660 lines
19 KiB
TypeScript
660 lines
19 KiB
TypeScript
/**
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* LLM Router Service - Multi-Provider LLM Integration
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*
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* Supports multiple LLM providers:
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* - RuvLLM (local, self-contained, SIMD-optimized, no external deps)
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* - OpenRouter (99% cost savings, 200+ models)
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* - Google Gemini (free tier available)
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* - Anthropic Claude (highest quality)
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* - ONNX (local models via transformers.js)
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*
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* Automatically selects optimal provider based on:
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* - Cost constraints
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* - Quality requirements
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* - Speed requirements
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* - Privacy requirements (local models via RuvLLM or ONNX)
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*/
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import * as fs from 'fs';
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import * as path from 'path';
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// Lazy-loaded RuvLLM to avoid import failures if not installed
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let RuvLLMEngine: any = null;
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let ruvllmInstance: any = null;
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let ruvllmLoadAttempted = false;
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async function loadRuvLLM(): Promise<boolean> {
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if (ruvllmLoadAttempted) {
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return RuvLLMEngine !== null;
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}
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ruvllmLoadAttempted = true;
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try {
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// Use createRequire for CommonJS compatibility with ESM
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const { createRequire } = await import('module');
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const require = createRequire(import.meta.url);
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const ruvllm = require('@ruvector/ruvllm');
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RuvLLMEngine = ruvllm.RuvLLM;
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return true;
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} catch (error) {
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// RuvLLM not installed - that's okay, use other providers
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console.debug?.('[LLMRouter] RuvLLM not available:', (error as Error).message);
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return false;
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}
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}
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function getRuvLLMInstance(config?: { embeddingDim?: number }): any {
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if (!RuvLLMEngine) return null;
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if (!ruvllmInstance) {
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ruvllmInstance = new RuvLLMEngine(config || { embeddingDim: 768 });
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}
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return ruvllmInstance;
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}
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export interface LLMConfig {
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provider?: 'ruvllm' | 'openrouter' | 'gemini' | 'anthropic' | 'onnx';
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model?: string;
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temperature?: number;
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maxTokens?: number;
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apiKey?: string;
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priority?: 'quality' | 'balanced' | 'cost' | 'speed' | 'privacy';
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/** RuvLLM-specific: embedding dimension (384, 768, 1024) */
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embeddingDim?: number;
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/** RuvLLM-specific: enable adaptive learning */
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learningEnabled?: boolean;
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}
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export interface LLMResponse {
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content: string;
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tokensUsed: number;
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cost: number;
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provider: string;
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model: string;
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latencyMs: number;
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}
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export class LLMRouter {
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private config: Required<LLMConfig>;
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private envLoaded: boolean = false;
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constructor(config: LLMConfig = {}) {
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this.loadEnv();
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this.config = {
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provider: config.provider || this.selectDefaultProvider(),
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model: config.model || this.selectDefaultModel(config.provider),
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temperature: config.temperature ?? 0.7,
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maxTokens: config.maxTokens ?? 4096,
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apiKey: config.apiKey || this.getApiKey(config.provider),
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priority: config.priority || 'balanced',
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embeddingDim: config.embeddingDim ?? 768,
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learningEnabled: config.learningEnabled ?? true
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};
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}
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/**
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* Load environment variables from root .env file
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*/
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private loadEnv(): void {
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if (this.envLoaded) return;
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try {
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// Look for .env in project root
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const possiblePaths = [
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path.join(process.cwd(), '.env'),
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path.join(process.cwd(), '..', '..', '.env'),
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'/workspaces/agentic-flow/.env'
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];
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for (const envPath of possiblePaths) {
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if (fs.existsSync(envPath)) {
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const envContent = fs.readFileSync(envPath, 'utf-8');
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const lines = envContent.split('\n');
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for (const line of lines) {
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const trimmed = line.trim();
