{"version":3,"sources":["../src/core/Provider.ts","../src/storage/index.ts","../src/core/context.ts","../src/utils/costs.ts","../src/cloud/pricingFetcher.ts","../src/config/index.ts","../src/cloud/index.ts","../src/core/gating.ts","../src/features/hooks.ts","../src/features/recommendations.ts","../src/core/Tracker.ts","../src/providers/openai.ts","../src/providers/anthropic.ts","../src/providers/gemini.ts","../src/index.ts","../src/middleware/index.ts","../src/middleware/context.ts","../src/features/alerts.ts","../src/core/auto.ts"],"sourcesContent":["import { UsageMetrics } from '../types/index.js';\n\nexport interface AIProviderTracker {\n name: string;\n trackRequest(params: T): void;\n trackResponse(response: R): UsageMetrics;\n calculateCost(model: string, promptTokens: number, completionTokens: number): number;\n}\n\nexport abstract class BaseProviderTracker implements AIProviderTracker {\n abstract name: string;\n protected costTable: Record;\n\n constructor(costTable: Record) {\n this.costTable = costTable;\n }\n\n abstract trackRequest(params: T): void;\n abstract trackResponse(response: R): UsageMetrics;\n\n calculateCost(model: string, promptTokens: number, completionTokens: number): number {\n const costInfo = this.costTable[model] || { prompt: 0, completion: 0 };\n const promptCost = (promptTokens / 1000) * costInfo.prompt;\n const completionCost = (completionTokens / 1000) * costInfo.completion;\n return Number((promptCost + completionCost).toFixed(6));\n }\n}\n","import fs from 'fs';\nimport path from 'path';\nimport { UsageMetrics } from '../types/index.js';\n\nexport interface StorageProvider {\n save(metrics: UsageMetrics): Promise;\n getAll(): Promise;\n}\n\nexport class JSONStorage implements StorageProvider {\n private filePath: string;\n\n constructor(filePath?: string) {\n this.filePath = filePath || path.join(process.cwd(), '.ai-usage.json');\n }\n\n private async ensureFile(): Promise {\n if (!fs.existsSync(this.filePath)) {\n await fs.promises.writeFile(this.filePath, JSON.stringify([], null, 2));\n }\n }\n\n async save(metrics: UsageMetrics): Promise {\n await this.ensureFile();\n const data = await this.getAll();\n data.push(metrics);\n await fs.promises.writeFile(this.filePath, JSON.stringify(data, null, 2));\n }\n\n async getAll(): Promise {\n await this.ensureFile();\n const content = await fs.promises.readFile(this.filePath, 'utf-8');\n try {\n return JSON.parse(content);\n } catch (e) {\n return [];\n }\n }\n}\n","import { AsyncLocalStorage } from 'async_hooks';\nimport { AITrackingContext } from '../types/index.js';\n\nconst contextStorage = new AsyncLocalStorage();\n\nexport function setGlobalAIContext(context: AITrackingContext) {\n // This sets a default for the current execution context\n const current = contextStorage.getStore() || {};\n contextStorage.enterWith({ ...current, ...context });\n}\n\nexport function getGlobalAIContext(): AITrackingContext {\n return contextStorage.getStore() || {};\n}\n\nexport { contextStorage };\n","import { CostTable } from '../types/index.js';\n\nexport const OPENAI_COSTS: CostTable = {\n 'gpt-4o': { prompt: 0.005, completion: 0.015 },\n 'gpt-4o-mini': { prompt: 0.00015, completion: 0.0006 },\n 'gpt-4-turbo': { prompt: 0.01, completion: 0.03 },\n 'gpt-3.5-turbo': { prompt: 0.0005, completion: 0.0015 },\n};\n\nexport const ANTHROPIC_COSTS: CostTable = {\n 'claude-3-opus': { prompt: 0.015, completion: 0.075 },\n 'claude-3-sonnet': { prompt: 0.003, completion: 0.015 },\n 'claude-3-haiku': { prompt: 0.00025, completion: 0.00125 },\n 