> For the complete documentation index, see [llms.txt](https://docs.lufs.space/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lufs.space/introduction.md).

# Introduction

LUFS Analyzer

> Professional audio analysis — instant BPM, Key, Tuning, Loudness detection and stem separation, right in Telegram.

***

### What is LUFS?

**LUFS Analyzer** is a precision audio analysis tool built for music producers, DJs, audio engineers, and anyone working with sound. Send a link or file — get back accurate BPM, musical key, tuning frequency, loudness measurement, and a tagged MP3 — in seconds.

Available as a **Telegram bot** ([@lufs\_loader\_bot](https://t.me/lufs_loader_bot)) and a **REST API** for programmatic access.

#### Why LUFS?

* **Multi-engine analysis** — each metric is detected by multiple independent engines that cross-validate results, giving you confidence scores alongside every value
* **Sub-10-second turnaround** — full analysis (BPM + Key + Hz + Loudness) completes in \~5 seconds on dedicated GPU hardware
* **10-stem separation** — split any track into vocals, instrumental, bass, drums, kick, snare, toms, hi-hats, and cymbals
* **Clean tagged MP3** — every analysis returns an MP3 file with embedded ID3 tags (BPM, Key, Hz) ready for your library or DAW
* **Platform support** — YouTube, SoundCloud, TikTok, Beatstars, Traktrain, or any direct audio URL


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.lufs.space/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.