fluffy-guide
A live lecture copilot prototype that maintains rolling context and lets learners ask quiet questions without interrupting the speaker.
Lecture confusion is time-sensitive. If someone misses a definition or transition, waiting until the end can make the rest of the session harder to follow.
Inside the experience
What someone can actually do
- Rolling transcript and short evolving summary
- Silent text or voice questions from the learner
- Answers grounded in recent lecture context
- Demo mode for reliable presentations
- Future direction toward slides and XR/spatial input
How the idea took shape
A Streamlit prototype separates continuous transcription and rolling-summary logic from a learner-facing question flow grounded in recent context.
“Lecture confusion is time-sensitive: help is most valuable while the missed context can still repair the rest of the session.”
Explore how it was built +
I framed the learning problem and built the transcription, rolling-context, grounded-question, and reliable demo flows.
- Python
- Streamlit
- faster-whisper
- OpenAI API
- Realtime context buffers
Where it could go next