'claude-3-5-sonnet': { prompt: 0.003, completion: 0.015 },\n};\n\nexport const GEMINI_COSTS: CostTable = {\n 'gemini-1.5-pro': { prompt: 0.0035, completion: 0.0105 },\n 'gemini-1.5-flash': { prompt: 0.00035, completion: 0.00105 },\n 'gemini-2.5-pro': { prompt: 0.00125, completion: 0.00375 },\n 'gemini-2.5-flash': { prompt: 0.0001, completion: 0.0004 },\n};\n","import fs from 'fs';\nimport path from 'path';\nimport { OPENAI_COSTS, ANTHROPIC_COSTS, GEMINI_COSTS } from '../utils/costs.js';\n\nconst CACHE_FILE = path.join(process.cwd(), '.ai-pricing.json');\nconst CACHE_TTL_MS = 24 * 60 * 60 * 1000; // 24 hours\nconst PRICING_URL = 'https://ai-monitor-740g.onrender.com/api/v1/meta/pricing';\n\nfunction applyPricing(data: any) {\n if (data?.pricing?.openai) Object.assign(OPENAI_COSTS, data.pricing.openai);\n if (data?.pricing?.anthropic) Object.assign(ANTHROPIC_COSTS, data.pricing.anthropic);\n if (data?.pricing?.google) Object.assign(GEMINI_COSTS, data.pricing.google);\n}\n\nexport function loadFromCache(): boolean {\n try {\n if (!fs.existsSync(CACHE_FILE)) return false;\n \n const raw = fs.readFileSync(CACHE_FILE, 'utf-8');\n const data = JSON.parse(raw);\n \n // Check TTL\n const age = Date.now() - new Date(data.lastUpdated).getTime();\n if (age > CACHE_TTL_MS) return false; // Cache is stale\n \n applyPricing(data);\n return true;\n } catch {\n return false;\n }\n}\n\nexport async function fetchLatestPricing(): Promise {\n try {\n const response = await fetch(PRICING_URL, { signal: AbortSignal.timeout(5000) });\n if (!response.ok) throw new Error(`HTTP ${response.status}`);\n \n const data = await response.json();\n \n // Persist to cache\n fs.writeFileSync(CACHE_FILE, JSON.stringify(data, null, 2), 'utf-8');\n \n applyPricing(data);\n console.log('[AI Cost Tracker] Pricing updated from cloud ☁️');\n } catch {\n // Silent fail — hardcoded fallbacks in costs.ts remain active\n }\n}\n","import { AITrackerConfig } from '../types/index.js';\nimport { loadFromCache, fetchLatestPricing } from '../cloud/pricingFetcher.js';\n\nlet config: AITrackerConfig = {};\n\nexport function configureAITracker(newConfig: AITrackerConfig) {\n config = { ...config, ...newConfig };\n\n // 1. Load cached pricing immediately (sync, no latency)\n loadFromCache();\n\n // 2. Refresh from cloud in background (non-blocking)\n fetchLatestPricing().catch(() => {\n // Silent fail — hardcoded defaults in costs.ts remain active\n });\n}\n\nexport function getConfig(): AITrackerConfig {\n return config;\n}\n\nexport function isProEnabled(): boolean {\n return !!config.apiKey;\n}\n","import { UsageMetrics } from '../types/index.js';\nimport { getConfig } from '../config/index.js';\n\nexport async function sendUsageToCloud(metrics: UsageMetrics, retries = 3): Promise {\n const config = getConfig();\n if (!config.apiKey) return;\n\n const endpoint = config.endpoint || 'https://ai-monitor-backend.onrender.com/api/v1/usage';\n\n const attemptSync = async (remaining: number): Promise => {\n try {\n const response = await fetch(endpoint, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'x-api-key': config.apiKey!,\n },\n body: JSON.stringify(metrics),\n });\n\n if (!response.ok && remaining > 0) {\n // Simple exponential backoff or just wait a bit\n await new Promise(resolve => setTimeout(resolve, 1000 * (4 - remaining)));\n return attemptSync(remaining - 1);\n }\n } catch (error) {\n if (remaining > 0) {\n await new Promise(resolve => setTimeout(resolve, 1000 * (4 - remaining)));\n return attemptSync(remaining - 1);\n }\n // Fail silently as requested\n }\n };\n\n // Start attempt (non-blocking call from Tracker usually, but here we just return the promise)\n return attemptSync(retries);\n}\n\n// Alias for backward compatibility if needed, but the user specifically asked for sendUsageToCloud\nexport const trackToCloud = sendUsageToCloud;\n","import { isProEnabled } from '../config/index.js';\n\nexport function requirePro(featureName: string) {\n if (!isProEnabled()) {\n throw new Error(`${featureName} is a paid feature. Please add an API key using configureAITracker({ apiKey: '...' }).