Purpose

This project offers a privacy-focused solution for transcribing and summarizing audio recordings through entirely local processing on you. Using OpenAI's Whisper for transcription and local LLMs via Ollama for summarization, it processes audio files (MP3/WAV) entirely on your machine, ensuring sensitive content never leaves your environment.

The tool automatically generates structured summaries including:

• Executive overview
• Detailed content breakdown
• Action items
• Meeting metadata

NOTE: This project is currently functional and tested on Windows 11.

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Setup

Select Python Interpreter Version Between 3.8-3.11

• I am using Python 3.10.11

Install ffmpeg Globally as PowerShell Administrator

NOTE: ffmpeg DOES NOT work in virutal environment and is required for Whisper to work. A "[Win2]File not found error" is thrown when attempting to use within a virtual environment, although it is not best practice, utilize your global environment instead.

• Follow the instructions HERE and install choclatey install via PowerShell Administration to install ffmpeg.

• Install FFmpeg:

    choco install ffmpeg

Requirements Installation

python3.10 -m pip install -r requirements.txt --no-warn-script-location

Enable Long Paths

• From PowerShell Administrator run the following:

New-ItemProperty -Path "HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1 -PropertyType DWORD -Force

Download PyTorch with CUDA Support for GPU Acceleration

• If you have NVIDIA GPUs, determine what compute platform you have present:

  nvidia-smi.exe

• Identify "CUDA Version"
• Navigate to: https://pytorch.org/get-started/locally/
• Select options specific to your environment and install the command specified!
• Once installation is complete run:

  python3.10 pytorch_verify.py

Example Successfull Output:

• True
• NVIDIA GeForce RTX 3080 Ti Laptop GPU

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Usage

LLM Customization

• Install Ollama on your system and select model.
• Modify the config.yaml file located in src/utils/config.yaml and specify the model that you've downloaded.
• Refer to the Ollama documentation for details on other available options like num_ctx, num_predict, top_k, repeat_penalty, and num_gpu.

llm:
  model_name: "mistral:latest" # Choose your Ollama model (e.g., "mistral:latest")
  # ... other options ...
  options:
    temperature: 0.3 # Controls response creativity (0.0-1.0). Higher values are more creative.
    top_p: 0.5 # Controls similarity sampling (accuracy) when generating a response (0.1-1).
    # ... other options ...

Begin Ollama Server

ollama serve

Run Project

To run the project, use the main.py script with the following options:

python3.10 main.py [OPTIONS]

Command	Description
python3.10 main.py --gui	Use the graphical user interface (GUI) to select an audio file.
python3.10 main.py --audio path/to/recording.mp3	Process a specific audio file with default settings.
python3.10 main.py --audio path/to/recording.mp3 --output path/to/output --transcript medium	Specify the output directory and the Whisper model size for transcription.
python3.10 main.py --audio path/to/recording.mp3 --llm mistral:latest	Use a specific LLM model for summarization.
python3.10 main.py --audio path/to/recording.mp3 --output path/to/summaries --transcript medium --llm mistral:latest	Full example with all available options.
python3.10 main.py --help	For more information on the available options

The results of the processing will be stored in a results directory created in the same location where you run main.py. This directory will contain the following subdirectories:

• converted_audio/: Stores the audio files converted to the required format (if necessary).
• meeting_summaries/: Contains the generated meeting summary files.
• transcribed_text/: Holds the transcriptions of the audio files.

System Prompt Customization

• Modify the config.yaml file located in src/utils/config.yaml. You can customize the summarization process by modifying the following sections:

prompts:
  summary_prompt: | # Modify this prompt to customize the summary generation
    Analyze the provided transcript and create a comprehensive Summary Report that captures all essential information.

    Structure the summary as follows:

    1. **EXECUTIVE OVERVIEW**
    - Synthesize core meeting purpose and outcomes
    - ... (more details)

    2. **KEY DISCUSSION POINTS**
    - Present main topics chronologically with timestamps
    - ... (more details)

    3. **ACTION ITEMS AND RESPONSIBILITIES**
    - List concrete tasks with clear ownership and deliverables
    - ... (more details)

    4. **CONCLUSIONS AND NEXT STEPS**
    - Summarize achieved outcomes against objectives
    - ... (more details)

    Format Guidelines:
    - Use clear, professional language ...
    - ... (more guidelines)