This is an example implementation of an LLM (Large Language Model) transceiver, which enables users to submit prompts and stream prompts (and outputs) using WebRTC connections. This code serves as a starting point for building your own LLM-based communication system.
What this code does
This repository contains a Python class that establishes WebRTC connections with a server and enables bidirectional communication between the user and the LLM. The code allows users to submit prompts, receive responses from the LLM, and stream outputs in real-time.
How to use this code
Clone this repository: git clone https://github.com/YOUR-USERNAME/LLM-Transceiver-Example.git
Install required dependencies: pip install websockets
Run the code: python main.py
Features and limitations
Supports bidirectional communication between user and LLM
Allows for submission of prompts and streaming of outputs (and responses)
Demonstrates use of WebRTC connections for real-time communication
Note: This is an example implementation, and you will need to modify the code to suit your specific use case. You may also want to add additional features, such as error handling, logging, or security measures.
Next steps
Customize this code to fit your project's requirements
Test and refine the code for robustness and performance
Integrate with your LLM model and server implementation
Contributing
If you'd like to contribute to this repository or have suggestions for improvement, please feel free to open an issue or pull request!
This README file serves as a starting point for using and customizing this code for your own project. Happy coding!