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const { VertexAI, RequestOptions } = require('@google-cloud/vertexai'); | |
const fs = require('fs'); | |
const path = require('path'); | |
const os = require('os'); | |
const { writeFileSync } = require('fs'); | |
// Import fetch if the SDK uses it | |
const originalFetch = global.fetch || require('node-fetch'); | |
// Monkey-patch the fetch used internally | |
global.fetch = async function patchedFetch(url, options) { | |
// Modify the URL to use HTTP instead of HTTPS | |
if (url.startsWith('https://localhost:4000')) { | |
url = url.replace('https://', 'http://'); | |
} | |
console.log('Patched fetch sending request to:', url); | |
return originalFetch(url, options); | |
}; | |
function loadVertexAiCredentials() { | |
console.log("loading vertex ai credentials"); | |
const filepath = path.dirname(__filename); | |
const vertexKeyPath = path.join(filepath, "vertex_key.json"); | |
// Initialize default empty service account data | |
let serviceAccountKeyData = {}; | |
// Try to read existing vertex_key.json | |
try { | |
const content = fs.readFileSync(vertexKeyPath, 'utf8'); | |
if (content && content.trim()) { | |
serviceAccountKeyData = JSON.parse(content); | |
} | |
} catch (error) { | |
// File doesn't exist or is invalid, continue with empty object | |
} | |
// Update with environment variables | |
const privateKeyId = process.env.VERTEX_AI_PRIVATE_KEY_ID || ""; | |
const privateKey = (process.env.VERTEX_AI_PRIVATE_KEY || "").replace(/\\n/g, "\n"); | |
serviceAccountKeyData.private_key_id = privateKeyId; | |
serviceAccountKeyData.private_key = privateKey; | |
// Create temporary file | |
const tempFilePath = path.join(os.tmpdir(), `vertex-credentials-${Date.now()}.json`); | |
writeFileSync(tempFilePath, JSON.stringify(serviceAccountKeyData, null, 2)); | |
// Set environment variable | |
process.env.GOOGLE_APPLICATION_CREDENTIALS = tempFilePath; | |
} | |
// Run credential loading before tests | |
beforeAll(() => { | |
loadVertexAiCredentials(); | |
}); | |
describe('Vertex AI Tests', () => { | |
test('should successfully generate content from Vertex AI', async () => { | |
const vertexAI = new VertexAI({ | |
project: 'pathrise-convert-1606954137718', | |
location: 'us-central1', | |
apiEndpoint: "localhost:4000/vertex-ai" | |
}); | |
const customHeaders = new Headers({ | |
"x-litellm-api-key": "sk-1234" | |
}); | |
const requestOptions = { | |
customHeaders: customHeaders | |
}; | |
const generativeModel = vertexAI.getGenerativeModel( | |
{ model: 'gemini-1.5-pro' }, | |
requestOptions | |
); | |
const request = { | |
contents: [{role: 'user', parts: [{text: 'How are you doing today tell me your name?'}]}], | |
}; | |
const streamingResult = await generativeModel.generateContentStream(request); | |
// Add some assertions | |
expect(streamingResult).toBeDefined(); | |
for await (const item of streamingResult.stream) { | |
console.log('stream chunk:', JSON.stringify(item)); | |
expect(item).toBeDefined(); | |
} | |
const aggregatedResponse = await streamingResult.response; | |
console.log('aggregated response:', JSON.stringify(aggregatedResponse)); | |
expect(aggregatedResponse).toBeDefined(); | |
}); | |
test('should successfully generate non-streaming content from Vertex AI', async () => { | |
const vertexAI = new VertexAI({project: 'pathrise-convert-1606954137718', location: 'us-central1', apiEndpoint: "localhost:4000/vertex-ai"}); | |
const customHeaders = new Headers({"x-litellm-api-key": "sk-1234"}); | |
const requestOptions = {customHeaders: customHeaders}; | |
const generativeModel = vertexAI.getGenerativeModel({model: 'gemini-1.5-pro'}, requestOptions); | |
const request = {contents: [{role: 'user', parts: [{text: 'What is 2+2?'}]}]}; | |
const result = await generativeModel.generateContent(request); | |
expect(result).toBeDefined(); | |
expect(result.response).toBeDefined(); | |
console.log('non-streaming response:', JSON.stringify(result.response)); | |
}); | |
}); |