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import os | |
# NOTE: Configure models in `models.py` | |
######################### | |
# General Configuration # | |
######################### | |
DB_NAME = "database.db" | |
TOXICITY_CHECK = False | |
MAX_SAMPLE_TXT_LENGTH = 300 # Maximum text length (characters) | |
MIN_SAMPLE_TXT_LENGTH = 10 # Minimum text length (characters) | |
DB_PATH = f"/data/{DB_NAME}" if os.path.isdir("/data") else DB_NAME # If /data available => means local storage is enabled => let's use it! | |
ROUTER_ID = "TTS-AGI/tts-router" # You should use a router space to route TTS models to avoid exposing your API keys! | |
SYNC_DB = True # Sync DB to HF dataset? | |
DB_DATASET_ID = os.getenv('DATASET_ID') # HF dataset ID, can be None if not syncing | |
SPACE_ID = os.getenv('SPACE_ID') # Don't change this! It detects if we're running in a HF Space | |
with open(os.path.dirname(__file__) + '/../harvard_sentences.txt', 'r') as f: | |
sents = f.read().strip().splitlines() | |
###################### | |
# TTS Arena Settings # | |
###################### | |
CITATION_TEXT = """@misc{tts-arena, | |
title = {Text to Speech Arena}, | |
author = {mrfakename and Srivastav, Vaibhav and Fourrier, Clémentine and Pouget, Lucain and Lacombe, Yoach and main and Gandhi, Sanchit}, | |
year = 2024, | |
publisher = {Hugging Face}, | |
howpublished = "\\url{https://huggingface.co/spaces/TTS-AGI/TTS-Arena}" | |
}""" |