AI Content Generation Services

import $, { ai, db, on, send } from 'sdk.do'

// Define the blog post generation service
const blogPostService = await $.Service.create({
  id: 'blog-post-generator',
  name: 'AI Blog Post Writer',
  description: 'Generate SEO-optimized blog posts on any topic',
  type: $.ServiceType.ContentGeneration,
  subtype: 'blog-posts',

  capabilities: ['long-form-content', 'seo-optimization', 'keyword-integration', 'image-suggestions', 'meta-generation'],

  pricing: {
    model: 'per-word',
    baseRate: 0.05, // $0.05 per word
    minimumCharge: 50.0, // Minimum $50 per article
    tiers: [
      { wordCount: { min: 0, max: 1000 }, rate: 0.05 },
      { wordCount: { min: 1001, max: 2500 }, rate: 0.04 },
      { wordCount: { min: 2501, max: Infinity }, rate: 0.03 },
    ],
    qualityModifiers: {
      standard: 1.0,
      premium: 1.5, // +50% for human review
      urgent: 2.0, // +100% for 1-hour delivery
    },
  },

  inputSchema: {
    topic: { type: 'string', required: true },
    keywords: { type: 'array', items: { type: 'string' }, required: true },
    wordCount: { type: 'number', default: 1500, min: 500, max: 5000 },
    tone: {
      type: 'string',
      enum: ['professional', 'casual', 'technical', 'conversational', 'formal'],
      default: 'professional',
    },
    audience: {
      type: 'string',
      enum: ['general', 'technical', 'business', 'academic'],
      default: 'general',
    },
    includeImages: { type: 'boolean', default: true },
    quality: {
      type: 'string',
      enum: ['standard', 'premium', 'urgent'],
      default: 'standard',
    },
  },

  outputSchema: {
    content: { type: 'string' },
    title: { type: 'string' },
    excerpt: { type: 'string' },
    wordCount: { type: 'number' },
    seo: {
      type: 'object',
      properties: {
        metaDescription: { type: 'string' },
        metaKeywords: { type: 'array' },
        ogTitle: { type: 'string' },
        ogDescription: { type: 'string' },
      },
    },
    images: {
      type: 'array',
      items: {
        type: 'object',
        properties: {
          position: { type: 'number' },
          caption: { type: 'string' },
          altText: { type: 'string' },
          searchQuery: { type: 'string' },
        },
      },
    },
    readabilityScore: { type: 'number' },
    uniquenessScore: { type: 'number' },
  },
})

// Handle blog post generation requests
on($.ServiceRequest.created, async (request) => {
  if (request.serviceId !== blogPostService.id) return

  try {
    // Update request status
    await send($.ServiceRequest.update, {
      requestId: request.id,
      status: 'processing',
      progress: 0.1,
    })

    // Research the topic to build context
    const research = await ai.generate({
      model: 'gpt-5',
      prompt: `Research the topic "${request.inputs.topic}" and provide:
        1. Key facts and statistics
        2. Current trends and developments
        3. Common questions and pain points
        4. Expert perspectives
        5. Related subtopics

        Keywords to incorporate: ${request.inputs.keywords.join(', ')}`,
      maxTokens: 1500,
    })

    await send($.ServiceRequest.update, {
      requestId: request.id,
      progress: 0.3,
    })

    // Generate the outline
    const outline = await ai.generate({
      model: 'gpt-5',
      prompt: `Create a detailed outline for a ${request.inputs.wordCount}-word blog post about "${request.inputs.topic}".

        Context: ${research.text}

        Requirements:
        - Tone: ${request.inputs.tone}
        - Audience: ${request.inputs.audience}
        - Keywords: ${request.inputs.keywords.join(', ')}

        Include:
        - Compelling headline
        - Introduction (hook + thesis)
        - 3-5 main sections with subheadings
        - Conclusion with call-to-action
        - Suggested image placements`,
      maxTokens: 1000,
    })

    await send($.ServiceRequest.update, {
      requestId: request.id,
      progress: 0.5,
    })

    // Generate the full article
    const article = await ai.generate({
      model: 'gpt-5',
      prompt: `Write a complete ${request.inputs.wordCount}-word blog post following this outline:

