# NOTE!!NOTE!!!NOTE!!NOTE!!!NOTE!!NOTE!!!NOTE!!NOTE!!!
# THE WORD "CHAPTER" IN THE CODE DOES NOT MEAN
# IT'S THE REAL CHAPTER OF THE EBOOK SINCE NO STANDARDS
# ARE DEFINING A CHAPTER ON .EPUB FORMAT. THE WORD "BLOCK"
# IS USED TO PRINT IT OUT TO THE TERMINAL, AND "CHAPTER" TO THE CODE
# WHICH IS LESS GENERIC FOR THE DEVELOPERS
import argparse, asyncio, csv, fnmatch, hashlib, io, json, math, os, platform, random, shutil, socket, subprocess, sys, tempfile, threading, time, traceback
import unicodedata, urllib.request, uuid, zipfile, ebooklib, gradio as gr, psutil, pymupdf4llm, regex as re, requests, stanza, torch, uvicorn
from soynlp.tokenizer import LTokenizer
from pythainlp.tokenize import word_tokenize
from sudachipy import dictionary, tokenizer
from PIL import Image
from tqdm import tqdm
from bs4 import BeautifulSoup, NavigableString, Tag
from collections import Counter
from collections.abc import Mapping
from collections.abc import MutableMapping
from datetime import datetime
from ebooklib import epub
from glob import glob
from iso639 import languages
from markdown import markdown
from multiprocessing import Pool, cpu_count
from multiprocessing import Manager, Event
from multiprocessing.managers import DictProxy, ListProxy
from num2words import num2words
from pathlib import Path
from pydub import AudioSegment
from pydub.utils import mediainfo
from queue import Queue, Empty
from types import MappingProxyType
from urllib.parse import urlparse
from starlette.requests import ClientDisconnect
from lib import *
from lib.classes.voice_extractor import VoiceExtractor
from lib.classes.tts_manager import TTSManager
#from lib.classes.redirect_console import RedirectConsole
#from lib.classes.argos_translator import ArgosTranslator
context = None
is_gui_process = False
active_sessions = set()
#import logging
#logging.basicConfig(
# level=logging.INFO, # DEBUG for more verbosity
# format="%(asctime)s [%(levelname)s] %(message)s"
#)
class DependencyError(Exception):
def __init__(self, message=None):
super().__init__(message)
print(message)
# Automatically handle the exception when it's raised
self.handle_exception()
def handle_exception(self):
# Print the full traceback of the exception
traceback.print_exc()
# Print the exception message
error = f'Caught DependencyError: {self}'
print(error)
# Exit the script if it's not a web process
if not is_gui_process:
sys.exit(1)
class SessionTracker:
def __init__(self):
self.lock = threading.Lock()
def start_session(self, id):
with self.lock:
session = context.get_session(id)
if session['status'] is None:
session['status'] = 'ready'
return True
return False
def end_session(self, id, socket_hash):
active_sessions.discard(socket_hash)
with self.lock:
session = context.get_session(id)
session['cancellation_requested'] = True
session['tab_id'] = None
session['status'] = None
session[socket_hash] = None
class SessionContext:
def __init__(self):
self.manager = Manager()
self.sessions = self.manager.dict()
self.cancellation_events = {}
def get_session(self, id):
if id not in self.sessions:
self.sessions[id] = recursive_proxy({
"script_mode": NATIVE,
"id": id,
"tab_id": None,
"process_id": None,
"status": None,
"event": None,
"progress": 0,
"cancellation_requested": False,
"device": default_device,
"system": None,
"client": None,
"language": default_language_code,
"language_iso1": None,
"audiobook": None,
"audiobooks_dir": None,
"process_dir": None,
"ebook": None,
"ebook_list": None,
"ebook_mode": "single",
"chapters_dir": None,
"chapters_dir_sentences": None,
"epub_path": None,
"filename_noext": None,
"tts_engine": default_tts_engine,
"fine_tuned": default_fine_tuned,
"voice": None,
"voice_dir": None,
"custom_model": None,
"custom_model_dir": None,
"temperature": default_engine_settings[TTS_ENGINES['XTTSv2']]['temperature'],
"length_penalty": default_engine_settings[TTS_ENGINES['XTTSv2']]['length_penalty'],
"num_beams": default_engine_settings[TTS_ENGINES['XTTSv2']]['num_beams'],
"repetition_penalty": default_engine_settings[TTS_ENGINES['XTTSv2']]['repetition_penalty'],
"top_k": default_engine_settings[TTS_ENGINES['XTTSv2']]['top_k'],
"top_p": default_engine_settings[TTS_ENGINES['XTTSv2']]['top_p'],
"speed": default_engine_settings[TTS_ENGINES['XTTSv2']]['speed'],
"enable_text_splitting": default_engine_settings[TTS_ENGINES['XTTSv2']]['enable_text_splitting'],
"text_temp": default_engine_settings[TTS_ENGINES['BARK']]['text_temp'],
"waveform_temp": default_engine_settings[TTS_ENGINES['BARK']]['waveform_temp'],
"final_name": None,
"output_format": default_output_format,
"output_split": default_output_split,
"output_split_hours": default_output_split_hours,
"metadata": {
"title": None,
"creator": None,
"contributor": None,
"language": None,
"identifier": None,
"publisher": None,
"date": None,
"description": None,
"subject": None,
"rights": None,
"format": None,
"type": None,
"coverage": None,
"relation": None,
"Source": None,
"Modified": None,
},
"toc": None,
"chapters": None,
"cover": None,
"duration": 0,
"playback_time": 0
}, manager=self.manager)
return self.sessions[id]
def find_id_by_hash(self, socket_hash):
for id, session in self.sessions.items():
if socket_hash in session:
return session.get('id')
return None
ctx_tracker = SessionTracker()
def recursive_proxy(data, manager=None):
if manager is None:
manager = Manager()
if isinstance(data, dict):
proxy_dict = manager.dict()
for key, value in data.items():
proxy_dict[key] = recursive_proxy(value, manager)
return proxy_dict
elif isinstance(data, list):
proxy_list = manager.list()
for item in data:
proxy_list.append(recursive_proxy(item, manager))
return proxy_list
elif isinstance(data, (str, int, float, bool, type(None))):
return data
else:
error = f"Unsupported data type: {type(data)}"
print(error)
return
def prepare_dirs(src, session):
try:
resume = False
os.makedirs(os.path.join(models_dir,'tts'), exist_ok=True)
os.makedirs(session['session_dir'], exist_ok=True)
os.makedirs(session['process_dir'], exist_ok=True)
os.makedirs(session['custom_model_dir'], exist_ok=True)
os.makedirs(session['voice_dir'], exist_ok=True)
os.makedirs(session['audiobooks_dir'], exist_ok=True)
session['ebook'] = os.path.join(session['process_dir'], os.path.basename(src))
if os.path.exists(session['ebook']):
if compare_files_by_hash(session['ebook'], src):
resume = True
if not resume:
shutil.rmtree(session['chapters_dir'], ignore_errors=True)
os.makedirs(session['chapters_dir'], exist_ok=True)
os.makedirs(session['chapters_dir_sentences'], exist_ok=True)
shutil.copy(src, session['ebook'])
return True
except Exception as e:
DependencyError(e)
return False
def check_programs(prog_name, command, options):
try:
subprocess.run(
[command, options],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
check=True,
text=True,
encoding='utf-8'
)
return True, None
except FileNotFoundError:
e = f'''********** Error: {prog_name} is not installed! if your OS calibre package version
is not compatible you still can run ebook2audiobook.sh (linux/mac) or ebook2audiobook.cmd (windows) **********'''
DependencyError(e)
return False, None
except subprocess.CalledProcessError:
e = f'Error: There was an issue running {prog_name}.'
DependencyError(e)
return False, None
def analyze_uploaded_file(zip_path, required_files):
try:
if not os.path.exists(zip_path):
error = f"The file does not exist: {os.path.basename(zip_path)}"
print(error)
return False
files_in_zip = {}
empty_files = set()
with zipfile.ZipFile(zip_path, 'r') as zf:
for file_info in zf.infolist():
file_name = file_info.filename
if file_info.is_dir():
continue
base_name = os.path.basename(file_name)
files_in_zip[base_name.lower()] = file_info.file_size
if file_info.file_size == 0:
empty_files.add(base_name.lower())
required_files = [file.lower() for file in required_files]
missing_files = [f for f in required_files if f not in files_in_zip]
required_empty_files = [f for f in required_files if f in empty_files]
if missing_files:
print(f"Missing required files: {missing_files}")
if required_empty_files:
print(f"Required files with 0 KB: {required_empty_files}")
return not missing_files and not required_empty_files
except zipfile.BadZipFile:
error = "The file is not a valid ZIP archive."
