Explain AJAX and how it’s used to fetch AI model predictions from a backend ?

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Explain AJAX and how it’s used to fetch AI model predictions from a backend ?

1. What is AJAX?

AJAX (Asynchronous JavaScript and XML) is a technique that allows a web page to communicate with a server without reloading the page.  Even though “XML” is in the name, it’s commonly used with JSON today.

Key features:

  • Makes browser HTTP requests (GET, POST, etc.).
  • Accepts replies in an asynchronous manner.
  • Serves the web page dynamically on the data within the server.

2. How AJAX Works

  1. User communicates with the web page (e.g. clicks a button, type in text).
  2. JavaScript causes an AJAX call to the server.
  3. The request is processed by the server (e.g. an AI model is run).
  4. Response is sent (normally JSON) by server.
  5. JavaScript also changes the UI without reloading the page.

3. Using AJAX to Fetch AI Model Predictions
Suppose that you have an AI model on the back-end (Python/Flask, Node.js/Express, or Laravel). There is some input entered by the user, and you desire to receive the prediction of the model:

Step 1: Frontend sends data to backend

// Using fetch API (modern AJAX)

const inputData = { text: “Hello, AI!” };

fetch(“/predict”, {

  method: “POST”,

  headers: {

    “Content-Type”: “application/json”,

  },

  body: JSON.stringify(inputData),

})

  .then((response) => response.json())

  .then((data) => {

    console.log(“AI Prediction:”, data.prediction);

    document.getElementById(“result”).innerText = data.prediction;

  })

  .catch((error) => console.error(“Error:”, error));

Step 2: Backend handles request and returns prediction

Example with Node.js + Express:

app.post(“/predict”, async (req, res) => {

  const userInput = req.body.text;

  

  // Call your AI model here (Python ML model or Node.js model)

  const prediction = await aiModel.predict(userInput);

  

  res.json({ prediction });

});
4. Why AJAX is Ideal for AI Predictions

  • Asynchronous: The user does not have to wait until a complete reload of a page.
  • Dynamic updates: The results may be shown immediately on the page.
  • Scalable: Is effective with large AI models in a server.

AJAX can be used to transmit user input to the back-end AI model and dynamically get the predictions without reloading the page. Request is sent to the frontend, then the backend computes and the response is sent, which is then displayed in the UI.

Abarna Vijayarathinam Asked question September 23, 2025
0