`);\n }\n}\n","import { UsageMetrics } from '../types/index.js';\nimport { requirePro } from '../core/gating.js';\nimport EventEmitter from 'events';\n\nconst usageEmitter = new EventEmitter();\n\nexport function onUsage(callback: (data: UsageMetrics) => void) {\n requirePro('Real-Time Hooks');\n usageEmitter.on('usage', callback);\n}\n\nexport function emitUsage(metrics: UsageMetrics) {\n usageEmitter.emit('usage', metrics);\n}\n","import { UsageMetrics } from '../types/index.js';\n\nexport interface ModelMetadata {\n id: string;\n name: string;\n provider: string;\n promptCost: number; // per 1M tokens\n completionCost: number; // per 1M tokens\n capability: number; // 1-5 scale\n}\n\nconst MODELS: Record = {\n 'gpt-4': { id: 'gpt-4', name: 'GPT-4', provider: 'OpenAI', promptCost: 30, completionCost: 60, capability: 5 },\n 'gpt-4o': { id: 'gpt-4o', name: 'GPT-4o', provider: 'OpenAI', promptCost: 5, completionCost: 15, capability: 5 },\n 'gpt-4o-mini': { id: 'gpt-4o-mini', name: 'GPT-4o-mini', provider: 'OpenAI', promptCost: 0.15, completionCost: 0.60, capability: 3 },\n 'claude-3-opus': { id: 'claude-3-opus', name: 'Claude 3 Opus', provider: 'Anthropic', promptCost: 15, completionCost: 75, capability: 5 },\n 'claude-3-5-sonnet': { id: 'claude-3-5-sonnet', name: 'Claude 3.5 Sonnet', provider: 'Anthropic', promptCost: 3, completionCost: 15, capability: 5 },\n 'claude-3-haiku': { id: 'claude-3-haiku', name: 'Claude 3 Haiku', provider: 'Anthropic', promptCost: 0.25, completionCost: 1.25, capability: 2 },\n 'gemini-2.5-pro': { id: 'gemini-2.5-pro', name: 'Gemini 2.5 Pro', provider: 'Google', promptCost: 1.25, completionCost: 3.75, capability: 5 },\n 'gemini-2.5-flash': { id: 'gemini-2.5-flash', name: 'Gemini 2.5 Flash', provider: 'Google', promptCost: 0.1, completionCost: 0.4, capability: 3 },\n};\n\nexport interface Recommendation {\n currentModel: string;\n suggestedModel: string;\n reason: string;\n potentialSavings: number; // percentage\n}\n\nexport function generateRecommendations(metrics: UsageMetrics[]): Recommendation[] {\n const modelUsage = metrics.reduce((acc: any, m) => {\n acc[m.model] = (acc[m.model] || 0) + m.cost;\n return acc;\n }, {});\n\n const recommendations: Recommendation[] = [];\n\n // Logic: If using GPT-4, suggest GPT-4o\n if (modelUsage['gpt-4']) {\n recommendations.push({\n currentModel: 'gpt-4',\n suggestedModel: 'gpt-4o',\n reason: 'GPT-4o is faster and ~80% cheaper for the same capability level.',\n potentialSavings: 80\n });\n }\n\n // Logic: If using Opus, suggest Sonnet 3.5\n if (modelUsage['claude-3-opus']) {\n recommendations.push({\n currentModel: 'claude-3-opus',\n suggestedModel: 'claude-3-5-sonnet',\n reason: 'Claude 3.5 Sonnet is significantly cheaper and outperforms Opus in many benchmarks.',\n potentialSavings: 75\n });\n }\n\n // Logic: If using Gemini 2.5 Pro, suggest Gemini 2.5 Flash\n if (modelUsage['gemini-2.5-pro']) {\n recommendations.push({\n currentModel: 'gemini-2.5-pro',\n suggestedModel: 'gemini-2.5-flash',\n reason: 'Gemini 2.5 Flash is