raise ValueError(error)
except Exception as e:
error = f"An error occurred: {e}"
raise RuntimeError(error)
def extract_custom_model(file_src, session, required_files=None):
try:
model_path = None
if required_files is None:
required_files = models[session['tts_engine']][default_fine_tuned]['files']
model_name = re.sub('.zip', '', os.path.basename(file_src), flags=re.IGNORECASE)
model_name = get_sanitized(model_name)
with zipfile.ZipFile(file_src, 'r') as zip_ref:
files = zip_ref.namelist()
files_length = len(files)
tts_dir = session['tts_engine']
model_path = os.path.join(session['custom_model_dir'], tts_dir, model_name)
if os.path.exists(model_path):
print(f'{model_path} already exists, bypassing files extraction')
return model_path
os.makedirs(model_path, exist_ok=True)
required_files_lc = set(x.lower() for x in required_files)
with tqdm(total=files_length, unit='files') as t:
for f in files:
base_f = os.path.basename(f).lower()
if base_f in required_files_lc:
out_path = os.path.join(model_path, base_f)
with zip_ref.open(f) as src, open(out_path, 'wb') as dst:
shutil.copyfileobj(src, dst)
t.update(1)
if is_gui_process:
os.remove(file_src)
if model_path is not None:
msg = f'Extracted files to {model_path}'
print(msg)
return model_path
else:
error = f'An error occured when unzip {file_src}'
return None
except asyncio.exceptions.CancelledError as e:
DependencyError(e)
if is_gui_process:
os.remove(file_src)
return None
except Exception as e:
DependencyError(e)
if is_gui_process:
os.remove(file_src)
return None
def hash_proxy_dict(proxy_dict):
return hashlib.md5(str(proxy_dict).encode('utf-8')).hexdigest()
def calculate_hash(filepath, hash_algorithm='sha256'):
hash_func = hashlib.new(hash_algorithm)
with open(filepath, 'rb') as f:
while chunk := f.read(8192): # Read in chunks to handle large files
hash_func.update(chunk)
return hash_func.hexdigest()
def compare_files_by_hash(file1, file2, hash_algorithm='sha256'):
return calculate_hash(file1, hash_algorithm) == calculate_hash(file2, hash_algorithm)
def compare_dict_keys(d1, d2):
if not isinstance(d1, Mapping) or not isinstance(d2, Mapping):
return d1 == d2
d1_keys = set(d1.keys())
d2_keys = set(d2.keys())
missing_in_d2 = d1_keys - d2_keys
missing_in_d1 = d2_keys - d1_keys
if missing_in_d2 or missing_in_d1:
return {
"missing_in_d2": missing_in_d2,
"missing_in_d1": missing_in_d1,
}
for key in d1_keys.intersection(d2_keys):
nested_result = compare_keys(d1[key], d2[key])
if nested_result:
return {key: nested_result}
return None
def proxy2dict(proxy_obj):
def recursive_copy(source, visited):
# Handle circular references by tracking visited objects
if id(source) in visited:
return None # Stop processing circular references
visited.add(id(source)) # Mark as visited
if isinstance(source, dict):
result = {}
for key, value in source.items():
result[key] = recursive_copy(value, visited)
return result
elif isinstance(source, list):
return [recursive_copy(item, visited) for item in source]
elif isinstance(source, set):
return list(source)
elif isinstance(source, (int, float, str, bool, type(None))):
return source
elif isinstance(source, DictProxy):
# Explicitly handle DictProxy objects
return recursive_copy(dict(source), visited) # Convert DictProxy to dict
else:
return str(source) # Convert non-serializable types to strings
return recursive_copy(proxy_obj, set())
def convert2epub(id):
session = context.get_session(id)
if session['cancellation_requested']:
print('Cancel requested')
return False
try:
title = False
author = False
util_app = shutil.which('ebook-convert')
if not util_app:
error = "The 'ebook-convert' utility is not installed or not found."
print(error)
return False
file_input = session['ebook']
if os.path.getsize(file_input) == 0:
error = f"Input file is empty: {file_input}"
print(error)
return False
file_ext = os.path.splitext(file_input)[1].lower()
if file_ext not in ebook_formats:
error = f'Unsupported file format: {file_ext}'
print(error)
return False
if file_ext == '.pdf':
import fitz
msg = 'File input is a PDF. flatten it in MarkDown...'
print(msg)
doc = fitz.open(session['ebook'])
pdf_metadata = doc.metadata
filename_no_ext = os.path.splitext(os.path.basename(session['ebook']))[0]
title = pdf_metadata.get('title') or filename_no_ext
author = pdf_metadata.get('author') or False
markdown_text = pymupdf4llm.to_markdown(session['ebook'])
# Remove single asterisks for italics (but not bold **)
markdown_text = re.sub(r'(? in the head of the first XHTML document
if all_docs:
html = all_docs[0].get_content().decode("utf-8")
soup = BeautifulSoup(html, "html.parser")
title_tag = soup.select_one("head > title")
if title_tag and title_tag.text.strip():
return title_tag.text.strip()
# 3. Try if no visible
img = soup.find("img", alt=True)
if img:
alt = img['alt'].strip()
if alt and "cover" not in alt.lower():
return alt
return None
def get_cover(epubBook, session):
try:
if session['cancellation_requested']:
msg = 'Cancel requested'
print(msg)
return False
cover_image = None
cover_path = os.path.join(session['process_dir'], session['filename_noext'] + '.jpg')
for item in epubBook.get_items_of_type(ebooklib.ITEM_COVER):
cover_image = item.get_content()
break
if not cover_image:
for item in epubBook.get_items_of_type(ebooklib.ITEM_IMAGE):
if 'cover' in item.file_name.lower() or 'cover' in item.get_id().lower():
cover_image = item.get_content()
break
if cover_image:
# Open the image from bytes
image = Image.open(io.BytesIO(cover_image))
# Convert to RGB if needed (JPEG doesn't support alpha)
if image.mode in ('RGBA', 'P'):
image = image.convert('RGB')
image.save(cover_path, format='JPEG')
return cover_path
return True
except Exception as e:
DependencyError(e)
return False
def get_chapters(epubBook, session):
try:
msg = r'''
*******************************************************************************
NOTE:
The warning "Character xx not found in the vocabulary."
MEANS THE MODEL CANNOT INTERPRET THE CHARACTER AND WILL MAYBE GENERATE
(AS WELL AS WRONG PUNCTUATION POSITION) AN HALLUCINATION TO IMPROVE THIS MODEL,
IT NEEDS TO ADD THIS CHARACTER INTO A NEW TRAINING MODEL.
YOU CAN IMPROVE IT OR ASK TO A TRAINING MODEL EXPERT.
*******************************************************************************
'''
print(msg)
if session['cancellation_requested']:
print('Cancel requested')
return False
# Step 1: Extract TOC (Table of Contents)
try:
toc = epubBook.toc # Extract TOC
toc_list = [
nt for item in toc if hasattr(item, 'title')
if (nt := normalize_text(
str(item.title),
session['language'],
session['language_iso1'],
session['tts_engine']
)) is not None
]
except Exception as toc_error:
error = f"Error extracting TOC: {toc_error}"
print(error)
# Get spine item IDs
spine_ids = [item[0] for item in epubBook.spine]
# Filter only spine documents (i.e., reading order)
all_docs = [
item for item in epubBook.get_items_of_type(ebooklib.ITEM_DOCUMENT)
if item.id in spine_ids
]
if not all_docs:
return [], []
title = get_ebook_title(epubBook, all_docs)
chapters = []
stanza_nlp = False
if session['language'] in year_to_decades_languages:
stanza.download(session['language_iso1'])
stanza_nlp = stanza.Pipeline(session['language_iso1'], processors='tokenize,ner')
is_num2words_compat = get_num2words_compat(session['language_iso1'])
msg = 'Analyzing numbers, maths signs, dates and time to convert in words...'
print(msg)
for doc in all_docs:
sentences_list = filter_chapter(doc, session['language'], session['language_iso1'], session['tts_engine'], stanza_nlp, is_num2words_compat)
if sentences_list is None:
break
elif len(sentences_list) > 0:
chapters.append(sentences_list)
if len(chapters) == 0:
error = 'No chapters found!'
return None, None
return toc, chapters
except Exception as e:
error = f'Error extracting main content pages: {e}'
DependencyError(error)
return None, None
def filter_chapter(doc, lang, lang_iso1, tts_engine, stanza_nlp, is_num2words_compat):
def tuple_row(node, last_text_char=None):
try:
for child in node.children:
if isinstance(child, NavigableString):
text = child.strip()
if text:
yield ("text", text)
last_text_char = text[-1] if text else last_text_char
elif isinstance(child, Tag):
name = child.name.lower()
if name in heading_tags:
title = child.get_text(strip=True)
if title:
yield ("heading", title)
last_text_char = title[-1] if title else last_text_char
elif name == "table":
yield ("table", child)
else:
return_data = False
if name in proc_tags:
for inner in tuple_row(child, last_text_char):
return_data = True
yield inner
# Track last char if this is text or heading
if inner[0] in ("text", "heading") and inner[1]:
last_text_char = inner[1][-1]
if return_data:
if name in break_tags:
# Only yield break if last char is NOT alnum or space
if not (last_text_char and (last_text_char.isalnum() or last_text_char.isspace())):
yield ("break", TTS_SML['break'])
elif name in heading_tags or name in pause_tags:
yield ("pause", TTS_SML['pause'])
else:
yield from tuple_row(child, last_text_char)
except Exception as e:
error = f'filter_chapter() tuple_row() error: {e}'
DependencyError(error)
return None
try:
heading_tags = [f'h{i}' for i in range(1, 5)]
break_tags = ['br', 'p']
pause_tags = ['div', 'span']
proc_tags = heading_tags + break_tags + pause_tags
raw_html = doc.get_body_content().decode("utf-8")
soup = BeautifulSoup(raw_html, 'html.parser')
body = soup.body
if not body or not body.get_text(strip=True):
return []
# Skip known non-chapter types
epub_type = body.get("epub:type", "").lower()
if not epub_type:
section_tag = soup.find("section")
if section_tag:
epub_type = section_tag.get("epub:type", "").lower()
excluded = {
"frontmatter", "backmatter", "toc", "titlepage", "colophon",
"acknowledgments", "dedication", "glossary", "index",
"appendix", "bibliography", "copyright-page", "landmark"
}
if any(part in epub_type for part in excluded):
return []
# remove scripts/styles
for tag in soup(["script", "style"]):
tag.decompose()
tuples_list = list(tuple_row(body))
if not tuples_list:
error = 'No tuples_list from body created!'
