Remi is a chatbot that utilizes a pre-trained language model, LL7M, to provide engaging conversations.
- Python 3.12 or higher
torch
andtransformers
libraries
- Clone the repository.
git clone https://github.com/alexlnkp/Remi.git
- Create a Python virtual environment.
python -m venv .venv
- Install required libraries in the virtual environment.
pip install -r infer.req
- Activate the virtual environment.
source .venv/bin/activate
(Linux) or. .venv/Scripts/activate
(Windows) - To run Remi in chatting mode, use
python prompt.py
or./prompt.py
(Linux only)
Your contributions will be met with gratitude and will help greatly! If You would like to help Remi, please fork the repository and submit a pull request.
-
General:
-
Fine-tune the LLM to directly improve quality of the responses
-
Do some fancy prompt-engineering.
-
TTS related:
-
Bootstrap a TTS in an external script to have an option to convert generated output directly to audio.
-
^ Using
Bark
, TTS can produce output with emotions. Therefore, also bootstrapping a tone recognition of the generated text would make the chatbot sound more natural. -
User input related:
-
Bootstrap Whisper or any other voice recognition AI model to convert user speech into text which is then used as an input for inference of an LLM.
-
Bootstrap the aforementioned tone recognition of the text to the user's voice recognition to add on layers of communications.
This project is licensed under the MIT License - see the LICENSE
file for details.
LL7M - the pre-trained LLM used by Remi.
For any questions or concerns, please contact the project maintainers at [email protected].