
  }),
  execute: async ({ inputData }) => {
    console.log("📝 General processing for non-short/simple content...");

    // Simulate more involved processing
    await new Promise((resolve) => setTimeout(resolve, 500));

    return {
      processedContent: inputData.content,
      processingType: "general",
      recommendations: [
        "Consider simplifying content",
        "Break up long paragraphs",
        "Add examples or explanations if needed",
      ],
    };
  },
});

These two steps will be used in different branches based on the content assessment. Next, you'll create the conditional workflow!