AI Search Engine - Anusandhan

Anusandhan is an AI-powered search engine designed to provide real-time search capabilities with concise answers and reference sources. It features a frontend UI written in Streamlit for easy interaction and a backend API developed using Node.js.

Directory Structure

• ai_search_ui

  • app.py
  • LLM.py
  • requirements.txt
  • search.py
  • searching.gif
  • trans.py
  • util.py

• package-lock.json

• playwright.config.ts

• app.js

• package.json

• page_pool.js

• search_engine.js

Setup and Usage

Frontend (UI)

1. Streamlit Setup:

   • Ensure you have Python installed with Streamlit (pip install streamlit).

2. Environment Setup:

   • Create .env file in /ai_search_ui directory of project
   • Replace .env content with

   HF_TOKEN=YOUR_HF_API_TOKEN
   

   • How to get your hf token for free
     • Log in to huggingface
     • Go to Profie > then go to Setttings > then go to Access Tokens tab
     • Access Tokens Page
     • If there exists Access Token then copy it and paste it as HF_TOKEN in .env file of project
     • If Access Token does not exist then click on new token Write the "Name of Token" and Select the "Type of Token" (Read / Write) Access.
     • After creating copy the token and paste it as HF_TOKEN in .env file of project.

3. Running the UI:

   • Navigate to the ai_search_ui directory:

     cd ai_search_ui

   • Create Virtual Enviornment & Install Dependencies
   • For windows ( git bash )

     python -m venv .venv
     source .venv/Scripts/activate
     pip install -r requirements.txt

   • For windows ( cmd )

     python -m venv .venv
     .venv\Scripts\activate
     pip install -r requirements.txt

   • For Linux & Mac

     python -m venv .venv
     souce .venv/bin/activate
     pip install -r requirements.txt

   • Run the Streamlit app:

     streamlit run app.py

   • Access the UI in your browser at localhost:8501 (default Streamlit address).

Backend (API)

1. Node.js Setup:

   • Verify Node.js installation (node --version).

2. Installing Dependencies:

   • Install required Node.js packages:

     npm install
     npx playwright install

3. Environment Setup:

   • Create .env file in root directory of project
   • Replace .env content with

   PAGE_POOL_SIZE=5
   WEB_STORE='https://www.google.com'
   

4. Starting the Backend:

   • From the project root, start the backend server using nodemon:

     nodemon app.js

   • The backend server will run and listen for requests.

Additional Notes

• Frontend (UI):

  • The main Streamlit app file is app.py in the ai_search_ui directory.
  • Explore the UI to interact with the search interface.

• Backend (API):

  • The backend server script is app.js in the project root.
  • Ensure all required packages from package.json are installed (npm install).
  • Use nodemon to run the server for automatic restarts on file changes.

Contributions and Feedback

This project was developed independently without external funding. Contributions and feedback are welcome through GitHub issues and pull requests.

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Feel free to modify and expand upon this README as needed to provide more detailed instructions, information about APIs, deployment steps, or any other relevant details for users and contributors.