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Edufrent

About Project:

Problem Statement The current landscape of EdTechs presents several challenges, including Lack of engagement Limited personalization Insufficient human interaction Technological barriers Lack of hands-on experience, motivational and self-discipline Limited feedback and assessment Overemphasis on content delivery

Existing Solution and the gap we are filling We aim to harness the power of AI by taking personalization to new heights. We strive to make education adaptable to various study methods through innovative solutions such as Personalized learning Intelligent virtual assistants Adaptive assessments Experiential learning Intelligent content generation Learning analytics

Features

Personalized curriculum generator
Personalized Learning 
Intelligent Virtual Assistants
Adaptive Assessments 
Learning Analytics and Insights
Interview and Viva voce Preparation Bot

Technical Architecture: Implement OpenAI's GPT-3.5 /4 (for implementing above mentioned) Using Streamlit (for making Project UI interactable)

Scope for future upgradations Option to upload the file to read form it. Bionic reading(Speed reading and ADHD) Collaboration feature with friends Real time audio support for confidence enhancement

Brief Description: In this project with the help of Generative AI and streamlit, we are making the application which helps in making the curriculum and making the students to learn on the specified topics based on their capabilities and willing, and In this we also implemented Assessment bot and Interview Bot, so that it asks questions and waits for our answer, based on our input it will give feedback where we need to focus to overcome mistakes.

How to run this project In your system:

  1. Create one new directory: mkdir dir_name
  2. Create one virtual environment using : python3 -m venv venv
  3. Activate your virtual environment :
  4. Clone our github repo using command : git clone https://github.com/Anilabhimanyu/Edufrent
  5. Install all the dependencies (make sure you are in same path of requirements.txt) by using: pip install -r requirements.txt
  6. Create one env file and add your own open AI api token
  7. Run app.py by using streamlit by command: streamlit run app.py for using first two features
  8. Run app2.py by using streamlit by command: streamlit run app.py for using remaining features .