print(error)
return None
text_list = []
handled_tables = set()
prev_typ = None
for typ, payload in tuples_list:
if typ == "heading":
text_list.append(payload.strip())
elif typ == "break":
if prev_typ != 'break':
text_list.append(TTS_SML['break'])
elif typ == 'pause':
if prev_typ != 'pause':
text_list.append(TTS_SML['pause'])
elif typ == "table":
table = payload
if table in handled_tables:
prev_typ = typ
continue
handled_tables.add(table)
rows = table.find_all("tr")
if not rows:
prev_typ = typ
continue
headers = [c.get_text(strip=True) for c in rows[0].find_all(["td", "th"])]
for row in rows[1:]:
cells = [c.get_text(strip=True).replace('\xa0', ' ') for c in row.find_all("td")]
if not cells:
continue
if len(cells) == len(headers) and headers:
line = " — ".join(f"{h}: {c}" for h, c in zip(headers, cells))
else:
line = " — ".join(cells)
if line:
text_list.append(line.strip())
else:
text = payload.strip()
if text:
text_list.append(text)
prev_typ = typ
max_chars = language_mapping[lang]['max_chars'] - 4
clean_list = []
i = 0
while i < len(text_list):
current = text_list[i]
if current == "‡break‡":
if clean_list:
prev = clean_list[-1]
if prev in ("‡break‡", "‡pause‡"):
i += 1
continue
if prev and (prev[-1].isalnum() or prev[-1] == ' '):
if i + 1 < len(text_list):
next_sentence = text_list[i + 1]
merged_length = len(prev.rstrip()) + 1 + len(next_sentence.lstrip())
if merged_length <= max_chars:
# Merge with space handling
if not prev.endswith(" ") and not next_sentence.startswith(" "):
clean_list[-1] = prev + " " + next_sentence
else:
clean_list[-1] = prev + next_sentence
i += 2
continue
else:
clean_list.append(current)
i += 1
continue
clean_list.append(current)
i += 1
text = ' '.join(clean_list)
if not re.search(r"[^\W_]", text):
error = 'No valid text found!'
print(error)
return None
if stanza_nlp:
# Check if there are positive integers so possible date to convert
re_ordinal = re.compile(
r'(? "sixteenth"
if is_num2words_compat:
processed = re_ordinal.sub(
lambda m: num2words(int(m.group(1)), to="ordinal", lang=(lang_iso1 or "en")),
processed
)
else:
processed = re_ordinal.sub(
lambda m: math2words(m.group(), lang, lang_iso1, tts_engine, is_num2words_compat),
processed
)
# 3) convert other numbers (skip 4-digit years)
def _num_repl(m):
s = m.group(0)
# leave years alone (already handled above)
if re.fullmatch(r"\d{4}", s):
return s
n = float(s) if "." in s else int(s)
if is_num2words_compat:
return num2words(n, lang=(lang_iso1 or "en"))
else:
return math2words(m, lang, lang_iso1, tts_engine, is_num2words_compat)
processed = re_num.sub(_num_repl, processed)
result.append(processed)
last_pos = end
result.append(text[last_pos:])
text = ''.join(result)
else:
if is_num2words_compat:
text = re_ordinal.sub(
lambda m: num2words(int(m.group(1)), to="ordinal", lang=(lang_iso1 or "en")),
text
)
else:
text = re_ordinal.sub(
lambda m: math2words(int(m.group(1)), lang, lang_iso1, tts_engine, is_num2words_compat),
text
)
text = re.sub(
r"\b\d{4}\b",
lambda m: year2words(m.group(), lang, lang_iso1, is_num2words_compat),
text
)
text = roman2number(text)
text = clock2words(text, lang, lang_iso1, tts_engine, is_num2words_compat)
text = math2words(text, lang, lang_iso1, tts_engine, is_num2words_compat)
# build a translation table mapping each bad char to a space
specialchars_remove_table = str.maketrans({ch: ' ' for ch in specialchars_remove})
text = text.translate(specialchars_remove_table)
text = normalize_text(text, lang, lang_iso1, tts_engine)
# Ensure space before and after punctuation_list
#pattern_space = re.escape(''.join(punctuation_list))
#punctuation_pattern_space = r'(? max_chars:
yield buffer
buffer = ''
# 3) Append the token (word, punctuation, whatever) unless it's a sml token (already checked)
buffer += token
# 4) Flush any trailing text
if buffer:
yield buffer
except Exception as e:
DependencyError(e)
if buffer:
yield buffer
try:
max_chars = language_mapping[lang]['max_chars'] - 4
min_tokens = 5
# List or tuple of tokens that must never be appended to buffer
sml_tokens = tuple(TTS_SML.values())
sml_list = re.split(rf"({'|'.join(map(re.escape, sml_tokens))})", text)
sml_list = [s for s in sml_list if s.strip() or s in sml_tokens]
pattern_split = '|'.join(map(re.escape, punctuation_split_hard_set))
pattern = re.compile(rf"(.*?(?:{pattern_split}){''.join(punctuation_list_set)})(?=\s|$)", re.DOTALL)
hard_list = []
for s in sml_list:
if s in [TTS_SML['break'], TTS_SML['pause']] or len(s) <= max_chars:
hard_list.append(s)
else:
parts = split_inclusive(s, pattern)
if parts:
for text_part in parts:
text_part = text_part.strip()
if text_part:
hard_list.append(text_part)
else:
s = s.strip()
if s:
hard_list.append(s)
# Check if some hard_list entries exceed max_chars, so split on soft punctuation
pattern_split = '|'.join(map(re.escape, punctuation_split_soft_set))
pattern = re.compile(rf"(.*?(?:{pattern_split}))(?=\s|$)", re.DOTALL)
soft_list = []
for s in hard_list:
if s in [TTS_SML['break'], TTS_SML['pause']] or len(s) <= max_chars:
soft_list.append(s)
elif len(s) > max_chars:
parts = [p for p in split_inclusive(s, pattern) if p]
if parts:
buffer = ''
for idx, part in enumerate(parts):
# Predict length if we glue this part
predicted_length = len(buffer) + (1 if buffer else 0) + len(part)
# Peek ahead to see if gluing will exceed max_chars
if predicted_length <= max_chars:
buffer = (buffer + ' ' + part).strip() if buffer else part
else:
# If we overshoot, check if buffer ends with punctuation
if buffer and not any(buffer.rstrip().endswith(p) for p in punctuation_split_soft_set):
# Try to backtrack to last punctuation inside buffer
last_punct_idx = max((buffer.rfind(p) for p in punctuation_split_soft_set if p in buffer), default=-1)
if last_punct_idx != -1:
soft_list.append(buffer[:last_punct_idx+1].strip())
leftover = buffer[last_punct_idx+1:].strip()
buffer = leftover + ' ' + part if leftover else part
else:
# No punctuation, just split as-is
soft_list.append(buffer.strip())
buffer = part
else:
soft_list.append(buffer.strip())
buffer = part
if buffer:
cleaned = re.sub(r'[^\p{L}\p{N} ]+', '', buffer)
if any(ch.isalnum() for ch in cleaned):
soft_list.append(buffer.strip())
else:
cleaned = re.sub(r'[^\p{L}\p{N} ]+', '', s)
if any(ch.isalnum() for ch in cleaned):
soft_list.append(s.strip())
else:
cleaned = re.sub(r'[^\p{L}\p{N} ]+', '', s)
if any(ch.isalnum() for ch in cleaned):
soft_list.append(s.strip())
if lang in ['zho', 'jpn', 'kor', 'tha', 'lao', 'mya', 'khm']:
result = []
for s in soft_list:
if s in [TTS_SML['break'], TTS_SML['pause']]:
result.append(s)
else:
tokens = segment_ideogramms(s)
if isinstance(tokens, list):
result.extend([t for t in tokens if t.strip()])
else:
tokens = tokens.strip()
if tokens:
result.append(tokens)
return list(join_ideogramms(result))
else:
sentences = []
for s in soft_list:
if s in [TTS_SML['break'], TTS_SML['pause']] or len(s) <= max_chars:
sentences.append(s)
else:
words = s.split(' ')
text_part = words[0]
for w in words[1:]:
if len(text_part) + 1 + len(w) <= max_chars:
text_part += ' ' + w
else:
text_part = text_part.strip()
if text_part:
sentences.append(text_part)
text_part = w
if text_part:
cleaned = re.sub(r'[^\p{L}\p{N} ]+', '', text_part).strip()
if not any(ch.isalnum() for ch in cleaned):
continue
sentences.append(text_part)
return sentences
except Exception as e:
error = f'get_sentences() error: {e}'
print(error)
return None
def get_ram():
vm = psutil.virtual_memory()
return vm.total // (1024 ** 3)
def get_vram():
os_name = platform.system()
# NVIDIA (Cross-Platform: Windows, Linux, macOS)
try:
from pynvml import nvmlInit, nvmlDeviceGetHandleByIndex, nvmlDeviceGetMemoryInfo
nvmlInit()
handle = nvmlDeviceGetHandleByIndex(0) # First GPU
info = nvmlDeviceGetMemoryInfo(handle)
vram = info.total
return int(vram // (1024 ** 3)) # Convert to GB
except ImportError:
pass
except Exception as e:
pass
# AMD (Windows)
if os_name == "Windows":
try:
cmd = 'wmic path Win32_VideoController get AdapterRAM'
output = subprocess.run(cmd, capture_output=True, text=True, shell=True)
lines = output.stdout.splitlines()
vram_values = [int(line.strip()) for line in lines if line.strip().isdigit()]
if vram_values:
return int(vram_values[0] // (1024 ** 3))
except Exception as e:
pass
# AMD (Linux)
if os_name == "Linux":
try:
cmd = "lspci -v | grep -i 'VGA' -A 12 | grep -i 'preallocated' | awk '{print $2}'"
output = subprocess.run(cmd, capture_output=True, text=True, shell=True)
if output.stdout.strip().isdigit():
return int(output.stdout.strip()) // 1024
except Exception as e:
pass
# Intel (Linux Only)
intel_vram_paths = [
"/sys/kernel/debug/dri/0/i915_vram_total", # Intel dedicated GPUs
"/sys/class/drm/card0/device/resource0" # Some integrated GPUs
]
for path in intel_vram_paths:
if os.path.exists(path):
try:
with open(path, "r") as f:
vram = int(f.read().strip()) // (1024 ** 3)
return vram
except Exception as e:
pass
# macOS (OpenGL Alternative)
if os_name == "Darwin":
try:
from OpenGL.GL import glGetIntegerv
from OpenGL.GLX import GLX_RENDERER_VIDEO_MEMORY_MB_MESA
vram = int(glGetIntegerv(GLX_RENDERER_VIDEO_MEMORY_MB_MESA) // 1024)
return vram
except ImportError:
pass
except Exception as e:
pass
msg = 'Could not detect GPU VRAM Capacity!'
