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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'); | |
| let lastCallId; | |
| // 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://127.0.0.1:4000')) { | |
| url = url.replace('https://', 'http://'); | |
| } | |
| console.log('Patched fetch sending request to:', url); | |
| const response = await originalFetch(url, options); | |
| // Store the call ID if it exists | |
| lastCallId = response.headers.get('x-litellm-call-id'); | |
| return response; | |
| }; | |
| 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-${Date.now()}.json`); | |
| writeFileSync(tempFilePath, JSON.stringify(serviceAccountKeyData, null, 2)); | |
| // Set environment variable | |
| process.env.GOOGLE_APPLICATION_CREDENTIALS = tempFilePath; | |
| } | |
| // Run credential loading before tests | |
| beforeAll(() => { | |
| loadVertexAiCredentials(); | |
| }); | |
| describe('Vertex AI Tests', () => { | |
| test('should successfully generate non-streaming content with tags', async () => { | |
| const vertexAI = new VertexAI({ | |
| project: 'pathrise-convert-1606954137718', | |
| location: 'us-central1', | |
| apiEndpoint: "127.0.0.1:4000/vertex_ai" | |
| }); | |
| const customHeaders = new Headers({ | |
| "x-litellm-api-key": "sk-1234", | |
| "tags": "vertex-js-sdk,pass-through-endpoint" | |
| }); | |
| const requestOptions = { | |
| customHeaders: customHeaders | |
| }; | |
| const generativeModel = vertexAI.getGenerativeModel( | |
| { model: 'gemini-1.5-pro' }, | |
| requestOptions | |
| ); | |
| const request = { | |
| contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] | |
| }; | |
| const result = await generativeModel.generateContent(request); | |
| expect(result).toBeDefined(); | |
| // Use the captured callId | |
| const callId = lastCallId; | |
| console.log("Captured Call ID:", callId); | |
| // Wait for spend to be logged | |
| await new Promise(resolve => setTimeout(resolve, 15000)); | |
| // Check spend logs | |
| const spendResponse = await fetch( | |
| `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, | |
| { | |
| headers: { | |
| 'Authorization': 'Bearer sk-1234' | |
| } | |
| } | |
| ); | |
| const spendData = await spendResponse.json(); | |
| console.log("spendData", spendData) | |
| expect(spendData).toBeDefined(); | |
| expect(spendData[0].request_id).toBe(callId); | |
| expect(spendData[0].call_type).toBe('pass_through_endpoint'); | |
| expect(spendData[0].request_tags).toEqual(['vertex-js-sdk', 'pass-through-endpoint']); | |
| expect(spendData[0].metadata).toHaveProperty('user_api_key'); | |
| expect(spendData[0].model).toContain('gemini'); | |
| expect(spendData[0].spend).toBeGreaterThan(0); | |
| expect(spendData[0].custom_llm_provider).toBe('vertex_ai'); | |
| }, 25000); | |
| test('should successfully generate streaming content with tags', async () => { | |
| const vertexAI = new VertexAI({ | |
| project: 'pathrise-convert-1606954137718', | |
| location: 'us-central1', | |
| apiEndpoint: "127.0.0.1:4000/vertex_ai" | |
| }); | |
| const customHeaders = new Headers({ | |
| "x-litellm-api-key": "sk-1234", | |
| "tags": "vertex-js-sdk,pass-through-endpoint" | |
| }); | |
| const requestOptions = { | |
| customHeaders: customHeaders | |
| }; | |
| const generativeModel = vertexAI.getGenerativeModel( | |
| { model: 'gemini-1.5-pro' }, | |
| requestOptions | |
| ); | |
| const request = { | |
| contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] | |
| }; | |
| const streamingResult = await generativeModel.generateContentStream(request); | |
| expect(streamingResult).toBeDefined(); | |
| // 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(); | |
| // Use the captured callId | |
| const callId = lastCallId; | |
| console.log("Captured Call ID:", callId); | |
| // Wait for spend to be logged | |
| await new Promise(resolve => setTimeout(resolve, 15000)); | |
| // Check spend logs | |
| const spendResponse = await fetch( | |
| `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, | |
| { | |
| headers: { | |
| 'Authorization': 'Bearer sk-1234' | |
| } | |
| } | |
| ); | |
| const spendData = await spendResponse.json(); | |
| console.log("spendData", spendData) | |
| expect(spendData).toBeDefined(); | |
| expect(spendData[0].request_id).toBe(callId); | |
| expect(spendData[0].call_type).toBe('pass_through_endpoint'); | |
| expect(spendData[0].request_tags).toEqual(['vertex-js-sdk', 'pass-through-endpoint']); | |
| expect(spendData[0].metadata).toHaveProperty('user_api_key'); | |
| expect(spendData[0].model).toContain('gemini'); | |
| expect(spendData[0].spend).toBeGreaterThan(0); | |
| expect(spendData[0].custom_llm_provider).toBe('vertex_ai'); | |
| }, 25000); | |
| }); |