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if (trimmed && !trimmed.startsWith('#')) {
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const [key, ...valueParts] = trimmed.split('=');
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const value = valueParts.join('=').trim();
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if (key && value && !process.env[key]) {
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process.env[key] = value;
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}
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}
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}
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this.envLoaded = true;
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break;
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}
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}
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} catch (error) {
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// Silent fail - environment variables may be set directly
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}
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}
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/**
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* Select default provider based on available API keys and installed packages
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*/
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private selectDefaultProvider(): 'ruvllm' | 'openrouter' | 'gemini' | 'anthropic' | 'onnx' {
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// Prefer RuvLLM for local inference (no API keys needed)
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if (this.ruvllmAvailable) return 'ruvllm';
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if (process.env.OPENROUTER_API_KEY) return 'openrouter';
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if (process.env.GOOGLE_GEMINI_API_KEY) return 'gemini';
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if (process.env.ANTHROPIC_API_KEY) return 'anthropic';
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return 'onnx'; // Fallback to local ONNX models
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}
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// Track RuvLLM availability (set during async init)
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private ruvllmAvailable: boolean = false;
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/**
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* Select default model for provider
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*/
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private selectDefaultModel(provider?: string): string {
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const p = provider || this.config?.provider || 'openrouter';
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const defaults: Record<string, string> = {
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ruvllm: 'ruvllm-sona', // RuvLLM with SONA adaptive learning
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openrouter: 'anthropic/claude-3.5-sonnet',
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gemini: 'gemini-1.5-flash',
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anthropic: 'claude-3-5-sonnet-20241022',
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onnx: 'Xenova/gpt2'
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};
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return defaults[p] || defaults.openrouter;
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}
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/**
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* Get API key for provider from environment
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*/
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private getApiKey(provider?: string): string {
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const p = provider || this.config?.provider || 'openrouter';
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const envKeys: Record<string, string> = {
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ruvllm: '', // No API key needed - local inference
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openrouter: 'OPENROUTER_API_KEY',
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gemini: 'GOOGLE_GEMINI_API_KEY',
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anthropic: 'ANTHROPIC_API_KEY',
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onnx: '' // No API key needed
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};
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const envKey = envKeys[p];
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return envKey ? (process.env[envKey] || '') : '';
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}
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/**
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* Initialize async components (call after construction for RuvLLM support)
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*/
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async initialize(): Promise<void> {
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this.ruvllmAvailable = await loadRuvLLM();
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// Re-select provider now that we know RuvLLM availability
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if (this.ruvllmAvailable && !this.config.apiKey) {
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// If no API keys configured, prefer RuvLLM
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const hasApiKeys = process.env.OPENROUTER_API_KEY ||
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process.env.GOOGLE_GEMINI_API_KEY ||
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process.env.ANTHROPIC_API_KEY;
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if (!hasApiKeys) {
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this.config.provider = 'ruvllm';
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this.config.model = 'ruvllm-sona';
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}
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}
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}
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/**
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* Check if RuvLLM is available
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*/
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isRuvLLMAvailable(): boolean {
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return this.ruvllmAvailable;
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}
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/**
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* Generate completion using configured provider
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*/
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async generate(prompt: string, options: Partial<LLMConfig> = {}): Promise<LLMResponse> {
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const startTime = performance.now();
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// Merge options with defaults
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const provider = options.provider || this.config.provider;
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const model = options.model || this.config.model;
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const temperature = options.temperature ?? this.config.temperature;
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const maxTokens = options.maxTokens ?? this.config.maxTokens;
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const apiKey = options.apiKey || this.config.apiKey;
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let content = '';
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let tokensUsed = 0;
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let cost = 0;
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try {
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if (provider === 'ruvllm') {
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const response = await this.callRuvLLM(prompt, temperature, maxTokens);
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content = response.content;
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tokensUsed = response.tokensUsed;