return 0
def get_sanitized(str, replacement="_"):
str = str.replace('&', 'And')
forbidden_chars = r'[<>:"/\\|?*\x00-\x1F ()]'
sanitized = re.sub(r'\s+', replacement, str)
sanitized = re.sub(forbidden_chars, replacement, sanitized)
sanitized = sanitized.strip("_")
return sanitized
def get_date_entities(text, stanza_nlp):
try:
doc = stanza_nlp(text)
date_spans = []
for ent in doc.ents:
if ent.type == 'DATE':
date_spans.append((ent.start_char, ent.end_char, ent.text))
return date_spans
except Exception as e:
error = f'get_date_entities() error: {e}'
print(error)
return False
def get_num2words_compat(lang_iso1):
try:
test = num2words(1, lang=lang_iso1.replace('zh', 'zh_CN'))
return True
except NotImplementedError:
return False
except Exception as e:
return False
def set_formatted_number(text: str, lang, lang_iso1: str, is_num2words_compat: bool, max_single_value: int = 999_999_999_999_999_999):
# match up to 18 digits, optional “,…” groups (allowing spaces or NBSP after comma), optional decimal of up to 12 digits
# handle optional range with dash/en dash/em dash between numbers, and allow trailing punctuation
number_re = re.compile(
r'(? str:
"""Normalize number string to standard comma format: 1,234,567"""
tok = num_str.replace('\u00A0', '').replace(' ', '')
if '.' in tok:
integer_part, decimal_part = tok.split('.', 1)
integer_part = integer_part.replace(',', '')
integer_part = "{:,}".format(int(integer_part))
return f"{integer_part}.{decimal_part}"
else:
integer_part = tok.replace(',', '')
return "{:,}".format(int(integer_part))
def clean_single_num(num_str):
tok = unicodedata.normalize('NFKC', num_str)
if tok.lower() in ('inf', 'infinity', 'nan'):
return tok
clean = tok.replace(',', '').replace('\u00A0', '').replace(' ', '')
try:
num = float(clean) if '.' in clean else int(clean)
except (ValueError, OverflowError):
return tok
if not math.isfinite(num) or abs(num) > max_single_value:
return tok
# Normalize commas before final output
tok = normalize_commas(tok)
if is_num2words_compat:
new_lang_iso1 = lang_iso1.replace('zh', 'zh_CN')
return num2words(num, lang=new_lang_iso1)
else:
phoneme_map = language_math_phonemes.get(
lang,
language_math_phonemes.get(default_language_code, language_math_phonemes['eng'])
)
return ' '.join(phoneme_map.get(ch, ch) for ch in str(num))
def clean_match(match):
first_num = clean_single_num(match.group(1))
dash_char = match.group(2) or ''
second_num = clean_single_num(match.group(3)) if match.group(3) else ''
trailing = match.group(4) or ''
if second_num:
return f"{first_num}{dash_char}{second_num}{trailing}"
else:
return f"{first_num}{trailing}"
return number_re.sub(clean_match, text)
def year2words(year_str, lang, lang_iso1, is_num2words_compat):
try:
year = int(year_str)
first_two = int(year_str[:2])
last_two = int(year_str[2:])
lang_iso1 = lang_iso1 if lang in language_math_phonemes.keys() else default_language_code
lang_iso1 = lang_iso1.replace('zh', 'zh_CN')
if not year_str.isdigit() or len(year_str) != 4 or last_two < 10:
if is_num2words_compat:
return num2words(year, lang=lang_iso1)
else:
return ' '.join(language_math_phonemes[lang].get(ch, ch) for ch in year_str)
if is_num2words_compat:
return f"{num2words(first_two, lang=lang_iso1)} {num2words(last_two, lang=lang_iso1)}"
else:
return ' '.join(language_math_phonemes[lang].get(ch, ch) for ch in first_two) + ' ' + ' '.join(language_math_phonemes[lang].get(ch, ch) for ch in last_two)
except Exception as e:
error = f'year2words() error: {e}'
print(error)
raise
return False
def clock2words(text, lang, lang_iso1, tts_engine, is_num2words_compat):
time_rx = re.compile(r'(\d{1,2})[:.](\d{1,2})(?:[:.](\d{1,2}))?')
lang_lc = (lang or "").lower()
lc = language_clock.get(lang_lc) if 'language_clock' in globals() else None
_n2w_cache = {}
def n2w(n: int) -> str:
key = (n, lang_lc, is_num2words_compat)
if key in _n2w_cache:
return _n2w_cache[key]
if is_num2words_compat:
word = num2words(n, lang=lang_lc)
else:
word = math2words(n, lang, lang_iso1, tts_engine, is_num2words_compat)
_n2w_cache[key] = word
return word
def repl_num(m: re.Match) -> str:
# Parse hh[:mm[:ss]]
try:
h = int(m.group(1))
mnt = int(m.group(2))
sec = m.group(3)
sec = int(sec) if sec is not None else None
except Exception:
return m.group(0)
# basic validation; if out of range, keep original
if not (0 <= h <= 23 and 0 <= mnt <= 59 and (sec is None or 0 <= sec <= 59)):
return m.group(0)
# If no language clock rules, just say numbers plainly
if not lc:
parts = [n2w(h)]
if mnt != 0:
parts.append(n2w(mnt))
if sec is not None and sec > 0:
parts.append(n2w(sec))
return " ".join(parts)
next_hour = (h + 1) % 24
special_hours = lc.get("special_hours", {})
# Build main phrase
if mnt == 0 and (sec is None or sec == 0):
if h in special_hours:
phrase = special_hours[h]
else:
phrase = lc["oclock"].format(hour=n2w(h))
elif mnt == 15:
phrase = lc["quarter_past"].format(hour=n2w(h))
elif mnt == 30:
# German "halb drei" (= 2:30) uses next hour
if lang_lc == "deu":
phrase = lc["half_past"].format(next_hour=n2w(next_hour))
else:
phrase = lc["half_past"].format(hour=n2w(h))
elif mnt == 45:
phrase = lc["quarter_to"].format(next_hour=n2w(next_hour))
elif mnt < 30:
phrase = lc["past"].format(hour=n2w(h), minute=n2w(mnt)) if mnt != 0 else lc["oclock"].format(hour=n2w(h))
else:
minute_to_hour = 60 - mnt
phrase = lc["to"].format(next_hour=n2w(next_hour), minute=n2w(minute_to_hour))
# Append seconds if present
if sec is not None and sec > 0:
second_phrase = lc["second"].format(second=n2w(sec))
phrase = lc["full"].format(phrase=phrase, second_phrase=second_phrase)
return phrase
return time_rx.sub(repl_num, text)
def math2words(text, lang, lang_iso1, tts_engine, is_num2words_compat):
def repl_ambiguous(match):
# handles "num SYMBOL num" and "SYMBOL num"
if match.group(2) and match.group(2) in ambiguous_replacements:
return f"{match.group(1)} {ambiguous_replacements[match.group(2)]} {match.group(3)}"
if match.group(3) and match.group(3) in ambiguous_replacements:
return f"{ambiguous_replacements[match.group(3)]} {match.group(4)}"
return match.group(0)
def _ordinal_to_words(m):
n = int(m.group(1))
if is_num2words_compat:
try:
from num2words import num2words
return num2words(n, to="ordinal", lang=(lang_iso1 or "en"))
except Exception:
pass
# If num2words isn't available/compatible, keep original token as-is.
return m.group(0)
# Matches any digits + optional space/NBSP + st/nd/rd/th, not glued into words.
re_ordinal = re.compile(r'(?= 2
# This avoids: 19C, 19°C, °C, AC/DC, CD-ROM, single-letter "I"
text = re.sub(r'(? str:
token = match.group(1)
for k, expansion in mapping.items():
if token.lower() == k.lower():
return expansion
return token # fallback
mapping = abbreviations_mapping[lang]
# Sort keys by descending length so longer ones match first
keys = sorted(mapping.keys(), key=len, reverse=True)
# Build a regex that only matches whole “words” (tokens) exactly
pattern = re.compile(
r'(? resume_sentence or (sentence_number == 0 and resume_sentence == 0):
if sentence_number <= resume_sentence and sentence_number > 0:
msg = f'**Recovering missing file sentence {sentence_number}'
print(msg)
sentence = sentence.strip()
success = tts_manager.convert_sentence2audio(sentence_number, sentence) if sentence else True
if success:
total_progress = (t.n + 1) / total_iterations
progress_bar(total_progress)
is_sentence = sentence.strip() not in TTS_SML.values()
percentage = total_progress * 100
t.set_description(f'{percentage:.2f}%')
msg = f" | {sentence}" if is_sentence else f" | {sentence}"
print(msg)
else:
return False
if sentence.strip() not in TTS_SML.values():
sentence_number += 1
t.update(1) # advance for every iteration, including SML
end = sentence_number - 1 if sentence_number > 1 else sentence_number
msg = f"End of Block {chapter_num}"
print(msg)
if chapter_num in missing_chapters or sentence_number > resume_sentence:
if chapter_num <= resume_chapter:
msg = f'**Recovering missing file block {chapter_num}'
print(msg)
if combine_audio_sentences(chapter_audio_file, start, end, session):
msg = f'Combining block {chapter_num} to audio, sentence {start} to {end}'
print(msg)
else:
msg = 'combine_audio_sentences() failed!'