significantly cheaper and offers excellent performance for high-volume tasks.',\n potentialSavings: 90\n });\n }\n\n // Logic: If high volume but low complexity tasks (simple heuristic: low token count/req)\n // This could be expanded later with task_type metadata\n \n return recommendations;\n}\n","import { UsageMetrics, UsageReport, AITrackingContext } from '../types/index.js';\nimport { StorageProvider, JSONStorage } from '../storage/index.js';\nimport { getGlobalAIContext } from './context.js';\nimport { sendUsageToCloud } from '../cloud/index.js';\nimport { isProEnabled } from '../config/index.js';\nimport { emitUsage } from '../features/hooks.js';\nimport { generateRecommendations, Recommendation } from '../features/recommendations.js';\nimport chalk from 'chalk';\n\nexport class CostTracker {\n private storage: StorageProvider;\n\n constructor(storage?: StorageProvider) {\n this.storage = storage || new JSONStorage();\n }\n\n async recordUsage(metrics: UsageMetrics, context?: AITrackingContext): Promise {\n const globalContext = getGlobalAIContext();\n \n // Merge context: Request context overrides Global context\n const finalMetrics: UsageMetrics = {\n ...globalContext,\n ...metrics,\n ...context, // Request specific context\n timestamp: metrics.timestamp || Date.now(),\n };\n\n await this.storage.save(finalMetrics);\n\n // Sync to cloud if Pro is enabled (non-blocking)\n if (isProEnabled()) {\n emitUsage(finalMetrics);\n sendUsageToCloud(finalMetrics).catch(() => {\n // Silent failure already handled in sendUsageToCloud\n });\n } else {\n // Viral Nudges for Free users\n this.checkMilestones(finalMetrics.totalTokens);\n this.maybeLogNudge();\n }\n }\n\n private async checkMilestones(newTokens: number): Promise {\n const report = await this.getUsageReport();\n const oldTokens = report.totalTokens - newTokens;\n \n const milestone = 10000;\n if (Math.floor(report.totalTokens / milestone) > Math.floor(oldTokens / milestone)) {\n console.log(chalk.green(`\\n✨ Milestone Reached: You've tracked over ${chalk.bold(Math.floor(report.totalTokens / milestone) * milestone)} tokens with AI Cost Tracker!`));\n console.log(chalk.gray(`View your full report with: ${chalk.cyan('npx ai-cost-tracker report')}\\n`));\n }\n }\n\n private maybeLogNudge(): void {\n // 5% chance to show a subtle nudge\n if (Math.random() < 0.05) {\n const nudges = [\n \"🚀 Tip: Upgrade to Pro for team-wide analytics and cost alerts.\",\n \"💡 Pro users save an average of 30% using advanced model recommendations.\",\n \"📱 Monitor your costs on the go with our SaaS dashboard.\",\n \"🔗 Run 'npx ai-cost-tracker upgrade' to see what you're missing!\",\n ];\n const nudge = nudges[Math.floor(Math.random() * nudges.length)];\n console.log(chalk.blue.dim(`\\n${nudge}\\n`));\n }\n }\n\n async getUsageReport(): Promise {\n const allMetrics = await this.storage.getAll();\n \n const report: UsageReport = {\n totalCost: 0,\n totalTokens: 0,\n usageByModel: {},\n usageByProvider: {},\n };\n\n for (const m of allMetrics) {\n report.totalCost += m.cost;\n report.totalTokens += m.totalTokens;\n\n // Model grouping\n if (!report.usageByModel[m.model]) {\n report.usageByModel[m.model] = { cost: 0, tokens: 0, count: 0 };\n }\n report.usageByModel[m.model].cost += m.cost;\n report.usageByModel[m.model].tokens += m.totalTokens;\n report.usageByModel[m.model].count += 1;\n\n // Provider grouping\n if (!report.usageByProvider[m.provider]) {\n report.usageByProvider[m.provider] = { cost: 0, tokens: 0, count: 0 };\n }\n report.usageByProvider[m.provider].cost += m.cost;\n