        ${outline.text}

        Research context: ${research.text}

        Guidelines:
        - Tone: ${request.inputs.tone}
        - Target audience: ${request.inputs.audience}
        - Naturally incorporate keywords: ${request.inputs.keywords.join(', ')}
        - Use examples and data where appropriate
        - Include transitions between sections
        - Write in an engaging, scannable format
        - End with a strong conclusion and clear call-to-action`,
      maxTokens: request.inputs.wordCount * 2,
      temperature: 0.7,
      quality: {
        minReadability: request.inputs.audience === 'technical' ? 50 : 60,
        keywordDensity: { min: 0.01, max: 0.03 },
        uniqueness: 0.95,
      },
    })

    await send($.ServiceRequest.update, {
      requestId: request.id,
      progress: 0.7,
    })

    // Generate SEO metadata
    const seo = await ai.generate({
      model: 'gpt-5',
      prompt: `Generate SEO metadata for this blog post:

        Title: ${outline.text.split('\n')[0]}
        Content preview: ${article.text.substring(0, 500)}...
        Keywords: ${request.inputs.keywords.join(', ')}

        Provide:
        1. Meta description (150-160 characters)
        2. Meta keywords (5-10 keywords)
        3. Open Graph title (60 characters max)
        4. Open Graph description (200 characters max)`,
      schema: {
        metaDescription: { type: 'string' },
        metaKeywords: { type: 'array', items: { type: 'string' } },
        ogTitle: { type: 'string' },
        ogDescription: { type: 'string' },
      },
    })

    // Generate image suggestions if requested
    let images = []
    if (request.inputs.includeImages) {
      const imagePrompt = await ai.generate({
        model: 'gpt-5',
        prompt: `Based on this blog post outline, suggest 3-5 relevant images:

          ${outline.text}

          For each image, provide:
          - Position in article (paragraph number)
          - Caption
          - Alt text for accessibility
          - Image search query

          Format as JSON array.`,
        schema: {
          images: {
            type: 'array',
            items: {
              type: 'object',
              properties: {
                position: { type: 'number' },
                caption: { type: 'string' },
                altText: { type: 'string' },
                searchQuery: { type: 'string' },
              },
            },
          },
        },
      })
      images = imagePrompt.data.images
    }

    await send($.ServiceRequest.update, {
      requestId: request.id,
      progress: 0.9,
    })

    // Extract title and create excerpt
    const lines = article.text.split('\n').filter((line) => line.trim())
    const title = lines[0].replace(/^#\s*/, '')
    const excerpt = lines.slice(1, 3).join(' ').substring(0, 200) + '...'

    // Calculate metrics
    const wordCount = article.text.split(/\s+/).length
    const readabilityScore = calculateReadability(article.text)
    const uniquenessScore = 0.98 // Would integrate with plagiarism checker

    // Deliver the completed blog post
    await send($.ServiceResult.deliver, {
      requestId: request.id,
      outputs: {
        content: article.text,
        title,
        excerpt,
        wordCount,
        seo: seo.data,
        images,
        readabilityScore,
        uniquenessScore,
      },
      format: 'markdown',
      quality: {
        readability: readabilityScore,
        uniqueness: uniquenessScore,
      },
    })

    // Calculate cost based on word count and quality tier
    const tier = blogPostService.pricing.tiers.find((t) => wordCount >= t.wordCount.min && wordCount <= t.wordCount.max)
    const baseRate = tier?.rate || blogPostService.pricing.baseRate
    const qualityMultiplier = blogPostService.pricing.qualityModifiers[request.inputs.quality] || 1.0
    const cost = Math.max(wordCount * baseRate * qualityMultiplier, blogPostService.pricing.minimumCharge)

    // Process payment
    await send($.Payment.charge, {
      customerId: request.customerId,
      amount: cost,
      description: `Blog Post: "${title}" (${wordCount} words)`,
      metadata: {
        serviceId: blogPostService.id,
        requestId: request.id,
        wordCount,
        quality: request.inputs.quality,
      },
    })

    // Update service analytics
    await db.update(blogPostService, {
      'metrics.totalPosts': { increment: 1 },
      'metrics.totalWords': { increment: wordCount },
      'metrics.totalRevenue': { increment: cost },
      'metrics.avgReadability': { average: readabilityScore },
    })
  } catch (error) {
    await send($.ServiceRequest.fail, {
      requestId: request.id,
      error: {
        code: 'GENERATION_FAILED',
        message: error.message,
        details: error,
      },
    })
  }
})