print(msg)
return False
return True
except Exception as e:
DependencyError(e)
return False
def assemble_chunks(txt_file, out_file):
try:
ffmpeg_cmd = [
shutil.which('ffmpeg'), '-hide_banner', '-nostats', '-y',
'-safe', '0', '-f', 'concat', '-i', txt_file,
'-c:a', default_audio_proc_format, '-map_metadata', '-1', '-threads', '1', out_file
]
process = subprocess.Popen(
ffmpeg_cmd,
env={},
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
encoding='utf-8',
errors='ignore'
)
for line in process.stdout:
print(line, end='') # Print each line of stdout
process.wait()
if process.returncode == 0:
return True
else:
error = process.returncode
print(error, ffmpeg_cmd)
return False
except subprocess.CalledProcessError as e:
DependencyError(e)
return False
except Exception as e:
error = f"assemble_chanks() Error: Failed to process {txt_file} → {out_file}: {e}"
print(error)
return False
def combine_audio_sentences(chapter_audio_file, start, end, session):
try:
chapter_audio_file = os.path.join(session['chapters_dir'], chapter_audio_file)
chapters_dir_sentences = session['chapters_dir_sentences']
batch_size = 1024
sentence_files = [
f for f in os.listdir(chapters_dir_sentences)
if f.endswith(f'.{default_audio_proc_format}')
]
sentences_ordered = sorted(
sentence_files, key=lambda x: int(os.path.splitext(x)[0])
)
selected_files = [
os.path.join(chapters_dir_sentences, f)
for f in sentences_ordered
if start <= int(os.path.splitext(f)[0]) <= end
]
if not selected_files:
print('No audio files found in the specified range.')
return False
with tempfile.TemporaryDirectory() as tmpdir:
chunk_list = []
for i in range(0, len(selected_files), batch_size):
batch = selected_files[i:i + batch_size]
txt = os.path.join(tmpdir, f'chunk_{i:04d}.txt')
out = os.path.join(tmpdir, f'chunk_{i:04d}.{default_audio_proc_format}')
with open(txt, 'w') as f:
for file in batch:
f.write(f"file '{file.replace(os.sep, '/')}'\n")
chunk_list.append((txt, out))
try:
with Pool(cpu_count()) as pool:
results = pool.starmap(assemble_chunks, chunk_list)
except Exception as e:
error = f"combine_audio_sentences() multiprocessing error: {e}"
print(error)
return False
if not all(results):
error = "combine_audio_sentences() One or more chunks failed."
print(error)
return False
# Final merge
final_list = os.path.join(tmpdir, 'sentences_final.txt')
with open(final_list, 'w') as f:
for _, chunk_path in chunk_list:
f.write(f"file '{chunk_path.replace(os.sep, '/')}'\n")
if assemble_chunks(final_list, chapter_audio_file):
msg = f'********* Combined block audio file saved in {chapter_audio_file}'
print(msg)
return True
else:
error = "combine_audio_sentences() Final merge failed."
print(error)
return False
except Exception as e:
DependencyError(e)
return False
def combine_audio_chapters(id):
def get_audio_duration(filepath):
try:
ffprobe_cmd = [
shutil.which('ffprobe'),
'-v', 'error',
'-show_entries', 'format=duration',
'-of', 'json',
filepath
]
result = subprocess.run(ffprobe_cmd, capture_output=True, text=True)
try:
return float(json.loads(result.stdout)['format']['duration'])
except Exception:
return 0
except subprocess.CalledProcessError as e:
DependencyError(e)
return 0
except Exception as e:
error = f"get_audio_duration() Error: Failed to process {txt_file} → {out_file}: {e}"
print(error)
return 0
def generate_ffmpeg_metadata(part_chapters, session, output_metadata_path, default_audio_proc_format):
try:
out_fmt = session['output_format']
is_mp4_like = out_fmt in ['mp4', 'm4a', 'm4b', 'mov']
is_vorbis = out_fmt in ['ogg', 'webm']
is_mp3 = out_fmt == 'mp3'
def tag(key):
return key.upper() if is_vorbis else key
ffmpeg_metadata = ';FFMETADATA1\n'
if session['metadata'].get('title'):
ffmpeg_metadata += f"{tag('title')}={session['metadata']['title']}\n"
if session['metadata'].get('creator'):
ffmpeg_metadata += f"{tag('artist')}={session['metadata']['creator']}\n"
if session['metadata'].get('language'):
ffmpeg_metadata += f"{tag('language')}={session['metadata']['language']}\n"
if session['metadata'].get('description'):
ffmpeg_metadata += f"{tag('description')}={session['metadata']['description']}\n"
if session['metadata'].get('publisher') and (is_mp4_like or is_mp3):
ffmpeg_metadata += f"{tag('publisher')}={session['metadata']['publisher']}\n"
if session['metadata'].get('published'):
try:
if '.' in session['metadata']['published']:
year = datetime.strptime(session['metadata']['published'], '%Y-%m-%dT%H:%M:%S.%f%z').year
else:
year = datetime.strptime(session['metadata']['published'], '%Y-%m-%dT%H:%M:%S%z').year
except Exception:
year = datetime.now().year
else:
year = datetime.now().year
if is_vorbis:
ffmpeg_metadata += f"{tag('date')}={year}\n"
else:
ffmpeg_metadata += f"{tag('year')}={year}\n"
if session['metadata'].get('identifiers') and isinstance(session['metadata']['identifiers'], dict):
if is_mp3 or is_mp4_like:
isbn = session['metadata']['identifiers'].get('isbn')
if isbn:
ffmpeg_metadata += f"{tag('isbn')}={isbn}\n"
asin = session['metadata']['identifiers'].get('mobi-asin')
if asin:
ffmpeg_metadata += f"{tag('asin')}={asin}\n"
start_time = 0
for filename, chapter_title in part_chapters:
filepath = os.path.join(session['chapters_dir'], filename)
duration_ms = len(AudioSegment.from_file(filepath, format=default_audio_proc_format))
clean_title = re.sub(r'(^#)|[=\\]|(-$)', lambda m: '\\' + (m.group(1) or m.group(0)), chapter_title.replace(TTS_SML['pause'], ''))
ffmpeg_metadata += '[CHAPTER]\nTIMEBASE=1/1000\n'
ffmpeg_metadata += f'START={start_time}\nEND={start_time + duration_ms}\n'
ffmpeg_metadata += f"{tag('title')}={clean_title}\n"
start_time += duration_ms
with open(output_metadata_path, 'w', encoding='utf-8') as f:
f.write(ffmpeg_metadata)
return output_metadata_path
except Exception as e:
error = f"generate_ffmpeg_metadata() Error: Failed to process {txt_file} → {out_file}: {e}"
print(error)
return False
def export_audio(ffmpeg_combined_audio, ffmpeg_metadata_file, ffmpeg_final_file):
try:
if session['cancellation_requested']:
print('Cancel requested')
return False
cover_path = None
ffmpeg_cmd = [shutil.which('ffmpeg'), '-hide_banner', '-nostats', '-i', ffmpeg_combined_audio]
if session['output_format'] == 'wav':
ffmpeg_cmd += ['-map', '0:a', '-ar', '44100', '-sample_fmt', 's16']
elif session['output_format'] == 'aac':
ffmpeg_cmd += ['-c:a', 'aac', '-b:a', '192k', '-ar', '44100']
elif session['output_format'] == 'flac':
ffmpeg_cmd += ['-c:a', 'flac', '-compression_level', '5', '-ar', '44100', '-sample_fmt', 's16']
else:
ffmpeg_cmd += ['-f', 'ffmetadata', '-i', ffmpeg_metadata_file, '-map', '0:a']
if session['output_format'] in ['m4a', 'm4b', 'mp4', 'mov']:
ffmpeg_cmd += ['-c:a', 'aac', '-b:a', '192k', '-ar', '44100', '-movflags', '+faststart+use_metadata_tags']
elif session['output_format'] == 'mp3':
ffmpeg_cmd += ['-c:a', 'libmp3lame', '-b:a', '192k', '-ar', '44100']
elif session['output_format'] == 'webm':
ffmpeg_cmd += ['-c:a', 'libopus', '-b:a', '192k', '-ar', '48000']
elif session['output_format'] == 'ogg':
ffmpeg_cmd += ['-c:a', 'libopus', '-compression_level', '0', '-b:a', '192k', '-ar', '48000']
ffmpeg_cmd += ['-map_metadata', '1']
ffmpeg_cmd += ['-af', 'loudnorm=I=-16:LRA=11:TP=-1.5,afftdn=nf=-70', '-strict', 'experimental', '-threads', '1', '-y', ffmpeg_final_file]
process = subprocess.Popen(
ffmpeg_cmd,
env={},
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
encoding='utf-8',
errors='ignore'
)
for line in process.stdout:
print(line, end='')
process.wait()
if process.returncode == 0:
if session['output_format'] in ['mp3', 'm4a', 'm4b', 'mp4']:
if session['cover'] is not None:
cover_path = session['cover']
msg = f'Adding cover {cover_path} into the final audiobook file...'
