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{ IRouter, SelectionCriteria, SelectionResult } from '../../types/routing';\nimport { ModelCatalog } from '../ModelCatalog';\nimport { Logger } from '../../utils/logger';\nimport { Model } from '../../types/models';\n\nexport class CostOptimizer implements IRouter {\n constructor(\n private catalog: ModelCatalog,\n private logger: Logger,\n ) {}\n\n getName(): string {\n return 'cost';\n }\n\n async route(query: string, criteria: SelectionCriteria): Promise {\n await Promise.resolve(); // Keep async for consistent interface\n this.logger.debug('CostOptimizer: Finding cheapest model (prioritizing free)', { criteria });\n\n // First, try to get free models\n let candidates = this.catalog.getFreeModels();\n\n // If no free models or criteria specified, get filtered models\n if (candidates.length === 0 || Object.keys(criteria).length > 0) {\n candidates = this.catalog.filterModels(criteria);\n }\n\n if (candidates.length === 0) {\n throw new Error('No models match the specified criteria');\n }\n\n // Sort by total cost (input + output) - free models naturally come first\n const sorted = candidates.sort((a, b) => {\n const aCost = a.pricing.inputTokens + a.pricing.outputTokens;\n const bCost = b.pricing.inputTokens + b.pricing.outputTokens;\n return aCost - bCost;\n });\n\n const selected = sorted[0];\n const isFree = selected.pricing.inputTokens === 0 && selected.pricing.outputTokens === 0;\n\n const alternatives = sorted.slice(1, 4).map((m, idx) => {\n const mIsFree = m.pricing.inputTokens === 0 && m.pricing.outputTokens === 0;\n return {\n modelId: m.id,\n score: this.calculateCostScore(m),\n reason: mIsFree\n ? `Alternative ${idx + 1}: FREE`\n : `Alternative ${idx + 1}: ${this.formatCost(m)}`,\n };\n });\n\n const expectedCost = (selected.pricing.inputTokens + selected.pricing.outputTokens) / 2;\n\n return {\n modelId: selected.id,\n model: selected,\n provider: selected.provider,\n expectedCost,\n reason: isFree\n ? `FREE model: ${selected.name}`\n : `Cheapest option: ${this.formatCost(selected)}`,\n alternatives,\n confidence: 0.95,\n };\n }\n\n private calculateCostScore(model: Model): number {\n // Lower cost = higher score\n const totalCost = model.pricing.inputTokens + model.pricing.outputTokens;\n return 1 / (totalCost + 1);\n }\n\n private formatCost(model: Model): string {\n const input = model.pricing.inputTokens.toFixed(2);\n const output = model.pricing.outputTokens.toFixed(2);\n return `$${input}/$${output} per 1M tokens`;\n }\n}\n","import { IRouter, SelectionCriteria, SelectionResult } from '../../types/routing';\nimport { ModelCatalog } from '../ModelCatalog';\nimport { Logger } from '../../utils/logger';\nimport { Model } from '../../types/models';\n\nexport class PerformanceRouter implements IRouter {\n private performanceMetrics: Map = new Map();\n\n constructor(\n private catalog: ModelCatalog,\n private logger: Logger,\n ) {\n this.initializeMetrics();\n }\n\n getName(): string {\n return 'performance';\n }\n\n async route(query: string, criteria: SelectionCriteria): Promise {\n await Promise.resolve(); // Keep async for consistent interface\n this.logger.debug('PerformanceRouter: Finding fastest model', { criteria });\n\n const candidates = this.catalog.filterModels(criteria);\n\n if (candidates.length === 0) {\n throw new Error('No models match the specified criteria');\n }\n\n // Sort by performance score\n const sorted = candidates.sort((a, b) => {\n const aScore = this.getPerformanceScore(a);\n const bScore = this.getPerformanceScore(b);\n return bScore - aScore; // Higher is better\n });\n\n const selected = sorted[0];\n const alternatives = sorted.slice(1, 4).map((m, idx) => ({\n modelId: m.id,\n score: this.getPerformanceScore(m),\n reason: `Alternative ${idx + 1}: estimated ${this.getLatency(m)}ms latency`,\n }));\n\n const expectedCost = (selected.pricing.inputTokens + selected.pricing.outputTokens) / 