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import random
import numpy as np
from elevenlabs import voices, generate, set_api_key, UnauthenticatedRateLimitError, save
import huggingface_hub
from huggingface_hub import Repository
import os
from huggingface_hub import HfApi
import gradio as gr
DATASET_REPO_URL = "https://huggingface.co/datasets/laxsvips/audiofiles"
DATA_FILENAME = "audio.wav"
DATA_FILE = os.path.join("data", DATA_FILENAME)
api = HfApi()
HF_TOKEN = os.environ.get("HF_TOKEN")
repo = Repository(
local_dir="data",
clone_from=DATASET_REPO_URL,
use_auth_token=HF_TOKEN
)
def pad_buffer(audio):
# Pad buffer to multiple of 2 bytes
buffer_size = len(audio)
element_size = np.dtype(np.int16).itemsize
if buffer_size % element_size != 0:
audio = audio + b'\0' * (element_size - (buffer_size % element_size))
return audio
def generate_voice(text):
try:
audio = generate(
text,
voice="Arnold",
model="eleven_monolingual_v1"
)
save(audio,'data/audio.wav')
# save(audio,'audio.wav')
commit_url = repo.push_to_hub()
return_url = "failure"
if commit_url:
return_url = DATASET_REPO_URL+"/"+ DATA_FILENAME
return (return_url)
# return (44100, np.frombuffer(pad_buffer(audio), dtype=np.int16))
except UnauthenticatedRateLimitError as e:
raise gr.Error("Thanks for trying out ElevenLabs TTS! You've reached the free tier limit. Please provide an API key to continue.")
except Exception as e:
raise gr.Error(e) |