Quickstart

private func createWorkflowTasks(
    mealPlannerAgent: Agent,
    recipeResearchAgent: Agent,
    shoppingListAgent: Agent
) -> (ORTask, ORTask, ORTask) {
    
    // Task 1: Meal Planning
    let planningTask = ORTask(
        description: """
        Create a 7-day meal plan for a family of 4 with the following requirements:
        - 2 adults, 2 children (ages 8 and 12)
        - Budget: $150 per week
        - Dietary preferences: Reduce processed foods, include more vegetables
        - Allergies: One child has a mild nut allergy
        - Cooking time: Maximum 45 minutes per meal on weekdays, unlimited on weekends
        - Must include: 7 breakfasts, 7 lunches, 7 dinners
        
        Consider seasonal ingredients (current season), nutritional balance, 
        and variety in cuisines and flavors.
        """,
        expectedOutput: """
        A detailed 7-day meal plan formatted as follows:
        - Day-by-day breakdown (Monday through Sunday)
        - Each day should include breakfast, lunch, and dinner
        - Estimated prep time for each meal
        - Nutritional highlights
        - Special notes for dietary considerations
        - Total estimated weekly cost
        """,
        agent: await mealPlannerAgent.id,
        outputFormat: .markdown,
        maxExecutionTime: 120,
        guardrails: [.noHarmfulContent]
    )
    
    // Task 2: Recipe Research (depends on meal planning)
    let researchTask = ORTask(
        description: """
        Based on the meal plan from the previous task, research and provide detailed recipes 
        for each meal.
        
        Previous meal plan: {task_0_output}
        
        Research priority should be given to meals that are:
        - Family-friendly and kid-approved
        - Use common, easily-found ingredients
        - Have good nutritional balance
        - Fit within the time constraints specified
        """,
        expectedOutput: """
        A comprehensive recipe collection with step-by-step instructions, 
        ingredient lists, and cooking tips for each meal.
        """,
        agent: await recipeResearchAgent.id,
        context: [planningTask.id],  // Depends on meal planning task
        outputFormat: .markdown,
        maxExecutionTime: 180,
        guardrails: [.noHarmfulContent]
    )
    
    // Task 3: Shopping List Generation (depends on recipe research)
    let shoppingTask = ORTask(
        description: """
        Create an organized shopping list based on all the recipes from the previous task.
        
        Recipe collection: {task_1_output}
        
        Requirements:
        1. Consolidate duplicate ingredients across all recipes
        2. Calculate total quantities needed for the week
        3. Organize by grocery store sections
        4. Include estimated prices and total budget
        """,
        expectedOutput: """
        A comprehensive shopping list organized by store sections with quantities, 
        estimated prices, and shopping tips.
        """,
        agent: await shoppingListAgent.id,
        context: [researchTask.id],  // Depends on recipe research task
        outputFormat: .markdown,
        maxExecutionTime: 90,
        guardrails: [.noHarmfulContent]
    )
    
    return (planningTask, researchTask, shoppingTask)
}

func execute() async throws {
    print("👨‍🍳 Building Recipe Preparation Orbit...")
    
    // Create specialized agents
    let mealPlannerAgent = createMealPlannerAgent()
    let recipeResearchAgent = createRecipeResearchAgent()
    let shoppingListAgent = createShoppingListAgent()
    
    // Define the workflow tasks
    let (planningTask, researchTask, shoppingTask) = createWorkflowTasks(
        mealPlannerAgent: mealPlannerAgent,
        recipeResearchAgent: recipeResearchAgent,
        shoppingListAgent: shoppingListAgent
    )
    
    // Create the orbit
    let orbit = try await Orbit.create(
        name: "Recipe Prep Orbit",
        description: "Multi-agent system for meal planning and preparation",
        agents: [mealPlannerAgent, recipeResearchAgent, shoppingListAgent],
        tasks: [planningTask, researchTask, shoppingTask],
        process: .sequential,
        verbose: true,
        memory: true,
        usageMetrics: true
    )
    
    print("🎯 Executing Recipe Prep Workflow...")
    
    // Execute the orbit and get results
    let result = try await orbit.start()
    
    // Display results
    await displayResults(result)
}

# Build the project
swift build

# Run your recipe prep workflow
swift run

🚀 OrbitAI Recipe Prep System Starting...
👨‍🍳 Building Recipe Preparation Orbit...
🎯 Executing Recipe Prep Workflow...

[Agent: Meal Planning Specialist] Starting task: Create a 7-day meal plan...
[Agent: Meal Planning Specialist] Task completed successfully

[Agent: Recipe Research Specialist] Starting task: Research detailed recipes...
[Agent: Recipe Research Specialist] Using context from previous task...
[Agent: Recipe Research Specialist] Task completed successfully

[Agent: Shopping List Organizer] Starting task: Generate organized shopping list...
[Agent: Shopping List Organizer] Using context from recipe collection...
[Agent: Shopping List Organizer] Task completed successfully

🎉 Recipe Prep Workflow Complete!
=====================================
📊 Execution Summary:
   • Total tokens used: 4,521
   • Completion tokens: 3,089
   • Prompt tokens: 1,432

✅ Results saved to local files!