2;\n\n return {\n modelId: selected.id,\n model: selected,\n provider: selected.provider,\n expectedCost,\n estimatedLatency: this.getLatency(selected),\n reason: `Fastest option: estimated ${this.getLatency(selected)}ms latency`,\n alternatives,\n confidence: 0.85,\n };\n }\n\n private initializeMetrics(): void {\n // Simulated performance metrics (in production, these would come from monitoring)\n this.performanceMetrics.set('google/gemini-flash-1.5', 500);\n this.performanceMetrics.set('google/gemini-pro-1.5', 800);\n this.performanceMetrics.set('anthropic/claude-3.5-sonnet', 1000);\n this.performanceMetrics.set('openai/gpt-4-turbo', 1200);\n this.performanceMetrics.set('anthropic/claude-3-opus', 1500);\n this.performanceMetrics.set('meta-llama/llama-3.1-70b-instruct', 900);\n this.performanceMetrics.set('meta-llama/llama-3.1-405b-instruct', 1400);\n }\n\n private getPerformanceScore(model: Model): number {\n const latency = this.getLatency(model);\n // Lower latency = higher score\n return 10000 / latency;\n }\n\n private getLatency(model: Model): number {\n return this.performanceMetrics.get(model.id) || 1000;\n }\n\n /**\n * Update performance metrics (for production use)\n */\n updateMetrics(modelId: string, latency: number): void {\n this.performanceMetrics.set(modelId, latency);\n }\n}\n","import { IRouter, SelectionCriteria, SelectionResult } from '../../types/routing';\nimport { ModelCatalog } from '../ModelCatalog';\nimport { Logger } from '../../utils/logger';\nimport { Model } from '../../types/models';\n\nexport interface BalancedWeights {\n cost: number;\n performance: number;\n capability: number;\n reliability: number;\n}\n\nexport class BalancedRouter implements IRouter {\n private weights: BalancedWeights = {\n cost: 0.4,\n performance: 0.3,\n capability: 0.2,\n reliability: 0.1,\n };\n\n private performanceMetrics: Map = new Map();\n\n constructor(\n private catalog: ModelCatalog,\n private logger: Logger,\n weights?: Partial,\n ) {\n if (weights) {\n this.weights = { ...this.weights, ...weights };\n }\n this.initializeMetrics();\n }\n\n getName(): string {\n return 'balanced';\n }\n\n async route(query: string, criteria: SelectionCriteria): Promise {\n await Promise.resolve(); // Keep async for consistent interface\n this.logger.debug('BalancedRouter: Finding balanced model', {\n criteria,\n weights: this.weights,\n });\n\n let candidates = this.catalog.filterModels(criteria);\n\n // Boost free models by including them if available\n const freeModels = this.catalog.getFreeModels();\n if (freeModels.length > 0 && Object.keys(criteria).length === 0) {\n // Merge free models with candidates, avoiding duplicates\n const candidateIds = new Set(candidates.map((c) => c.id));\n const newFreeModels = freeModels.filter((fm) => !candidateIds.has(fm.id));\n candidates = [...candidates, ...newFreeModels];\n }\n\n if (candidates.length === 0) {\n throw new Error('No models match the specified criteria');\n }\n\n // Score each model (free models get a significant boost)\n const scored = candidates.map((model) => {\n const isFree = model.pricing.inputTokens === 0 && model.pricing.outputTokens === 0;\n const baseScore = this.calculateBalancedScore(model);\n // Give free models a 20 point bonus to make them competitive\n const finalScore = isFree ? baseScore + 20 : baseScore;\n\n return {\n model,\n score: finalScore,\n isFree,\n };\n });\n\n // Sort by score (higher is better)\n scored.sort((a, b) => b.score - a.score);\n\n const selected = scored[0];\n const alternatives = scored.slice(1, 4).map((s, idx) => ({\n modelId: s.model.id,\n score: s.score,\n reason: s.isFree\n ? `Alternative ${idx + 1}: FREE (Score ${s.score.toFixed(2)})`\n : `Alternative ${idx + 1}: Score ${s.score.toFixed(2)}`,\n }));\n\n const expectedCost =\n (selected.model.pricing.inputTokens + selected.model.pricing.outputTokens) / 2;\n\n const reasonPrefix = selected.isFree ? 