// Helper function to calculate readability score
function calculateReadability(text: string): number {
  const sentences = text.split(/[.!?]+/).length
  const words = text.split(/\s+/).length
  const syllables = words * 1.5 // Approximation

  // Flesch Reading Ease
  const score = 206.835 - 1.015 * (words / sentences) - 84.6 * (syllables / words)
  return Math.max(0, Math.min(100, score))
}

import $, { ai, db, on, send } from 'sdk.do'

const technicalDocsService = await $.Service.create({
  id: 'technical-docs-generator',
  name: 'Technical Documentation Writer',
  description: 'Generate API docs, user guides, and technical specifications',
  type: $.ServiceType.ContentGeneration,
  subtype: 'technical-documentation',

  pricing: {
    model: 'per-document',
    rates: {
      apiDocs: 200.0,
      userGuide: 150.0,
      technicalSpec: 300.0,
      tutorial: 100.0,
    },
  },
})

on($.ServiceRequest.created, async (request) => {
  if (request.serviceId !== technicalDocsService.id) return

  const { documentType, codebase, apiSpec, targetAudience } = request.inputs

  // Analyze codebase or API specification
  const analysis = await ai.generate({
    model: 'gpt-5',
    prompt: `Analyze this ${documentType} specification and extract:
      - Key components and their purposes
      - API endpoints or functions
      - Parameters and return values
      - Common use cases
      - Error scenarios

      Specification: ${apiSpec || codebase}`,
    maxTokens: 2000,
  })

  // Generate documentation structure
  const structure = await ai.generate({
    model: 'gpt-5',
    prompt: `Create a documentation outline for ${documentType}:

      Analysis: ${analysis.text}
      Target audience: ${targetAudience}

      Include:
      - Overview and introduction
      - Getting started guide
      - Detailed reference sections
      - Code examples
      - Best practices
      - Troubleshooting`,
    maxTokens: 1500,
  })

  // Generate each section with code examples
  const sections = await Promise.all(
    extractSections(structure.text).map(async (section) => {
      const content = await ai.generate({
        model: 'gpt-5',
        prompt: `Write the "${section.title}" section of the ${documentType} documentation.

          Context: ${analysis.text}
          Audience: ${targetAudience}

          Include:
          - Clear explanations
          - Code examples in multiple languages
          - Parameter descriptions
          - Response examples
          - Common pitfalls and solutions`,
        maxTokens: 3000,
      })

      return {
        title: section.title,
        content: content.text,
        level: section.level,
      }
    })
  )

  // Compile complete documentation
  const documentation = {
    title: `${documentType} Documentation`,
    sections,
    format: 'markdown',
    tableOfContents: generateTOC(sections),
    lastUpdated: new Date().toISOString(),
  }

  await send($.ServiceResult.deliver, {
    requestId: request.id,
    outputs: { documentation },
  })

  const cost = technicalDocsService.pricing.rates[documentType] || 200
  await send($.Payment.charge, {
    customerId: request.customerId,
    amount: cost,
    description: `Technical Documentation: ${documentType}`,
  })
})

function extractSections(outline: string) {
  return outline
    .split('\n')
    .filter((line) => line.match(/^#+\s/))
    .map((line) => ({
      title: line.replace(/^#+\s*/, ''),
      level: (line.match(/^#+/) || [''])[0].length,
    }))
}

function generateTOC(sections: any[]) {
  return sections.map((s) => ({
    title: s.title,
    level: s.level,
    anchor: s.title.toLowerCase().replace(/\s+/g, '-'),
  }))
}

import $, { ai, on, send } from 'sdk.do'

const marketingCopyService = await $.Service.create({
  id: 'marketing-copy-generator',
  name: 'Marketing Copy Writer',
  description: 'Generate ads, landing pages, emails, and social media content',
  type: $.ServiceType.ContentGeneration,
  subtype: 'marketing-copy',

  pricing: {
    model: 'per-piece',
    rates: {
      adCopy: 50.0,
      landingPage: 200.0,
      emailCampaign: 100.0,
      socialPost: 25.0,
      productDescription: 30.0,
    },
    packages: [
      {
        name: 'Social Media Bundle',
        includes: ['10 social posts', '5 ad copies'],
        price: 200.0,
        savings: 50.0,
      },
      {
        name: 'Launch Campaign',
        includes: ['1 landing page', '5 emails', '20 social posts', '10 ads'],
        price: 800.0,
        savings: 250.0,
      },
    ],
  },
})

on($.ServiceRequest.created, async (request) => {
  if (request.serviceId !== marketingCopyService.id) return

  const { contentType, product, audience, platform, tone, callToAction } = request.inputs

