https://github.com/emingenc/g1_voice_ai_assistant
voice ai assistant for even-realities g1 smart glasses
https://github.com/emingenc/g1_voice_ai_assistant
Last synced: about 1 year ago
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voice ai assistant for even-realities g1 smart glasses
- Host: GitHub
- URL: https://github.com/emingenc/g1_voice_ai_assistant
- Owner: emingenc
- License: gpl-3.0
- Created: 2024-11-11T06:56:23.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-12T04:05:11.000Z (over 1 year ago)
- Last Synced: 2025-03-28T09:51:33.625Z (over 1 year ago)
- Language: Python
- Size: 5.26 MB
- Stars: 15
- Watchers: 1
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Emotional AI Voice Chat
Fast conversation with emotional AI with even-realities G1 smart glass connection
This project implements a real-time ai conversation system with emotional text-to-speech (TTS) capabilities. It uses a large language model (LLM) for generating responses and a TTS engine with voice-cloning for voice output.
Based on:
- Voice TTS/STT implementation from [LocalEmotionalAIVoiceChat](https://github.com/KoljaB/LocalEmotionalAIVoiceChat)
- LLM agent from [memory-agent](https://github.com/langchain-ai/memory-agent)
## Features
- Real-time speech-to-text input
- Cnversation generation powered by: Ollama, LMStudio, OpenAI, Anthropic or llama.cpp Webserver
- Emotion-aware realtime text-to-speech output
- Configurable system and user personas
## Requirements
- Python <=3.10 (3.10.9 is recommended)
- Docker for redis and langraph
## Installation
1. Clone the repository
```bash
git clone https://github.com/emingenc/G1_voice_ai_assistant.git
cd G1_voice_ai_assistant
```
2. Install the required packages
- venv (optional)
```bash
python -m venv venv
source venv/bin/activate
```
- Install the required packages
```bash
pip install -r requirements.txt
```
3. setup the environment variables in llm_agent folder example .env file
```bash
cp llm_agent/.env.example llm_agent/.env
```
## Usage
Run the scripts in different terminals to start the system:
1. start the langraph
```bash
cd llm_agent
langgraph up
cd ..
```
2. start the redis
```bash
docker run --name my-redis -p 6379:6379 -d redis
```
3. start g1 smart glass connection
```bash
python g1_smart_glass.py
```
4. start the voice ai assistant
```bash
python voice_ai_assistant.py
```