本地语音助手
AI Skill Hub 强烈推荐：本地语音助手 是一款优质的Agent工作流。AI 综合评分 8.5 分，在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案，这是一个值得深入了解的选择。
📚 深度解析
本地语音助手 工作流的设计遵循"最小配置，最大复用"原则：核心逻辑已经封装好，用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制，在网络波动或 API 限速等情况下仍能稳定运行，适合作为生产环境的自动化基础设施。
在实际部署时，建议先在测试环境中运行 3-5 次，验证各个环节的输出结果符合预期，再部署到生产环境。AI Skill Hub 评分 8.5 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
本地语音助手 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
📖 中文文档
本地语音助手 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
# 方式一：pip 安装（推荐）
pip install fulloch
# 方式二：虚拟环境安装（推荐生产环境）
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install fulloch
# 方式三：从源码安装（获取最新功能）
git clone https://github.com/liampetti/fulloch
cd fulloch
pip install -e .
# 验证安装
python -c "import fulloch; print('安装成功')"
- 访问 GitHub 仓库获取工作流文件
- 在对应平台（Dify / Flowise / Make 等）中找到「导入工作流」功能
- 上传工作流文件
- 按照提示配置必要的环境变量和 API Key
- 运行测试确认流程正常后投入使用
# 命令行使用
fulloch --help
# 基本用法
fulloch input_file -o output_file
# Python 代码中调用
import fulloch
# 示例
result = fulloch.process("input")
print(result)
# fulloch 配置文件示例（config.yml） app: name: "fulloch" debug: false log_level: "INFO" # 运行时指定配置文件 fulloch --config config.yml # 或通过环境变量配置 export FULLOCH_API_KEY="your-key" export FULLOCH_OUTPUT_DIR="./output"
Fulloch
[![GitHub Release][releases-shield]][releases] [![License][license-shield]](LICENSE) [![hacs][hacs-shield]][hacs]
<p align="center"> <img src="fulloch.png" alt="Fulloch Logo" width="200"> </p>
The Fully Local Home Voice Assistant, a private voice layer for your notes, your home, and the web.
Fulloch is your privacy-focused local voice assistant running on your own PC or Mac. Ask questions, capture thoughts, and search your Obsidian vault by voice. Control your home via Home Assistant. Pull live answers from the web with SearXNG. The local stack keeps speech, language processing, notes, facts, and conversation history on your machine; optional web search, Spotify, and remote language models contact their configured services.
Click here to see the satellite companion project for running multiple ESP32-S3 satellites around your home.
Features
- Private, local by default - speech, language processing, notes, facts, and conversation history stay on your machine; web search, Spotify, and remote language models are explicit opt-ins
- Natural voice conversations - use the browser dashboard or connected satellites; Fulloch keeps conversational context, supports follow-up turns, and lets you barge in with the wakeword
- Your voice, your way - GPU and CPU stacks support voice cloning; ask it to whisper or speak quietly for per-turn reduced-volume delivery
- Obsidian notes and memory - read, write, append, and semantically search your vault by voice; remembered facts persist across restarts
- Smart-home control - control Home Assistant lights, locks, covers, climate, media, calendars, todos, weather, and more in natural language
- Music and reminders - find music with Spotify and play it through Home Assistant; create calendar reminders that Fulloch announces at the right time
- Live answers - get concise, source-aware summaries from self-hosted SearXNG web search, with the option to save results to your vault
- Deliberate research and planning - queue deeper background investigations for comparisons, academic literature, and multi-stop travel plans; research prefers Semantic Scholar and falls back to arXiv and OpenAlex, while travel searches use an optional SerpApi key
- Home Assistant automation - use the HACS integration for status, mic control, proactive speech, chat, and scheduled deliberate-thinking tasks
Higgs TTS 3: The optional Higgs GPU backend is available only under Boson AI's Research and Non-Commercial License, not Fulloch's MIT license. It requires explicit consent for every voice reference. See Model Sources and Licenses.
Pocket TTS PyTorch: The experimental GPU streaming option uses Kyutai's official gated model. Accept its Hugging Face terms before selecting it. If the download is denied, the wizard prompts for a Hugging Face read token, saves it in data/credentials.json, and retries. See Model Sources and Licenses.
openWakeWord feature extractors: The optional wakeword gate includes unmodified pre-trained feature extractor models from openWakeWord v0.5.1 under CC BY-NC-SA 4.0, not Fulloch's MIT license. See Model Sources and Licenses.
Quick installation
The default stack runs on CPU (mac/linux/windows). Audio runs through the browser dashboard. The LLM is either regex-only (simple commands) or off-box via an OpenAI-compatible endpoint you configure in the wizard (e.g. Ollama / LM Studio / another machine on your LAN). The dashboard avatar swaps to Parloch, the Partially-local home voice assistant, when the LLM is running off-device.