report.usageByProvider[m.provider].tokens += m.totalTokens;\n report.usageByProvider[m.provider].count += 1;\n }\n\n // Round total cost\n report.totalCost = Number(report.totalCost.toFixed(6));\n \n // Round model costs\n for (const model in report.usageByModel) {\n report.usageByModel[model].cost = Number(report.usageByModel[model].cost.toFixed(6));\n }\n\n return report;\n }\n\n async getTotalCost(): Promise {\n const report = await this.getUsageReport();\n return report.totalCost;\n }\n\n async getUsageByUser(userId: string): Promise {\n const all = await this.storage.getAll();\n return all.filter(m => m.userId === userId);\n }\n\n async getUsageByFeature(feature: string): Promise {\n const all = await this.storage.getAll();\n return all.filter(m => m.feature === feature);\n }\n\n async getUsageByTeam(teamId: string): Promise {\n const all = await this.storage.getAll();\n return all.filter(m => m.teamId === teamId);\n }\n\n async getOptimizationSuggestions(): Promise {\n const all = await this.storage.getAll();\n return generateRecommendations(all);\n }\n}\n\n// Singleton for easy access\nexport const tracker = new CostTracker();\n","import { BaseProviderTracker } from '../core/Provider.js';\nimport { UsageMetrics } from '../types/index.js';\nimport { tracker } from '../core/Tracker.js';\nimport { OPENAI_COSTS } from '../utils/costs.js';\n\nexport class OpenAITracker extends BaseProviderTracker {\n name = 'OpenAI';\n\n constructor(customCosts?: Record) {\n super({ ...OPENAI_COSTS, ...customCosts });\n }\n\n trackRequest(params: any): void {\n // Optionally log request params\n }\n\n trackResponse(response: any): UsageMetrics {\n const model = response.model;\n const usage = response.usage || { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 };\n const promptTokens = usage.prompt_tokens;\n const completionTokens = usage.completion_tokens;\n const totalTokens = usage.total_tokens;\n\n const cost = this.calculateCost(model, promptTokens, completionTokens);\n\n return {\n model,\n promptTokens,\n completionTokens,\n totalTokens,\n cost,\n timestamp: Date.now(),\n provider: this.name,\n };\n }\n}\n\nexport function trackOpenAI(client: any, options: { context?: any; customCosts?: any } = {}) {\n const openaiTracker = new OpenAITracker(options.customCosts);\n\n const originalCreate = client.chat.completions.create.bind(client.chat.completions);\n\n client.chat.completions.create = async function (params: any, reqOptions: any) {\n openaiTracker.trackRequest(params);\n const response = await originalCreate(params, reqOptions);\n\n if (!params.stream) {\n const metrics = openaiTracker.trackResponse(response);\n await tracker.recordUsage(metrics, options.context);\n }\n\n return response;\n };\n\n return client;\n}\n","import { BaseProviderTracker } from '../core/Provider.js';\nimport { UsageMetrics } from '../types/index.js';\nimport { tracker } from '../core/Tracker.js';\nimport { ANTHROPIC_COSTS } from '../utils/costs.js';\n\nexport class AnthropicTracker extends BaseProviderTracker {\n name = 'Anthropic';\n\n constructor(customCosts?: Record) {\n super({ ...ANTHROPIC_COSTS, ...customCosts });\n }\n\n trackRequest(params: any): void {\n }\n\n trackResponse(response: any): UsageMetrics {\n const model = response.model;\n const usage = response.usage || { input_tokens: 0, output_tokens: 0 };\n const promptTokens = usage.input_tokens;\n const completionTokens = usage.output_tokens;\n const totalTokens = promptTokens + completionTokens;\n\n const cost = this.calculateCost(model, promptTokens, completionTokens);\n\n return {\n model,\n promptTokens,\n completionTokens,\n totalTokens,\n cost,\n timestamp: Date.now(),\n provider: this.name,\n };\n }\n}\n\nexport function trackAnthropic(client: any, options: { context?: any; customCosts?: any } = {}) {\n const anthropicTracker = new AnthropicTracker(options.customCosts);\n\n const originalCreate = client.messages.create.bind(client.messages);\n\n client.messages.create = async function (params: any, reqOptions: any) {\n anthropicTracker.trackRequest(params);\n const response = await originalCreate(params, reqOptions);\n\n if (!params.stream) {\n const metrics = anthropicTracker.trackResponse(response);\n await tracker.recordUsage(metrics, options.context);\n }\n\n return response;\n };\n\n return client;\n}\n","import { BaseProviderTracker } from '../core/Provider.js';\nimport { UsageMetrics } from '../types/index.js';\nimport { tracker } from '../core/Tracker.js';\nimport { GEMINI_COSTS } from '../utils/costs.js';\n\nexport class GeminiTracker extends BaseProviderTracker {\n name = 'Google Gemini';\n\n constructor(customCosts?: Record) {\n super({ ...GEMINI_COSTS, ...customCosts });\n }\n\n trackRequest(params: any): void {\n }\n\n trackResponse(response: any): UsageMetrics {\n // Gemini response structure is slightly different\n const model = response._model || 'gemini-unknown';\n const usage = response.usageMetadata || { promptTokenCount: 0, candidatesTokenCount: 0, totalTokenCount: 0 };\n \n const promptTokens = usage.promptTokenCount;\n const completionTokens = usage.candidatesTokenCount;\n const totalTokens = usage.totalTokenCount;\n\n const cost = this.calculateCost(model, promptTokens, completionTokens);\n\n return {\n model,\n promptTokens,\n completionTokens,\n totalTokens,\n cost,\n timestamp: Date.now(),\n provider: this.name,\n };\n }\n}\n\nexport function trackGemini(model: any, options: { context?: any; customCosts?: any } = {}) {\n const geminiTracker = new GeminiTracker(options.customCosts);\n\n const originalGenerateContent = model.generateContent.bind(model);\n\n model.generateContent = async function (...args: any[]) {\n const response = await originalGenerateContent(...args);\n \n // Extract metadata from response\n const actualResponse = response.response ? response.response : response;\n \n const metrics = geminiTracker.trackResponse({\n ...actualResponse,\n _model: model.model || args[0]?.model || 'gemini-1.5-flash'\n });\n \n await tracker.recordUsage(metrics, options.context);\n\n return response;\n };\n\n return model;\n}\n\n/**\n * Support for the new @google/genai SDK\n */\nexport function trackGenAI(ai: any, options: { context?: any; customCosts?: any } = {}) {\n const geminiTracker = new GeminiTracker(options.customCosts);\n\n // Patch generateContent on ai.models\n const originalGenerateContent = ai.models.generateContent.bind(ai.models);\n\n ai.models.generateContent = async function (params: any) {\n const response = await originalGenerateContent(params);\n \n // The new SDK response includes model and usageMetadata at the top level\n const metrics = geminiTracker.trackResponse({\n ...response,\n _model: response.model || params.model\n });\n \n await tracker.recordUsage(metrics, options.context);\n\n return response;\n };\n\n return ai;\n}\n","export * from './types/index.js';\nexport * from './core/Provider.js';\nexport * from './core/Tracker.js';\nexport * from './core/context.js';\nexport * from './config/index.js';\nexport * from './providers/openai.js';\nexport * from './providers/anthropic.js';\nexport * from './providers/gemini.js';\nexport * from './middleware/index.js';\nexport * from './middleware/context.js';\nexport * from './features/alerts.js';\nexport * from './features/hooks.js';\nexport * from './core/auto.js';\nexport * from './cloud/index.js';\nexport { tracker } from './core/Tracker.js';\n","import { Request, Response, NextFunction } from 'express';\nimport { tracker } from '../core/Tracker.js';\n\nexport function aiCostMiddleware() {\n return async (req: Request, res: Response, next: NextFunction) => {\n // We can attach the tracker to the request if needed, \n // but the global tracker already records usage.\n // This middleware could be used to tag requests with metadata.\n \n // For now, it just ensures the tracker is accessible if we want to \n // record endpoint-specific usage later.\n \n const start = Date.now();\n \n res.on('finish', () => {\n const duration = Date.now() - start;\n // Potentially log duration or other metrics\n });\n\n next();\n };\n}\n","import { Request, Response, NextFunction } from 'express';\nimport { contextStorage } from '../core/context.js';\nimport { AITrackingContext } from '../types/index.js';\n\nexport interface ContextMiddlewareOptions {\n getUserId?: (req: Request) => string | undefined;\n getTeamId?: (req: Request) => string | undefined;\n getFeature?: (req: Request) => string | undefined;\n getRequestId?: (req: Request) => string | undefined;\n getMetadata?: (req: Request) => Record | undefined;\n}\n\nexport function createAIContextMiddleware(options: ContextMiddlewareOptions) {\n return (req: any, res: Response, next: NextFunction) => {\n const context: AITrackingContext = {\n userId: options.getUserId?.(req),\n teamId: options.getTeamId?.(req),\n feature: options.getFeature?.(req),\n requestId: options.getRequestId?.(req),\n metadata: options.getMetadata?.(req),\n };\n\n // Attach to request for easy access\n req.aiContext = context;\n\n // Use AsyncLocalStorage to make it available globally in this request's scope\n contextStorage.run(context, () => {\n next();\n });\n };\n}\n","import { tracker } from '../core/Tracker.js';\nimport { requirePro } from '../core/gating.js';\n\nexport interface AlertOptions {\n dailyLimit: number;\n onAlert?: (currentCost: number, limit: number) => void;\n}\n\nexport function enableCostAlerts(options: AlertOptions) {\n requirePro('Cost Alerts');\n\n // Simple implementation: check usage periodically or on every record\n // For now, we'll provide a check function\n console.log(`[ai-cost-tracker] Cost alerts enabled with daily limit: $${options.dailyLimit}`);\n}\n\nexport async function checkCostAlerts(limit: number) {\n const totalCost = await tracker.getTotalCost();\n if (totalCost > limit) {\n console.warn(`[ai-cost-tracker] ALERT: Total cost $${totalCost.toFixed(4)} exceeds limit $${limit.toFixed(4)}`);\n }\n}\n","import { configureAITracker } from '../config/index.js';\n\nexport async function monitorAI() {\n console.log('[ai-cost-tracker] Initializing Zero-Config Auto Tracking...');\n\n // 1. Auto-detect API Keys from Environment\n const openAIKey = process.env.OPENAI_API_KEY;\n const anthropicKey = process.env.ANTHROPIC_API_KEY;\n const geminiKey = process.env.GEMINI_API_KEY;\n const proApiKey = process.env.AI_TRACKER_API_KEY;\n\n if (proApiKey) {\n configureAITracker({ apiKey: proApiKey });\n console.log('[ai-cost-tracker] Pro mode enabled via environment variable.');\n }\n\n // 2. Log detected providers\n const activeProviders: string[] = [];\n if (openAIKey) activeProviders.push('OpenAI');\n if (anthropicKey) activeProviders.push('Anthropic');\n if (geminiKey) activeProviders.push('Gemini');\n \n if (activeProviders.length > 0) {\n console.log(`[ai-cost-tracker] Detected keys for: ${activeProviders.join(', ')}`);\n } else {\n console.warn('[ai-cost-tracker] No AI provider keys detected in environment variables.');\n }\n\n // 3. Monkey Patch OpenAI (if available)\n try {\n const OpenAI = (global as any).OpenAI || (typeof require !