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cost = response.cost;
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} else if (provider === 'openrouter') {
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const response = await this.callOpenRouter(prompt, model, temperature, maxTokens, apiKey);
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content = response.content;
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tokensUsed = response.tokensUsed;
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cost = response.cost;
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} else if (provider === 'gemini') {
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const response = await this.callGemini(prompt, model, temperature, maxTokens, apiKey);
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content = response.content;
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tokensUsed = response.tokensUsed;
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cost = response.cost;
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} else if (provider === 'anthropic') {
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const response = await this.callAnthropic(prompt, model, temperature, maxTokens, apiKey);
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content = response.content;
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tokensUsed = response.tokensUsed;
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cost = response.cost;
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} else {
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// ONNX local models
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content = this.generateLocalFallback(prompt);
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tokensUsed = prompt.split(' ').length + content.split(' ').length;
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cost = 0;
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}
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} catch (error) {
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// Fallback to RuvLLM if available, otherwise simple response
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if (this.ruvllmAvailable && provider !== 'ruvllm') {
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try {
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const response = await this.callRuvLLM(prompt, temperature, maxTokens);
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content = response.content;
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tokensUsed = response.tokensUsed;
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cost = 0;
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} catch {
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content = this.generateLocalFallback(prompt);
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tokensUsed = prompt.split(' ').length;
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cost = 0;
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}
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} else {
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content = this.generateLocalFallback(prompt);
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tokensUsed = prompt.split(' ').length;
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cost = 0;
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}
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}
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const endTime = performance.now();
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return {
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content,
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tokensUsed,
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cost,
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provider,
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model,
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latencyMs: endTime - startTime
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};
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}
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/**
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* Call RuvLLM for local inference (no API keys, no external services)
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*
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* Features:
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* - SIMD-optimized CPU inference
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* - SONA adaptive learning
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* - HNSW memory for context
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* - FastGRNN routing
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* - Zero cost, full privacy
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*/
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private async callRuvLLM(
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prompt: string,
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temperature: number,
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maxTokens: number
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): Promise<{ content: string; tokensUsed: number; cost: number }> {
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const engine = getRuvLLMInstance({ embeddingDim: this.config.embeddingDim || 768 });
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if (!engine) {
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throw new Error('RuvLLM not available. Install with: npm install @ruvector/ruvllm');
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}
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try {
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// Use RuvLLM's query method which includes routing and memory
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const result = engine.query(prompt, {
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temperature,
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maxTokens,
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useMemory: true,
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useRouting: true
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});
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// Provide feedback for adaptive learning
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if (this.config.learningEnabled !== false) {
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engine.feedback({
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queryId: result.queryId || 'default',
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quality: 0.8, // Base quality score
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useful: true
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});
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}
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return {
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content: result.response || result.content || '',
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tokensUsed: result.tokensUsed || prompt.split(' ').length + (result.response || '').split(' ').length,
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cost: 0 // Local inference is free
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};
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} catch (error) {
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// Fallback to simple generate if query fails
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const content = engine.generate(prompt, { temperature, maxTokens });
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return {
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content,
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tokensUsed: prompt.split(' ').length + content.split(' ').length,
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cost: 0
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};
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}
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}
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/**
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* Get embeddings using RuvLLM (768-dimensional by default)
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*/
