Skip to main content

An AI assistant powered by Llama models

Project description

Llama Assistant

🌟 Llama Assistant 🌟

Your Local AI Assistant with Llama Models

Website: llama-assistant.nrl.ai

Python Llama 3 License Version Stars Forks Issues

AI-powered assistant to help you with your daily tasks, powered by Llama 3.2. It can recognize your voice, process natural language, and perform various actions based on your commands: summarizing text, rephrasing sentences, answering questions, writing emails, and more.

This assistant can run offline on your local machine, and it respects your privacy by not sending any data to external servers.

Screenshot

Settings

Supported Models

TODO

  • 🖼️ Support multimodal model: moondream2.
  • 🗣️ Add wake word detection: "Hey Llama!".
  • 🛠️ Custom models: Add support for custom models.
  • 📚 Support 5 other text models.
  • 🖼️ Support 5 other multimodal models.
  • ⚡ Streaming support for response.
  • 🎙️ Add offline STT support: WhisperCPP (WIP - Experimental Code).
  • 🧠 Knowledge database: Langchain or LlamaIndex?.
  • 🔌 Plugin system for extensibility.
  • 📰 News and weather updates.
  • 📧 Email integration with Gmail and Outlook.
  • 📝 Note-taking and task management.
  • 🎵 Music player and podcast integration.
  • 🤖 Workflow with multiple agents.
  • 🌐 Multi-language support: English, Spanish, French, German, etc.
  • 📦 Package for Windows, Linux, and macOS.
  • 🔄 Automated tests and CI/CD pipeline.

Features

  • 🎙️ Voice recognition for hands-free interaction
  • 💬 Natural language processing with Llama 3.2
  • 🖼️ Image analysis capabilities (TODO)
  • ⚡ Global hotkey for quick access (Cmd+Shift+Space on macOS)
  • 🎨 Customizable UI with adjustable transparency

Note: This project is a work in progress, and new features are being added regularly.

Technologies Used

  • Python
  • Llama
  • SpeechRecognition
  • PyQt

Installation

Install from PyPI:

pip install llama-assistant
pip install pyaudio

Or install from source:

  1. Clone the repository:

    git clone https://github.com/vietanhdev/llama-assistant.git
    cd llama-assistant
    
  2. Install the required dependencies:

    pip install -r requirements.txt
    pip install pyaudio
    

Speed Hack for Apple Silicon (M1, M2, M3) users: 🔥🔥🔥

  • Install Xcode:
# check the path of your xcode install
xcode-select -p

# xcode installed returns
# /Applications/Xcode-beta.app/Contents/Developer

# if xcode is missing then install it... it takes ages;
xcode-select --install
  • Build llama-cpp-python with METAL support:
pip uninstall llama-cpp-python -y
CMAKE_ARGS="-DGGML_METAL=on" pip install -U llama-cpp-python --no-cache-dir

# You should now have llama-cpp-python v0.1.62 or higher installed
# llama-cpp-python         0.1.68

Usage

Run the assistant using the following command:

llama-assistant

# Or with a
python -m llama_assistant.main

Use the global hotkey (default: Cmd+Shift+Space) to quickly access the assistant from anywhere on your system.

Configuration

The assistant's settings can be customized by editing the settings.json file located in your home directory: ~/llama_assistant/settings.json.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

Star History

Star History Chart

Contact

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llama_assistant-0.1.22.tar.gz (11.3 MB view details)

Uploaded Source

Built Distribution

llama_assistant-0.1.22-py3-none-any.whl (369.9 kB view details)

Uploaded Python 3

File details

Details for the file llama_assistant-0.1.22.tar.gz.

File metadata

  • Download URL: llama_assistant-0.1.22.tar.gz
  • Upload date:
  • Size: 11.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for llama_assistant-0.1.22.tar.gz
Algorithm Hash digest
SHA256 a6e0cad22bb50432bd15c62a45395bccaffd31201b728172bbc59cb051a00e6c
MD5 b8e28722e0b8fca8d6152bc3ab3452d5
BLAKE2b-256 36171a001b5dd934c460e8d07e5436a825711372a40840ed9a886a61d243a7e7

See more details on using hashes here.

File details

Details for the file llama_assistant-0.1.22-py3-none-any.whl.

File metadata

File hashes

Hashes for llama_assistant-0.1.22-py3-none-any.whl
Algorithm Hash digest
SHA256 0b9975f9097204a7d1ea3a2778f6804670f1c0ada50d072c6c91d67f2b5e9bca
MD5 9a515d599ee1ac36a74a00644c06e1f1
BLAKE2b-256 ae83e17eb8902c9ccb1bd010e4dd9059807f781a6c7d13853d1c282d0b626823

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page