  // Analyze product and competitive landscape
  const productAnalysis = await ai.generate({
    model: 'gpt-5',
    prompt: `Analyze this product for marketing purposes:

      Product: ${product.name}
      Description: ${product.description}
      Features: ${product.features.join(', ')}
      Benefits: ${product.benefits.join(', ')}
      Target audience: ${audience}

      Identify:
      - Unique value propositions
      - Key differentiators
      - Emotional triggers
      - Pain points addressed
      - Competitive advantages`,
    maxTokens: 1000,
  })

  let copy: string

  switch (contentType) {
    case 'adCopy':
      copy = await generateAdCopy({
        product,
        audience,
        platform,
        tone,
        callToAction,
        analysis: productAnalysis.text,
      })
      break

    case 'landingPage':
      copy = await generateLandingPage({
        product,
        audience,
        tone,
        analysis: productAnalysis.text,
      })
      break

    case 'emailCampaign':
      copy = await generateEmailCampaign({
        product,
        audience,
        campaignType: request.inputs.campaignType,
        analysis: productAnalysis.text,
      })
      break

    case 'socialPost':
      copy = await generateSocialPost({
        product,
        platform,
        tone,
        analysis: productAnalysis.text,
      })
      break

    case 'productDescription':
      copy = await generateProductDescription({
        product,
        tone,
        analysis: productAnalysis.text,
      })
      break
  }

  // A/B test variations
  const variations = await ai.generate({
    model: 'gpt-5',
    prompt: `Create 2 alternative versions of this ${contentType}:

      Original: ${copy}

      For each variation:
      - Maintain the core message
      - Try different emotional appeals
      - Use different headline structures
      - Test different CTAs`,
    maxTokens: 2000,
  })

  await send($.ServiceResult.deliver, {
    requestId: request.id,
    outputs: {
      primaryCopy: copy,
      variations: parseVariations(variations.text),
      metadata: {
        wordCount: copy.split(/\s+/).length,
        characterCount: copy.length,
        readingTime: estimateReadingTime(copy),
        sentiment: 'positive',
        cta: callToAction,
      },
    },
  })

  const cost = marketingCopyService.pricing.rates[contentType]
  await send($.Payment.charge, {
    customerId: request.customerId,
    amount: cost,
    description: `Marketing Copy: ${contentType}`,
  })
})

async function generateAdCopy(params: any): Promise<string> {
  const result = await ai.generate({
    model: 'gpt-5',
    prompt: `Write compelling ad copy for ${params.platform}:

      Product: ${params.product.name}
      Analysis: ${params.analysis}
      Audience: ${params.audience}
      Tone: ${params.tone}

      Platform specs:
      ${getplatformSpecs(params.platform)}

      Include:
      - Attention-grabbing headline
      - Clear value proposition
      - Strong ${params.callToAction}
      - Urgency or scarcity element`,
    maxTokens: 500,
  })

  return result.text
}

async function generateLandingPage(params: any): Promise<string> {
  const result = await ai.generate({
    model: 'gpt-5',
    prompt: `Create landing page copy with high conversion focus:

      Product: ${params.product.name}
      Analysis: ${params.analysis}
      Audience: ${params.audience}

      Structure:
      1. Hero section (headline + subheadline)
      2. Value propositions (3-4 key benefits)
      3. Feature highlights with descriptions
      4. Social proof section
      5. FAQ section
      6. Final CTA section

      Tone: ${params.tone}
      Focus on conversion and trust-building.`,
    maxTokens: 3000,
  })

  return result.text
}

async function generateEmailCampaign(params: any): Promise<string> {
  const result = await ai.generate({
    model: 'gpt-5',
    prompt: `Write email campaign copy:

      Product: ${params.product.name}
      Campaign type: ${params.campaignType}
      Analysis: ${params.analysis}
      Audience: ${params.audience}

      Include:
      - Compelling subject line (+ 2 alternatives)
      - Preview text
      - Email body (personalized greeting, value prop, details, CTA)
      - P.S. with additional incentive

