This chatbot functions as an academic tool that processes YouTube videos, enabling users to engage interactively with the content. For instance, after analyzing a playlist on linear algebra, users can ask specific questions such as, "How do I solve a system of linear equations?" The bot will then provide explanations based on the video content and direct users to the relevant sections of the video for further information.
- frontend
- rag
- data_pipeline
- vector_db
- graph_db
- Clone project:
git clone https://github.com/dneumnn/AcademicChatBot.git - Create a virtual envrionment for the project:
conda create -n academic_chat_bot python=3.11 - Activate the virtual environment for the project:
conda activate academic_chat_bot - Adjust git credentials:
git config user.name <your name>git config user.email <your email> - Install dependencies
pip install -r requirements.txt - Start the FastAPI
uvicorn main:app --reload
- Install packages from requirements.txt:
pip install -r requirements.txt - Write all packages from your current envrionment to requirements.txt:
pip freeze > requirements.txt
- There are five projects, each housed in its own subfolder to avoid merging conflicts.
- Each team has its own dedicated branch.
- Developers should commit regulary, ensuring that each commit is small and focused on a single topic.
- Commits should be written in present tense.
- After completing a feature, teams merge their updates into the main branch.
- Teams should notify others vai MS Teams when they release a new feature that could be important for teams.
- To utilize features developed by other teams, a team should merge these updates into their own branch.
