stellarlinkco

stellarlinkco / llm-wiki

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A pattern for building personal knowledge bases using LLMs.

14
1
100% credibility
Found Apr 06, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A tool for turning personal documents into a structured, searchable wiki that can be enhanced by large language models.

How It Works

1
💡 Discover LLM Wiki

You learn about a simple way to turn your scattered notes, papers, and files into a growing personal knowledge book that stays organized and searchable.

2
🏠 Set up your wiki

Create a special folder for your knowledge base, give it a name like 'My Research Notes', and add a quick description of what it's for.

3
📄 Add your documents

Drop in your PDFs, Word files, images, or web pages, and the tool neatly converts them into clean, readable notes stored in your wiki.

4
🔍 Build the smart search

With one action, create a full catalog and search system so you can instantly find anything in your growing collection.

5
🧐 Search and explore

Type a question or topic, and get ranked results with helpful snippets from your notes and wiki pages.

6
✅ Check and tidy up

Run a quick review to ensure all links work, pages are complete, and everything is in perfect shape.

🌟 Your living knowledge base

Now your wiki is ready to grow endlessly—pair it with an AI helper to connect ideas, update summaries, and uncover new insights effortlessly.

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Star Growth

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AI-Generated Review

What is llm-wiki?

llm-wiki is a Python CLI tool that scaffolds and manages personal knowledge bases powered by LLMs, turning raw documents like PDFs, DOCX, or images into searchable markdown stores. Inspired by Andrej Karpathy's llm wiki github pattern, it handles parsing via MarkItDown, BM25-powered search (English and Chinese), indexing, validation, and status checks—all outputting JSON for easy LLM integration. You get a structured wiki with raw docs and LLM-synthesized pages for entities, concepts, and summaries, solving the maintenance drudgery of growing knowledge bases.

Why is it gaining traction?

Unlike basic RAG setups or llm wikipedia datasets, this follows a github pattern for persistent, self-compounding wikis—CLI commands like `llm-wiki parse`, `search`, and `validate` feed directly into LLM agents for synthesis without constant human bookkeeping. Multilingual BM25 search with deduping and snippets stands out for small corpora, plus auto-generated catalogs and dead-link checks keep things clean. Devs dig the clean separation: ingest once, let LLMs handle the living fabric pattern github-style evolution.

Who should use this?

AI researchers ingesting papers into llm wiki english or llm wikipedia deutsch repos; devs building internal docs for law teams with llm wiki law; or Claude users automating pattern building blocks from notes. Ideal for solo knowledge workers tired of manual wiki updates, especially with github pattern matching for queries across evolving sources.

Verdict

Try it if you're prototyping llm wiki github flows—strong docs, 162 tests, and MIT license make setup painless despite 14 stars and 1.0% credibility score signaling early maturity. Solid for personal use, but watch for community growth before team adoption.

(198 words)

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