← 返回 Skills 市场
zettabrain

ZettaBrain RAG

作者 zettabrain · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ⚠ suspicious
87
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install zettabrain-rag
功能描述
Chat with your private documents using a fully local RAG pipeline. No cloud, no API keys — runs on your own machine with Ollama + ChromaDB.
使用说明 (SKILL.md)

ZettaBrain RAG Skill

Chat with your own documents using a local AI. Document data stays on your machine when you use local storage and a local Ollama endpoint (the default). Remote storage (S3, NFS, SMB) and a remote OLLAMA_HOST are optional and will move data off-device — see the Privacy section.

Supports PDF, DOCX, TXT, Markdown. Works on Linux, macOS (including EC2 Mac Apple Silicon), and Windows.

Install

Recommended — pipx (no elevated privileges, fully inspectable)

pipx install zettabrain-rag
sudo zettabrain-setup

One-line installer (review source before running)

The installer scripts are open source and auditable at the links above before execution.

# Linux — review first: https://github.com/zettabrain/zettabrain-rag/blob/main/install.sh
curl -fsSL https://zettabrain.app/install.sh | sudo bash

# macOS — review first: https://github.com/zettabrain/zettabrain-rag/blob/main/install.sh
curl -fsSL https://zettabrain.app/install.sh | bash

# Windows — review first: https://github.com/zettabrain/zettabrain-rag/blob/main/install.ps1
irm https://zettabrain.app/install.ps1 | iex

The Linux installer requires sudo to install Ollama system-wide and register a systemd service. The macOS installer does not require sudo for the package install step.

Setup

Run the interactive setup wizard once after install:

sudo zettabrain-setup

This will:

  1. Configure your document storage (local, NFS, SMB, or S3)
  2. Install and start Ollama locally
  3. Pull the recommended AI model for your hardware
  4. Generate a self-signed TLS certificate (stays on-device)
  5. Register ZettaBrain as a background service (see Service Management to stop or remove it)

Commands

Command Description
zettabrain-chat Interactive CLI chat with your documents
zettabrain-server Start the web GUI server (HTTPS on port 7860)
zettabrain-ingest Index documents into the vector store
zettabrain-ingest --rebuild Wipe and re-index all documents
zettabrain-status Show Ollama, vector store, and storage status
zettabrain-storage add Add an additional storage source
zettabrain-setup Re-run the setup wizard

Usage Examples

Chat via CLI:

zettabrain-chat
# > What does our Q3 report say about cloud costs?

Start the web GUI (https://localhost:7860):

zettabrain-server

Ingest a specific folder:

ZETTABRAIN_DOCS=/path/to/docs zettabrain-ingest

Vector Store — Location, Retention & Deletion

The vector index (document embeddings) is stored only on your local machine:

Item Location
Vector database /opt/zettabrain/src/zettabrain_vectorstore/
Ingestion log (MD5 hashes) /opt/zettabrain/src/ingested_files.json
Configuration /opt/zettabrain/src/zettabrain.env

Embeddings are never transmitted to any remote service. They are derived from your documents and stored locally in ChromaDB.

Delete the vector index:

# Via CLI
zettabrain-server &
curl -X DELETE http://localhost:7860/api/vectorstore

# Or directly
rm -rf /opt/zettabrain/src/zettabrain_vectorstore
rm -f  /opt/zettabrain/src/ingested_files.json

Rebuild from scratch:

zettabrain-ingest --rebuild

Exclude files or folders by not including them in ZETTABRAIN_DOCS — only files under that path are indexed.

Service Management

ZettaBrain registers a background service so the web GUI auto-starts on boot. Here is how to control or fully remove it:

Linux (systemd)

# Stop the service
sudo systemctl stop zettabrain

# Disable auto-start on boot
sudo systemctl disable zettabrain

# Check status
sudo systemctl status zettabrain

# View logs
journalctl -u zettabrain -f

# Remove service completely
sudo systemctl stop zettabrain
sudo systemctl disable zettabrain
sudo rm /etc/systemd/system/zettabrain.service
sudo systemctl daemon-reload

macOS (launchd)

# Stop the service
sudo launchctl unload /Library/LaunchDaemons/io.zettabrain.server.plist

# Remove auto-start on boot
sudo rm /Library/LaunchDaemons/io.zettabrain.server.plist

# View logs
tail -f /opt/zettabrain/logs/server.log

Uninstall completely

# Remove the package
pipx uninstall zettabrain-rag

# Stop and remove service (Linux)
sudo systemctl stop zettabrain && sudo systemctl disable zettabrain
sudo rm -f /etc/systemd/system/zettabrain.service && sudo systemctl daemon-reload

