shaketune-cli-docker

A Docker image that runs Klippain Shaketune locally and exposes a browser-based UI for generating input shaper graphs — no running Klipper printer required.

What it does

Upload your raw accelerometer data (.csv) through the web UI, select a graph type, configure parameters, and get a ShakeTune PNG graph back in the browser.

Powered by:

• Klippain Shaketune for graph generation
• Klipper (cloned at build time, used as a dependency)
• Gradio for the pure-Python web UI

Supported graph types

Graph type	Description
input_shaper	Calibrate input shaper settings
belts	Compare belt tension (CoreXY / CoreXZ)

Generating raw measurement data

Use Klipper's TEST_RESONANCES command with OUTPUT=raw_data to capture raw accelerometer data. The resulting .csv files are what you upload to this tool.

Important: Always add OUTPUT=raw_data. Without it, Klipper writes a processed PSD file (resonances_x_*.csv with a freq,psd_x,... header) that shaketune cannot use as input. SHAPER_CALIBRATE also produces unusable output (calibration_data_*.csv).

Input Shaper

Run one command per axis. Upload one or both files together.

TEST_RESONANCES AXIS=X OUTPUT=raw_data
TEST_RESONANCES AXIS=Y OUTPUT=raw_data

Files are saved to /tmp/ as resonances_x_YYYYMMDD_HHMMSS.csv and resonances_y_YYYYMMDD_HHMMSS.csv.

Belts (CoreXY)

Run both diagonal directions. Upload both files together.

TEST_RESONANCES AXIS=1,-1 OUTPUT=raw_data
TEST_RESONANCES AXIS=-1,1 OUTPUT=raw_data

Files are saved to /tmp/ as resonances_1_-1_YYYYMMDD_HHMMSS.csv and resonances_-1_1_YYYYMMDD_HHMMSS.csv.

Usage with Docker Compose

Run with remote image

docker-compose up -d

Open http://localhost:7860 in your browser.

Stop

docker-compose down

Optional environment variables

Edit docker-compose.yml and modify SHAKETUNE_TIMEOUT:

environment:
  - SHAKETUNE_TIMEOUT=180

Build and run locally

docker-compose up -d --build

Note: The first build takes several minutes because numpy is compiled from source against OpenBLAS on Alpine Linux.

Publishing

The image is built and published automatically via GitHub Actions on every push to main (tagged latest) and on version tags like v1.0.0.

Image registry: ghcr.io/beattune-core/shaketune-cli-docker

License

This repository is MIT licensed. Shaketune and Klipper are subject to their own respective licenses.