AI MCP Gateway

import OpenAI from 'openai'; import { LLMClient, calculateCost } from './client.js'; import { LLMRequest, LLMResponse } from '../../mcp/types.js'; import { ModelConfig } from '../../config/models.js'; import { env } from '../../config/env.js'; import { logger } from '../../logging/logger.js'; import { providerManager } from '../../config/provider-manager.js'; /** * OpenAI GPT LLM client */ export class OpenAIClient implements LLMClient { private client: OpenAI | null = null; private async getClient(): Promise<OpenAI> { if (!this.client) { // Try to get API key from database first let apiKey = await providerManager.getApiKey('openai'); // Fallback to environment variable if (!apiKey) { apiKey = env.OPENAI_API_KEY; } if (!apiKey) { throw new Error('OPENAI_API_KEY is not configured in database or environment'); } this.client = new OpenAI({ apiKey }); } return this.client; } canHandle(provider: string): boolean { return provider === 'openai'; } async call( request: LLMRequest, model: ModelConfig, ): Promise<Omit<LLMResponse, 'routingSummary'>> { const client = await this.getClient(); logger.debug('Calling OpenAI API', { model: model.apiModelName, promptLength: request.prompt.length, }); try { const messages: OpenAI.Chat.ChatCompletionMessageParam[] = []; if (request.systemPrompt) { messages.push({ role: 'system', content: request.systemPrompt, }); } messages.push({ role: 'user', content: request.prompt, }); // Log full prompt for debugging logger.info('[OpenAI] Sending prompt to model', { model: model.apiModelName, systemPrompt: request.systemPrompt ? request.systemPrompt.substring(0, 200) + '...' : 'none', userPrompt: request.prompt.substring(0, 500) + (request.prompt.length > 500 ? '...' : ''), fullPromptLength: request.prompt.length, maxTokens: request.maxTokens || 4096, temperature: request.temperature || 0.7, }); // Log complete messages array for detailed debugging logger.debug('[OpenAI] Complete messages array', { messagesCount: messages.length, messages: messages.map(m => ({ role: m.role, contentPreview: typeof m.content === 'string' ? m.content.substring(0, 200) + (m.content.length > 200 ? '...' : '') : '[complex content]' })), }); const response = await client.chat.completions.create({ model: model.apiModelName, messages, max_tokens: request.maxTokens || 4096, temperature: request.temperature || 0.7, }); const content = response.choices[0]?.message?.content || ''; const inputTokens = response.usage?.prompt_tokens || 0; const outputTokens = response.usage?.completion_tokens || 0; const cost = calculateCost(inputTokens, outputTokens, model); return { content, modelId: model.id, provider: model.provider, inputTokens, outputTokens, cost, }; } catch (error) { logger.error('OpenAI API error', { model: model.apiModelName, error: error instanceof Error ? error.message : 'Unknown error', }); throw error; } } }