== 'undefined' ? require('openai') : null);\n \n if (OpenAI && OpenAI.prototype) {\n const originalCreate = OpenAI.Chat?.Completions?.prototype?.create;\n \n if (originalCreate && !originalCreate.__isPatched) {\n console.log('[ai-cost-tracker] ✅ Automatically patching OpenAI Chat.Completions...');\n \n OpenAI.Chat.Completions.prototype.create = async function(...args: any[]) {\n const result = await originalCreate.apply(this, args);\n const { OpenAITracker } = await import('../providers/openai.js');\n const trackerInstance = new OpenAITracker();\n trackerInstance.trackResponse(result);\n return result;\n };\n OpenAI.Chat.Completions.prototype.create.__isPatched = true;\n }\n }\n } catch (e) { /* skip */ }\n\n // 4. Monkey Patch Gemini (if available)\n try {\n const genaiPkg = (global as any).GoogleGenAI || (typeof require !== 'undefined' ? require('@google/genai') : null);\n if (genaiPkg && genaiPkg.GoogleGenAI) {\n const { trackGenAI } = await import('../providers/gemini.js');\n const originalConstructor = genaiPkg.GoogleGenAI;\n \n genaiPkg.GoogleGenAI = function(...args: any[]) {\n const instance = new originalConstructor(...args);\n console.log('[ai-cost-tracker] ✅ Automatically patching GoogleGenAI instance...');\n return trackGenAI(instance);\n };\n genaiPkg.GoogleGenAI.prototype = originalConstructor.prototype;\n }\n\n const standardGeminiPkg = (global as any).GoogleGenerativeAI || (typeof require !== 'undefined' ? require('@google/generative-ai') : null);\n if (standardGeminiPkg && standardGeminiPkg.GoogleGenerativeAI) {\n const { trackGemini } = await import('../providers/gemini.js');\n const prototype = standardGeminiPkg.GoogleGenerativeAI.prototype;\n const originalGetModel = prototype.getGenerativeModel;\n\n if (originalGetModel && !originalGetModel.__isPatched) {\n console.log('[ai-cost-tracker] ✅ Automatically patching GoogleGenerativeAI.getGenerativeModel...');\n prototype.getGenerativeModel = function(...args: any[]) {\n const model = originalGetModel.apply(this, args);\n return trackGemini(model);\n };\n prototype.getGenerativeModel.__isPatched = true;\n }\n }\n } catch (e) { /* skip */ }\n\n // 5. Monkey Patch Anthropic (if available)\n try {\n const AnthropicPkg = (global as any).Anthropic || (typeof require !== 'undefined' ? require('@anthropic-ai/sdk') : null);\n if (AnthropicPkg && AnthropicPkg.prototype) {\n const { trackAnthropic } = await import('../providers/anthropic.js');\n \n // Patch the prototype's messages.create\n const proto = AnthropicPkg.prototype;\n if (proto.messages && proto.messages.create && !proto.messages.create.__isPatched) {\n console.log('[ai-cost-tracker] ✅ Automatically patching Anthropic instance creation...');\n const originalMessagesCreate = proto.messages.create;\n proto.messages.create = async function(params: any, options: any) {\n const response = await originalMessagesCreate.apply(this, [params, options]);\n const { AnthropicTracker } = await import('../providers/anthropic.js');\n const trackerInstance = new AnthropicTracker();\n const metrics = trackerInstance.trackResponse(response);\n const { tracker } = await import('./Tracker.js');\n 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