UNPKG

multi-llm

Version:

A unified TypeScript/JavaScript package to use LLMs across ALL platforms with support for 17 major providers, streaming, MCP tools, and intelligent response parsing

122 lines 5 kB
"use strict"; var __importDefault = (this && this.__importDefault) || function (mod) { return (mod && mod.__esModule) ? mod : { "default": mod }; }; Object.defineProperty(exports, "__esModule", { value: true }); exports.CerebrasProvider = void 0; const axios_1 = __importDefault(require("axios")); const provider_1 = require("../provider"); const llm_1 = require("../llm"); const parser_1 = require("../utils/parser"); class CerebrasProvider extends provider_1.Provider { constructor(apiKey, baseUrl) { super(apiKey, baseUrl); this.baseUrl = baseUrl || 'https://api.cerebras.ai/v1'; } async getModels() { // Cerebras doesn't have a models endpoint, so we return known models return [ { id: 'llama3.1-8b', name: 'Llama 3.1 8B', contextWindow: 128000, maxOutputTokens: 8192, pricing: { input: 0.00010, output: 0.00010, currency: 'USD' } }, { id: 'llama3.1-70b', name: 'Llama 3.1 70B', contextWindow: 128000, maxOutputTokens: 8192, pricing: { input: 0.00060, output: 0.00060, currency: 'USD' } } ]; } createLLM(modelId) { return new llm_1.LLM(this, modelId); } async chat(modelId, messages, options, streamCallback) { try { const payload = { model: modelId, messages: messages.map(msg => ({ role: msg.role, content: msg.content })), temperature: options.temperature, max_tokens: options.maxTokens, top_p: options.topP, stream: !!streamCallback }; if (streamCallback) { return this.streamChat(payload, streamCallback); } else { const response = await axios_1.default.post(`${this.baseUrl}/chat/completions`, payload, { headers: { 'Authorization': `Bearer ${this.apiKey}`, 'Content-Type': 'application/json' } }); const content = response.data.choices[0].message.content; const parsed = parser_1.ResponseParser.parseResponse(content); return { raw: response.data, parsed, usage: { inputTokens: response.data.usage?.prompt_tokens || 0, outputTokens: response.data.usage?.completion_tokens || 0, totalTokens: response.data.usage?.total_tokens || 0 } }; } } catch (error) { throw new Error(`Cerebras chat failed: ${error}`); } } async streamChat(payload, streamCallback) { return new Promise((resolve, reject) => { let fullContent = ''; let rawResponse = null; const source = axios_1.default.post(`${this.baseUrl}/chat/completions`, payload, { headers: { 'Authorization': `Bearer ${this.apiKey}`, 'Content-Type': 'application/json' }, responseType: 'stream' }); source.then(response => { response.data.on('data', (chunk) => { const lines = chunk.toString().split('\n'); for (const line of lines) { if (line.startsWith('data: ')) { const data = line.slice(6); if (data === '[DONE]') { const parsed = parser_1.ResponseParser.parseResponse(fullContent); resolve({ raw: rawResponse, parsed, usage: undefined }); return; } try { const parsed = JSON.parse(data); rawResponse = parsed; const content = parsed.choices[0]?.delta?.content || ''; if (content) { fullContent += content; streamCallback(content); } } catch (e) { // Ignore parsing errors for partial chunks } } } }); response.data.on('error', reject); }).catch(reject); }); } } exports.CerebrasProvider = CerebrasProvider; //# sourceMappingURL=cerebras.js.map