Table of Contents

• Table of Contents
• About the App
• Official help guide
• Dependencies
• Installation (with pre-built binaries)
• Manual Installing (from source)
• Optional Development Installation
  • Development Environment Setup
  • Packaging for Production
  • Testing
  • Generating IPC Handlers
  • Running the Collab server
  • Configuring Local Transcription
• Contributors
• Other READMEs

About the App

The Machine Learning Video Editing Toolkit (MLVET for short) is a desktop application which allows users to edit their videos via a transcription of the video audio. This transcription is produced with a machine learning model, and users are given the option to transcribe both online (with AssemblyAI) and offline (with VOSK).

This project adheres to the Contributor Covenant code of conduct. By participating, you are expected to uphold this code.

Official help guide

For offical 'how-to' documentation visit MLVET Docs

To learn the codebase visit MLVET codebase walkthrough

Dependencies

Supported Hardware - Windows - Mac (Intel) - Mac (ARM) - Linux

Node v16: download from https://nodejs.org/en/

Yarn package manager - run the following from your command line

npm install -g yarn

This will install yarn globally. Then you can install project-specific dependencies as follows

Installation (with pre-built binaries)

There are multiple ways of downloading the MLVET app.

1. Through out website https://www.mlvet.app/download
2. Through the github releases tab

Manual Installing (from source)

1. Dependencies: Node, yarn

2. Clone the repository and cd into the directory

   git clone https://github.com/MLVETDevelopers/mlvet.git
   cd mlvet

3. Package mlvet

   yarn package

4. Get executable/installer from package result

   cd ./release/build

5. Execute MLVET Setup file

You should now see MLVET in your file system.

Optional Development Installation

Development Environment Setup

1. Dependencies: Node, yarn

2. Clone the repository and cd into the directory

   git clone https://github.com/MLVETDevelopers/mlvet.git
   cd mlvet

3. Install node dependencies

   yarn && cd src/collabServer/ && yarn && cd ../../release/app && yarn

4. Start the app in the dev environment

   yarn start

This will install all dependencies required by electron needed to run the app.

To make development easier, it's recommended to use VSCode, and install the following extensions:

• ESLint https://marketplace.visualstudio.com/items?itemName=dbaeumer.vscode-eslint
• Prettier https://marketplace.visualstudio.com/items?itemName=esbenp.prettier-vscode

These will be automatically configured for the project based on the .eslintrc and .prettierrc files in the root directory.

Packaging for Production

To package apps for the local platform:

yarn package

Testing

if app has not already been built, run:

yarn build

To run unit tests:

yarn test

Generating IPC Handlers

Refer to the Code Generate documentation and IPC Handlers documentation

Running the Collab server

Refer to the Collab Server documentation

Configuring local transcription

Refer to the Local Transcription documentation and the help docs on the landing page.

Contributors

This project exists thanks to all the people who contribute. If you are interested in helping, check out the Contributing Guide.

Other READMEs

• CONTRIBUTING.md
• GENCODE.md
• Handlers README.md
• Collab server README.md