ChordMini API Documentation

A comprehensive guide to using our powerful audio analysis API, covering beat detection, chord recognition, and more.

Getting Started

The ChordMini API provides powerful audio analysis capabilities with no authentication required. Start making requests immediately to analyze audio files and extract musical information.

Beat Detection

Identify beat positions and downbeats using advanced ML models.

Chord Recognition

Recognize chord progressions with multiple model options.

Lyrics Fetching

Retrieve synchronized lyrics from LRClib database.

Model Info

Get details about available models and capabilities.

Authentication

No API Key Required

The ChordMini API is currently open and does not require authentication. All endpoints are publicly accessible, making it easy to get started immediately.

Future Changes

Authentication may be required in future versions. Implement proper error handling for potential `401/403` responses.

Rate Limits

The ChordMini API implements production-grade rate limiting to ensure fair usage and system stability. Rate limits vary by endpoint based on computational requirements.

EndpointMethodRate LimitReason
/GET30/minuteHealth checks, status monitoring
/api/model-infoGET20/minuteInformation endpoint, moderate usage
/api/detect-beatsPOST2/minuteHeavy processing, resource intensive
/api/recognize-chords*POST2/minuteHeavy processing, ML inference
/api/lrclib-lyricsPOST10/minuteSynchronized lyrics with timestamps
/api/genius-lyricsPOST10/minuteGenius.com lyrics fetching

Available Models

ChordMini provides multiple machine learning models for different audio analysis tasks. Each model is optimized for specific use cases and performance characteristics.

Beat Detection Models

Madmom

Default

Neural network with high accuracy and speed, best for common time signatures (3/4, 4/4).

Best for: Pop, Rock, Electronic music

Beat-Transformer

DL model with 5-channel audio separation, flexible in time signatures, slow processing speed.

Best for: Complex mixes, layered instrumentation

Chord Recognition Models

Chord-CNN-LSTM

Default

Convolutional and LSTM neural network for chord recognition with 301 chord labels. Excellent balance of accuracy and performance.

Labels: 301 chord types • Best for: General purpose chord recognition

API Endpoints

All endpoints are available at the base URL: https://chordmini-backend-191567167632.us-central1.run.app

POST/api/detect-beats

Analyzes audio file and returns beat timestamps, BPM, and time signature.

  • Parameters: `file` (audio file), `model` (optional: `beat-transformer`, `madmom`, `auto`)
POST/api/recognize-chords

Analyzes audio file and returns chord progression with timestamps.

  • Parameters: `file` (audio file), `model` (optional: `chord-cnn-lstm`)

Usage Examples

Here are some practical examples of how to use the ChordMini API using Javascript and cURL.

Chord Recognition with Javascript

1const formData = new FormData();
2formData.append('file', audioFile);
3formData.append('model', 'chord-cnn-lstm');
4
5const response = await fetch(
6 'https://chordmini-backend-191567167632.us-central1.run.app/api/recognize-chords',
7 {
8 method: 'POST',
9 body: formData
10 }
11);
12
13const result = await response.json();
14console.log(result);

Beat Detection with cURL

1curl -X POST "https://chordmini-backend-191567167632.us-central1.run.app/api/detect-beats" \
2 -F "file=@your-audio-file.mp3" \
3 -F "model=beat-transformer"

Chord Recognition with cURL

1curl -X POST "https://chordmini-backend-191567167632.us-central1.run.app/api/recognize-chords" \
2 -F "file=@your-audio-file.mp3" \
3 -F "model=chord-cnn-lstm"

API Status

Monitor the real-time status of ChordMini API services and endpoints.

Backend Services

Beat DetectionOperational
Chord RecognitionOperational
Lyrics ServicesOperational

Infrastructure

Google Cloud RunOnline
Rate LimitingActive
CORS SupportEnabled

Detailed Status Page

For real-time monitoring and detailed service metrics, visit our dedicated status page.

View Status Page