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print("importing runpod")
import runpod
print("importing requests")
import requests
print("importing generate_wav")
from voice_generation import generate_wav
print("importing boto3")
import boto3
print("importing os")
import os
print("importing uuid")
import uuid
print("importing pydub")
from pydub import AudioSegment
import time
import subprocess
print("setting up environment variables")
AWS_ACCESS_KEY_ID = os.environ.get('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.environ.get('AWS_SECRET_ACCESS_KEY')
models = {
'kanye': 'weights/kanye.pth',
'rose-bp': 'weights/rose-bp.pth',
'jungkook': 'weights/jungkook.pth',
'iu': 'weights/iu.pth',
'drake': 'weights/drake.pth',
'ariana-grande': 'weights/ariana-grande.pth'
}
print('run handler')
def split_audio():
subprocess.call(["deezer-spleeter-env/bin/python", "/deezer-split.py"])
def combine_audio(voice_path, instrumental_path):
audio1 = AudioSegment.from_file(instrumental_path, format="mp3")
audio2 = AudioSegment.from_file(voice_path, format="mp3")
length = max(len(audio1), len(audio2))
audio1 = audio1 + AudioSegment.silent(duration=length - len(audio1))
audio2 = audio2 + AudioSegment.silent(duration=length - len(audio2))
combined = audio1.overlay(audio2)
combined.export("combined.mp3", format="mp3")
def upload_file_to_s3(local_file_path, s3_file_path):
bucket_name = 'voice-gen-audios'
s3 = boto3.client('s3', aws_access_key_id=AWS_ACCESS_KEY_ID, aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
try:
s3.upload_file(local_file_path, bucket_name, s3_file_path)
return {"url": f"https://{bucket_name}.s3.eu-north-1.amazonaws.com/{s3_file_path}"}
except boto3.exceptions.S3UploadFailedError as e:
return {"error": f"failed to upload file {local_file_path} to s3 as {s3_file_path}"}
def clean_up_files(remove_voice_model=False):
files = [
"song.mp3",
"accompaniment.mp3",
"vocals.mp3",
"output_vocal.wav",
"combined.mp3",
]
if remove_voice_model:
files.append("voice_model.pth")
for file in files:
try:
os.remove(file)
except FileNotFoundError:
return {"error": f"failed to remove file {file}"}
return {"success": "files removed successfully"}
def get_voice_model(event):
voice_model_id = event["input"].get("voice_model_id", "")
voice_model_url = event["input"].get("voice_model_url", "")
if not voice_model_url and not voice_model_id:
return {"error": "voice_model_url or voice_model_id is required"}
if voice_model_id and voice_model_id not in models:
return {"error": "model not found in pre-loaded models"}
if voice_model_id:
return {"model_path": models[voice_model_id]}
print("downloading voice_model")
voice_model_response = requests.get(voice_model_url)
if voice_model_response.status_code != 200:
return {"error": f"failed to download voice_model, error: {voice_model_response.text}"}
with open("voice_model.pth", "wb") as f:
f.write(voice_model_response.content)
return {"model_path": "voice_model.pth"}
def handler(event):
print(event)
file_id = str(uuid.uuid4())
user_id = event["input"].get("user_id", "not provided")
if not AWS_ACCESS_KEY_ID or not AWS_SECRET_ACCESS_KEY:
return {"error": "AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are missing from environment variables"}
voice_model = get_voice_model(event)
if "error" in voice_model:
return voice_model.get("error")
song_url = event["input"].get("song_url", "")
if song_url == "":
return {"error": "voice_url is required"}
song_file = requests.get(song_url)
if song_file.status_code != 200:
return {"error": "failed to download song_file"}
with open("song.mp3", "wb") as f:
f.write(song_file.content)
splitting_start = time.time() # remove after testing
split_audio()
splitting_end = time.time() # remove after testing
time_taken_splitting = splitting_end - splitting_start # remove after testing
print(f"splitting took {time_taken_splitting} seconds") # remove after testing
if not os.path.exists("accompaniment.mp3") or not os.path.exists("vocals.mp3"):
return {"error": "failed to split song"}
song_instruments = upload_file_to_s3("accompaniment.mp3", f"{file_id}-split-accompaniment.mp3")
song_vocals = upload_file_to_s3("vocals.mp3", f"{file_id}-split-vocals.mp3")
if "error" in song_instruments:
return song_instruments.get("error")
if "error" in song_vocals:
return song_vocals.get("error")
gemeration_start = time.time() # remove after testing
generation = generate_wav(
audio_file='vocals.mp3',
method='pm',
index_rate=0.6,
output_file='output_vocal.wav',
model_path=voice_model.get("model_path")
)
generation_end = time.time() # remove after testing
time_taken_generation = generation_end - gemeration_start # remove after testing
print(f"generation took {time_taken_generation} seconds") # remove after testing
if "error" in generation:
return generation.get("error")
combine_audio("output_vocal.wav", "accompaniment.mp3")
if not os.path.exists("combined.mp3"):
return {"error": "failed to combine audio"}
combined = upload_file_to_s3("combined.mp3", f"{file_id}.mp3")
output_voice = upload_file_to_s3("output_vocal.wav", f"{file_id}-generated-voical.mp3")
if combined_error := combined.get("error"):
return combined_error
if output_voice_error := output_voice.get("error"):
return output_voice_error
combined_url = combined.get("url")
output_voice_url = output_voice.get("url")
need_to_remove_voice_model = False
if voice_model.get("model_path") == "voice_model.pth":
need_to_remove_voice_model = True
cleanup_result = clean_up_files(need_to_remove_voice_model)
if cleanup_error := cleanup_result.get("error"):
return cleanup_error
return {
"combined_url": combined_url,
"output_voice_url": output_voice_url,
"user_id": user_id,
"time_taken_splitting": time_taken_splitting, # remove after testing
"time_taken_generation": time_taken_generation, # remove after testing
}
runpod.serverless.start({"handler": handler})
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