// Pricing configuration for different AI models
// Prices are per 1M tokens

export const MODEL_PRICING = {
  // DeepSeek pricing (very cost-effective)
  'deepseek-chat': {
    input: 0.14,  // $0.14 per 1M input tokens
    output: 0.28, // $0.28 per 1M output tokens
    currency: 'USD',
    displayName: 'DeepSeek Chat'
  },
  
  // OpenAI pricing
  'gpt-4o-mini': {
    input: 0.15,   // $0.15 per 1M input tokens
    output: 0.60,  // $0.60 per 1M output tokens
    currency: 'USD',
    displayName: 'GPT-4o Mini'
  },
  
  'gpt-4o': {
    input: 5.00,   // $5.00 per 1M input tokens
    output: 15.00, // $15.00 per 1M output tokens
    currency: 'USD',
    displayName: 'GPT-4o'
  },
  
  'gpt-3.5-turbo': {
    input: 0.50,   // $0.50 per 1M input tokens
    output: 1.50,  // $1.50 per 1M output tokens
    currency: 'USD',
    displayName: 'GPT-3.5 Turbo'
  }
}

export interface TokenUsage {
  promptTokens: number
  completionTokens: number
  totalTokens: number
}

export interface CostCalculation {
  inputCost: number
  outputCost: number
  totalCost: number
  currency: string
  formattedCost: string
}

export function calculateCost(
  model: string,
  tokenUsage: TokenUsage
): CostCalculation {
  const pricing = MODEL_PRICING[model as keyof typeof MODEL_PRICING] || MODEL_PRICING['deepseek-chat']
  
  // Calculate costs (convert from per 1M tokens to actual usage)
  const inputCost = (tokenUsage.promptTokens / 1_000_000) * pricing.input
  const outputCost = (tokenUsage.completionTokens / 1_000_000) * pricing.output
  const totalCost = inputCost + outputCost
  
  // Format cost with appropriate decimal places
  const formattedCost = totalCost < 0.01 
    ? `$${totalCost.toFixed(6)}` 
    : `$${totalCost.toFixed(4)}`
  
  return {
    inputCost,
    outputCost,
    totalCost,
    currency: pricing.currency,
    formattedCost
  }
}

export function estimateTokens(text: string): number {
  // Rough estimation: 1 token ≈ 4 characters for English
  // For Chinese/Japanese: 1 token ≈ 2 characters
  // This is a simplified estimation
  
  const hasAsianChars = /[\u4e00-\u9fff\u3040-\u309f\u30a0-\u30ff]/.test(text)
  
  if (hasAsianChars) {
    // Chinese, Japanese, Korean text
    return Math.ceil(text.length / 2)
  } else {
    // English and other Latin-based languages
    return Math.ceil(text.length / 4)
  }
}

export function formatTokenCount(tokens: number): string {
  if (tokens >= 1_000_000) {
    return `${(tokens / 1_000_000).toFixed(2)}M`
  } else if (tokens >= 1_000) {
    return `${(tokens / 1_000).toFixed(1)}K`
  }
  return tokens.toString()
}