In our increasingly connected world, we often take reliable internet access for granted. But what happens when that connection disappears? Whether you’re in a remote location, experiencing a natural disaster, or simply want to maintain your digital sovereignty, having access to comprehensive knowledge without relying on cloud services becomes crucial.

This is exactly why I built zim-llm. This is a complete system for creating your own offline knowledge base using compressed Wikipedia/offline content and local LLMs.

The Problem: Digital Fragility

• Remote Locations and Travel: When traveling to remote areas (whether hiking in national parks, sailing offshore, or working in rural communities) internet connectivity can be spotty or nonexistent. Yet, access to reliable information might be more critical than ever in these situations.

• Emergency Scenarios: Natural disasters, power outages, or cyber incidents can disrupt internet services for extended periods. Having a local knowledge base means you can still access critical information about medical emergencies, survival techniques, or technical troubleshooting.

• Digital Sovereignty and Privacy: Not everyone wants their queries sent to corporate servers. zim-llm runs entirely on your local machine, ensuring your questions and the AI’s responses remain private.

Quick Setup Guide

Getting started with zim-llm is straightforward. Here’s how to set up your offline knowledge base:

1. Install Dependencies

Clone the zim-llm repository and run the setup script:

git clone https://github.com/rouralberto/zim-llm.git
cd zim-llm
./setup.sh

This will create a virtual environment and install all necessary dependencies including:

• libzim for reading ZIM files
• sentence-transformers for creating embeddings
• ChromaDB or FAISS for vector storage
• LangChain for the RAG pipeline

2. Add Knowledge Sources

Download ZIM files from the Kiwix Library and place them in the zim_library directory:

# Example: Download and add engineering content
curl -L -o zim_library/engineering.zim "https://download.kiwix.org/zim/libretexts/libretexts.org_en_eng_2025-01.zim"

# Or manually copy files
cp ~/Downloads/*.zim ./zim_library/

3. Build Your Vector Database

Activate the virtual environment and build your knowledge base:

# Activate the virtual environment
source zim_rag_env/bin/activate

# Build the knowledge base
python zim_rag.py build

This process:

• Extracts articles from ZIM files
• Cleans and chunks the text content
• Creates embeddings using sentence-transformers
• Stores everything in a vector database for fast retrieval

Note: First-time setup can take several hours for large ZIM files, but subsequent queries are nearly instantaneous.

4. Start Querying

You’re now ready to query your offline knowledge base:

# Simple semantic search
python zim_rag.py query "What is an engineer?"

# Full RAG with AI-generated answers
python zim_rag.py rag-query "Explain Amplitude Quantization"

# Get system information
python zim_rag.py info

Real-World Use Cases

• Emergency Preparedness: Imagine a scenario where internet services are down during a crisis. With zim-llm, you can still access medical emergency procedures, water purification techniques, first aid instructions, and disaster response protocols.

• Field Research and Exploration: Researchers in remote locations can carry comprehensive knowledge bases covering their field of study without relying on satellite internet.

• Education in Low-Connectivity Areas: Students and educators in areas with poor internet can access extensive educational content through local, searchable knowledge bases.

• Digital Nomads and Off-Grid Living: Maintain access to reference materials, documentation, and learning resources without monthly data limits or connectivity concerns.

By combining the vast knowledge of projects like Wikipedia with modern AI techniques, we can create tools that work reliably even when disconnected from the cloud.

Whether you’re preparing for emergencies, conducting field research, or simply value your digital privacy, having an offline knowledge base powered by local AI gives you the freedom to learn and discover without boundaries.