Beaver Codes is a Retrieval-Augmented Generation (RAG) based chatbot developed for CCNY students. It provides intelligent, human-like assistance using course notes and contextual documents to answer questions and help students complete tasks efficiently.
This project integrates LlamaIndex, ChromaDB, and OpenAI to deliver a smart academic support tool built with students in mind.
- 🔍 Context-Aware QA: Uses RAG to retrieve relevant course materials before generating responses.
- 📚 Custom Knowledge Base: Ingests course notes, PDFs, and other academic resources.
- 💬 Natural Language Chat Interface: Responds in a helpful, conversational style via OpenAI's LLMs.
- 🧠 LlamaIndex Integration: Efficiently indexes and queries structured and unstructured data.
- 🗂️ ChromaDB Vector Store: Stores and retrieves semantically relevant document chunks.
- 🏫 Tailored for CCNY: Specifically designed to support CCNY courses and student needs.
- Frontend: Streamlit
- Backend: Python
- Core Libraries:
llama-indexchromadbopenailangchain(optional)