AI-Powered Custom Search Engine (Exa API)

A lightweight, AI-powered search engine built using Flask, JavaScript, and the Exa Search API.
This project allows users to enter natural-language search queries and receive relevant, high-quality results powered by Exa’s AI-driven search capabilities.

The goal of this project was to understand how modern search systems work, practice full-stack development, and integrate an AI-based search API into a clean, responsive web interface.

📦 Technologies

Backend

• Python
• Flask
• Exa Search API

Frontend

• HTML
• CSS (custom styling, responsive layout)
• JavaScript (async fetch, DOM manipulation)

💡 Features

Here’s what you can do with the AI Search Engine:

🔍 AI-Powered Search

• Enter natural-language search queries
• Queries are sent to the backend and processed using the Exa API
• Returns relevant, high-quality search results

⚡ Real-Time Results

• Asynchronous requests using fetch()
• Results are rendered dynamically without page reloads
• Displays titles and external links for each result

🧠 Backend API Layer

• Flask server handles:
  • Input validation
  • API requests to Exa
  • Response normalization for frontend use
• Clean separation between backend logic and frontend UI

📱 Clean & Responsive UI

• Minimal, modern search interface
• Responsive layout that works on desktop and mobile
• Visual feedback for searching, empty results, and errors

🔄 How It Works

1. The user enters a search query in the frontend.
2. The query is sent as JSON to the Flask backend.
3. Flask calls the Exa Search API using keyword-based search.
4. Exa returns relevant results.
5. The backend formats the response and sends it back to the frontend.
6. Results are rendered dynamically in the browser.

🚦 Running the Project Locally

To run this project on your local machine:

1. Clone or download this repository.
2. Install the required Python dependencies:

   pip install flask exa-py

3. Open app.py and ensure your Exa API key is set.
4. Start the Flask development server:

   python app.py

5. Open your browser and navigate to:

   http://127.0.0.1:5000
   

📚 What I Learned

This project helped strengthen both my backend and AI-integration skills.

🧠 AI & Search Systems

• Learned how AI-powered search engines retrieve and rank results
• Worked with natural-language queries instead of simple keyword matching
• Understood how modern search APIs differ from traditional search engines

🔄 Backend Development

• Built a Flask API to handle client requests
• Processed and normalized third-party API responses
• Implemented input validation and error handling

🌐 Frontend–Backend Integration

• Connected a JavaScript frontend to a Python backend
• Used asynchronous fetch requests and dynamic DOM rendering
• Maintained clean separation of concerns between layers

🍿 Demo

🎥 Search Engine Walkthrough

This demo shows:

• Entering a natural-language query
• AI-powered search results returned from Exa
• Dynamic rendering of results in the UI