'Best FREE balanced model' : 'Best balanced option';\n return {\n modelId: selected.model.id,\n model: selected.model,\n provider: selected.model.provider,\n expectedCost,\n reason: `${reasonPrefix}: score ${selected.score.toFixed(2)} (cost + performance + capability)`,\n alternatives,\n confidence: 0.88,\n };\n }\n\n private calculateBalancedScore(model: Model): number {\n const costScore = this.calculateCostScore(model);\n const perfScore = this.calculatePerformanceScore(model);\n const capScore = this.calculateCapabilityScore(model);\n const relScore = this.calculateReliabilityScore(model);\n\n const totalScore =\n costScore * this.weights.cost +\n perfScore * this.weights.performance +\n capScore * this.weights.capability +\n relScore * this.weights.reliability;\n\n return totalScore;\n }\n\n private calculateCostScore(model: Model): number {\n const totalCost = model.pricing.inputTokens + model.pricing.outputTokens;\n // Normalize: cheaper is better, max cost ~100, min ~0.1\n const normalized = Math.max(0, 1 - totalCost / 100);\n return normalized * 100;\n }\n\n private calculatePerformanceScore(model: Model): number {\n const latency = this.getLatency(model);\n // Normalize: faster is better, max latency ~2000ms\n const normalized = Math.max(0, 1 - latency / 2000);\n return normalized * 100;\n }\n\n private calculateCapabilityScore(model: Model): number {\n let score = 0;\n const caps = model.capabilities;\n\n if (caps.vision) score += 20;\n if (caps.functionCalling) score += 20;\n if (caps.tools) score += 15;\n if (caps.jsonMode) score += 15;\n if (caps.streaming) score += 10;\n if (caps.codeGeneration) score += 20;\n\n // Context window bonus\n if (model.contextWindow >= 100000) score += 10;\n else if (model.contextWindow >= 32000) score += 5;\n\n return Math.min(score, 100);\n }\n\n private calculateReliabilityScore(model: Model): number {\n // Favor well-known providers and non-deprecated models\n let score = 50;\n\n if (!model.deprecated) score += 30;\n\n // Provider reliability (subjective, can be updated with real metrics)\n const providerScores: Record = {\n anthropic: 20,\n openai: 20,\n google: 15,\n meta: 10,\n mistral: 15,\n };\n\n score += providerScores[model.provider] || 5;\n\n return Math.min(score, 100);\n }\n\n private initializeMetrics(): void {\n // Simulated latency metrics\n this.performanceMetrics.set('google/gemini-flash-1.5', 500);\n this.performanceMetrics.set('google/gemini-pro-1.5', 800);\n this.performanceMetrics.set('anthropic/claude-3.5-sonnet', 1000);\n this.performanceMetrics.set('openai/gpt-4-turbo', 1200);\n this.performanceMetrics.set('anthropic/claude-3-opus', 1500);\n this.performanceMetrics.set('meta-llama/llama-3.1-70b-instruct', 900);\n this.performanceMetrics.set('meta-llama/llama-3.1-405b-instruct', 1400);\n this.performanceMetrics.set('mistralai/mistral-large', 1000);\n }\n\n private getLatency(model: Model): number {\n return this.performanceMetrics.get(model.id) || 1000;\n }\n\n /**\n * Update weights for custom balancing\n */\n setWeights(weights: Partial): void {\n this.weights = { ...this.weights, ...weights };\n\n // Normalize weights to sum to 1\n const total = Object.values(this.weights).reduce((a, b) => a + b, 0);\n this.weights = {\n cost: this.weights.cost / total,\n performance: this.weights.performance / total,\n capability: this.weights.capability / total,\n reliability: this.weights.reliability / total,\n };\n }\n}\n","import { IRouter, SelectionCriteria, SelectionResult } from '../../types/routing';\nimport { ModelCatalog } from '../ModelCatalog';\nimport { Logger } from '../../utils/logger';\nimport { Model, ModelCapabilities } from '../../types/models';\n\nexport class CapabilityRouter implements IRouter {\n constructor(\n private catalog: ModelCatalog,\n private logger: Logger,\n ) {}\n\n getName(): string {\n return 'capability';\n }\n\n async route(query: string, criteria: SelectionCriteria): Promise {\n await Promise.resolve(); // Keep async for consistent interface\n this.logger.debug('CapabilityRouter: Finding best model for capabilities', { criteria });\n\n // Detect required capabilities from query\n const detectedCaps = this.detectCapabilities(query);\n\n // Merge detected capabilities with criteria\n const requiredCapabilities = {\n ...detectedCaps,\n ...