      Keep it conversational and benefit-focused.`,
    maxTokens: 1500,
  })

  return result.text
}

function getplatformSpecs(platform: string) {
  const specs = {
    facebook: 'Headline: 40 chars, Text: 125 chars, Link description: 30 chars',
    google: 'Headlines: 30 chars (3), Descriptions: 90 chars (2)',
    linkedin: 'Headline: 200 chars, Text: 600 chars',
    instagram: 'Caption: 2200 chars (but 125 visible), Hashtags: 30 max',
  }
  return specs[platform] || 'Standard format'
}

function parseVariations(text: string): string[] {
  return text
    .split(/Variation \d+:/)
    .slice(1)
    .map((v) => v.trim())
}

function estimateReadingTime(text: string): number {
  const words = text.split(/\s+/).length
  return Math.ceil(words / 200) // 200 words per minute
}

import $, { ai, on, send } from 'sdk.do'

const productDescriptionService = await $.Service.create({
  id: 'product-description-generator',
  name: 'E-commerce Description Writer',
  description: 'Generate SEO-optimized product descriptions for online stores',
  type: $.ServiceType.ContentGeneration,
  subtype: 'product-descriptions',

  pricing: {
    model: 'per-product',
    tiers: [
      { name: 'basic', price: 10.0, features: ['Short description', 'Bullet points'] },
      { name: 'standard', price: 25.0, features: ['Long description', 'SEO', 'Features'] },
      { name: 'premium', price: 50.0, features: ['All standard', 'A/B variations', 'Multi-channel'] },
    ],
    bulk: [
      { min: 10, max: 49, discount: 0.1 },
      { min: 50, max: 99, discount: 0.2 },
      { min: 100, max: Infinity, discount: 0.3 },
    ],
  },
})

on($.ServiceRequest.created, async (request) => {
  if (request.serviceId !== productDescriptionService.id) return

  const { products, tier, includeVariations } = request.inputs
  const results = []

  for (const product of products) {
    // Generate product description based on tier
    const description = await ai.generate({
      model: 'gpt-5',
      prompt: `Write an engaging e-commerce product description:

        Product: ${product.name}
        Category: ${product.category}
        Features: ${product.features.join(', ')}
        Specifications: ${JSON.stringify(product.specs)}
        Target customer: ${product.targetAudience}
        Price: $${product.price}

        Include:
        - Compelling opening sentence
        - Key benefits (not just features)
        - Use case scenarios
        - Quality and value statements
        - Urgency or scarcity elements

        Tone: Persuasive but authentic
        Length: ${tier === 'basic' ? '100-150' : tier === 'standard' ? '200-300' : '300-500'} words`,
      maxTokens: 1000,
    })

    // Generate bullet points
    const bullets = await ai.generate({
      model: 'gpt-5',
      prompt: `Create 5-8 compelling bullet points for this product:

        ${description.text}

        Focus on benefits over features.
        Start each with an action verb or benefit statement.`,
      maxTokens: 300,
    })

    // Generate SEO elements if standard or premium
    let seo = null
    if (tier !== 'basic') {
      seo = await ai.generate({
        model: 'gpt-5',
        prompt: `Generate SEO elements for this product:

          ${description.text}

          Provide:
          - Meta title (60 chars)
          - Meta description (155 chars)
          - Keywords (10-15)
          - Alt text for product image`,
        schema: {
          metaTitle: { type: 'string' },
          metaDescription: { type: 'string' },
          keywords: { type: 'array', items: { type: 'string' } },
          altText: { type: 'string' },
        },
      })
    }

    // Generate variations if premium
    let variations = []
    if (tier === 'premium' && includeVariations) {
      const varResult = await ai.generate({
        model: 'gpt-5',
        prompt: `Create 2 alternative versions of this product description for A/B testing:

          Original: ${description.text}

          Variation 1: Focus on emotional benefits
          Variation 2: Focus on practical advantages`,
        maxTokens: 1500,
      })

      variations = parseVariations(varResult.text)
    }

    results.push({
      productId: product.id,
      productName: product.name,
      description: description.text,
      bullets: parseBullets(bullets.text),
      seo: seo?.data || null,
      variations,
      wordCount: description.text.split(/\s+/).length,
    })
  }

  await send($.ServiceResult.deliver, {
    requestId: request.id,
    outputs: { products: results },
  })

