Building Parallel Workflow

Now you'll create a workflow that runs your analysis steps in parallel for maximum performance.

Creating the Parallel Workflow

Add this workflow to your file:

typescript

export const parallelAnalysisWorkflow = createWorkflow({
  id: 'parallel-analysis-workflow',
  description: 'Run multiple content analyses in parallel',
  inputSchema: z.object({
    content: z.string(),
    type: z.enum(['article', 'blog', 'social']).default('article'),
  }),
  outputSchema: z.object({
    results: z.object({
      seo: z.object({
        seoScore: z.number(),
        keywords: z.array(z.string()),
      }),
      readability: z.object({
        readabilityScore: z.number(),
        gradeLevel: z.string(),
      }),
      sentiment: z.object({
        sentiment: z.enum(['positive', 'neutral', 'negative']),
        confidence: z.number(),
      }),
    }),
  }),
})
  .parallel([seoAnalysisStep, readabilityStep, sentimentStep])
  .then(
    createStep({
      id: 'combine-results',
      description: 'Combines parallel analysis results',
      inputSchema: z.object({
        'seo-analysis': z.object({
          seoScore: z.number(),
          keywords: z.array(z.string()),
        }),
        'readability-analysis': z.object({
          readabilityScore: z.number(),
          gradeLevel: z.string(),
        }),
        'sentiment-analysis': z.object({
          sentiment: z.enum(['positive', 'neutral', 'negative']),
          confidence: z.number(),
        }),
      }),
      outputSchema: z.object({
        results: z.object({
          seo: z.object({
            seoScore: z.number(),
            keywords: z.array(z.string()),
          }),
          readability: z.object({
            readabilityScore: z.number(),
            gradeLevel: z.string(),
          }),
          sentiment: z.object({
            sentiment: z.enum(['positive', 'neutral', 'negative']),
            confidence: z.number(),
          }),
        }),
      }),
      execute: async ({ inputData }) => {
        console.log('🔄 Combining parallel results...')

        return {
          results: {
            seo: inputData['seo-analysis'],
            readability: inputData['readability-analysis'],
            sentiment: inputData['sentiment-analysis'],
          },
        }
      },
    }),
  )
  .commit()

Understanding Parallel Data Flow

When steps run in parallel:

Each step receives the same input data
Steps execute simultaneously
Results are collected into an object with step IDs as keys
The next step receives all parallel results

Key Points

.parallel([step1, step2, step3]): Runs all steps simultaneously
Result object keys: Use the step IDs (e.g., "seo-analysis")
Combine step: Processes all parallel results together

Next, you'll test this parallel workflow and see the performance improvement!