CoursePath is a learning project I built to explore Retrieval-Augmented Generation (RAG) techniques in AI development. It’s a prototype chatbot that helps CU Boulder Computer Science students navigate their degree requirements and course prerequisites.
The goal was to simulate an intelligent academic counselor using a RAG-based backend that pulls course information from predefined documents.
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🤖 AI Chatbot for Course Planning
- Ask natural language questions like:
- "What are the prerequisites for CS401?"
- "What classes should I take next semester?"
- Uses a RAG pipeline for accurate answers from structured course info.
- Ask natural language questions like:
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🔎 Course Prerequisite Lookup
- Simulates prerequisite tracing by referencing curated academic data.
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🎓 Focus on CU Boulder Computer Science Major
- Currently tailored for Computer Science undergrad courses at CU Boulder.
- Easily extendable for other majors with updated data.
- Python 3.8+
- OpenAI API key (for the RAG chatbot)
- (Optional) Docker if you want to containerize your environment later
git clone https://github.com/yourusername/coursepath.git
cd coursepathCreate a .env file or export directly:
OPENAI_API_KEY=your_openai_api_keypython app.py(Assuming your chatbot server script is called app.py — adjust if needed.)
- Learning-Focused:
This project was built for learning purposes—exploring LangChain, RAG, OpenAI API usage, and AI prompt engineering. Not production-ready.
This is an early-stage, learning project.
If you’re interested in collaborating on expanding this (adding Neo4j, improving retrieval, building a front end, etc.), feel free to reach out or open an issue!