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How to use Lecture to Notes: what you can do with it

lecture-to-notes is a local GPU pipeline and Claude Code skill that turns lecture recordings into slide-illustrated notes and a synced HTML viewer where video, timestamped transcript and summary sit on one page.

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What do you want to do?

3 use cases

  • Get the exact processing plan for a folder of lecture files

    Drop video, audio, PDF decks or slide images in a folder and get the ordered commands to run.

    View prompt
    Run `python scripts/route_inputs.py <folder>` from drpwchen/lecture-to-notes with --json and list each step with whether it needs GPU or network. Confirm nothing was written to disk.

  • Turn a lecture video into a synced notes page

    Transcribe locally, extract slides, ground them to speech, and export one HTML page with video, transcript and summary.

    View prompt
    Process <lecture.mp4> with drpwchen/lecture-to-notes, passing the spoken language to --lang, and export the synced HTML viewer. Verify three random note timestamps seek to matching transcript lines.

  • Let Claude Code run the whole lecture pipeline

    Install the repo as a Claude Code skill so the agent drives every stage and writes the final notes.

    View prompt
    Using the lecture-to-notes skill, process <folder> into notes and the HTML viewer. Report any claims audit_note.py flagged and confirm each summary point cites a timestamp.

Quick start with Lecture to Notes

  1. Check you have what it needs: Python with the requirements files; A GPU for local Whisper transcription; Ollama with minicpm-v:8b for optional slide semantics.
  2. Open drpwchen/lecture-to-notes on GitHub and read the README and license.
  3. Clone with git clone https://github.com/drpwchen/lecture-to-notes and install requirements
  4. Copy the config with cp config.example.yaml config.yaml
  5. Run python scripts/route_inputs.py /path/to/material_folder
  6. Answer the listed questions, then run the printed commands

These steps come from our top use case, Get the exact processing plan for a folder of lecture files, which also has a copy-paste agent prompt.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for drpwchen/lecture-to-notes

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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Lecture to Notes alternatives · Best AI repos for Research

About this repo

  • Who it is forStudents, clinicians and researchers who record courses or talks and need traceable notes instead of rewatching hours of video.
  • Why it is hot111 stars, launched 83 days ago
  • LanguagePython
  • Sourcegithub.com/drpwchen/lecture-to-notes · Back to Hot repos

Requirements

  • Python with the requirements files
  • A GPU for local Whisper transcription
  • Ollama with minicpm-v:8b for optional slide semantics
  • An LLM for the final synthesis stage

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Questions about Lecture to Notes

What is Lecture to Notes?

lecture-to-notes is a local GPU pipeline and Claude Code skill that turns lecture recordings into slide-illustrated notes and a synced HTML viewer where video, timestamped transcript and summary sit on one page. It is an open-source project on GitHub: https://github.com/drpwchen/lecture-to-notes.

Who is Lecture to Notes for?

Students, clinicians and researchers who record courses or talks and need traceable notes instead of rewatching hours of video.

What can I do with Lecture to Notes?

3 use cases so far, for example: Get the exact processing plan for a folder of lecture files; Turn a lecture video into a synced notes page; Let Claude Code run the whole lecture pipeline. Each has steps and a copy-paste agent prompt.

What do I need to run Lecture to Notes?

Python with the requirements files; A GPU for local Whisper transcription; Ollama with minicpm-v:8b for optional slide semantics; An LLM for the final synthesis stage.

What are alternatives to Lecture to Notes?

Other hot AI repos in Research: Scientific Agent Skills, Trustworthy Agent Simulation, Kaas, By2 KB, Md2 HD.

Is Lecture to Notes safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.