Introduction LibreQoS is an open source project for monitoring and providing quality-of-experience for Internet Service Providers (ISPs) and large networks. It runs as a “middle-box”, monitoring traffic that passes through it. It recently gained the ability to track individual data flows - connections between two endpoints. It’s also my favorite Open Source project, to which I contribute regularly. Public Internet IP addresses belong to an ASN - an Autonomous System Number.

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LibreQoS is an open-source project for monitoring and ensuring quality-of-experience for ISPs by tracking individual data flows. To make the data understandable, ASN (Autonomous System Numbers) needs categorization, which is automated using Rust and large language models (LLMs). The post explains how to obtain ASN data, load and deduplicate it, set up a local LLM, and categorize data using context scraped from associated websites. The process involves using crates like Serde, CSV, Itertools, Reqwest, and Scraper for efficient data handling, and leveraging Tokio for parallel processing to speed up the categorization task.

Categorizing Data with Large Language Models in Rust

Categorizing the Data: First Try - Oneshot!

<p>i’m a simple man</p>
<p>i see rust, i upvote</p>
