Part 5: Making Predictions via REST API (JSON Input/Output) – RainPredict-AI

🌐 Part 5: Making Predictions via REST API (JSON Input/Output)

Send Live Data to Your AI Model and Get Predictions from Vertex AI – Powered by Siraat AI Academy


In Part 5 of our RainPredict-AI series, we go from “trained & deployed” to “live and working” — by calling your model’s API endpoint with real-time weather data! 🛰️ You’ll learn how to send JSON input and receive predictions using Google Cloud’s REST API tools.

This is your model’s first true test in the wild — and the final step before adding a user-friendly UI (coming in Part 6). Let's get started!


🧰 What You Need Before Starting

  • 🟢 A trained AutoML Tabular model (from Part 3)
  • 🟢 Deployed to Vertex AI Endpoint (from Part 4)
  • 🟢 Your Project ID, Endpoint ID, and Service Account JSON key
  • 🟢 curl installed OR use Postman for API testing

🔐 Authenticate Your API Request

You must authenticate using a service account key file. Use the following command to get an auth token: 

gcloud auth activate-service-account --key-file="your-key.json"
gcloud auth print-access-token

☝️ Copy the token – you'll use it to call the API.


📤 Send JSON Data to the API

Here's an example prediction request using curl:

curl -X POST \
  -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  https://us-central1-aiplatform.googleapis.com/v1/projects/YOUR_PROJECT_ID/locations/us-central1/endpoints/YOUR_ENDPOINT_ID:predict \
  -d '{
    "instances": [
      {
        "temperature": 78,
        "humidity": 60,
        "pressure": 1015
      }
    ]
  }'

You’ll receive a response like:

{
  "predictions": [0.42]
}

🎯 Boom! Your AI just predicted rainfall in real time.


🧪 Use Postman or Apps to Test (Optional)

  • Import the endpoint URL into Postman
  • Add Authorization: Bearer <access-token>
  • Paste your JSON input
  • Send → Receive predicted rainfall instantly!

💡 Final Insights

  • You’ve successfully triggered your AI model using REST API
  • This approach can be integrated into ANY software, website, or app
  • JSON makes it universal, and Google handles the scale

🔥 You’ve now reached the production edge of AI. Well done!


⏭️ Up Next: Part 6 – BONUS: Connecting to AppSheet or Cloud Run UI (Optional Frontend)

Now that you have live predictions, it’s time to build a frontend interface — even without coding! Use AppSheet or create a form in Cloud Run.

📱 Ready to make it visual? Stay tuned for the bonus finale in Part 6!

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