const OpenAI = require('openai'); const WebSocket = require('ws'); /** * Creates and returns an OpenAI client instance for STT (Speech-to-Text). * @param {string} apiKey - The API key for authentication. * @returns {OpenAI} The initialized OpenAI client. */ function createOpenAiClient(apiKey) { return new OpenAI({ apiKey: apiKey, }); } /** * Creates and returns an OpenAI client instance for text/image generation. * @param {string} apiKey - The API key for authentication. * @returns {OpenAI} The initialized OpenAI client. */ function createOpenAiGenerativeClient(apiKey) { return new OpenAI({ apiKey: apiKey, }); } /** * Connects to an OpenAI Realtime WebSocket session for STT. * @param {string} key - Portkey vKey or OpenAI apiKey. * @param {object} config - The configuration object for the realtime session. * @param {'apiKey'|'vKey'} keyType - key type ('apiKey' | 'vKey'). * @returns {Promise} A promise that resolves to the session object with send and close methods. */ async function connectToOpenAiSession(key, config, keyType) { if (keyType !== 'apiKey' && keyType !== 'vKey') { throw new Error('keyType must be either "apiKey" or "vKey".'); } const wsUrl = keyType === 'apiKey' ? 'wss://api.openai.com/v1/realtime?intent=transcription' : 'wss://api.portkey.ai/v1/realtime?intent=transcription'; const headers = keyType === 'apiKey' ? { 'Authorization': `Bearer ${key}`, 'OpenAI-Beta' : 'realtime=v1', } : { 'x-portkey-api-key' : 'gRv2UGRMq6GGLJ8aVEB4e7adIewu', 'x-portkey-virtual-key': key, 'OpenAI-Beta' : 'realtime=v1', }; const ws = new WebSocket(wsUrl, { headers }); return new Promise((resolve, reject) => { ws.onopen = () => { console.log("WebSocket session opened."); const sessionConfig = { type: 'transcription_session.update', session: { input_audio_format: 'pcm16', input_audio_transcription: { model: 'gpt-4o-mini-transcribe', prompt: config.prompt || '', language: config.language || 'en' }, turn_detection: { type: 'server_vad', threshold: 0.5, prefix_padding_ms: 50, silence_duration_ms: 25, }, input_audio_noise_reduction: { type: 'near_field' } } }; ws.send(JSON.stringify(sessionConfig)); resolve({ sendRealtimeInput: (audioData) => { if (ws.readyState === WebSocket.OPEN) { const message = { type: 'input_audio_buffer.append', audio: audioData }; ws.send(JSON.stringify(message)); } }, close: () => { if (ws.readyState === WebSocket.OPEN) { ws.send(JSON.stringify({ type: 'session.close' })); ws.close(1000, 'Client initiated close.'); } } }); }; ws.onmessage = (event) => { const message = JSON.parse(event.data); if (config.callbacks && config.callbacks.onmessage) { config.callbacks.onmessage(message); } }; ws.onerror = (error) => { console.error('WebSocket error:', error.message); if (config.callbacks && config.callbacks.onerror) { config.callbacks.onerror(error); } reject(error); }; ws.onclose = (event) => { console.log(`WebSocket closed: ${event.code} ${event.reason}`); if (config.callbacks && config.callbacks.onclose) { config.callbacks.onclose(event); } }; }); } /** * Gets a GPT model for text/image generation. * @param {OpenAI} client - The OpenAI client instance. * @param {string} [model='gpt-4.1'] - The name for the text/vision model. * @returns {object} Model object with generateContent method */ function getOpenAiGenerativeModel(client, model = 'gpt-4.1') { return { generateContent: async (parts) => { const messages = []; let systemPrompt = ''; let userContent = []; for (const part of parts) { if (typeof part === 'string') { if (systemPrompt === '' && part.includes('You are')) { systemPrompt = part; } else { userContent.push({ type: 'text', text: part }); } } else if (part.inlineData) { userContent.push({ type: 'image_url', image_url: { url: `data:${part.inlineData.mimeType};base64,${part.inlineData.data}` } }); } } if (systemPrompt) messages.push({ role: 'system', content: systemPrompt }); if (userContent.length > 0) messages.push({ role: 'user', content: userContent }); const response = await client.chat.completions.create({ model: model, messages: messages, temperature: 0.7, max_tokens: 2048 }); return { response: { text: () => response.choices[0].message.content } }; } }; } module.exports = { createOpenAiClient, connectToOpenAiSession, createOpenAiGenerativeClient, getOpenAiGenerativeModel, };