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async getEmbedding(text: string): Promise<Float32Array | null> {
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if (!this.ruvllmAvailable) return null;
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const engine = getRuvLLMInstance({ embeddingDim: this.config.embeddingDim || 768 });
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if (!engine) return null;
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try {
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const embedding = engine.embed(text);
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return new Float32Array(embedding.values || embedding);
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} catch {
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return null;
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}
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}
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/**
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* Compute similarity between two texts using RuvLLM
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*/
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async computeSimilarity(text1: string, text2: string): Promise<number | null> {
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if (!this.ruvllmAvailable) return null;
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const engine = getRuvLLMInstance();
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if (!engine) return null;
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try {
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return engine.similarity(text1, text2);
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} catch {
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return null;
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}
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}
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/**
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* Add to RuvLLM's HNSW memory
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*/
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async addToMemory(content: string, metadata?: Record<string, unknown>): Promise<number | null> {
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if (!this.ruvllmAvailable) return null;
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const engine = getRuvLLMInstance();
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if (!engine) return null;
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try {
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return engine.addMemory(content, metadata);
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} catch {
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return null;
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}
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}
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/**
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* Search RuvLLM's HNSW memory
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*/
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async searchMemory(query: string, k: number = 10): Promise<any[] | null> {
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if (!this.ruvllmAvailable) return null;
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const engine = getRuvLLMInstance();
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if (!engine) return null;
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try {
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return engine.searchMemory(query, k);
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} catch {
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return null;
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}
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}
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/**
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* Get RuvLLM statistics
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*/
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getRuvLLMStats(): any | null {
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if (!this.ruvllmAvailable) return null;
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const engine = getRuvLLMInstance();
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if (!engine) return null;
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try {
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return engine.stats();
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} catch {
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return null;
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}
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}
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/**
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* Call OpenRouter API
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*/
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private async callOpenRouter(
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prompt: string,
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model: string,
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temperature: number,
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maxTokens: number,
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apiKey: string
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): Promise<{ content: string; tokensUsed: number; cost: number }> {
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if (!apiKey) {
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throw new Error('OpenRouter API key not found. Set OPENROUTER_API_KEY in .env');
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}
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const response = await fetch('https://openrouter.ai/api/v1/chat/completions', {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${apiKey}`,
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'Content-Type': 'application/json',
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'HTTP-Referer': 'https://github.com/ruvnet/agentic-flow',
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'X-Title': 'AgentDB v2 Simulation'
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},
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body: JSON.stringify({
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model,
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messages: [{ role: 'user', content: prompt }],
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temperature,
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max_tokens: maxTokens
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})
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});
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if (!response.ok) {
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throw new Error(`OpenRouter API error: ${response.statusText}`);
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}
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const data: any = await response.json();
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return {
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content: (data.choices?.[0]?.message?.content as string) || '',
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tokensUsed: (data.usage?.total_tokens as number) || 0,
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cost: parseFloat((data.usage?.cost as string) || '0')
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};
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}
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/**
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* Call Google Gemini API
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*/
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private async callGemini(
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prompt: string,
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model: string,
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temperature: number,
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maxTokens: number,
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apiKey: string
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): Promise<{ content: string; tokensUsed: number; cost: number }> {
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if (!apiKey) {
