import json import os import ffmpegio from nostr_sdk import Kind from nostr_dvm.utils.mediasource_utils import organize_input_media_data from nostr_dvm.utils.nip88_utils import NIP88Config os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" from pathlib import Path import urllib.request from nostr_dvm.interfaces.dvmtaskinterface import DVMTaskInterface, process_venv from nostr_dvm.utils.admin_utils import AdminConfig from nostr_dvm.utils.definitions import EventDefinitions from nostr_dvm.utils.dvmconfig import DVMConfig, build_default_config from nostr_dvm.utils.nip89_utils import NIP89Config, check_and_set_d_tag from nostr_dvm.utils.output_utils import upload_media_to_hoster from nostr_dvm.utils.nostr_utils import get_event_by_id, get_referenced_event_by_id """ This File contains a Module to generate Audio based on an input and a voice Accepted Inputs: Text Outputs: Generated Audiofile """ class TextToSpeech(DVMTaskInterface): KIND: Kind = EventDefinitions.KIND_NIP90_TEXT_TO_SPEECH TASK: str = "text-to-speech" FIX_COST: float = 50 PER_UNIT_COST = 0.5 dependencies = [("nostr-dvm", "nostr-dvm"), ("TTS", "TTS==0.22.0")] async def init_dvm(self, name, dvm_config: DVMConfig, nip89config: NIP89Config, nip88config: NIP88Config = None, admin_config: AdminConfig = None, options=None): dvm_config.SCRIPT = os.path.abspath(__file__) self.dvm_config = dvm_config async def is_input_supported(self, tags, client=None, dvm_config=None): for tag in tags: if tag.as_vec()[0] == 'i': input_value = tag.as_vec()[1] input_type = tag.as_vec()[2] if input_type != "event" and input_type != "job" and input_type != "text": return False #if input_type == "text" and len(input_value) > 250: # return False if input_type == "event": evt = await get_event_by_id(tag.as_vec()[1], client=client, config=dvm_config) #if len(evt.content()) > 250: # return False elif tag.as_vec()[0] == 'param': param = tag.as_vec()[1] if param == "language": # check for param type if tag.as_vec()[2] != "en": # todo add other available languages return False return True async def create_request_from_nostr_event(self, event, client=None, dvm_config=None): request_form = {"jobID": event.id().to_hex() + "_" + self.NAME.replace(" ", "")} prompt = "test" if self.options.get("input_file") and self.options.get("input_file") != "": input_file = self.options['input_file'] else: input_file = "cache/input.wav" language = "en" for tag in event.tags(): if tag.as_vec()[0] == 'i': input_type = tag.as_vec()[2] if input_type == "event": evt = await get_event_by_id(tag.as_vec()[1], client=client, config=dvm_config) if evt is not None: prompt = evt.content() else: raise FileNotFoundError("Couldn't find event") elif input_type == "text": prompt = tag.as_vec()[1] elif input_type == "job": evt = await get_referenced_event_by_id(event_id=tag.as_vec()[1], client=client, kinds=[EventDefinitions.KIND_NIP90_RESULT_EXTRACT_TEXT, EventDefinitions.KIND_NIP90_RESULT_SUMMARIZE_TEXT, EventDefinitions.KIND_NIP90_RESULT_TRANSLATE_TEXT], dvm_config=dvm_config) prompt = evt.content() if input_type == "url": input_file = tag.as_vec()[1] elif tag.as_vec()[0] == 'param': param = tag.as_vec()[1] if param == "language": # check for param type language = tag.as_vec()[2] elif param == "voice": # check for param type input_file = "cache/" + tag.as_vec()[2] + ".wav" if not Path.exists(Path(input_file)): input_file_url = "https://media.nostr.build/av/de104e3260be636533a56fd4468b905c1eb22b226143a997aa936b011122af8a.wav" urllib.request.urlretrieve(input_file_url, "cache/input.wav") input_file = "cache/input.wav" options = { "prompt": prompt, "input_wav": input_file, "language": language } request_form['options'] = json.dumps(options) return request_form async def process(self, request_form): import torch from TTS.api import TTS import re options = self.set_options(request_form) device = "cuda" if torch.cuda.is_available() else "cpu" #else "mps" if torch.backends.mps.is_available() print(device) print(TTS().list_models().list_tts_models()) try: # model = "tts_models/deu/fairseq/vits" # model = "tts_models/multilingual/multi-dataset/your_tts" model = "tts_models/multilingual/multi-dataset/xtts_v2" tts = TTS(model).to(device) text = (options["prompt"].replace("~", "around ").replace("#", "hashtag") .replace(" LFG", " Let's fucking go").replace("_", " ").replace("*", " ") .replace("![]", " ").replace("( )", "").replace("**", " ").replace("\xa0", "") ) text_clean = re.sub( r'''(?i)\b((?:https?://|www\d{0,3}[.]|[a-z0-9.\-]+[.][a-z]{2,4}/)(?:[^\s()<>]+|\(([^\s()<>]+|(\([^\s()<>]+\)))*\))+(?:\(([^\s()<>]+|(\([^\s()<>]+\)))*\)|[^\s`!()\[\]{};:'".,<>?«»“”‘’]))''', " ", text) tts.tts_to_file( text=text_clean, speaker_wav=options["input_wav"], language=options["language"], file_path="outputs/output.wav") try: print("Converting Audio") final_filename = "outputs/output.mp3" fs, x = ffmpegio.audio.read("outputs/output.wav", sample_fmt='dbl', ac=1) ffmpegio.audio.write(final_filename, fs, x, overwrite=True) except: final_filename = "outputs/output.wav" result = await upload_media_to_hoster(final_filename, key_hex=self.dvm_config.PRIVATE_KEY) print(result) return result except Exception as e: print("Error in Module: " + str(e)) raise Exception(e) # We build an example here that we can call by either calling this file directly from the main directory, # or by adding it to our playground. You can call the example and adjust it to your needs or redefine it in the # playground or elsewhere def build_example(name, identifier, admin_config): dvm_config = build_default_config(identifier) admin_config.LUD16 = dvm_config.LN_ADDRESS # use an alternative local wav file you want to use for cloning options = {'input_file': ""} nip89info = { "name": name, "image": "https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg", "about": "I Generate Speech from Text", "encryptionSupported": True, "cashuAccepted": True, "nip90Params": { "language": { "required": False, "values": [] } } } nip89config = NIP89Config() nip89config.DTAG = check_and_set_d_tag(identifier, name, dvm_config.PRIVATE_KEY, nip89info["image"]) nip89config.CONTENT = json.dumps(nip89info) return TextToSpeech(name=name, dvm_config=dvm_config, nip89config=nip89config, admin_config=admin_config, options=options) if __name__ == '__main__': process_venv(TextToSpeech)