Text-to-Speech
Transformers
ONNX
GGUF
Chinese
English
voice-dialogue
speech-recognition
large-language-model
asr
tts
llm
chinese
english
real-time
conversational
Instructions to use MoYoYoTech/VoiceDialogue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoYoYoTech/VoiceDialogue with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="MoYoYoTech/VoiceDialogue") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MoYoYoTech/VoiceDialogue", dtype="auto") - llama-cpp-python
How to use MoYoYoTech/VoiceDialogue with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MoYoYoTech/VoiceDialogue", filename="assets/models/llm/qwen/Qwen3-8B-Q6_K.gguf", )
llm.create_chat_completion( messages = "\"The answer to the universe is 42\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MoYoYoTech/VoiceDialogue with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: llama cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: llama cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: ./llama-cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Use Docker
docker model run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- LM Studio
- Jan
- Ollama
How to use MoYoYoTech/VoiceDialogue with Ollama:
ollama run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- Unsloth Studio
How to use MoYoYoTech/VoiceDialogue with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MoYoYoTech/VoiceDialogue to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MoYoYoTech/VoiceDialogue to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MoYoYoTech/VoiceDialogue to start chatting
- Pi
How to use MoYoYoTech/VoiceDialogue with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "MoYoYoTech/VoiceDialogue:Q6_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use MoYoYoTech/VoiceDialogue with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default MoYoYoTech/VoiceDialogue:Q6_K
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use MoYoYoTech/VoiceDialogue with Docker Model Runner:
docker model run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- Lemonade
How to use MoYoYoTech/VoiceDialogue with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MoYoYoTech/VoiceDialogue:Q6_K
Run and chat with the model
lemonade run user.VoiceDialogue-Q6_K
List all available models
lemonade list
File size: 3,773 Bytes
28762c8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 | # VoiceDialogue 安装指南
本文档提供 VoiceDialogue 智能语音对话系统的详细安装说明。
## 系统要求
在开始安装之前,请确保您的系统满足以下要求:
- **操作系统**: macOS 14+ (推荐)
- **Python 版本**: 3.9 或更高版本
- **内存要求**: 至少 16GB RAM (推荐 32GB 用于大模型)
- **存储空间**: 至少 20GB 可用空间 (用于模型文件)
## 安装步骤
### 1. 克隆项目
```bash
git clone https://huggingface.co/MoYoYoTech/VoiceDialogue
cd VoiceDialogue
```
### 2. 创建并激活虚拟环境
建议使用虚拟环境来避免依赖冲突:
```bash
# 使用 uv (推荐)
pip install uv
uv venv
source .venv/bin/activate
# 或使用 conda
conda create -n voicedialogue python=3.11
conda activate voicedialogue
# 或使用 venv
python -m venv voicedialogue
source voicedialogue/bin/activate
```
### 3. 安装项目依赖
```bash
# 使用 uv (推荐)
WHISPER_COREML=1 CMAKE_ARGS="-DGGML_METAL=on" uv sync
# 或使用 pip
WHISPER_COREML=1 CMAKE_ARGS="-DGGML_METAL=on" pip install -r requirements.txt
```
### 4. 安装音频处理工具
```bash
# macOS
brew install ffmpeg
```
### 5. 安装额外依赖
```bash
# 安装 kokoro-onnx
uv pip install kokoro-onnx
# 或
pip install kokoro-onnx
# 重新安装指定版本的 numpy
uv pip install numpy==1.26.4
# 或
pip install numpy==1.26.4
```
## 验证安装
安装完成后,可以通过以下命令验证安装是否成功:
```bash
# 查看帮助信息
python main.py --help
# 启动系统(默认使用中文,沈逸角色)
python main.py
```
如果看到 "服务启动成功" 提示,说明安装成功。
## 故障排除
### 1. 模型下载失败
- **问题**: 网络连接超时或模型下载失败。
- **解决方案**: 设置 Hugging Face 镜像。
```bash
export HF_ENDPOINT=https://hf-mirror.com
pip install -U huggingface_hub
```
### 2. 音频设备问题
- **问题**: 找不到音频设备或权限被拒绝。
- **macOS 解决方案**: 系统设置 → 隐私与安全性 → 麦克风 → 启用你的终端应用 (如 iTerm, Terminal)。
### 3. 内存不足错误 (OOM)
- **问题**: `CUDA out of memory` 或 RAM 不足。
- **解决方案**: LLM 是主要的内存消耗者。你可以通过修改 `src/VoiceDialogue/services/text/generator.py` 来降低资源消耗:
- **更换模型**: 将模型路径指向一个更小的模型(如 7B Q4 量化模型)。
- **减少批处理大小**: 减小模型参数中的 `n_batch` 值(如 `256`)。
- **减少上下文长度**: 减小 `n_ctx` 的值(如 `1024`)。
### 4. 依赖包冲突
- **问题**: 包版本冲突或导入错误。
- **解决方案**: 强烈建议在虚拟环境中安装。如果遇到问题,尝试重建虚拟环境。
```bash
# 使用 conda
conda deactivate
conda env remove -n voicedialogue
# 使用 uv
rm -rf .venv
uv venv
```
### 5. FFmpeg 相关错误
- **问题**: 音频处理失败或编解码错误。
- **解决方案**: 确保正确安装 FFmpeg:
```bash
# 检查 FFmpeg 安装
ffmpeg -version
# 重新安装 FFmpeg
# macOS
brew reinstall ffmpeg
```
### 6. Python 版本兼容性
- **问题**: Python 版本过低导致的兼容性问题。
- **解决方案**: 确保使用 Python 3.11+ 版本:
```bash
python --version
# 如果版本过低,请升级或使用虚拟环境
```
## 下一步
安装完成后,您可以:
1. [查看使用指南](../README.md#🖥️-应用模式) 了解如何使用系统
2. [查看配置选项](../README.md#⚙️-配置选项) 了解如何自定义配置
3. [查看系统架构](../README.md#🔧-系统架构) 了解系统工作原理
如果遇到其他问题,请查看 [完整故障排除指南](../README.md#🛠️-故障排除) 或提交 Issue。 |