#!/usr/bin/env python3 from pathlib import Path from typing import Tuple import re # import sox # from mutagen import MutagenError # from mutagen.mp3 import MP3, HeaderNotFoundError import translators as ts from rich.progress import track from moviepy.editor import AudioFileClip, CompositeAudioClip, concatenate_audioclips from utils.console import print_step, print_substep from utils.voice import sanitize_text from utils import settings DEFAULT_MAX_LENGTH: int = 50 # video length variable class TTSEngine: """Calls the given TTS engine to reduce code duplication and allow multiple TTS engines. Args: tts_module : The TTS module. Your module should handle the TTS itself and saving to the given path under the run method. reddit_object : The reddit object that contains the posts to read. path (Optional) : The unix style path to save the mp3 files to. This must not have leading or trailing slashes. max_length (Optional) : The maximum length of the mp3 files in total. Notes: tts_module must take the arguments text and filepath. """ def __init__( self, tts_module, reddit_object: dict, path: str = "assets/temp/mp3", max_length: int = DEFAULT_MAX_LENGTH, last_clip_length: int = 0, ): self.tts_module = tts_module() self.reddit_object = reddit_object self.path = path self.max_length = max_length self.length = 0 self.last_clip_length = last_clip_length def run(self) -> Tuple[int, int]: Path(self.path).mkdir(parents=True, exist_ok=True) # This file needs to be removed in case this post does not use post text, so that it won't appear in the final video try: Path(f"{self.path}/posttext.mp3").unlink() except OSError: pass print_step("Saving Text to MP3 files...") self.call_tts("title", process_text(self.reddit_object["thread_title"])) processed_text = process_text(self.reddit_object["thread_post"]) if ( processed_text != "" and settings.config["settings"]["storymode"] == True ): self.call_tts("posttext", processed_text) idx = None for idx, comment in track( enumerate(self.reddit_object["comments"]), "Saving..." ): # ! Stop creating mp3 files if the length is greater than max length. if self.length > self.max_length: self.length -= self.last_clip_length idx -= 1 break if ( len(comment["comment_body"]) > self.tts_module.max_chars ): # Split the comment if it is too long self.split_post(comment["comment_body"], idx) # Split the comment else: # If the comment is not too long, just call the tts engine self.call_tts(f"{idx}", process_text(comment["comment_body"])) print_substep("Saved Text to MP3 files successfully.", style="bold green") return self.length, idx def split_post(self, text: str, idx: int): split_files = [] split_text = [ x.group().strip() for x in re.finditer( r" *(((.|\n){0," + str(self.tts_module.max_chars) + "})(\.|.$))", text ) ] offset = 0 for idy, text_cut in enumerate(split_text): # print(f"{idx}-{idy}: {text_cut}\n") new_text = process_text(text_cut) if not new_text or new_text.isspace(): offset += 1 continue self.call_tts(f"{idx}-{idy - offset}.part", new_text) split_files.append( AudioFileClip(f"{self.path}/{idx}-{idy - offset}.part.mp3") ) CompositeAudioClip([concatenate_audioclips(split_files)]).write_audiofile( f"{self.path}/{idx}.mp3", fps=44100, verbose=False, logger=None ) for i in split_files: name = i.filename i.close() Path(name).unlink() # for i in range(0, idy + 1): # print(f"Cleaning up {self.path}/{idx}-{i}.part.mp3") # Path(f"{self.path}/{idx}-{i}.part.mp3").unlink() def call_tts(self, filename: str, text: str): self.tts_module.run( text, filepath=f"{self.path}/{filename}.mp3" ) # try: # self.length += MP3(f"{self.path}/{filename}.mp3").info.length # except (MutagenError, HeaderNotFoundError): # self.length += sox.file_info.duration(f"{self.path}/{filename}.mp3") try: clip = AudioFileClip(f"{self.path}/{filename}.mp3") if clip.duration + self.length < self.max_length: self.last_clip_length = clip.duration self.length += clip.duration clip.close() except: self.length = 0 def process_text(text: str): lang = settings.config["reddit"]["thread"]["post_lang"] new_text = sanitize_text(text) if lang: print_substep("Translating Text...") translated_text = ts.google(text, to_language=lang) new_text = sanitize_text(translated_text) return new_text