259 lines
8.7 KiB
Python
259 lines
8.7 KiB
Python
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#!flask/bin/python
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import argparse
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import io
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import json
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import os
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import sys
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from pathlib import Path
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from threading import Lock
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from typing import Union
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from urllib.parse import parse_qs
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from flask import Flask, render_template, render_template_string, request, send_file
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from TTS.config import load_config
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from TTS.utils.manage import ModelManager
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from TTS.utils.synthesizer import Synthesizer
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def create_argparser():
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def convert_boolean(x):
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return x.lower() in ["true", "1", "yes"]
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--list_models",
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type=convert_boolean,
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nargs="?",
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const=True,
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default=False,
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help="list available pre-trained tts and vocoder models.",
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)
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parser.add_argument(
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"--model_name",
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type=str,
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default="tts_models/en/ljspeech/tacotron2-DDC",
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help="Name of one of the pre-trained tts models in format <language>/<dataset>/<model_name>",
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)
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parser.add_argument("--vocoder_name", type=str, default=None, help="name of one of the released vocoder models.")
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# Args for running custom models
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parser.add_argument("--config_path", default=None, type=str, help="Path to model config file.")
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parser.add_argument(
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"--model_path",
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type=str,
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default=None,
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help="Path to model file.",
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)
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parser.add_argument(
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"--vocoder_path",
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type=str,
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help="Path to vocoder model file. If it is not defined, model uses GL as vocoder. Please make sure that you installed vocoder library before (WaveRNN).",
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default=None,
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)
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parser.add_argument("--vocoder_config_path", type=str, help="Path to vocoder model config file.", default=None)
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parser.add_argument("--speakers_file_path", type=str, help="JSON file for multi-speaker model.", default=None)
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parser.add_argument("--port", type=int, default=5002, help="port to listen on.")
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parser.add_argument("--use_cuda", type=convert_boolean, default=False, help="true to use CUDA.")
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parser.add_argument("--debug", type=convert_boolean, default=False, help="true to enable Flask debug mode.")
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parser.add_argument("--show_details", type=convert_boolean, default=False, help="Generate model detail page.")
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return parser
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# parse the args
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args = create_argparser().parse_args()
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path = Path(__file__).parent / "../.models.json"
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manager = ModelManager(path)
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if args.list_models:
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manager.list_models()
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sys.exit()
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# update in-use models to the specified released models.
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model_path = None
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config_path = None
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speakers_file_path = None
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vocoder_path = None
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vocoder_config_path = None
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# CASE1: list pre-trained TTS models
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if args.list_models:
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manager.list_models()
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sys.exit()
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# CASE2: load pre-trained model paths
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if args.model_name is not None and not args.model_path:
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model_path, config_path, model_item = manager.download_model(args.model_name)
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args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
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if args.vocoder_name is not None and not args.vocoder_path:
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vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name)
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# CASE3: set custom model paths
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if args.model_path is not None:
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model_path = args.model_path
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config_path = args.config_path
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speakers_file_path = args.speakers_file_path
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if args.vocoder_path is not None:
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vocoder_path = args.vocoder_path
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vocoder_config_path = args.vocoder_config_path
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# load models
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synthesizer = Synthesizer(
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tts_checkpoint=model_path,
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tts_config_path=config_path,
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tts_speakers_file=speakers_file_path,
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tts_languages_file=None,
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vocoder_checkpoint=vocoder_path,
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vocoder_config=vocoder_config_path,
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encoder_checkpoint="",
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encoder_config="",
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use_cuda=args.use_cuda,
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)
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use_multi_speaker = hasattr(synthesizer.tts_model, "num_speakers") and (
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synthesizer.tts_model.num_speakers > 1 or synthesizer.tts_speakers_file is not None
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)
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speaker_manager = getattr(synthesizer.tts_model, "speaker_manager", None)
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use_multi_language = hasattr(synthesizer.tts_model, "num_languages") and (
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synthesizer.tts_model.num_languages > 1 or synthesizer.tts_languages_file is not None
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)
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language_manager = getattr(synthesizer.tts_model, "language_manager", None)
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# TODO: set this from SpeakerManager
