UNPKG

@llumiverse/drivers

Version:

LLM driver implementations. Currently supported are: openai, huggingface, bedrock, replicate.

102 lines (75 loc) 3.25 kB
import { AIModel, DriverOptions, PromptOptions, PromptSegment, Providers } from "@llumiverse/core"; import { formatOpenAILikeMultimodalPrompt, OpenAIPromptFormatterOptions } from "../openai/openai_format.js"; import { FetchClient } from "@vertesia/api-fetch-client"; import OpenAI from "openai"; import { BaseOpenAIDriver } from "../openai/index.js"; export interface xAiDriverOptions extends DriverOptions { apiKey: string; endpoint?: string; } export class xAIDriver extends BaseOpenAIDriver { service: OpenAI; readonly provider = Providers.xai; xai_service: FetchClient; DEFAULT_ENDPOINT = "https://api.x.ai/v1"; constructor(opts: xAiDriverOptions) { super(opts); if (!opts.apiKey) { throw new Error("apiKey is required"); } this.service = new OpenAI({ apiKey: opts.apiKey, baseURL: opts.endpoint ?? this.DEFAULT_ENDPOINT, }); this.xai_service = new FetchClient(opts.endpoint ?? this.DEFAULT_ENDPOINT).withAuthCallback(async () => `Bearer ${opts.apiKey}`); //this.formatPrompt = this._formatPrompt; //TODO: fix xai prompt formatting } async _formatPrompt(segments: PromptSegment[], opts: PromptOptions): Promise<OpenAI.Chat.Completions.ChatCompletionMessageParam[]> { const options: OpenAIPromptFormatterOptions = { multimodal: opts.model.includes("vision"), schema: opts.result_schema, useToolForFormatting: false, } const p = await formatOpenAILikeMultimodalPrompt(segments, { ...options, ...opts }) as OpenAI.Chat.Completions.ChatCompletionMessageParam[]; return p; } // Note: We intentionally do NOT override extractDataFromResponse here. // The base class implementation properly handles tool_calls extraction. // xAI's API is OpenAI-compatible and returns tool_calls in the same format. async listModels(): Promise<AIModel[]> { const [lm, em] = await Promise.all([ this.xai_service.get("/language-models"), this.xai_service.get("/embedding-models") ]) as [xAIModelResponse, xAIModelResponse]; em.models.forEach(m => { m.output_modalities.push("vectors"); }); const models = [...lm.models, ...em.models].map(model => { return { id: model.id, provider: this.provider, name: model.id, description: `${model.id} by ${model.owned_by}`, is_multimodal: model.input_modalities.length > 1, input_modalities: model.input_modalities, output_modalities: model.output_modalities, tags: [...model.input_modalities.map(m => `i:${m}`), ...model.output_modalities.map(m => `o:${m}`)], } satisfies AIModel; }); return models; } } interface xAIModelResponse { models: xAIModel[]; } interface xAIModel { completion_text_token_price: number; created: number; id: string; input_modalities: string[]; object: string; output_modalities: string[]; owned_by: string; prompt_image_token_price: number; prompt_text_token_price: number; }