How to Integrate Replit with Google Cloud AI Platform

1// Example structure of a Google Cloud service account JSON key file
2// (Never store this in code — paste the content into Replit Secrets)
3{
4  "type": "service_account",
5  "project_id": "your-project-id",
6  "private_key_id": "key-id",
7  "private_key": "-----BEGIN RSA PRIVATE KEY-----\n...\n-----END RSA PRIVATE KEY-----\n",
8  "client_email": "replit-vertex-ai@your-project-id.iam.gserviceaccount.com",
9  "client_id": "...",
10  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
11  "token_uri": "https://oauth2.googleapis.com/token"
12}

1# Python: Parse credentials from Replit Secrets
2import os
3import json
4
5credentials_json = os.environ.get('GOOGLE_CREDENTIALS_JSON')
6if not credentials_json:
7    raise ValueError('GOOGLE_CREDENTIALS_JSON not set. Add it in Replit Secrets (lock icon 🔒).')
8
9credentials_dict = json.loads(credentials_json)
10print('Service account:', credentials_dict.get('client_email'))
11print('Project:', os.environ.get('GOOGLE_CLOUD_PROJECT'))
12print('Endpoint:', os.environ.get('VERTEX_AI_ENDPOINT_ID'))
13print('Location:', os.environ.get('VERTEX_AI_LOCATION'))

1# vertex_ai.py — Vertex AI prediction client for Replit (Python)
2import os
3import json
4from flask import Flask, request, jsonify
5from google.cloud import aiplatform
6from google.oauth2 import service_account
7
8# Load credentials from Replit Secrets
9credentials_dict = json.loads(os.environ['GOOGLE_CREDENTIALS_JSON'])
10credentials = service_account.Credentials.from_service_account_info(
11    credentials_dict,
12    scopes=['https://www.googleapis.com/auth/cloud-platform']
13)
14
15PROJECT_ID = os.environ['GOOGLE_CLOUD_PROJECT']
16LOCATION = os.environ.get('VERTEX_AI_LOCATION', 'us-central1')
17ENDPOINT_ID = os.environ['VERTEX_AI_ENDPOINT_ID']
18
19# Initialize Vertex AI with service account credentials
20aiplatform.init(
21    project=PROJECT_ID,
22    location=LOCATION,
23    credentials=credentials
24)
25
26# Load the endpoint once at startup
27endpoint = aiplatform.Endpoint(
28    endpoint_name=f'projects/{PROJECT_ID}/locations/{LOCATION}/endpoints/{ENDPOINT_ID}'
29)
30
31app = Flask(__name__)
32
33@app.route('/predict', methods=['POST'])
34def predict():
35    """Call Vertex AI online prediction endpoint."""
36    body = request.get_json()
37    instances = body.get('instances')
38    
39    if not instances:
40        return jsonify({'error': 'instances field required in request body'}), 400
41    
42    if not isinstance(instances, list):
43        instances = [instances]  # Wrap single instance in list
44    
45    try:
46        prediction = endpoint.predict(instances=instances)
47        return jsonify({
48            'predictions': prediction.predictions,
49            'deployed_model_id': prediction.deployed_model_id,
50            'model_display_name': prediction.model_display_name
51        })
52    except Exception as e:
53        return jsonify({'error': str(e)}), 500
54
55@app.route('/health')
56def health():
57    return jsonify({'status': 'ok', 'project': PROJECT_ID, 'endpoint': ENDPOINT_ID})
58
59if __name__ == '__main__':
60    app.run(host='0.0.0.0', port=3000)
61    print(f'Vertex AI server ready. Endpoint: {ENDPOINT_ID}')

1// vertex_ai.js — Vertex AI prediction client for Replit (Node.js)
2const { GoogleAuth } = require('google-auth-library');
3const axios = require('axios');
4const express = require('express');
5
6const credentialsJson = process.env.GOOGLE_CREDENTIALS_JSON;
7if (!credentialsJson) throw new Error('GOOGLE_CREDENTIALS_JSON not set. Add it in Replit Secrets (lock icon 🔒).');
8
9const credentials = JSON.parse(credentialsJson);
10const PROJECT_ID = process.env.GOOGLE_CLOUD_PROJECT;
11const LOCATION = process.env.VERTEX_AI_LOCATION || 'us-central1';
12const ENDPOINT_ID = process.env.VERTEX_AI_ENDPOINT_ID;
13
14// Initialize Google Auth client
15const auth = new GoogleAuth({
16  credentials,
17  scopes: 'https://www.googleapis.com/auth/cloud-platform'
18});
19
20const PREDICTION_URL = `https://${LOCATION}-aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/${LOCATION}/endpoints/${ENDPOINT_ID}:predict`;
21
22async function predictVertexAI(instances) {
23  const client = await auth.getClient();
24  const token = await client.getAccessToken();
25  
26  const response = await axios.post(PREDICTION_URL, { instances }, {
27    headers: {
28      Authorization: `Bearer ${token.token}`,
29      'Content-Type': 'application/json'
30    }
31  });
32  
33  return response.data;
34}
35
36const app = express();
37app.use(express.json());
38
39app.post('/predict', async (req, res) => {
40  let { instances } = req.body;
41  if (!instances) return res.status(400).json({ error: 'instances required' });
42  if (!Array.isArray(instances)) instances = [instances];
43  
44  try {
45    const result = await predictVertexAI(instances);
46    res.json(result);
47  } catch (err) {
48    const status = err.response?.status || 500;
49    res.status(status).json({ error: err.response?.data?.error || err.message });
50  }
51});
52
53app.get('/health', (req, res) => {
54  res.json({ status: 'ok', project: PROJECT_ID, endpoint: ENDPOINT_ID, location: LOCATION });
55});
56
57app.listen(3000, '0.0.0.0', () => {
58  console.log(`Vertex AI Node.js server running. Endpoint: ${ENDPOINT_ID}`);
59});