Aria

Meet Aria. A local and uncensored AI entity.

aria_demo.mp4

aria_demo_1.mp4

Installation

Clone the repo.

Method 1 - Easy installation for server/client mode using docker:

docker buildx build --tag ghcr.io/lef-fan/aria-server:latest .
pip install -r requirements_client.txt

Method 2 - Non docker server:

pip install -r requirements.txt
pip install --no-build-isolation flash-attn==2.7.4.post1

(Tested on Arch Linux + NVIDIA GPUs with python == 3.12)

More are coming, work in progress...

Usage

First run will take a while to download all the required models.
You may edit the default config for your device or use case (change model, specify devices, etc...)
If you have the resources, strongly recommended to use bigger model and/or bigger quant method.

Non server/client mode:

python main.py

Server and Client Mode

server machine - docker:

docker run --net=host --gpus all --name aria-server -it ghcr.io/lef-fan/aria-server:latest
source venv/bin/activate
python server.py

server machine - no docker:

python server.py 

client machine (edit client target ip in the config):

python client.py

Upcoming Features

• Android client
• Raspberry Pi client
• Ollama support

Documentation

Work in progress...

Contributions

🌟 We'd love your contribution! Please submit your changes via pull request to join in the fun! 🚀

Disclaimer

Aria is a powerful AI entity designed for local use. Users are advised to exercise caution and responsibility when interacting with Aria, as its capabilities may have unintended consequences if used improperly or without careful consideration.

By engaging with Aria, you understand and agree that the suggestions and responses provided are for informational purposes only, and should be used with caution and discretion.

We cannot be held responsible for any actions, decisions, or outcomes resulting from the use of Aria. We explicitly disclaim liability for any direct, indirect, incidental, consequential, or punitive damages arising from reliance on Aria's responses.

We encourage users to exercise discernment, judgment, and thorough consideration when utilizing information from Aria. Your use of this service constitutes acceptance of these disclaimers and limitations.

Should you have any doubts regarding the accuracy or suitability of Aria's responses, we advise consulting with qualified professionals or experts in the relevant field.

Acknowledgments

• silero-vad
• transformers
• whisper
• llama-cpp-python
• TTS
• TTS fork
• kokoro
• opuslib
• TheBloke
• Bartowski
• mradermacher
• mlabonne

License Information

❗ Important Note:

While this project is licensed under GNU AGPLv3, the usage of some of the components it depends on might not and they will be listed below:

TTS MODEL

• License: Open-source only for non-commercial projects.
• Commercial Use: Requires a paid plan.
• Details: Coqui Public Model License 1.0.0

opuslib

• License: BSD-3-Clause license
• Details: opuslib license

Llama

• License: llama3.1
• Details: llama license