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Streamstem

Implements ML audio separation algorithm on audio from YouTube or Spotify resulting in "stems" for download (e.g. vocals, drums, bass) in MP3, WAV or FLAC.

Install / Use

/learn @otonomee/Streamstem

README

StemStream

Extract the "stems" (e.g. drums, vocals, bass) from any song on Spotify or Youtube into separate audio files

Introduction

This is a Flask web app using the following resources:

Screenshot

alt text

Installation

  1. Install Python 3.8 or higher

  2. Clone the repository: Open a terminal and clone the repository using the following command:

    git clone https://github.com/otonomee/streamstem.git
    cd streamstem
    
  3. Install dependencies: Navigate to the project directory and install the required dependencies:

    pip install -r requirements.txt
    
  4. Set up environment variables (Required for Spotify URL conversion):

    a. Copy the example environment file:

    cp .env.example .env
    

    b. Edit .env and add your API credentials:

    SPOTIFY_CLIENT_ID=your_spotify_client_id_here
    SPOTIFY_CLIENT_SECRET=your_spotify_client_secret_here
    GOOGLE_API_KEY=your_google_api_key_here
    

    How to get API credentials:

    Note: API credentials are only required if you want to use Spotify URLs. YouTube URLs work without any API keys.

  5. Run the web app: Start the web app by running the following command:

    python application.py
    
  6. Access the web app: Open your web browser and go to http://localhost:8001 to access the web app.

Usage

  1. Enter the YouTube video URL: On the web app's homepage, enter the URL of the YouTube video you want to convert the audio from.

  2. Select the number of stems you'd like:

    • 2 stems: vocals and instrumental
    • 4 stems: vocals, drums, bass, other
    • 6 stems: vocals, drums, bass, guitar, piano, other
  3. Select desired output format

  4. Hit Submit and wait a few minutes. Download prompt will appear when finished :)

Related Skills

View on GitHub
GitHub Stars37
CategoryEducation
Updated1mo ago
Forks2

Languages

Python

Security Score

80/100

Audited on Jan 28, 2026

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