ChatTube

Introduction

ChatTube is an innovative AI-powered tool designed to enhance learning experiences while watching educational videos. It leverages the power of OpenAI's GPT-4 API to analyze video transcripts and provide instant clarification for students' doubts. Additionally, it assists teachers in generating quiz questions based on the video content.

Getting Started

Setting up locally

1. Clone the repo:

   git clone https://github.com/roshangeorge97/ChatTube

2. Navigate to the repository:

   cd ChatTube

3. Install the required dependencies:

   pip install -r requirements.txt

4. Change your OPEN AI KEY on streamlitui.py

   st.session_state["OPENAI_API_KEY"] = "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"

5. Run the StreamLit App:

   python -m streamlit run streamlitui.py

Screenshots

Features

• Real-time Doubt Clarification: Students can ask questions and receive immediate answers during the lecture.
• Timestamp Tagging: Users can tag specific timestamps in the video to ask questions related to particular sections.
• Lecture Notes Generation: ChatTube facilitates the creation of lecture notes within seconds.
• Quiz Question Generation: Teachers can easily generate quiz questions from the video content.

Technologies Used

• OpenAI's GPT-4 API: Powers the AI connectivity for analyzing video transcripts.
• Streamlit: Utilized for the user interface and backend development.
• StreamChat: Integrated for deployment purposes.

Challenges Faced

• Deployment Hurdles: Overcoming challenges with package recognition during deployment, specifically with the StreamChat package.
• Model Selection: Experimentation with different AI models to find the most suitable one for educational purposes.

Accomplishments

• Successful implementation of real-time doubt clarification during video lectures.
• Streamlining the process of note-taking and quiz question generation.
• Creation of a user-friendly interface for seamless interaction.

Lessons Learned

• Enhanced understanding of StreamChat deployment and package management.
• Identification of the most effective AI models for educational applications.

Future Plans

• Expansion of language support beyond English.
• Continued refinement and improvement of doubt clarification algorithms.
• Integration of additional features to enhance the learning experience further.