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.

Endpoint	Method	Rate Limit	Reason
/	GET	30/minute	Health checks, status monitoring
/api/model-info	GET	20/minute	Information endpoint, moderate usage
/api/detect-beats	POST	2/minute	Heavy processing, resource intensive
/api/recognize-chords*	POST	2/minute	Heavy processing, ML inference
/api/lrclib-lyrics	POST	10/minute	Synchronized lyrics with timestamps
/api/genius-lyrics	POST	10/minute	Genius.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

Beat-Transformer

Default

Deep learning model for beat tracking with downbeat detection. Provides high accuracy for modern music genres.

Best for: Pop, Rock, Electronic music

Madmom

Classical beat tracking algorithm with neural network components. Reliable for complex rhythmic patterns.

Best for: Jazz, Classical, Complex rhythms

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-full-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

const formData = new FormData();
formData.append('file', audioFile);
formData.append('model', 'chord-cnn-lstm');

const response = await fetch(
  'https://chordmini-backend-full-191567167632.us-central1.run.app/api/recognize-chords',
  {
    method: 'POST',
    body: formData
  }
);

const result = await response.json();
console.log(result);

Beat Detection with cURL

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

Chord Recognition with cURL

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curl -X POST "https://chordmini-backend-full-191567167632.us-central1.run.app/api/recognize-chords" \
  -F "file=@your-audio-file.mp3" \
  -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