print(msg)
if session['output_format'] == 'mp3':
from mutagen.mp3 import MP3
from mutagen.id3 import ID3, APIC, error
audio = MP3(ffmpeg_final_file, ID3=ID3)
try:
audio.add_tags()
except error:
pass
with open(cover_path, 'rb') as img:
audio.tags.add(
APIC(
encoding=3,
mime='image/jpeg',
type=3,
desc='Cover',
data=img.read()
)
)
elif session['output_format'] in ['mp4', 'm4a', 'm4b']:
from mutagen.mp4 import MP4, MP4Cover
audio = MP4(ffmpeg_final_file)
with open(cover_path, 'rb') as f:
cover_data = f.read()
audio["covr"] = [MP4Cover(cover_data, imageformat=MP4Cover.FORMAT_JPEG)]
if audio:
audio.save()
final_vtt = f"{Path(ffmpeg_final_file).stem}.vtt"
proc_vtt_path = os.path.join(session['process_dir'], final_vtt)
final_vtt_path = os.path.join(session['audiobooks_dir'], final_vtt)
shutil.move(proc_vtt_path, final_vtt_path)
return True
else:
error = process.returncode
print(error, ffmpeg_cmd)
return False
except Exception as e:
DependencyError(e)
return False
try:
session = context.get_session(id)
chapter_files = [f for f in os.listdir(session['chapters_dir']) if f.endswith(f'.{default_audio_proc_format}')]
chapter_files = sorted(chapter_files, key=lambda x: int(re.search(r'\d+', x).group()))
chapter_titles = [c[0] for c in session['chapters']]
if len(chapter_files) == 0:
print('No block files exists!')
return None
# Calculate total duration
durations = []
for file in chapter_files:
filepath = os.path.join(session['chapters_dir'], file)
durations.append(get_audio_duration(filepath))
total_duration = sum(durations)
exported_files = []
if session.get('output_split'):
part_files = []
part_chapter_indices = []
cur_part = []
cur_indices = []
cur_duration = 0
max_part_duration = session['output_split_hours'] * 3600
needs_split = total_duration > (int(session['output_split_hours']) * 2) * 3600
for idx, (file, dur) in enumerate(zip(chapter_files, durations)):
if cur_part and (cur_duration + dur > max_part_duration):
part_files.append(cur_part)
part_chapter_indices.append(cur_indices)
cur_part = []
cur_indices = []
cur_duration = 0
cur_part.append(file)
cur_indices.append(idx)
cur_duration += dur
if cur_part:
part_files.append(cur_part)
part_chapter_indices.append(cur_indices)
for part_idx, (part_file_list, indices) in enumerate(zip(part_files, part_chapter_indices)):
with tempfile.TemporaryDirectory() as tmpdir:
batch_size = 1024
chunk_list = []
for i in range(0, len(part_file_list), batch_size):
batch = part_file_list[i:i + batch_size]
txt = os.path.join(tmpdir, f'chunk_{i:04d}.txt')
out = os.path.join(tmpdir, f'chunk_{i:04d}.{default_audio_proc_format}')
with open(txt, 'w') as f:
for file in batch:
path = os.path.join(session['chapters_dir'], file).replace("\\", "/")
f.write(f"file '{path}'\n")
chunk_list.append((txt, out))
with Pool(cpu_count()) as pool:
results = pool.starmap(assemble_chunks, chunk_list)
if not all(results):
print(f"assemble_segments() One or more chunks failed for part {part_idx+1}.")
return None
# Final merge for this part
combined_chapters_file = os.path.join(
session['process_dir'],
f"{get_sanitized(session['metadata']['title'])}_part{part_idx+1}.{default_audio_proc_format}" if needs_split else f"{get_sanitized(session['metadata']['title'])}.{default_audio_proc_format}"
)
final_list = os.path.join(tmpdir, f'part_{part_idx+1:02d}_final.txt')
with open(final_list, 'w') as f:
for _, chunk_path in chunk_list:
f.write(f"file '{chunk_path.replace(os.sep, '/')}'\n")
if not assemble_chunks(final_list, combined_chapters_file):
print(f"assemble_segments() Final merge failed for part {part_idx+1}.")
return None
metadata_file = os.path.join(session['process_dir'], f'metadata_part{part_idx+1}.txt')
part_chapters = [(chapter_files[i], chapter_titles[i]) for i in indices]
generate_ffmpeg_metadata(part_chapters, session, metadata_file, default_audio_proc_format)
final_file = os.path.join(
session['audiobooks_dir'],
f"{session['final_name'].rsplit('.', 1)[0]}_part{part_idx+1}.{session['output_format']}" if needs_split else session['final_name']
)
if export_audio(combined_chapters_file, metadata_file, final_file):
exported_files.append(final_file)
else:
with tempfile.TemporaryDirectory() as tmpdir:
# 1) build a single ffmpeg file list
txt = os.path.join(tmpdir, 'all_chapters.txt')
merged_tmp = os.path.join(tmpdir, f'all.{default_audio_proc_format}')
with open(txt, 'w') as f:
for file in chapter_files:
path = os.path.join(session['chapters_dir'], file).replace("\\", "/")
f.write(f"file '{path}'\n")
# 2) merge into one temp file
if not assemble_chunks(txt, merged_tmp):
print("assemble_segments() Final merge failed.")
return None
# 3) generate metadata for entire book
metadata_file = os.path.join(session['process_dir'], 'metadata.txt')
all_chapters = list(zip(chapter_files, chapter_titles))
generate_ffmpeg_metadata(all_chapters, session, metadata_file, default_audio_proc_format)
# 4) export in one go
final_file = os.path.join(
session['audiobooks_dir'],
session['final_name']
)
if export_audio(merged_tmp, metadata_file, final_file):
exported_files.append(final_file)
return exported_files if exported_files else None
except Exception as e:
DependencyError(e)
return False
def delete_unused_tmp_dirs(web_dir, days, session):
dir_array = [
tmp_dir,
web_dir,
os.path.join(models_dir, '__sessions'),
os.path.join(voices_dir, '__sessions')
]
current_user_dirs = {
f"proc-{session['id']}",
f"web-{session['id']}",
f"voice-{session['id']}",
f"model-{session['id']}"
}
current_time = time.time()
threshold_time = current_time - (days * 24 * 60 * 60) # Convert days to seconds
for dir_path in dir_array:
if os.path.exists(dir_path) and os.path.isdir(dir_path):
for dir in os.listdir(dir_path):
if dir in current_user_dirs:
full_dir_path = os.path.join(dir_path, dir)
if os.path.isdir(full_dir_path):
try:
dir_mtime = os.path.getmtime(full_dir_path)
dir_ctime = os.path.getctime(full_dir_path)
if dir_mtime < threshold_time and dir_ctime < threshold_time:
shutil.rmtree(full_dir_path, ignore_errors=True)
msg = f"Deleted expired session: {full_dir_path}"
print(msg)
except Exception as e:
error = f"Error deleting {full_dir_path}: {e}"
print(error)
def compare_file_metadata(f1, f2):
if os.path.getsize(f1) != os.path.getsize(f2):
return False
if os.path.getmtime(f1) != os.path.getmtime(f2):
return False
return True
def get_compatible_tts_engines(language):
compatible_engines = [
tts for tts in models.keys()
if language in language_tts.get(tts, {})
]
return compatible_engines
def convert_ebook_batch(args, ctx=None):
if isinstance(args['ebook_list'], list):
ebook_list = args['ebook_list'][:]
for file in ebook_list: # Use a shallow copy
if any(file.endswith(ext) for ext in ebook_formats):
args['ebook'] = file
print(f'Processing eBook file: {os.path.basename(file)}')
progress_status, passed = convert_ebook(args, ctx)
if passed is False:
print(f'Conversion failed: {progress_status}')
sys.exit(1)
args['ebook_list'].remove(file)
reset_ebook_session(args['session'])
return progress_status, passed
else:
print(f'the ebooks source is not a list!')
sys.exit(1)
def convert_ebook(args, ctx=None):
try:
global is_gui_process, context
error = None
id = None
info_session = None
if args['language'] is not None:
if not os.path.splitext(args['ebook'])[1]:
error = f"{args['ebook']} needs a format extension."
print(error)
return error, false
if not os.path.exists(args['ebook']):
error = 'File does not exist or Directory empty.'
