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