aura-ai/src/init/command.js

AI-powered marketing strategist CLI tool for developers

import fs from 'fs/promises'
import { existsSync } from 'fs'
import path from 'path'

export async function initCommand(options) {
  const { answers, file, force, json, quiet, interactive } = options
  
  try {
    // Check if already initialized
    if (existsSync('aura.md') && !force) {
      const error = 'Product already analyzed. Use --force to overwrite.'
      if (json) {
        console.log(JSON.stringify({ status: 'error', error }))
        process.exit(1)
      } else {
        console.error(`❌ ${error}`)
        process.exit(1)
      }
    }

    let productAnswers = []

    // Get answers from different sources
    if (answers) {
      // Parse answers from command line
      productAnswers = answers.split('|').map(a => a.trim())
      if (productAnswers.length !== 3) {
        throw new Error('Must provide exactly 3 answers separated by |')
      }
    } else if (file) {
      // Read answers from file
      const content = await fs.readFile(file, 'utf-8')
      productAnswers = content.split('\n').filter(line => line.trim()).slice(0, 3)
      if (productAnswers.length !== 3) {
        throw new Error('File must contain exactly 3 lines of answers')
      }
    } else if (!interactive) {
      // For non-interactive mode, answers are required
      throw new Error('Answers required in non-interactive mode. Use --answers or --file')
    } else {
      // Interactive mode - launch the full Ink app
      if (!quiet) {
        console.log('Launching interactive product analysis...')
      }
      
      // Dynamic import to avoid loading Ink when not needed
      const { runInitInteractive } = await import('./interactive.jsx')
      await runInitInteractive()
      
      if (json) {
        console.log(JSON.stringify({
          status: 'success',
          message: 'Product analysis completed',
          file: 'aura.md'
        }))
      }
      return
    }

    // Process answers and generate analysis
    const [description, audience, value] = productAnswers
    
    if (!quiet && !json) {
      console.log('🔍 Analyzing your product...')
    }

    // Generate marketing analysis using AI
    const analysis = await generateAnalysis(description, audience, value)
    
    // Save to aura.md
    await fs.writeFile('aura.md', analysis)
    
    // Output result
    if (json) {
      // For agents: print full analysis
      console.log('\n' + '='.repeat(60))
      console.log('🎯 PRODUCT MARKETING ANALYSIS')
      console.log('='.repeat(60))
      console.log('\n📝 Product:', description)
      console.log('👥 Audience:', audience)
      console.log('💡 Value:', value)
      console.log('\n' + '-'.repeat(60))
      console.log('\n📊 Generated Marketing Strategy:\n')
      console.log(analysis)
      console.log('\n' + '='.repeat(60))
      console.log('✅ Analysis saved to aura.md')
      console.log('='.repeat(60))
    } else if (!quiet) {
      console.log('✅ Product analysis completed!')
      console.log('📄 Marketing strategy saved to: aura.md')
      console.log('\nYour product profile:')
      console.log(`  • Product: ${description}`)
      console.log(`  • Audience: ${audience}`)
      console.log(`  • Value: ${value}`)
    }

  } catch (error) {
    if (json) {
      console.log(JSON.stringify({
        status: 'error',
        error: error.message
      }))
      process.exit(1)
    } else {
      console.error(`❌ Error: ${error.message}`)
      process.exit(1)
    }
  }
}

async function generateAnalysis(description, audience, value) {
  // Import AI service
  const { openai } = await import('@ai-sdk/openai')
  const { generateText } = await import('ai')
  
  const prompt = `Create a comprehensive marketing strategy for:
Product: ${description}
Target Audience: ${audience}
Value Proposition: ${value}

Generate a detailed marketing analysis including:
1. Product positioning
2. Target market analysis
3. Marketing channels
4. Growth strategies
5. Key messaging
6. Competitive advantages

Format as markdown with clear sections.`

  try {
    const result = await generateText({
      model: openai('gpt-4o-mini'),
      prompt,
      temperature: 0.7,
      maxTokens: 1000,
    })
    
    return `# Product Marketing Analysis

## Product Overview
**Product:** ${description}
**Target Audience:** ${audience}
**Value Proposition:** ${value}

---

${result.text}`
  } catch (error) {
    // Fallback if AI fails
    return `# Product Marketing Analysis

## Product Overview
**Product:** ${description}
**Target Audience:** ${audience}
**Value Proposition:** ${value}

## Marketing Strategy
This analysis will be enhanced with AI insights when API is configured.

### Target Market
Your target audience is: ${audience}

### Value Proposition
Key benefit: ${value}

### Next Steps
1. Define your unique selling points
2. Research competitor positioning
3. Identify primary marketing channels
4. Create messaging framework
5. Develop content strategy`
  }
}