(criteria.capabilities || {}),\n };\n\n this.logger.debug('Required capabilities', { requiredCapabilities });\n\n // Filter models by capabilities\n const candidates = this.catalog.filterModels({\n ...criteria,\n capabilities: requiredCapabilities,\n });\n\n if (candidates.length === 0) {\n throw new Error('No models match the required capabilities');\n }\n\n // Score models by capability match\n const scored = candidates.map((model) => ({\n model,\n score: this.calculateCapabilityScore(model, requiredCapabilities),\n }));\n\n // Sort by score\n scored.sort((a, b) => b.score - a.score);\n\n const selected = scored[0];\n const alternatives = scored.slice(1, 4).map((item, idx) => ({\n modelId: item.model.id,\n score: item.score,\n reason: `Alternative ${idx + 1}: ${this.formatCapabilities(item.model)}`,\n }));\n\n const expectedCost =\n (selected.model.pricing.inputTokens + selected.model.pricing.outputTokens) / 2;\n\n return {\n modelId: selected.model.id,\n model: selected.model,\n provider: selected.model.provider,\n expectedCost,\n reason: `Best capability match: ${this.formatCapabilities(selected.model)}`,\n alternatives,\n confidence: 0.85,\n };\n }\n\n private detectCapabilities(query: string): Partial {\n const lowerQuery = query.toLowerCase();\n const capabilities: Partial = {};\n\n // Detect vision needs\n if (\n lowerQuery.includes('image') ||\n lowerQuery.includes('picture') ||\n lowerQuery.includes('photo') ||\n lowerQuery.includes('visual') ||\n lowerQuery.includes('see')\n ) {\n capabilities.vision = true;\n }\n\n // Detect function calling needs\n if (\n lowerQuery.includes('function') ||\n lowerQuery.includes('tool') ||\n lowerQuery.includes('api') ||\n lowerQuery.includes('call')\n ) {\n capabilities.functionCalling = true;\n capabilities.tools = true;\n }\n\n // Detect JSON mode needs\n if (\n lowerQuery.includes('json') ||\n lowerQuery.includes('structured') ||\n lowerQuery.includes('format')\n ) {\n capabilities.jsonMode = true;\n }\n\n // Detect code generation needs\n if (\n lowerQuery.includes('code') ||\n lowerQuery.includes('program') ||\n lowerQuery.includes('script') ||\n lowerQuery.includes('implement')\n ) {\n capabilities.codeGeneration = true;\n }\n\n return capabilities;\n }\n\n private calculateCapabilityScore(model: Model, required: Partial): number {\n let score = 0;\n let totalRequired = 0;\n\n // Check each required capability\n for (const [key, value] of Object.entries(required)) {\n // eslint-disable-next-line @typescript-eslint/no-unnecessary-condition\n if (value !== undefined) {\n totalRequired++;\n const capKey = key as keyof ModelCapabilities;\n\n if (model.capabilities[capKey] === value) {\n score += 20; // Base score for matching\n }\n }\n }\n\n // Bonus for additional capabilities\n const additionalCaps = Object.values(model.capabilities).filter(Boolean).length;\n score += additionalCaps * 2;\n\n // Bonus for larger context window (useful for complex tasks)\n if (model.contextWindow >= 100000) score += 10;\n else if (model.contextWindow >= 32000) score += 5;\n\n // Normalize by number of required capabilities\n if (totalRequired > 0) {\n score = score / totalRequired;\n }\n\n return score;\n }\n\n private formatCapabilities(model: Model): string {\n const caps: string[] = [];\n\n if (model.capabilities.vision) caps.push('vision');\n if (model.capabilities.functionCalling) caps.push('functions');\n if (model.capabilities.tools) caps.push('tools');\n if (model.capabilities.jsonMode) caps.push('JSON');\n if (model.capabilities.codeGeneration) caps.push('coding');\n\n return caps.join(', ') || 'basic';\n }\n}\n"]}