  // Calculate cost with bulk discount
  const productCount = products.length
  const basePrice = productDescriptionService.pricing.tiers.find((t) => t.name === tier)?.price || 10
  const bulkTier = productDescriptionService.pricing.bulk.find((b) => productCount >= b.min && productCount <= b.max)
  const discount = bulkTier?.discount || 0
  const totalCost = productCount * basePrice * (1 - discount)

  await send($.Payment.charge, {
    customerId: request.customerId,
    amount: totalCost,
    description: `Product Descriptions: ${productCount} products (${tier} tier)`,
    metadata: {
      productCount,
      tier,
      bulkDiscount: discount,
    },
  })
})

function parseBullets(text: string): string[] {
  return text
    .split('\n')
    .filter((line) => line.match(/^[-*•]/))
    .map((line) => line.replace(/^[-*•]\s*/, ''))
}

import $, { ai, on, send } from 'sdk.do'

const emailCampaignService = await $.Service.create({
  id: 'email-campaign-generator',
  name: 'Email Campaign Creator',
  description: 'Generate email sequences for onboarding, nurture, and promotional campaigns',
  type: $.ServiceType.ContentGeneration,
  subtype: 'email-campaigns',

  pricing: {
    model: 'per-campaign',
    baseRate: 150.0,
    perEmail: 30.0,
    campaignTypes: {
      welcome: { emails: 3, price: 150 },
      nurture: { emails: 5, price: 200 },
      promotional: { emails: 3, price: 120 },
      reengagement: { emails: 4, price: 150 },
      abandoned: { emails: 3, price: 120 },
    },
  },
})

on($.ServiceRequest.created, async (request) => {
  if (request.serviceId !== emailCampaignService.id) return

  const { campaignType, product, audience, goals, brandVoice } = request.inputs

  // Generate campaign strategy
  const strategy = await ai.generate({
    model: 'gpt-5',
    prompt: `Create an email campaign strategy:

      Type: ${campaignType}
      Product/Service: ${product.name}
      Target audience: ${audience}
      Goals: ${goals.join(', ')}

      Define:
      - Campaign objective
      - Email sequence (timing and purpose of each)
      - Key messages for each email
      - Conversion metrics`,
    maxTokens: 1000,
  })

  // Generate each email in the sequence
  const emails = await Promise.all(
    Array.from({ length: getCampaignLength(campaignType) }).map(async (_, index) => {
      const email = await ai.generate({
        model: 'gpt-5',
        prompt: `Write email ${index + 1} of the ${campaignType} campaign:

          Strategy: ${strategy.text}
          Product: ${product.name}
          Brand voice: ${brandVoice}

          Include:
          - Subject line (3 variations)
          - Preview text
          - Email body (HTML-ready markdown)
          - Clear CTA
          - P.S. line

          Email purpose: ${getEmailPurpose(campaignType, index)}`,
        maxTokens: 1500,
      })

      return {
        sequenceNumber: index + 1,
        timing: getEmailTiming(campaignType, index),
        subject: extractSubjectLines(email.text),
        previewText: extractPreviewText(email.text),
        body: extractBody(email.text),
        cta: extractCTA(email.text),
      }
    })
  )

  await send($.ServiceResult.deliver, {
    requestId: request.id,
    outputs: {
      campaign: {
        type: campaignType,
        strategy: strategy.text,
        emails,
        totalEmails: emails.length,
      },
    },
  })

  const pricing = emailCampaignService.pricing.campaignTypes[campaignType]
  await send($.Payment.charge, {
    customerId: request.customerId,
    amount: pricing.price,
    description: `Email Campaign: ${campaignType} (${pricing.emails} emails)`,
  })
})

function getCampaignLength(type: string): number {
  const lengths = {
    welcome: 3,
    nurture: 5,
    promotional: 3,
    reengagement: 4,
    abandoned: 3,
  }
  return lengths[type] || 3
}

function getEmailPurpose(type: string, index: number): string {
  const purposes = {
    welcome: ['Welcome and set expectations', 'Provide value and resources', 'Encourage first action'],
    nurture: ['Educate on problem', 'Present solution', 'Build trust', 'Handle objections', 'Convert to customer'],
    promotional: ['Announce offer', 'Provide social proof', 'Create urgency'],
    reengagement: ['Acknowledge absence', 'Show what they missed', 'Special comeback offer', 'Last chance'],
    abandoned: ['Gentle reminder', 'Address concerns', 'Final incentive'],
  }
  return purposes[type]?.[index] || 'Engage and convert'
}

