LLM-powered Lecture Generation

This project developed an LLM-powered lecture generation system for the UC Berkeley COMPSCI 194-196 research project. The implementation is available in the pdf2lec_llm repository.

Report: PDF2Lec: Streamlining LLM-driven Lecture Generation (PDF), by Rachel Lin, Mutian Hong, Chuyan Zhou, Jan Chen and Lucy Struefing.

Work completed

• Independently developed the backend framework as a deployable FastAPI web service.
• Added asynchronous task execution with multithreading, API-based task management backed by Redis, and a metadata system for generated data.
• Integrated the different model components into the backend framework as the main developer.
• Developed an LLM-powered question-answering agent that uses the generated lectures as long context and dynamically indexes grounding sources, such as textbooks, with a RAG system.