lecsum

Automatically transcribe and summarize lecture recordings completely on-device using AI.

Environment Setup

Install Ollama.

Create a virtual Python environment:

python3 -m venv venv

Activate the virtual environment:

source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Edit lecsum.yaml:

Field	Default Value	Possible Values	Description
`whisper_model`	"base.en"	Whisper model name	Specifies which Whisper model to use for transcription
`ollama_model`	"llama3.1:8b"	Ollama model name	Specifies which Ollama model to use for summarization
`prompt`	"Summarize: "	Any string	Instructs the large language model during the summarization step

Run the Ollama server:

ollama serve

In a new terminal, run:

./lecsum.py -c [CONFIG_FILE] [AUDIO_FILE]

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
modules		modules
.gitignore		.gitignore
README.md		README.md
lecsum.py		lecsum.py
lecsum.yaml		lecsum.yaml
requirements.txt		requirements.txt