#!/usr/bin/env node // Test specific embedding models with Nebius const NEBIUS_API_KEY = process.env.NEBIUS_API_KEY || 'eyJhbGciOiJIUzI1NiIsImtpZCI6IlV6SXJWd1h0dnprLVRvdzlLZWstc0M1akptWXBvX1VaVkxUZlpnMDRlOFUiLCJ0eXAiOiJKV1QifQ.eyJzdWIiOiJnb29nbGUtb2F1dGgyfDEwMzQwMDk5NTQzMzIwMjU0MzY2NSIsInNjb3BlIjoib3BlbmlkIG9mZmxpbmVfYWNjZXNzIiwiaXNzIjoiYXBpX2tleV9pc3N1ZXIiLCJhdWQiOlsiaHR0cHM6Ly9uZWJpdXMtaW5mZXJlbmNlLmV1LmF1dGgwLmNvbS9hcGkvdjIvIl0sImV4cCI6MTkwNzE0NjM0OCwidXVpZCI6IjIwZDU3YWIxLTcxYmUtNGI4ZS05MDk5LWRkODJkMDA0NWQyMCIsIm5hbWUiOiJIYWNrYXRob24iLCJleHBpcmVzX2F0IjoiMjAzMC0wNi0wOFQxMDo1MjoyOCswMDAwIn0.8WDxq0i62K0jM3ADXShpye0kvE-UBLgAYQ_jMeyJalQ'; async function testEmbeddings() { console.log('๐Ÿงช Testing Nebius embedding models...\n'); const baseUrl = 'https://api.studio.nebius.ai/v1'; const testText = 'What is RAG?'; const embeddingModels = [ 'BAAI/bge-en-icl', 'BAAI/bge-multilingual-gemma2', 'intfloat/e5-mistral-7b-instruct' ]; for (const model of embeddingModels) { try { console.log(`Testing ${model}...`); const response = await fetch(`${baseUrl}/embeddings`, { method: 'POST', headers: { 'Authorization': `Bearer ${NEBIUS_API_KEY}`, 'Content-Type': 'application/json' }, body: JSON.stringify({ input: testText, model: model }) }); if (response.ok) { const result = await response.json(); console.log(`โœ… ${model} SUCCESS!`); console.log(` Dimensions: ${result.data[0].embedding.length}`); console.log(` First 5 values: [${result.data[0].embedding.slice(0, 5).map(v => v.toFixed(4)).join(', ')}...]`); console.log(` Usage: ${result.usage.total_tokens} tokens\n`); break; // Found working model } else { const error = await response.text(); console.log(`โŒ ${model} failed: ${response.status} - ${error}\n`); } } catch (error) { console.log(`โŒ ${model} error: ${error.message}\n`); } } } testEmbeddings();