Install Docker Desktop (or Docker Engine) first. The first run downloads the selected speech models, so it needs an internet connection, several GB of free disk, and enough Docker memory for the wizard's displayed estimate. For the GPU image, install a current NVIDIA driver and NVIDIA Container Toolkit, then confirm docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu22.04 nvidia-smi works before launching Fulloch.
Recovering Or Reconfiguring
Use Settings for normal changes: voices, model backends, language-model mode, Home Assistant, Search, and dashboard preferences. Model changes need a restart; if their weights are missing, the restart returns to the wizard to download them. The Re-run setup wizard action makes a backup under data/backups/; use it to choose a different stack, not to edit a custom model path or advanced remote-LLM settings. To repair a failed download, re-run setup and select the same stack; incomplete model caches are detected and downloaded again.
Advanced options not shown in Settings are documented in data/config.example.yml: Spotify OAuth, native satellite tokens, and external-LLM timeouts. Keep those files under the persistent data volume.
OpenAI Endpoint
<img src="parloch.png" alt="Fulloch being Parloch" width="180" align="right">
The moment you point the language model at an OpenAI-compatible endpoint, the avatar and favicon swap to a travelling version of the character (Let's call him Parloch: The Partially local home voice assistant), and the tagline reads "language model is off-device." Pick a local model again (None or the GPU 9B) and Fulloch comes home. It triggers as soon as a remote endpoint is configured, even if it is on your home network.
Obsidian Integration
Connect your Obsidian vault so Fulloch reads, writes, appends, and searches your notes by voice.
Just add your vault's directory as a volume when launching Docker container -v /Users/you/Documents/MyVault:/vault:rw
The Obsidian wizard's "Auto-detect" scans the container filesystem for a vault, so it'll find /vault (or wherever you mounted it) without further config.
The plugin is optional: the folder link alone supports reading, writing, appending, and searching notes. Install the separate plugin for live active-note and selection context, editor actions, and automatic note navigation; Docker installations with different host and container paths cannot yet navigate back to a written note automatically. See the Obsidian setup details.
Home Assistant Integration
When Fulloch runs in Docker, enter Home Assistant's LAN address, for example http://192.168.1.50:8123. localhost refers to the Fulloch container, not Home Assistant.
A HACS-installable integration for status sensors, mic control, proactive speech, and automation triggers.
| Entity | Description |
|---|---|
sensor.fulloch_status | idle / thinking / speaking |
sensor.fulloch_last_utterance | Last thing the user said |
sensor.fulloch_last_response | Last thing Fulloch said (full_text attribute has the full string) |
sensor.fulloch_thinking_task | Active deliberate-thinking task and status |
switch.fulloch_mic | Mute / unmute the microphone |
text.fulloch_speak | Submit text → Fulloch speaks it |
text.fulloch_chat | Submit a query → full agent loop |
| Action | Field | Description |
|---|---|---|
fulloch.speak | text | Speak a message |
fulloch.chat | text | Run a full agent query and speak the result |
fulloch.mic | enabled | Turn the mic on or off |
fulloch.run_thinking_task | task | Queue a deeper background investigation |
fulloch.cancel_thinking_task | job_id | Cancel a queued or active investigation |
fulloch.get_thinking_task_status | job_id | Retrieve an investigation's current status |
| Event | When |
|---|---|
fulloch_wakeword_detected | Voice turn starts |
fulloch_turn_ended | Fulloch finishes speaking |
高质量开源AI工作流项目
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 做语音类 AI 产品的开发者
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
- Python 依赖冲突：建议用 venv / uv 隔离环境
- Docker：fulloch 提供官方镜像，docker compose up 一键启动
- CLI：直接 npm install -g / pip install，命令行调用
- 本地部署：CPU 8GB 起，GPU 推荐 16GB+ 显存
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 做语音类 AI 产品的开发者
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
- Python 依赖冲突：建议用 venv / uv 隔离环境
👥 适合人群
🎯 使用场景
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
- +MIT 协议，可免费商用
- +大幅减少重复性人工操作
- +可视化流程，清晰直观
- +可扩展性强，支持复杂场景
- −初始配置和调试需投入一定时间
- −强依赖外部服务的稳定性
- −复杂场景需具备一定技术基础
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
🔗 相关工具推荐
❓ 常见问题 FAQ
总体来看，本地语音助手 是一款质量优秀的Agent工作流，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | fulloch |
| 原始描述 | 开源AI工作流：Fulloch - The Fully Local Home Voice Assistant。⭐88 · Python |
| Topics | aihome-assistantlocal-llm |
| GitHub | https://github.com/liampetti/fulloch |
| License | MIT |
| 语言 | Python |
收录时间：2026-06-01 · 更新时间：2026-06-01 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。