# Stop and remove service (macOS)
sudo launchctl unload /Library/LaunchDaemons/io.zettabrain.server.plist
sudo rm -f /Library/LaunchDaemons/io.zettabrain.server.plist

# Remove all data, config, and vector index
sudo rm -rf /opt/zettabrain

Privacy

Privacy depends on your configuration:

Configuration Data stays local?
Local storage + OLLAMA_HOST=http://localhost:11434 (default) ✅ Yes — fully on-device
NFS or SMB network storage ⚠️ Documents fetched over your LAN
S3 / object storage ⚠️ Documents streamed from cloud storage
Remote OLLAMA_HOST ⚠️ Queries and retrieved document chunks sent to remote Ollama

Default setup is fully local. The setup wizard defaults to local storage and a localhost Ollama endpoint. Remote options are opt-in and clearly labelled during setup.

Document embeddings (vector index) are always stored locally regardless of storage configuration.

Configuration

Settings file: /opt/zettabrain/src/zettabrain.env

Variable Default Description
ZETTABRAIN_DOCS set during setup Path to documents folder
ZETTABRAIN_LLM_MODEL set during setup Ollama model name
ZETTABRAIN_EMBED_MODEL nomic-embed-text Embedding model
OLLAMA_HOST http://localhost:11434 Ollama API endpoint (keep local for full privacy)
ZETTABRAIN_CHUNK_SIZE 1000 Document chunk size
ZETTABRAIN_CHUNK_OVERLAP 200 Chunk overlap

Supported Platforms

Platform Notes
Ubuntu 22.04 / 24.04 Full GPU support (NVIDIA auto-installed)
Amazon Linux 2 / 2023 Full support
RHEL / Rocky / AlmaLinux 8/9 Full support
macOS 12+ Apple Silicon Metal GPU via Ollama (mac2.metal, mac2-m2.metal)
macOS 12+ Intel CPU inference (mac1.metal)
Windows 10/11 Via PowerShell installer

Links

安全使用建议
This skill does not show artifact-backed malicious behavior, but install it only if you are comfortable running external installer/package code, granting sudo for setup on systems that need it, indexing the selected document folder into a persistent local vector database, and managing the auto-start service. Keep Ollama local unless you intentionally want document queries sent to a remote host.
功能分析
Type: OpenClaw Skill Name: zettabrain-rag Version: 1.0.1 The skill promotes high-risk installation patterns, specifically 'curl | bash' and PowerShell 'iex' (Invoke-Expression) from remote URLs (zettabrain.app) in SKILL.md, which are classic vectors for remote code execution. Additionally, the setup process requires 'sudo' privileges to register background services (systemd/launchd) and manage system-wide configurations in /opt/zettabrain. While these actions are documented as necessary for the RAG service's functionality, the combination of remote script execution and elevated privileges warrants a cautious classification.
能力评估
Purpose & Capability
The private-document indexing and chat behavior fits the stated RAG purpose, and the artifact discloses local vector storage plus optional remote storage or remote Ollama settings that can move data off-device.
Instruction Scope
The documented commands are user-directed setup, ingestion, service management, and cleanup commands. The delete command is destructive but scoped to the ZettaBrain vector store and ingestion log.
Install Mechanism
The skill is instruction-only and asks users to install an external package or run remote installer scripts, including sudo on Linux. This is disclosed and purpose-aligned, but the runnable installer/package code was not included in the artifact set.
Credentials
Reading and indexing private documents is central to the skill, and the artifacts describe path scoping through ZETTABRAIN_DOCS, storage locations, and deletion options. Users should still choose document paths carefully.
Persistence & Privilege
The setup registers a boot-starting background service and may require sudo to install Ollama/system services. The artifact provides stop, disable, and uninstall instructions, so this is disclosed rather than hidden.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install zettabrain-rag
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /zettabrain-rag 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
Address ClawScan findings: added installer source links, full uninstall instructions, vector store location and deletion docs, conditional privacy table
v1.0.0
Initial release — local RAG pipeline with macOS, Linux and Windows support
元数据
Slug zettabrain-rag
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

ZettaBrain RAG 是什么?

Chat with your private documents using a fully local RAG pipeline. No cloud, no API keys — runs on your own machine with Ollama + ChromaDB. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 87 次。

如何安装 ZettaBrain RAG?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install zettabrain-rag」即可一键安装,无需额外配置。

ZettaBrain RAG 是免费的吗?

是的,ZettaBrain RAG 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

ZettaBrain RAG 支持哪些平台?

ZettaBrain RAG 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 ZettaBrain RAG?

由 zettabrain(@zettabrain)开发并维护,当前版本 v1.0.1。

💬 留言讨论