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| # Copyright © [2024] 程序那些事 | |
| # | |
| # All rights reserved. This software and associated documentation files (the "Software") are provided for personal and educational use only. Commercial use of the Software is strictly prohibited unless explicit permission is obtained from the author. | |
| # | |
| # Permission is hereby granted to any person to use, copy, and modify the Software for non-commercial purposes, provided that the following conditions are met: | |
| # | |
| # 1. The original copyright notice and this permission notice must be included in all copies or substantial portions of the Software. | |
| # 2. Modifications, if any, must retain the original copyright information and must not imply that the modified version is an official version of the Software. | |
| # 3. Any distribution of the Software or its modifications must retain the original copyright notice and include this permission notice. | |
| # | |
| # For commercial use, including but not limited to selling, distributing, or using the Software as part of any commercial product or service, you must obtain explicit authorization from the author. | |
| # | |
| # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHOR OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | |
| # | |
| # Author: 程序那些事 | |
| # email: flydean@163.com | |
| # Website: [www.flydean.com](http://www.flydean.com) | |
| # GitHub: [https://github.com/ddean2009/MoneyPrinterPlus](https://github.com/ddean2009/MoneyPrinterPlus) | |
| # | |
| # All rights reserved. | |
| # | |
| # | |
| import datetime | |
| import lzma | |
| import os | |
| import zipfile | |
| from io import BytesIO | |
| import numpy as np | |
| import requests | |
| import torch | |
| from pydub import AudioSegment | |
| from pydub.playback import play | |
| from config.config import my_config | |
| from tools.file_utils import read_file, convert_mp3_to_wav | |
| from tools.utils import must_have_value, random_with_system_time | |
| import streamlit as st | |
| import pybase16384 as b14 | |
| # 获取当前脚本的绝对路径 | |
| script_path = os.path.abspath(__file__) | |
| # print("当前脚本的绝对路径是:", script_path) | |
| # 脚本所在的目录 | |
| script_dir = os.path.dirname(script_path) | |
| # 音频输出目录 | |
| audio_output_dir = os.path.join(script_dir, "../../work") | |
| audio_output_dir = os.path.abspath(audio_output_dir) | |
| def encode_spk_emb(spk_emb: torch.Tensor) -> str: | |
| arr: np.ndarray = spk_emb.to(dtype=torch.float16, device="cpu").detach().numpy() | |
| s = b14.encode_to_string( | |
| lzma.compress( | |
| arr.tobytes(), | |
| format=lzma.FORMAT_RAW, | |
| filters=[{"id": lzma.FILTER_LZMA2, "preset": 9 | lzma.PRESET_EXTREME}], | |
| ), | |
| ) | |
| del arr | |
| return s | |
| class ChatTTSAudioService: | |
| def __init__(self): | |
| super().__init__() | |
| self.service_location = my_config['audio']['local_tts']['chatTTS']['server_location'] | |
| must_have_value(self.service_location, "请设置ChatTTS server location") | |
| self.service_location = self.service_location + '/generate_voice' | |
| if st.session_state.get('refine_text'): | |
| self.skip_refine_text = False | |
| else: | |
| self.skip_refine_text = True | |
| if st.session_state.get('refine_text_prompt'): | |
| self.refine_text_prompt = st.session_state.get('refine_text_prompt') | |
| else: | |
| self.refine_text_prompt = "" | |
| self.text_seed = st.session_state.get('text_seed') | |
| self.audio_temperature = st.session_state.get('audio_temperature') | |
| self.audio_top_p = st.session_state.get('audio_top_p') | |
| self.audio_top_k = st.session_state.get('audio_top_k') | |
| if st.session_state.get('use_random_voice'): | |
| self.audio_seed = st.session_state.get('audio_seed') | |
| else: | |
| self.audio_seed = None | |
| if os.path.exists(st.session_state.get('audio_voice')): | |
| if st.session_state.get('audio_voice').endswith('.pt'): | |
| self.audio_content = encode_spk_emb(torch.load(st.session_state.get('audio_voice'), map_location=torch.device('cpu'))) | |
| if st.session_state.get('audio_voice').endswith('.txt'): | |
| self.audio_content = read_file(st.session_state.get('audio_voice')) | |
| audio_speed = st.session_state.get("audio_speed") | |
| if audio_speed == "normal": | |
| self.audio_speed = "[speed_5]" | |
| if audio_speed == "fast": | |
| self.audio_speed = "[speed_6]" | |
| if audio_speed == "slow": | |
| self.audio_speed = "[speed_4]" | |
| if audio_speed == "faster": | |
| self.audio_speed = "[speed_7]" | |
| if audio_speed == "slower": | |
| self.audio_speed = "[speed_3]" | |
| if audio_speed == "fastest": | |
| self.audio_speed = "[speed_8]" | |
| if audio_speed == "slowest": | |
| self.audio_speed = "[speed_2]" | |
| self.chats_url = f"{self.service_location}/generate_voice" | |
| def read_with_content(self, content): | |
| wav_file = os.path.join(audio_output_dir, str(random_with_system_time()) + ".wav") | |
| temp_file = self.chat_with_content(content, wav_file) | |
| # 读取音频文件 | |
| audio = AudioSegment.from_file(temp_file) | |
| play(audio) | |
| def chat_with_content(self, content, audio_output_file): | |
| # main infer params | |
| body = { | |
| "text": [content], | |
| "stream": False, | |
| "lang": None, | |
| "skip_refine_text": self.skip_refine_text, | |
| "refine_text_only": False, | |
| "use_decoder": True, | |
| "audio_seed": int(self.audio_seed) if self.audio_seed else 0, | |
| "text_seed": int(self.text_seed), | |
| "do_text_normalization": True, | |
| "do_homophone_replacement": False, | |
| } | |
| # refine text params | |
| params_refine_text = { | |
| "prompt": self.refine_text_prompt, | |
| "top_P": float(self.audio_top_p), | |
| "top_K": int(self.audio_top_k), | |
| "temperature": float(self.audio_temperature), | |
| "repetition_penalty": 1, | |
| "max_new_token": 384, | |
| "min_new_token": 0, | |
| "show_tqdm": True, | |
| "ensure_non_empty": True, | |
| "stream_batch": 24, | |
| } | |
| body["params_refine_text"] = params_refine_text | |
| # infer code params | |
| params_infer_code = { | |
| "prompt": self.audio_speed, | |
| "top_P": float(self.audio_top_p), | |
| "top_K": int(self.audio_top_k), | |
| "temperature": float(self.audio_temperature), | |
| "repetition_penalty": 1.05, | |
| "max_new_token": 2048, | |
| "min_new_token": 0, | |
| "show_tqdm": True, | |
| "ensure_non_empty": True, | |
| "stream_batch": True, | |
| "spk_emb": self.audio_content if not self.audio_seed else None, | |
| } | |
| body["params_infer_code"] = params_infer_code | |
| print(body) | |
| try: | |
| response = requests.post(self.service_location, json=body) | |
| response.raise_for_status() | |
| with zipfile.ZipFile(BytesIO(response.content), "r") as zip_ref: | |
| zip_ref.extractall(audio_output_dir) | |
| file_names = zip_ref.namelist() | |
| output_file = os.path.join(audio_output_dir, file_names[0]) | |
| convert_mp3_to_wav(output_file, audio_output_file) | |
| print("Extracted files into", audio_output_file) | |
| return audio_output_file | |
| except requests.exceptions.RequestException as e: | |
| print(f"Request Error: {e}") | |