20Hour Learning Tool - README

Introduction

Welcome to the 20Hour Learning Tool! This project is a Generative AI-based tool developed using Azure OpenAI, Bing Search ,Python, and Flask. Inspired by the principle of the "20-Hour Learning Method" popularized by Josh Kaufman, this tool aims to help users quickly acquire new skills by focusing on deliberate and efficient learning practices.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Configuration
• Contributing

Features

• Generative AI Assistance: Leverages Azure OpenAI to provide intelligent responses and learning guidance.
• Flask Web Interface: Easy-to-use web interface built with Flask.
• Python Backend: Robust backend using Python for processing and handling requests.
• 20-Hour Learning Framework: Implements the 20-hour learning principle to help users master new skills efficiently.
• Customization: Easily customizable to fit various learning topics and user needs.

Installation

To set up the 20Hour Learning Tool on your local machine, follow these steps:

1. Clone the Repository:

   git clone https://github.com/your-username/20Hour.git
   cd 20Hour
   
   
   
   

2. Set Up a Virtual Environment (optional but recommended):

      python3 -m venv venv
     source venv/bin/activate   # On Windows, use `venv\Scripts\activate`
   

3. Install Dependencies:

   pip install -r requirements.txt
   Configure Environment Variables:
   

4. Create a .env file in the project root directory and add your Azure OpenAI credentials and Bing Search Credentials env AZURE_OPENAI_KEY=your_openai_key AZURE_OPENAI_ENDPOINT=your_openai_endpoint bing_search_api_key = 'your_api_key' bing_search_endpoint = 'bing_search_endpoint'

5. Run the Flask Application:

    flask run
   

Usage

Once the Flask application is running, open your web browser and navigate to http://127.0.0.1:5000. You will be presented with the 20Hour Learning Tool interface where you can start your learning journey.

Key Functionalities

Skill Selection: Choose the skill you want to learn. Guided Learning: Follow the steps provided by the AI to efficiently learn the new skill. Progress Tracking: Monitor your learning progress and adjust your approach based on feedback. Configuration The 20Hour Learning Tool can be configured to suit different learning needs. Key configurations include:

Learning Modules: Customize or add new learning modules in the modules/ directory. AI Settings: Adjust AI parameters in the config.py file to fine-tune the responses and guidance provided.

Contributing

We welcome contributions to enhance the 20Hour Learning Tool. To contribute:

Fork the repository. Create a new branch: git checkout -b feature/your-feature-name. Commit your changes: git commit -m 'Add new feature'. Push to the branch: git push origin feature/your-feature-name. Open a pull request. Please ensure your code adheres to our coding standards and includes relevant tests.