litellm/tests/pass_through_tests/test_vertex.test.js
Ishaan Jaff b2b3e40d13
(feat) use @google-cloud/vertexai js sdk with litellm (#6873)
* stash gemini JS test

* add vertex js sdj example

* handle vertex pass through separately

* tes vertex JS sdk

* fix vertex_proxy_route

* use PassThroughStreamingHandler

* fix PassThroughStreamingHandler

* use common _create_vertex_response_logging_payload_for_generate_content

* test vertex js

* add working vertex jest tests

* move basic bass through test

* use good name for test

* test vertex

* test_chunk_processor_yields_raw_bytes

* unit tests for streaming

* test_convert_raw_bytes_to_str_lines

* run unit tests 1st

* simplify local

* docs add usage example for js

* use get_litellm_virtual_key

* add unit tests for vertex pass through
2024-11-22 16:50:10 -08:00

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JavaScript

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: 'adroit-crow-413218',
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-1.0-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: 'adroit-crow-413218', 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-1.0-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));
});
});