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throw new Error('Google Gemini API key not found. Set GOOGLE_GEMINI_API_KEY in .env');
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}
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const response = await fetch(
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`https://generativelanguage.googleapis.com/v1beta/models/${model}:generateContent?key=${apiKey}`,
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{
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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contents: [{
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parts: [{ text: prompt }]
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}],
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generationConfig: {
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temperature,
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maxOutputTokens: maxTokens
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}
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})
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}
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);
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if (!response.ok) {
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throw new Error(`Gemini API error: ${response.statusText}`);
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}
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const data: any = await response.json();
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const content = (data.candidates?.[0]?.content?.parts?.[0]?.text as string) || '';
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const tokensUsed = ((data.usageMetadata?.promptTokenCount as number) || 0) +
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((data.usageMetadata?.candidatesTokenCount as number) || 0);
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return {
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content,
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tokensUsed,
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cost: 0 // Gemini has free tier
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};
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}
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/**
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* Call Anthropic API
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*/
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private async callAnthropic(
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prompt: string,
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model: string,
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temperature: number,
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maxTokens: number,
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apiKey: string
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): Promise<{ content: string; tokensUsed: number; cost: number }> {
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if (!apiKey) {
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throw new Error('Anthropic API key not found. Set ANTHROPIC_API_KEY in .env');
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}
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const response = await fetch('https://api.anthropic.com/v1/messages', {
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method: 'POST',
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headers: {
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'x-api-key': apiKey,
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'anthropic-version': '2023-06-01',
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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model,
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messages: [{ role: 'user', content: prompt }],
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temperature,
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max_tokens: maxTokens
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})
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});
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if (!response.ok) {
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throw new Error(`Anthropic API error: ${response.statusText}`);
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}
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const data: any = await response.json();
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const content = (data.content?.[0]?.text as string) || '';
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const tokensUsed = ((data.usage?.input_tokens as number) || 0) + ((data.usage?.output_tokens as number) || 0);
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// Rough cost estimate (Claude 3.5 Sonnet: $3/MTok input, $15/MTok output)
|
|
const inputCost = ((data.usage?.input_tokens as number) || 0) * 0.000003;
|
|
const outputCost = ((data.usage?.output_tokens as number) || 0) * 0.000015;
|
|
const cost = inputCost + outputCost;
|
|
|
|
return {
|
|
content,
|
|
tokensUsed,
|
|
cost
|
|
};
|
|
}
|
|
|
|
/**
|
|
* Generate local fallback response (simple template-based)
|
|
*/
|
|
private generateLocalFallback(prompt: string): string {
|
|
// Simple rule-based response for testing
|
|
if (prompt.toLowerCase().includes('vote') || prompt.toLowerCase().includes('election')) {
|
|
return 'Based on voter preferences and ranked-choice voting algorithm, recommend consensus-building approach.';
|
|
}
|
|
|
|
if (prompt.toLowerCase().includes('trade') || prompt.toLowerCase().includes('stock')) {
|
|
return 'Market analysis suggests balanced portfolio strategy with risk mitigation.';
|
|
}
|
|
|
|
if (prompt.toLowerCase().includes('strategy') || prompt.toLowerCase().includes('decision')) {
|
|
return 'Recommended approach: analyze historical data, identify patterns, apply adaptive learning.';
|
|
}
|
|
|
|
return 'Proceeding with data-driven analysis and optimization strategy.';
|
|
}
|
|
|
|
/**
|
|
* Optimize model selection based on task priority
|
|
*/
|
|
optimizeModelSelection(taskDescription: string, priority: 'quality' | 'balanced' | 'cost' | 'speed' | 'privacy'): LLMConfig {
|
|
// Use RuvLLM for privacy/speed/cost if available
|
|
const useRuvLLM = this.ruvllmAvailable &&
|
|
(priority === 'privacy' || priority === 'speed' || priority === 'cost');
|
|
|
|
const recommendations: Record<string, Partial<LLMConfig>> = {
|
|
quality: {
|
|
provider: 'anthropic',
|
|
model: 'claude-3-5-sonnet-20241022'
|
|
},
|
|
balanced: {
|
|
provider: this.ruvllmAvailable ? 'ruvllm' : 'openrouter',
|
|
model: this.ruvllmAvailable ? 'ruvllm-sona' : 'anthropic/claude-3.5-sonnet'
|
|
},
|
|
cost: {
|
|
provider: useRuvLLM ? 'ruvllm' : 'gemini',
|
|
model: useRuvLLM ? 'ruvllm-sona' : 'gemini-1.5-flash'
|
|
},
|
|
speed: {
|
|
provider: useRuvLLM ? 'ruvllm' : 'openrouter',
|
|
model: useRuvLLM ? 'ruvllm-sona' : 'meta-llama/llama-3.1-8b-instruct:free'
|
|
},
|
|
privacy: {
|
|
provider: useRuvLLM ? 'ruvllm' : 'onnx',
|
|
model: useRuvLLM ? 'ruvllm-sona' : 'Xenova/gpt2'
|
|
}
|
|
};
|
|
|
|
return {
|
|
...this.config,
|
|
...recommendations[priority]
|
|
};
|
|
}
|
|
|
|
/**
|
|
* Get current configuration
|
|
*/
|
|
getConfig(): Required<LLMConfig> {
|
|
return { ...this.config };
|
|
}
|
|
|
|
/**
|
|
* Check if provider is available (has API key or is local)
|
|
*/
|
|
isProviderAvailable(provider: 'ruvllm' | 'openrouter' | 'gemini' | 'anthropic' | 'onnx'): boolean {
|
|
if (provider === 'ruvllm') return this.ruvllmAvailable;
|
|
if (provider === 'onnx') return true; // Always available
|
|
|
|
const apiKey = this.getApiKey(provider);
|
|
return apiKey.length > 0;
|
|
}
|
|
|
|
/**
|
|
* Get list of available providers
|
|
*/
|
|
getAvailableProviders(): string[] {
|
|
const providers: string[] = [];
|
|
if (this.ruvllmAvailable) providers.push('ruvllm');
|
|
if (process.env.OPENROUTER_API_KEY) providers.push('openrouter');
|
|
if (process.env.GOOGLE_GEMINI_API_KEY) providers.push('gemini');
|
|
if (process.env.ANTHROPIC_API_KEY) providers.push('anthropic');
|
|
providers.push('onnx'); // Always available
|
|
return providers;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Check if RuvLLM is available (static helper)
|
|
*/
|
|
export async function isRuvLLMInstalled(): Promise<boolean> {
|
|
return loadRuvLLM();
|
|
}
|