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Semantic Nexus

Overview

Semantic Nexus is a comprehensive search engine and information retrieval application designed to enhance user search experience with advanced features. The application integrates voice search capabilities, AI-generated responses, and reference provision to streamline the search process and deliver a user-friendly interface. Built using Docker, this project ensures consistent and scalable deployment.

Features

  • Voice Search: Utilize voice recognition to search for information hands-free.
  • AI-Generated Responses: Receive concise summaries and relevant insights generated by AI based on your search query.
  • Search Engine: Perform detailed searches with robust filtering and sorting options.
  • Reference Provision: Access detailed references and links related to your search results in a well-organized card view.

Demo Video

Semantic.Nexus.Demo.mp4

Technologies Used

  • Programming Language: JavaScript (React) for frontend, Python (FastAPI) for backend
  • Libraries and Frameworks:
    • React for building the user interface
    • FastAPI for creating the backend API
    • Docker for containerization
    • Web Speech API for voice search functionality
    • Custom AI model for generating responses

Installation

To get started with Semantic Nexus, follow these steps:

  1. Clone the Repository

    git clone https://github.com/Akshitkt001/SemanticNexus.git
cd SemanticNexus

Set Up Backend

Navigate to the backend directory and set up the environment:

  1. Clone the Repository

    cd backend
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
Start the FastAPI server:


uvicorn main:app --reload --host 0.0.0.0 --port 8000
Set Up Frontend
Navigate to the frontend directory and install dependencies:


cd ../frontend
npm install
Start the React development server:

npm start
Run Docker Containers
Ensure Docker is installed and running. Use Docker Compose to set  up and run the containers:

docker-compose up

Usage

Open the Application

Launch the frontend application by navigating to http://localhost:3000 in your web browser. The application will present the following components:

  • Search Bar: Allows users to enter search queries manually or use voice search.
  • AI Response Section: Displays a summary generated by the AI based on the search query.
  • Search Results: Shows detailed results in a card view format, providing organized references and links.

Perform a Search

  • Voice Search: Click the microphone icon to start voice recognition and speak your query.
  • Text Search: Enter your query into the search bar and press Enter or click the search button.

View Results

The results will be displayed in cards, each providing relevant information and links. The AI-generated response will summarize the main points based on the search query.

API Documentation

Endpoints

  • /search: Performs a search based on the query and returns results and AI-generated response.
    • Method: GET
    • Parameters:
      • q: The search query.

Examples

For detailed API usage examples, refer to the FastAPI documentation.

Docker Setup

The project uses Docker to ensure a consistent development and deployment environment. Make sure Docker and Docker Compose are installed. Use the following commands to manage the Docker containers:

  • Build Docker Images:

    docker-compose build

  • Start Containers:

    docker-compose up

  • Stop Containers:

    docker-compose down

Contributing

Contributions to Semantic Nexus are welcome! If you find a bug or want to add a new feature, please follow these steps:

  1. Fork the repository.
  2. Create a new branch (e.g., git checkout -b feature/your-feature).
  3. Make your changes.
  4. Commit your changes (e.g., git commit -am 'Add new feature').
  5. Push to the branch (e.g., git push origin feature/your-feature).
  6. Create a new Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any inquiries or issues, please contact: