Analysis updated 2026-05-18
Automatically rename and color code exported stem tracks after importing them into Reaper
Identify which instrument or vocal type each imported track contains without listening manually
Use a local AI model or Google Gemini's cloud analysis to classify audio content
Speed up project organization when working with dozens of tracks from FL Studio or Ableton exports
| pontojasko/ainomeator | 0xustaz/streamgate | a-bissell/unleash-lite | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | hard | hard |
| Complexity | 2/5 | 4/5 | 4/5 |
| Audience | general | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires Python 3.9+ and Reaper, a Gemini API key and the SWS Extension are optional add-ons.
AiNOMEATOR is a tool for the audio recording software Reaper that uses AI to automatically identify, rename, and color code your audio tracks. It is aimed at music producers who export separate stems, individual instrument or vocal tracks, from programs like FL Studio or Ableton into Reaper, and then have to spend time manually figuring out what each messy or generically named track actually contains before organizing it. The tool works as a script that runs inside Reaper. Once installed, it listens to the audio content of your tracks and applies names, colors, and icons automatically based on what it detects, such as which instrument or vocal type is present. The project's README describes it as experimental, noting that the AI models it relies on can still make mistakes, and it invites feedback and contributions to improve the detection process. To set it up, you need Python 3.9 or newer installed on your computer. A Google Gemini API key is optional, needed only if you want to use Gemini's cloud based analysis instead of, or alongside, the tool's local analysis. An extension called SWS is also optional and used for synchronizing track colors. Installation involves downloading the repository, adding its script file to Reaper's list of actions, and running a setup file that prepares the local environment. Once running inside Reaper, the interface has a main button to start the naming process, a toggle to switch the interface language between English and Portuguese, and an advanced options panel. In that panel you can choose which analysis method to use: a local model called PANNs as a starting option, Gemini's cloud analysis, or a combination of both, and you can adjust how many local processing threads run at once to control speed. The README notes that using Gemini can sometimes return temporary rate limit errors if too many requests are sent at once, which can be reduced by lowering the thread count. This project is released under the GNU General Public License version 3, which requires that any modified versions you distribute are also released under the same license with their source code available.
An AI powered tool for the Reaper audio software that automatically renames, colors, and organizes messy exported audio stems and tracks.
Mainly Python. The stack also includes Python, Reaper, Gemini API.
You can use and modify this code, but if you distribute a modified version you must also release its source code under the same license.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.