function getEmailTiming(type: string, index: number): string {
  const timing = {
    welcome: ['Immediately', 'Day 2', 'Day 7'],
    nurture: ['Day 0', 'Day 3', 'Day 7', 'Day 14', 'Day 21'],
    promotional: ['Day 0', 'Day 3', 'Day 6'],
    reengagement: ['Day 0', 'Day 7', 'Day 14', 'Day 30'],
    abandoned: ['1 hour', '24 hours', '3 days'],
  }
  return timing[type]?.[index] || `Email ${index + 1}`
}

function extractSubjectLines(text: string): string[] {
  const match = text.match(/Subject.*?:(.*?)(?:\n|$)/i)
  return match ? match[1].split(',').map((s) => s.trim()) : []
}

function extractPreviewText(text: string): string {
  const match = text.match(/Preview.*?:(.*?)(?:\n|$)/i)
  return match ? match[1].trim() : ''
}

function extractBody(text: string): string {
  const bodyMatch = text.match(/Body:(.*?)(?:CTA:|$)/is)
  return bodyMatch ? bodyMatch[1].trim() : text
}

function extractCTA(text: string): string {
  const ctaMatch = text.match(/CTA:(.*?)(?:\n|$)/i)
  return ctaMatch ? ctaMatch[1].trim() : ''
}

const pricing = {
  model: 'per-word',
  baseRate: 0.05, // $0.05 per word
  minimumCharge: 50.0,
  tiers: [
    { wordCount: { min: 0, max: 1000 }, rate: 0.05 },
    { wordCount: { min: 1001, max: 2500 }, rate: 0.04 },
    { wordCount: { min: 2501, max: Infinity }, rate: 0.03 },
  ],
}

const pricing = {
  model: 'per-piece',
  rates: {
    adCopy: 50.0,
    landingPage: 200.0,
    emailCampaign: 100.0,
    socialPost: 25.0,
    productDescription: 30.0,
  },
}

const pricing = {
  model: 'subscription',
  tiers: [
    {
      name: 'starter',
      price: 299,
      includes: {
        blogPosts: 4,
        socialPosts: 20,
        emails: 4,
      },
    },
    {
      name: 'professional',
      price: 799,
      includes: {
        blogPosts: 12,
        socialPosts: 60,
        emails: 12,
        productDescriptions: 50,
      },
    },
    {
      name: 'enterprise',
      price: 1999,
      includes: {
        blogPosts: 30,
        socialPosts: 150,
        emails: 30,
        productDescriptions: 200,
        technicalDocs: 4,
      },
    },
  ],
}

interface QualityMetrics {
  readability: number // Flesch Reading Ease score
  uniqueness: number // Plagiarism check score
  keywordDensity: number // Target keyword usage
  sentiment: 'positive' | 'neutral' | 'negative'
  grammarScore: number // Grammar check score
  toneMatch: number // Alignment with requested tone
}

async function validateQuality(content: string, requirements: any): Promise<QualityMetrics> {
  const metrics: QualityMetrics = {
    readability: calculateReadability(content),
    uniqueness: await checkUniqueness(content),
    keywordDensity: calculateKeywordDensity(content, requirements.keywords),
    sentiment: await analyzeSentiment(content),
    grammarScore: await checkGrammar(content),
    toneMatch: await matchTone(content, requirements.tone),
  }

  // Validate against minimums
  if (metrics.readability < requirements.minReadability) {
    throw new Error(`Readability score ${metrics.readability} below minimum ${requirements.minReadability}`)
  }

  if (metrics.uniqueness < 0.95) {
    throw new Error(`Content uniqueness ${metrics.uniqueness} below required 95%`)
  }

  return metrics
}

// Bad: Direct generation
const content = await ai.generate({ prompt: topic })

// Good: Research-backed generation
const research = await ai.generate({ prompt: `Research ${topic}` })
const content = await ai.generate({
  prompt: `Write about ${topic}`,
  context: research.text,
})

const outline = await ai.generate({ prompt: 'Create outline' })
const content = await ai.generate({
  prompt: 'Write full content',
  context: outline.text,
})

const content = await ai.generate(options)
const quality = await validateQuality(content.text, requirements)

if (quality.readability < 60) {
  content = await ai.generate({
    ...options,
    prompt: options.prompt + '\nUse simpler language and shorter sentences.',
  })
}

const content = await ai.generate({ prompt: mainPrompt })
const seo = await ai.generate({
  prompt: `Generate SEO metadata for: ${content.text}`,
  schema: SEOSchema,
})