Course Search Engine

A course search engine built with Flask, FAISS, and Sentence Transformers, enabling efficient retrieval of relevant courses based on user input.

Tech Stack

• Flask: A lightweight web framework for building the API.
• FAISS: A library for efficient similarity search and clustering of dense vectors.
• Sentence Transformers: A model for encoding text into embeddings for semantic search.

Features

• Semantic Search: Finds relevant courses based on user queries using vector embeddings.
• Fast Retrieval: Utilizes FAISS for quick and accurate search results.
• User-Friendly: Simple web interface for querying courses.

Setup

1. Clone the Repository

   git clone https://github.com/yourusername/course-search-engine.git
   cd course-search-engine

2. Install Dependencies

   pip install -r requirements.txt

3. Download Pre-trained Model and Index

   • Ensure you have the course_embeddings.index file in the project directory.
   • Download the Sentence Transformers model used for encoding.

4. Run the Application

   python app.py

5. Access the Application

   Open your web browser and navigate to http://127.0.0.1:5000 to use the search engine.

Usage

• Enter your query in the search bar and click "Submit."
• View the list of relevant courses based on your input.

Contributing

Feel free to open issues or submit pull requests to improve the project!