AllArkive — offline knowledge ark with a local AI

What this is

AllArkive bundles three things that already exist into something one person can install in an afternoon.

An offline knowledge archive — Wikipedia, Stack Exchange, Project Gutenberg, iFixit, and more, packaged as Kiwix ZIM files.
A local AI — an open-weight LLM via Ollama and Open WebUI, running entirely on your machine. No cloud calls.
A retrieval pipeline — RAG that lets the AI answer questions using the local archive, with citations back to the source.

Run it on a laptop, a home server, or a Raspberry Pi. Use it as a private research assistant. Keep it as a fallback for when the open web gets worse.

Why

The infrastructure of shared knowledge is more centralised, more surveilled, and more hostile to users than it has ever been. The tools to run a useful piece of it on cheap hardware already exist — they just hadn't been packaged together. We packaged them.

This is not a survival kit, a prepper bunker, or a doomsday cache. It's a library and a search tool, built on open weights and open content, that runs on your own machine. The framing is censorship resistance, privacy, and educational access.

What's in the default bundle

The balanced bundle, recommended for most laptops — roughly 23 GB of ZIM data plus a 5 GB model.

Wikipedia (English, text-only) — about 12 GB
WikiMed — medical reference, for general lookups, not medical advice
iFixit — repair guides
SuperUser — general tech Q&A
Project Gutenberg — a public-domain book selection

Smaller (minimal) and larger (comprehensive) bundles are documented in the bundle docs.

Install

git clone https://github.com/clupai8o0/allarkive.git
cd allarkive
cp compose/.env.example compose/.env
./scripts/bootstrap.sh

After install, open http://localhost:8080 for the local landing page.

Heads-up: after the stack starts, the RAG indexer keeps running in the background, embedding every ZIM chunk through your local Ollama. On CPU expect several hours for the balanced bundle, less for minimal. Leave it running — it's resumable and idempotent. Kiwix browsing at http://localhost:8081 works immediately; RAG answers improve as coverage grows.

System requirements

Minimum: 8 GB RAM, 30 GB disk, x86_64 or arm64
Recommended: 16 GB RAM, 50 GB SSD, modern CPU
Pi text-only build: Raspberry Pi 4 (4 GB+) with a USB SSD

Architecture

Three layers, each replaceable.

┌──────────────────────────────────────────┐
│  Glue: landing page, docker-compose,     │
│  bootstrap, RAG pipeline, docs           │
├──────────────────────────────────────────┤
│  Local AI: Ollama + Open WebUI + RAG     │
├──────────────────────────────────────────┤
│  Archive: Kiwix serving ZIM files        │
└──────────────────────────────────────────┘

Full breakdown in the architecture doc.

Documentation

Pick your starting point. Each doc has its own page with a sidebar and on-page table of contents.

Read first

README — one-line pitch, install snippet, license
Architecture — three-layer design, components, data flow
Threat model — what this does and does not protect against
Roadmap — what's in v0.1, what's deferred

Install

Deployment patterns

Contributing and governance

Contributing — DCO sign-off, PR checklist
Code of conduct
Governance — how decisions get made
Security — how to report a vulnerability
Full doc index

Security and honesty

Default-local binding. Nothing listens on the public internet unless you opt in.
No telemetry. Anywhere. Ever.
Pinned dependencies. Docker images pinned by digest. ZIM files verified by checksum.
Signed releases. Verify the artefacts you download.
Honest disclaimers. The AI can be wrong. RAG with citations makes its output checkable, not infallible.

Status

v0.1 is alpha. First public release lands alongside our BSides Melbourne talk in May 2026.

Co-built by Sam and Sham. Standing on the shoulders of Kiwix, Ollama, Open WebUI, and the people who maintain the open archives we bundle.