Audio Summary with local LLM

This tool is designed to provide a quick and concise summary of audio and video files. It supports summarizing content either from a local file or directly from YouTube. The tool uses Whisper for transcription and a local version of Mistral AI (Ollama) for generating summaries.

Tip

It is possible to change the model you wish to use. To do this, change the OLLAMA_MODEL variable, and download the associated model via ollama

Features

• YouTube Integration: Download and summarize content directly from YouTube.
• Local File Support: Summarize audio files available on your local disk.
• Transcription: Converts audio content to text using Whisper.
• Summarization: Generates a concise summary using Mistral AI (Ollama).
• Transcript Only Option: Option to only transcribe the audio content without generating a summary.

Prerequisites

Before you start using this tool, you need to install the following dependencies:

• Python 3.8 or higher
• pytube for downloading videos from YouTube.
• pathlib for local file handling
• openai-whisper for audio transcription.
• Ollama for LLM model management.
• ffmpeg (required for whisper)

Installation

Python Requirements

Clone the repository and install the required Python packages:

git clone https://github.com/damienarnodo/audio-summary-with-local-LLM.git
cd audio-summary-with-local-LLM
pip install -r src/requirements.txt

LLM Requirement

Download and install Ollama to carry out LLM Management. More details about LLM models supported can be found on the Ollama GitHub.

Download and use the Mistral model:

ollama pull mistral

## Test the access:
ollama run mistral "tell me a joke"

Usage

The tool can be executed with the following command line options:

• --from-youtube: To download and summarize a video from YouTube.
• --from-local: To load and summarize an audio or video file from the local disk.
• --transcript-only: To only transcribe the audio content without generating a summary. This option must be used with either --from-youtube or --from-local.

Examples

1. Summarizing a YouTube video:

   python src/summary.py --from-youtube <YouTube-Video-URL>

2. Summarizing a local audio file:

   python src/summary.py --from-local <path-to-audio-file>

3. Transcribing a YouTube video without summarizing:

   python src/summary.py --from-youtube <YouTube-Video-URL> --transcript-only

4. Transcribing a local audio file without summarizing:

   python src/summary.py --from-local <path-to-audio-file> --transcript-only

The output summary will be saved in a markdown file in the specified output directory, while the transcript will be saved in the temporary directory.

Output

The summarized content is saved as a markdown file named summary.md in the current working directory. This file includes the transcribed text and its corresponding summary. If --transcript-only is used, only the transcription will be saved in the temporary directory.

Sources

• YouTube Video Summarizer with OpenAI Whisper and GPT
• Mistral Python Client
• Ollama : Installez LLama 2 et Code LLama en quelques secondes !