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use_gst = synthesizer.tts_config.get("use_gst", False)
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app = Flask(__name__)
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def style_wav_uri_to_dict(style_wav: str) -> Union[str, dict]:
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"""Transform an uri style_wav, in either a string (path to wav file to be use for style transfer)
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or a dict (gst tokens/values to be use for styling)
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Args:
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style_wav (str): uri
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Returns:
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Union[str, dict]: path to file (str) or gst style (dict)
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"""
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if style_wav:
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if os.path.isfile(style_wav) and style_wav.endswith(".wav"):
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return style_wav # style_wav is a .wav file located on the server
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style_wav = json.loads(style_wav)
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return style_wav # style_wav is a gst dictionary with {token1_id : token1_weigth, ...}
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return None
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@app.route("/")
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def index():
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return render_template(
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"index.html",
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show_details=args.show_details,
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use_multi_speaker=use_multi_speaker,
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use_multi_language=use_multi_language,
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speaker_ids=speaker_manager.name_to_id if speaker_manager is not None else None,
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language_ids=language_manager.name_to_id if language_manager is not None else None,
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use_gst=use_gst,
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)
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@app.route("/details")
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def details():
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if args.config_path is not None and os.path.isfile(args.config_path):
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model_config = load_config(args.config_path)
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else:
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if args.model_name is not None:
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model_config = load_config(config_path)
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if args.vocoder_config_path is not None and os.path.isfile(args.vocoder_config_path):
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vocoder_config = load_config(args.vocoder_config_path)
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else:
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if args.vocoder_name is not None:
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vocoder_config = load_config(vocoder_config_path)
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else:
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vocoder_config = None
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return render_template(
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"details.html",
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show_details=args.show_details,
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model_config=model_config,
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vocoder_config=vocoder_config,
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args=args.__dict__,
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)
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lock = Lock()
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@app.route("/api/tts", methods=["GET", "POST"])
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def tts():
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with lock:
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text = request.headers.get("text") or request.values.get("text", "")
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speaker_idx = request.headers.get("speaker-id") or request.values.get("speaker_id", "")
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language_idx = request.headers.get("language-id") or request.values.get("language_id", "")
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style_wav = request.headers.get("style-wav") or request.values.get("style_wav", "")
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style_wav = style_wav_uri_to_dict(style_wav)
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print(f" > Model input: {text}")
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print(f" > Speaker Idx: {speaker_idx}")
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print(f" > Language Idx: {language_idx}")
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wavs = synthesizer.tts(text, speaker_name=speaker_idx, language_name=language_idx, style_wav=style_wav)
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out = io.BytesIO()
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synthesizer.save_wav(wavs, out)
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return send_file(out, mimetype="audio/wav")
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# Basic MaryTTS compatibility layer
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@app.route("/locales", methods=["GET"])
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def mary_tts_api_locales():
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"""MaryTTS-compatible /locales endpoint"""
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# NOTE: We currently assume there is only one model active at the same time
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if args.model_name is not None:
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model_details = args.model_name.split("/")
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else:
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model_details = ["", "en", "", "default"]
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return render_template_string("{{ locale }}\n", locale=model_details[1])
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@app.route("/voices", methods=["GET"])
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def mary_tts_api_voices():
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"""MaryTTS-compatible /voices endpoint"""
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# NOTE: We currently assume there is only one model active at the same time
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if args.model_name is not None:
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model_details = args.model_name.split("/")
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else:
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model_details = ["", "en", "", "default"]
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return render_template_string(
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"{{ name }} {{ locale }} {{ gender }}\n", name=model_details[3], locale=model_details[1], gender="u"
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)
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@app.route("/process", methods=["GET", "POST"])
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def mary_tts_api_process():
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"""MaryTTS-compatible /process endpoint"""
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with lock:
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if request.method == "POST":
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data = parse_qs(request.get_data(as_text=True))
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# NOTE: we ignore param. LOCALE and VOICE for now since we have only one active model
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text = data.get("INPUT_TEXT", [""])[0]
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else:
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text = request.args.get("INPUT_TEXT", "")
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print(f" > Model input: {text}")
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wavs = synthesizer.tts(text)
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out = io.BytesIO()
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synthesizer.save_wav(wavs, out)
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return send_file(out, mimetype="audio/wav")
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def main():
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app.run(debug=args.debug, host="::", port=args.port)
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if __name__ == "__main__":
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main()
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