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Install Alpaca Electron using Winget - wingetCollections
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Alpaca Electron Pi

ai alpaca chatbot large-language-model llama llm
Use this command to install Alpaca Electron:
winget install --id=ItsPi3141.AlpacaElectron -e

The simplest way to run Alpaca (and other LLaMA-based local LLMs) on your own computer

Alpaca Electron is a user-friendly application designed to simplify running Alpaca and other LLaMA-based local language models on your computer. Built with ease of use in mind, it eliminates the need for command-line interfaces or complex setup processes.

Key Features:

  • Runs locally without internet connectivity once models are downloaded.
  • Uses efficient llama.cpp backend to support Alpaca, Vicuna, and other compatible models.
  • Supports Windows, macOS, and Linux (untested).
  • Includes Docker integration for containerized deployment.
  • Features a clean, intuitive UI borrowed from popular chat AI interfaces.
  • Integrates with Stable Diffusion and DuckDuckGo for enhanced functionality.

Audience & Benefit: Ideal for developers, researchers, and enthusiasts looking to experiment with local large language models without the need for expensive GPUs or technical expertise. With Alpaca Electron, users can easily access and interact with AI models on their personal computers, enabling experimentation and prototyping in a simplified environment.

The application is designed to be accessible to all skill levels, ensuring that even those without deep technical knowledge can explore and utilize local LLMs effectively. Installation via winget is supported for easy setup on Windows systems.

README

Alpaca Electron

Alpaca Electron is built from the ground-up to be the easiest way to chat with the alpaca AI models. No command line or compiling needed!

Important:

Only windows is current supported for now. The new llama.cpp binaries that support GGUF have not been built for other platforms yet.
If you would like to help, please makea pull request and update the binaries in ./bin

📃 Features + to-do

  • Runs locally on your computer, internet connection is not needed except when downloading models
  • Compact and efficient since it uses llama.cpp as its backend (which supports Alpaca & Vicuna too)
  • Runs on CPU, anyone can run it without an expensive graphics card
  • No external dependencies required, everything is included in the installer
  • "Borrowed" UI from that popular chat AI :trollface:
  • Supports Windows, MacOS, and Linux (untested)
  • Docker-ized 🐋
  • Context memory
  • Chat history
  • Integration with Stable Diffusion
  • DuckDuckGo integration for web access
Versions
1.0.6
Website
github.com
License
Last Updated
5/15/2025
  • GPU acceleration (cuBLAS & openBLAS)

    • 🎞 Demo

    Demonstration

    🚀 Quick Start Guide

    1. Download an Alpaca model (7B native is recommended) and place it somewhere on your computer where it's easy to find. > Note
      > Download links will not be provided in this repository.

    2. Download the latest installer from the releases page section.

    3. Open the installer and wait for it to install.

    4. Once done installing, it'll ask for a valid path to a model. Now, go to where you placed the model, hold shift, right click on the file, and then click on "Copy as Path". Then, paste this into that dialog box and click Confirm.

    5. The program will automatically restart. Now you can begin chatting!

    > Note
    > The program will also accept any other 4 bit quantized .bin model files. If you can find other .bin Alpaca model files, you can use them instead of the one recommended in the Quick Start Guide to experiment with different models. As always, be careful about what you download from the internet.

    🔧 Troubleshooting

    General

    • If you get an error that says "Invalid file path" when pasting the path to the model file, you probably have some sort of misspelling in there. Try copying the path again or using the file picker.
    • If you get an error that says "Couldn't load model", your model is probably corrupted or incompatible. Try downloading the model again.
    • If you face other problems or issues not listed here, create an issue in the "Issues" tab at the top of this page. Describe in detail what happens, and include screenshots.

    Windows

    • If the model has been loaded into RAM but text generation doesn't seem start, check to see if your CPU is compatible with the AVX2 instruction set. If it does not support AVX2, Alpaca Electron will use AVX instead, which is much slower so be patient.
    • If you get an error saying "vcruntime140_1.dll is missing" or nothing happens at all and the model was not loaded into RAM, try installing the Microsoft Visual C++ Redistributable.

    MacOS

    • If you get an error that says "App can't be opened because it is from an unidentified developer.", go to the Applications folder. Then, hold the control key and click on the app. Then click "Open", then click "Open" when it gives you a warning. Your preference will be saved and MacOS will let you open the app normally from now on.
    • If the above method does not work, try running the following command in terminal: xattr -cr /Applications/Alpaca\ Electron.app/

    Linux

    • You can either download the prebuilt app (packaged as tar.gz) from the releases page, extract it and execute it with ./"alpaca electron" or build the application on yourself.

    • If you want to build the application yourself: >Clone the repository: > >git clone https://github.com/ItsPi3141/alpaca-electron.git > >Change your current directory to alpaca-electron: > >cd alpaca-electron > >Install application specific dependencies: > >npm install --save-dev > >Build the application: > >npm run linux-x64 > >Change your current directory to the build target: > >cd release-builds/'Alpaca Electron-linux-x64' > >Run the application with ./'Alpaca Electron'

    Docker Compose

    • You can run this electron application with docker compose. Therefore you need to compelete the following steps:

    >Clone the repository: > >git clone https://github.com/ItsPi3141/alpaca-electron.git > >Change your current directory to alpaca-electron: > >cd alpaca-electron > >Build the container image: > >docker compose build > >Run the application container: > >docker compose up -d

    • If no window opens up run docker compose up (without the -d). If there is an error like Authorization required, but no authorization protocol specified run xhost local:root on your docker host.

    ⚒️ Building

    Prerequisites

    • Node.js
    • Git
    • If you're on Windows and are planning on building llama.cpp binaries also, CMake.

    (OPTIONAL) Building llama.cpp from source

    1. Clone llama.cpp's GitHub repo
    git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
    1. Build llama.cpp On Windows:
    mkdir build
cd build
cmake ..
cmake . --config Release

    On Linux and MacOS:

    make

    Running the project from source

    1. Clone the GitHub repo
    git clone https://github.com/ItsPi3141/alpaca-electron
cd alpaca-electron
    1. Install node packages
    npm install
npm run rebuild

    > Info If you are on Linux, replace npm run rebuild with npm run rebuild-linux

    1. (OPTIONAL) Use your own llama.cpp build > Warning
      > This step is not required. Only do it if you had built llama.cpp yourself and you want to use that build. Otherwise, skip to step 4 If you had built llama.cpp in the previous section, copy the main executable file into the bin folder inside the alpaca-electron folder.

    Make sure the file replaces the correct file. E.g. if you're on Windows, replace chat.exe with your file. If you're on arm64 MacOS, replace chat_mac_arm64. Etc...

    1. Start the Electron app
    npm start

    Building a release and installer

    Run one of the following commands:

    • npm run win
    • npm run mac-x64
    • npm run mac-arm64
    • npm run linux-x64

    You can only build for the OS you are running the build on. E.g. if you are on Windows, you can build for Windows, but not for MacOS and Linux.

    👨‍💻 Credits

    Credits go to @antimatter15 for creating alpaca.cpp and to @ggerganov for creating llama.cpp, the backbones behind alpaca.cpp. Finally, credits go to Meta and Stanford for creating the LLaMA and Alpaca models, respectively.

    Special thanks to @keldenl for providing arm64 builds for MacOS and @W48B1T for providing Linux builds