import * as plugins from './plugins.js'; import * as paths from './paths.js'; import { MultiModalModel } from './abstract.classes.multimodal.js'; import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js'; import type { ChatCompletionMessageParam } from 'openai/resources/chat/completions'; export interface IXAIProviderOptions { xaiToken: string; } export class XAIProvider extends MultiModalModel { private options: IXAIProviderOptions; public openAiApiClient: plugins.openai.default; public smartpdfInstance: plugins.smartpdf.SmartPdf; constructor(optionsArg: IXAIProviderOptions) { super(); this.options = optionsArg; } public async start() { this.openAiApiClient = new plugins.openai.default({ apiKey: this.options.xaiToken, baseURL: 'https://api.x.ai/v1', }); this.smartpdfInstance = new plugins.smartpdf.SmartPdf(); } public async stop() {} public async chatStream(input: ReadableStream): Promise> { // Create a TextDecoder to handle incoming chunks const decoder = new TextDecoder(); let buffer = ''; let currentMessage: { role: string; content: string; } | null = null; // Create a TransformStream to process the input const transform = new TransformStream({ async transform(chunk, controller) { buffer += decoder.decode(chunk, { stream: true }); // Try to parse complete JSON messages from the buffer while (true) { const newlineIndex = buffer.indexOf('\n'); if (newlineIndex === -1) break; const line = buffer.slice(0, newlineIndex); buffer = buffer.slice(newlineIndex + 1); if (line.trim()) { try { const message = JSON.parse(line); currentMessage = { role: message.role || 'user', content: message.content || '', }; } catch (e) { console.error('Failed to parse message:', e); } } } // If we have a complete message, send it to X.AI if (currentMessage) { const stream = await this.openAiApiClient.chat.completions.create({ model: 'grok-2-latest', messages: [{ role: currentMessage.role, content: currentMessage.content }], stream: true, }); // Process each chunk from X.AI for await (const chunk of stream) { const content = chunk.choices[0]?.delta?.content; if (content) { controller.enqueue(content); } } currentMessage = null; } }, flush(controller) { if (buffer) { try { const message = JSON.parse(buffer); controller.enqueue(message.content || ''); } catch (e) { console.error('Failed to parse remaining buffer:', e); } } } }); // Connect the input to our transform stream return input.pipeThrough(transform); } public async chat(optionsArg: { systemMessage: string; userMessage: string; messageHistory: { role: string; content: string; }[]; }): Promise<{ role: 'assistant'; message: string; }> { // Prepare messages array with system message, history, and user message const messages: ChatCompletionMessageParam[] = [ { role: 'system', content: optionsArg.systemMessage }, ...optionsArg.messageHistory.map(msg => ({ role: msg.role as 'system' | 'user' | 'assistant', content: msg.content })), { role: 'user', content: optionsArg.userMessage } ]; // Call X.AI's chat completion API const completion = await this.openAiApiClient.chat.completions.create({ model: 'grok-2-latest', messages: messages, stream: false, }); // Return the assistant's response return { role: 'assistant', message: completion.choices[0]?.message?.content || '' }; } public async audio(optionsArg: { message: string }): Promise { throw new Error('Audio generation is not supported by X.AI'); } public async vision(optionsArg: { image: Buffer; prompt: string }): Promise { throw new Error('Vision tasks are not supported by X.AI'); } public async document(optionsArg: { systemMessage: string; userMessage: string; pdfDocuments: Uint8Array[]; messageHistory: { role: string; content: string; }[]; }): Promise<{ message: any }> { // First convert PDF documents to images let pdfDocumentImageBytesArray: Uint8Array[] = []; for (const pdfDocument of optionsArg.pdfDocuments) { const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument); pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray); } // Convert images to base64 for inclusion in the message const imageBase64Array = pdfDocumentImageBytesArray.map(bytes => Buffer.from(bytes).toString('base64') ); // Combine document images into the user message const enhancedUserMessage = ` ${optionsArg.userMessage} Document contents (as images): ${imageBase64Array.map((img, i) => `Image ${i + 1}: `).join('\n')} `; // Use chat completion to analyze the documents const messages: ChatCompletionMessageParam[] = [ { role: 'system', content: optionsArg.systemMessage }, ...optionsArg.messageHistory.map(msg => ({ role: msg.role as 'system' | 'user' | 'assistant', content: msg.content })), { role: 'user', content: enhancedUserMessage } ]; const completion = await this.openAiApiClient.chat.completions.create({ model: 'grok-2-latest', messages: messages, stream: false, }); return { message: completion.choices[0]?.message?.content || '' }; } }