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ZettaBrain RAG

ZettaBrain RAG 通过 pipx 或安装脚本部署,提供命令行聊天、网页界面与文档索引命令;setup 向导配置文档存储(本地、NFS、SMB、S3)、安装并启动本地 Ollama、拉取模型、生成自签名证书并注册后台服务。支持 PDF、DOCX、TXT、Markdown 索引问答,默认全程本地,远程存储或远程模型端点会外发数据。

zettabrain
zettabrain
热度 28.54
最近更新 2026-05-20 06:35:44
分类:知识依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:研究 / 摘要总结 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add zettabrain-rag
Metadata
name
zettabrain-rag
description
Query documents on your NFS shares, SMB servers, or local drive using local AI. No cloud, no Docker, no API keys — the only RAG skill that reads from enterprise storage directly. Runs on your own machine with Ollama + ChromaDB.
version
1.0.2
emoji
🧠
homepage
https://zettabrain.io
metadata
{"openclaw":{"requires":{"anyBins":["zettabrain-chat","zettabrain-ingest"]},"install":[{"kind":"brew","formula":"pipx","bins":["pipx"]}],"envVars":[{"name":"ZETTABRAIN_DOCS","required":false,"description":"Path to your documents folder (e.g. ~/Documents/ZettaBrain). Overrides the value set during zettabrain-setup."},{"name":"ZETTABRAIN_LLM_MODEL","required":false,"description":"Ollama model name to use (e.g. llama3.1:8b, qwen2.5:14b). Defaults to the model selected during setup."},{"name":"OLLAMA_HOST","required":false,"description":"Ollama API URL. Default: http://localhost:11434 (local). WARNING: setting this to a remote host sends document queries off-machine."}]}}

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