from pedalboard import Pedalboard, Chorus, Reverb
from pedalboard.io import AudioFile

# Make a Pedalboard object, containing multiple audio plugins:
board = Pedalboard([Chorus(), Reverb(room_size=0.25)])

# Open an audio file for reading, just like a regular file:
with AudioFile('some-file.wav') as f:
  
  # Open an audio file to write to:
  with AudioFile('output.wav', 'w', f.samplerate, f.num_channels) as o:
  
    # Read one second of audio at a time, until the file is empty:
    while f.tell() < f.frames:
      chunk = f.read(f.samplerate)
      
      # Run the audio through our pedalboard:
      effected = board(chunk, f.samplerate, reset=False)
      
      # Write the output to our output file:
      o.write(effected)

# Don't do import *! (It just makes this example smaller)
from pedalboard import *
from pedalboard.io import AudioFile

# Read in a whole file, resampling to our desired sample rate:
samplerate = 44100.0
with AudioFile('guitar-input.wav').resampled_to(samplerate) as f:
  audio = f.read(f.frames)

# Make a pretty interesting sounding guitar pedalboard:
board = Pedalboard([
    Compressor(threshold_db=-50, ratio=25),
    Gain(gain_db=30),
    Chorus(),
    LadderFilter(mode=LadderFilter.Mode.HPF12, cutoff_hz=900),
    Phaser(),
    Convolution("./guitar_amp.wav", 1.0),
    Reverb(room_size=0.25),
])

# Pedalboard objects behave like lists, so you can add plugins:
board.append(Compressor(threshold_db=-25, ratio=10))
board.append(Gain(gain_db=10))
board.append(Limiter())

# ... or change parameters easily:
board[0].threshold_db = -40

# Run the audio through this pedalboard!
effected = board(audio, samplerate)

# Write the audio back as a wav file:
with AudioFile('processed-output.wav', 'w', samplerate, effected.shape[0]) as f:
  f.write(effected)

from pedalboard import Pedalboard, Reverb, load_plugin
from pedalboard.io import AudioFile
from mido import Message # not part of Pedalboard, but convenient!

# Load a VST3 or Audio Unit plugin from a known path on disk:
instrument = load_plugin("./VSTs/Magical8BitPlug2.vst3")
effect = load_plugin("./VSTs/RoughRider3.vst3")

print(effect.parameters.keys())
# dict_keys([
#   'sc_hpf_hz', 'input_lvl_db', 'sensitivity_db',
#   'ratio', 'attack_ms', 'release_ms', 'makeup_db',
#   'mix', 'output_lvl_db', 'sc_active',
#   'full_bandwidth', 'bypass', 'program',
# ])

# Set the "ratio" parameter to 15
effect.ratio = 15

# Render some audio by passing MIDI to an instrument:
sample_rate = 44100
audio = instrument(
  [Message("note_on", note=60), Message("note_off", note=60, time=5)],
  duration=5, # seconds
  sample_rate=sample_rate,
)

# Apply effects to this audio:
effected = effect(audio, sample_rate)

# ...or put the effect into a chain with other plugins:
board = Pedalboard([effect, Reverb()])
# ...and run that pedalboard with the same VST instance!
effected = board(audio, sample_rate)

from pedalboard import Pedalboard, Compressor, Delay, Distortion, Gain, PitchShift, Reverb, Mix

passthrough = Gain(gain_db=0)

delay_and_pitch_shift = Pedalboard([
  Delay(delay_seconds=0.25, mix=1.0),
  PitchShift(semitones=7),
  Gain(gain_db=-3),
])

delay_longer_and_more_pitch_shift = Pedalboard([
  Delay(delay_seconds=0.5, mix=1.0),
  PitchShift(semitones=12),
  Gain(gain_db=-6),
])

board = Pedalboard([
  # Put a compressor at the front of the chain:
  Compressor(),
  # Run all of these pedalboards simultaneously with the Mix plugin:
  Mix([
    passthrough,
    delay_and_pitch_shift,
    delay_longer_and_more_pitch_shift,
  ]),
  # Add a reverb on the final mix:
  Reverb()
])

from pedalboard import Pedalboard, Chorus, Compressor, Delay, Gain, Reverb, Phaser
from pedalboard.io import AudioStream

# Open up an audio stream:
with AudioStream(
  input_device_name="Apogee Jam+",  # Guitar interface
  output_device_name="MacBook Pro Speakers"
) as stream:
  # Audio is now streaming through this pedalboard and out of your speakers!
  stream.plugins = Pedalboard([
      Compressor(threshold_db=-50, ratio=25),
      Gain(gain_db=30),
      Chorus(),
      Phaser(),
      Convolution("./guitar_amp.wav", 1.0),
      Reverb(room_size=0.25),
  ])
  input("Press enter to stop streaming...")

# The live AudioStream is now closed, and audio has stopped.

import tensorflow as tf 

sr = 48000 

# Put whatever plugins you like in here:
plugins = pedalboard.Pedalboard([pedalboard.Gain(), pedalboard.Reverb()]) 

# Make a dataset containing random noise:
# NOTE: for real training, here's where you'd want to load your audio somehow:
ds = tf.data.Dataset.from_tensor_slices([np.random.rand(sr)])

# Apply our Pedalboard instance to the tf.data Pipeline:
ds = ds.map(lambda audio: tf.numpy_function(plugins.process, [audio, sr], tf.float32)) 

# Create and train a (dummy) ML model on this audio:
model = tf.keras.models.Sequential([tf.keras.layers.InputLayer(input_shape=(sr,)), tf.keras.layers.Dense(1)])
model.compile(loss="mse") 
model.fit(ds.map(lambda effected: (effected, 1)).batch(1), epochs=10)