# RAG-vs-OKF-Open-Knowledge-Formatter-A-Retrieval-Benchmark

> A hands-on comparison of two ways to give a language model access to a knowledge base: classic Retrieval-Augmented Generation (RAG) using embeddings and vector search, versus Google's Open Knowledge Format (OKF), a markdown-based knowledge representation released in mid-2026.

## Details

- **Name:** RAG-vs-OKF-Open-Knowledge-Formatter-A-Retrieval-Benchmark
- **Author:** Thanush-pk
- **Stars:** 0
- **License:** MIT
- **Category:** Uncategorized
- **OKF Conformant:** No
- **OKF Version:** 0.1
- **Last Updated:** 2026-07-14

## Links

- **Source:** https://github.com/Thanush-pk/RAG-vs-OKF-Open-Knowledge-Formatter-A-Retrieval-Benchmark
- **OKF Bundle:** https://github.com/Thanush-pk/RAG-vs-OKF-Open-Knowledge-Formatter-A-Retrieval-Benchmark
- **View on BundleDex:** https://bundledex.net/bundles/rag-vs-okf-open-knowledge-formatter-a-retrieval-benchmark/

## How to Use

```
git clone https://github.com/Thanush-pk/RAG-vs-OKF-Open-Knowledge-Formatter-A-Retrieval-Benchmark
```

Point your AI agent (Claude Code, Cursor, OpenCode, etc.) at the cloned directory.