KnoCoBot

KnoCoBot is a smart tutor chatbot designed to assist users in both English and Tamil. It offers vernacular support, video rendering, text-to-speech, resource links, and YouTube video links. This repository contains the code and resources needed to set up and run KnoCoBot.

Table of Contents

Features

Getting Started

Prerequisites

Installation

Usage

Testing

Future Scope

Contributing

License

Features Multilingual support: English and Tamil Text-to-speech for both languages Video rendering with relevant YouTube links Resource links for further reading Optional multiple-choice questions (MCQs) for concept reinforcement User authentication and session management History tracking for questions and answers PDF download of answers and resources

Getting Started Prerequisites Python 3.7+ Streamlit SQLite Google Cloud API key for Gemini API deep_translator library for translation gTTS library for text-to-speech youtubesearchpython library for YouTube video search beautifulsoup4 and requests for web scraping Installation Clone the repository:

bash Copy code git clone https://github.com/asvitha1625/knocobot.git cd knocobot Create and activate a virtual environment:

bash Copy code python -m venv venv source venv/bin/activate # On Windows, use venv\Scripts\activate Install the required dependencies:

bash Copy code pip install -r requirements.txt Set up environment variables: Create a .env file in the root directory and add your Google Cloud API key:

makefile Copy code GEMINI_API_KEY=your_google_cloud_api_key Set up the SQLite databases:

bash Copy code python setup_db.py Usage Run the Streamlit application:

bash Copy code streamlit run app.py Open your web browser and navigate to http://localhost:8501.

Sign up or log in to start using KnoCoBot.

Select your preferred language and start asking questions.

Testing To run the test cases, follow the test script provided in the tests directory. Ensure all functionalities are working as expected.

Future Scope Expansion to More Languages: Adding support for additional languages to cater to a wider audience.

Important Information: This will involve integrating more translation APIs and enhancing the chatbot's NLP capabilities to handle multiple languages seamlessly. Image-based Question Input: Allowing users to submit questions via images.

Important Information: This feature will utilize OCR (Optical Character Recognition) to extract text from images and process the query. This will make the chatbot more accessible and user-friendly, especially for younger students or those with disabilities. Personalized Learning Paths: Creating customized learning paths based on the user's questions and progress.

Important Information: This will involve tracking user interactions, understanding their learning needs, and suggesting topics or resources. This personalized approach will enhance the learning experience and ensure users get the most relevant information. Contributing We welcome contributions from the community! Please read our Contributing Guide to learn how you can help.

License This project is licensed under the MIT License. See the LICENSE file for more details.