print(error)
return error, false
try:
if len(args['language']) == 2:
lang_array = languages.get(part1=args['language'])
if lang_array:
args['language'] = lang_array.part3
args['language_iso1'] = lang_array.part1
elif len(args['language']) == 3:
lang_array = languages.get(part3=args['language'])
if lang_array:
args['language'] = lang_array.part3
args['language_iso1'] = lang_array.part1
else:
args['language_iso1'] = None
except Exception as e:
pass
if args['language'] not in language_mapping.keys():
error = 'The language you provided is not (yet) supported'
print(error)
return error, false
if ctx is not None:
context = ctx
is_gui_process = args['is_gui_process']
id = args['session'] if args['session'] is not None else str(uuid.uuid4())
session = context.get_session(id)
session['script_mode'] = args['script_mode'] if args['script_mode'] is not None else NATIVE
session['ebook'] = args['ebook']
session['ebook_list'] = args['ebook_list']
session['device'] = args['device']
session['language'] = args['language']
session['language_iso1'] = args['language_iso1']
session['tts_engine'] = args['tts_engine'] if args['tts_engine'] is not None else get_compatible_tts_engines(args['language'])[0]
session['custom_model'] = args['custom_model'] if not is_gui_process or args['custom_model'] is None else os.path.join(session['custom_model_dir'], args['custom_model'])
session['fine_tuned'] = args['fine_tuned']
session['voice'] = args['voice']
session['temperature'] = args['temperature']
session['length_penalty'] = args['length_penalty']
session['num_beams'] = args['num_beams']
session['repetition_penalty'] = args['repetition_penalty']
session['top_k'] = args['top_k']
session['top_p'] = args['top_p']
session['speed'] = args['speed']
session['enable_text_splitting'] = args['enable_text_splitting']
session['text_temp'] = args['text_temp']
session['waveform_temp'] = args['waveform_temp']
session['audiobooks_dir'] = args['audiobooks_dir']
session['output_format'] = args['output_format']
session['output_split'] = args['output_split']
session['output_split_hours'] = args['output_split_hours'] if args['output_split_hours'] is not None else default_output_split_hours
info_session = f"\n*********** Session: {id} **************\nStore it in case of interruption, crash, reuse of custom model or custom voice,\nyou can resume the conversion with --session option"
if not is_gui_process:
session['voice_dir'] = os.path.join(voices_dir, '__sessions', f"voice-{session['id']}", session['language'])
os.makedirs(session['voice_dir'], exist_ok=True)
# As now uploaded voice files are in their respective language folder so check if no wav and bark folder are on the voice_dir root from previous versions
[shutil.move(src, os.path.join(session['voice_dir'], os.path.basename(src))) for src in glob(os.path.join(os.path.dirname(session['voice_dir']), '*.wav')) + ([os.path.join(os.path.dirname(session['voice_dir']), 'bark')] if os.path.isdir(os.path.join(os.path.dirname(session['voice_dir']), 'bark')) and not os.path.exists(os.path.join(session['voice_dir'], 'bark')) else [])]
session['custom_model_dir'] = os.path.join(models_dir, '__sessions',f"model-{session['id']}")
if session['custom_model'] is not None:
if not os.path.exists(session['custom_model_dir']):
os.makedirs(session['custom_model_dir'], exist_ok=True)
src_path = Path(session['custom_model'])
src_name = src_path.stem
if not os.path.exists(os.path.join(session['custom_model_dir'], src_name)):
required_files = models[session['tts_engine']]['internal']['files']
if analyze_uploaded_file(session['custom_model'], required_files):
model = extract_custom_model(session['custom_model'], session)
if model is not None:
session['custom_model'] = model
else:
error = f"{model} could not be extracted or mandatory files are missing"
else:
error = f'{os.path.basename(f)} is not a valid model or some required files are missing'
if session['voice'] is not None:
voice_name = get_sanitized(os.path.splitext(os.path.basename(session['voice']))[0])
final_voice_file = os.path.join(session['voice_dir'], f'{voice_name}.wav')
if not os.path.exists(final_voice_file):
extractor = VoiceExtractor(session, session['voice'], voice_name)
status, msg = extractor.extract_voice()
if status:
session['voice'] = final_voice_file
else:
error = f'VoiceExtractor.extract_voice() failed! {msg}'
print(error)
if error is None:
if session['script_mode'] == NATIVE:
bool, e = check_programs('Calibre', 'ebook-convert', '--version')
if not bool:
error = f'check_programs() Calibre failed: {e}'
bool, e = check_programs('FFmpeg', 'ffmpeg', '-version')
if not bool:
error = f'check_programs() FFMPEG failed: {e}'
if error is None:
old_session_dir = os.path.join(tmp_dir, f"ebook-{session['id']}")
session['session_dir'] = os.path.join(tmp_dir, f"proc-{session['id']}")
if os.path.isdir(old_session_dir):
os.rename(old_session_dir, session['session_dir'])
session['process_dir'] = os.path.join(session['session_dir'], f"{hashlib.md5(session['ebook'].encode()).hexdigest()}")
session['chapters_dir'] = os.path.join(session['process_dir'], "chapters")
session['chapters_dir_sentences'] = os.path.join(session['chapters_dir'], 'sentences')
if prepare_dirs(args['ebook'], session):
session['filename_noext'] = os.path.splitext(os.path.basename(session['ebook']))[0]
msg = ''
msg_extra = ''
vram_avail = get_vram()
if vram_avail <= 4:
msg_extra += 'VRAM capacity could not be detected. -' if vram_avail == 0 else 'VRAM under 4GB - '
if session['tts_engine'] == TTS_ENGINES['BARK']:
os.environ['SUNO_USE_SMALL_MODELS'] = 'True'
msg_extra += f"Switching BARK to SMALL models - "
else:
if session['tts_engine'] == TTS_ENGINES['BARK']:
os.environ['SUNO_USE_SMALL_MODELS'] = 'False'
if session['device'] == 'cuda':
session['device'] = session['device'] if torch.cuda.is_available() else 'cpu'
if session['device'] == 'cpu':
msg += f"GPU not recognized by torch! Read {default_gpu_wiki} - Switching to CPU - "
elif session['device'] == 'mps':
session['device'] = session['device'] if torch.backends.mps.is_available() else 'cpu'
if session['device'] == 'cpu':
msg += f"MPS not recognized by torch! Read {default_gpu_wiki} - Switching to CPU - "
if session['device'] == 'cpu':
if session['tts_engine'] == TTS_ENGINES['BARK']:
os.environ['SUNO_OFFLOAD_CPU'] = 'True'
if default_engine_settings[TTS_ENGINES['XTTSv2']]['use_deepspeed'] == True:
try:
import deepspeed
except:
default_engine_settings[TTS_ENGINES['XTTSv2']]['use_deepspeed'] = False
msg_extra += 'deepseed not installed or package is broken. set to False - '
else:
msg_extra += 'deepspeed detected and ready!'
if msg == '':
msg = f"Using {session['device'].upper()} - "
msg += msg_extra
if is_gui_process:
show_alert({"type": "warning", "msg": msg})
print(msg)
session['epub_path'] = os.path.join(session['process_dir'], '__' + session['filename_noext'] + '.epub')
if convert2epub(id):
epubBook = epub.read_epub(session['epub_path'], {'ignore_ncx': True})
metadata = dict(session['metadata'])
for key, value in metadata.items():
data = epubBook.get_metadata('DC', key)
if data:
for value, attributes in data:
metadata[key] = value
metadata['language'] = session['language']
metadata['title'] = metadata['title'] = metadata['title'] or Path(session['ebook']).stem.replace('_',' ')
metadata['creator'] = False if not metadata['creator'] or metadata['creator'] == 'Unknown' else metadata['creator']
session['metadata'] = metadata
try:
if len(session['metadata']['language']) == 2:
lang_array = languages.get(part1=session['language'])
if lang_array:
session['metadata']['language'] = lang_array.part3
except Exception as e:
pass
if session['metadata']['language'] != session['language']:
error = f"WARNING!!! language selected {session['language']} differs from the EPUB file language {session['metadata']['language']}"
print(error)
session['cover'] = get_cover(epubBook, session)
if session['cover']:
session['toc'], session['chapters'] = get_chapters(epubBook, session)
session['final_name'] = get_sanitized(session['metadata']['title'] + '.' + session['output_format'])
if session['chapters'] is not None:
if convert_chapters2audio(id):
msg = 'Conversion successful. Combining sentences and chapters...'
show_alert({"type": "info", "msg": msg})
exported_files = combine_audio_chapters(id)
if exported_files is not None:
chapters_dirs = [
dir_name for dir_name in os.listdir(session['process_dir'])
if fnmatch.fnmatch(dir_name, "chapters_*") and os.path.isdir(os.path.join(session['process_dir'], dir_name))
]
shutil.rmtree(os.path.join(session['voice_dir'], 'proc'), ignore_errors=True)
if is_gui_process:
if len(chapters_dirs) > 1:
if os.path.exists(session['chapters_dir']):
shutil.rmtree(session['chapters_dir'], ignore_errors=True)
if os.path.exists(session['epub_path']):
os.remove(session['epub_path'])
if os.path.exists(session['cover']):
os.remove(session['cover'])
else:
if os.path.exists(session['process_dir']):
shutil.rmtree(session['process_dir'], ignore_errors=True)
else:
if os.path.exists(session['voice_dir']):
if not any(os.scandir(session['voice_dir'])):
shutil.rmtree(session['voice_dir'], ignore_errors=True)
if os.path.exists(session['custom_model_dir']):
if not any(os.scandir(session['custom_model_dir'])):
shutil.rmtree(session['custom_model_dir'], ignore_errors=True)
if os.path.exists(session['session_dir']):
shutil.rmtree(session['session_dir'], ignore_errors=True)
progress_status = f'Audiobook(s) {", ".join(os.path.basename(f) for f in exported_files)} created!'
session['audiobook'] = exported_files[-1]
print(info_session)
return progress_status, True
else:
error = 'combine_audio_chapters() error: exported_files not created!'
else:
error = 'convert_chapters2audio() failed!'
else:
error = 'get_chapters() failed!'
else:
error = 'get_cover() failed!'
else:
error = 'convert2epub() failed!'
else:
error = f"Temporary directory {session['process_dir']} not removed due to failure."
else:
error = f"Language {args['language']} is not supported."
if session['cancellation_requested']:
error = 'Cancelled'
else:
if not is_gui_process and id is not None:
error += info_session
print(error)
return error, False
except Exception as e:
print(f'convert_ebook() Exception: {e}')
return e, False
def restore_session_from_data(data, session):
try:
for key, value in data.items():
if key in session: # Check if the key exists in session
if isinstance(value, dict) and isinstance(session[key], dict):
restore_session_from_data(value, session[key])
else:
session[key] = value
except Exception as e:
DependencyError(e)
def reset_ebook_session(id):
session = context.get_session(id)
data = {
"ebook": None,
"chapters_dir": None,
"chapters_dir_sentences": None,
"epub_path": None,
"filename_noext": None,
"chapters": None,
"cover": None,
"status": None,
"progress": 0,
"duration": 0,
"playback_time": 0,
"cancellation_requested": False,
"event": None,
"metadata": {
"title": None,
"creator": None,
"contributor": None,
"language": None,
"identifier": None,
"publisher": None,
"date": None,
"description": None,
"subject": None,
"rights": None,
"format": None,
"type": None,
"coverage": None,
"relation": None,
"Source": None,
"Modified": None
}
}
restore_session_from_data(data, session)
def get_all_ip_addresses():
ip_addresses = []
for interface, addresses in psutil.net_if_addrs().items():
for address in addresses:
if address.family == socket.AF_INET:
ip_addresses.append(address.address)
elif address.family == socket.AF_INET6:
ip_addresses.append(address.address)
return ip_addresses
def show_alert(state):
if isinstance(state, dict):
if state['type'] is not None:
if state['type'] == 'error':
gr.Error(state['msg'])
elif state['type'] == 'warning':
gr.Warning(state['msg'])
elif state['type'] == 'info':
gr.Info(state['msg'])
elif state['type'] == 'success':
gr.Success(state['msg'])
def web_interface(args, ctx):
global context, is_gui_process
context = ctx
script_mode = args['script_mode']
is_gui_process = args['is_gui_process']
is_gui_shared = args['share']
title = 'Ebook2Audiobook'
glass_mask_msg = 'Initialization, please wait...'
ebook_src = None
language_options = [
(
f"{details['name']} - {details['native_name']}" if details['name'] != details['native_name'] else details['name'],
lang
)
for lang, details in language_mapping.items()
]
voice_options = []
tts_engine_options = []
custom_model_options = []
fine_tuned_options = []
audiobook_options = []
options_output_split_hours = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12']
src_label_file = 'Select a File'
src_label_dir = 'Select a Directory'
visible_gr_tab_xtts_params = interface_component_options['gr_tab_xtts_params']
visible_gr_tab_bark_params = interface_component_options['gr_tab_bark_params']
visible_gr_group_custom_model = interface_component_options['gr_group_custom_model']
visible_gr_group_voice_file = interface_component_options['gr_group_voice_file']
theme = gr.themes.Origin(
primary_hue='green',
secondary_hue='amber',
neutral_hue='gray',
radius_size='lg',
font_mono=['JetBrains Mono', 'monospace', 'Consolas', 'Menlo', 'Liberation Mono']
)
header_css = '''
'''
with gr.Blocks(theme=theme, title=title, css=header_css, delete_cache=(86400, 86400)) as app:
with gr.Tabs(elem_id='gr_tabs'):
gr_tab_main = gr.TabItem('Main Parameters', elem_id='gr_tab_main', elem_classes='tab_item')
with gr_tab_main:
with gr.Row(elem_id='gr_row_tab_main'):
with gr.Column(elem_id='gr_col_1', scale=3):
with gr.Group(elem_id='gr1'):
gr_ebook_file = gr.File(label=src_label_file, elem_id='gr_ebook_file', file_types=ebook_formats, file_count='single', allow_reordering=True, height=140)
gr_ebook_mode = gr.Radio(label='', elem_id='gr_ebook_mode', choices=[('File','single'), ('Directory','directory')], value='single', interactive=True)
with gr.Group(elem_id='gr_group_language'):
gr_language = gr.Dropdown(label='Language', elem_id='gr_language', choices=language_options, value=default_language_code, type='value', interactive=True)
gr_group_voice_file = gr.Group(elem_id='gr_group_voice_file', visible=visible_gr_group_voice_file)
with gr_group_voice_file:
gr_voice_file = gr.File(label='*Cloning Voice Audio Fiie', elem_id='gr_voice_file', file_types=voice_formats, value=None, height=140)
gr_row_voice_player = gr.Row(elem_id='gr_row_voice_player')
with gr_row_voice_player:
gr_voice_player = gr.Audio(elem_id='gr_voice_player', type='filepath', interactive=False, show_download_button=False, container=False, visible=False, show_share_button=False, show_label=False, waveform_options=gr.WaveformOptions(show_controls=False), scale=0, min_width=60)
gr_voice_list = gr.Dropdown(label='', elem_id='gr_voice_list', choices=voice_options, type='value', interactive=True, scale=2)
gr_voice_del_btn = gr.Button('🗑', elem_id='gr_voice_del_btn', elem_classes=['small-btn'], variant='secondary', interactive=True, visible=False, scale=0, min_width=60)
gr_optional_markdown = gr.Markdown(elem_id='gr_markdown_optional', value='
')
with gr.Group(elem_id='gr_group_output_format'):
with gr.Row(elem_id='gr_row_output_format'):
gr_output_format_list = gr.Dropdown(label='Output Format', elem_id='gr_output_format_list', choices=output_formats, type='value', value=default_output_format, interactive=True, scale=2)
gr_output_split = gr.Checkbox(label='Split Output File', elem_id='gr_output_split', value=default_output_split, interactive=True, scale=1)
gr_output_split_hours = gr.Dropdown(label='Max hours / part', elem_id='gr_output_split_hours', choices=options_output_split_hours, type='value', value=default_output_split_hours, interactive=True, visible=False, scale=2)
gr_session = gr.Textbox(label='Session', elem_id='gr_session', interactive=False)
gr_tab_xtts_params = gr.TabItem('XTTSv2 Fine Tuned Parameters', elem_id='gr_tab_xtts_params', elem_classes='tab_item', visible=visible_gr_tab_xtts_params)
with gr_tab_xtts_params:
gr.Markdown(
elem_id='gr_markdown_tab_xtts_params',
value='''
### Customize XTTSv2 Parameters
Adjust the settings below to influence how the audio is generated. You can control the creativity, speed, repetition, and more.
'''
)
gr_xtts_temperature = gr.Slider(
label='Temperature',
minimum=0.05,
maximum=10.0,
step=0.05,
value=float(default_engine_settings[TTS_ENGINES['XTTSv2']]['temperature']),
elem_id='gr_xtts_temperature',
info='Higher values lead to more creative, unpredictable outputs. Lower values make it more monotone.'
)
gr_xtts_length_penalty = gr.Slider(
label='Length Penalty',
minimum=0.3,
maximum=5.0,
step=0.1,
value=float(default_engine_settings[TTS_ENGINES['XTTSv2']]['length_penalty']),
elem_id='gr_xtts_length_penalty',
info='Adjusts how much longer sequences are preferred. Higher values encourage the model to produce longer and more natural speech.',
visible=False
)
gr_xtts_num_beams = gr.Slider(
label='Number Beams',
minimum=1,
maximum=10,
step=1,
value=int(default_engine_settings[TTS_ENGINES['XTTSv2']]['num_beams']),
elem_id='gr_xtts_num_beams',
info='Controls how many alternative sequences the model explores. Higher values improve speech coherence and pronunciation but increase inference time.',
visible=False
)
gr_xtts_repetition_penalty = gr.Slider(
label='Repetition Penalty',
minimum=1.0,
maximum=10.0,
step=0.1,
value=float(default_engine_settings[TTS_ENGINES['XTTSv2']]['repetition_penalty']),
elem_id='gr_xtts_repetition_penalty',
info='Penalizes repeated phrases. Higher values reduce repetition.'
)
gr_xtts_top_k = gr.Slider(
label='Top-k Sampling',
minimum=10,
maximum=100,
step=1,
value=int(default_engine_settings[TTS_ENGINES['XTTSv2']]['top_k']),
elem_id='gr_xtts_top_k',
info='Lower values restrict outputs to more likely words and increase speed at which audio generates.'
)
gr_xtts_top_p = gr.Slider(
label='Top-p Sampling',
minimum=0.1,
maximum=1.0,
step=0.01,
value=float(default_engine_settings[TTS_ENGINES['XTTSv2']]['top_p']),
elem_id='gr_xtts_top_p',
info='Controls cumulative probability for word selection. Lower values make the output more predictable and increase speed at which audio generates.'
)
gr_xtts_speed = gr.Slider(
label='Speed',
minimum=0.5,
maximum=3.0,
step=0.1,
value=float(default_engine_settings[TTS_ENGINES['XTTSv2']]['speed']),
elem_id='gr_xtts_speed',
info='Adjusts how fast the narrator will speak.'
)
gr_xtts_enable_text_splitting = gr.Checkbox(
label='Enable Text Splitting',
value=default_engine_settings[TTS_ENGINES['XTTSv2']]['enable_text_splitting'],
elem_id='gr_xtts_enable_text_splitting',
info='Coqui-tts builtin text splitting. Can help against hallucinations bu can also be worse.',
visible=False
)
gr_tab_bark_params = gr.TabItem('BARK fine Tuned Parameters', elem_id='gr_tab_bark_params', elem_classes='tab_item', visible=visible_gr_tab_bark_params)
with gr_tab_bark_params:
gr.Markdown(
elem_id='gr_markdown_tab_bark_params',
value='''
### Customize BARK Parameters
Adjust the settings below to influence how the audio is generated, emotional and voice behavior random or more conservative
'''
)
gr_bark_text_temp = gr.Slider(
label='Text Temperature',
minimum=0.0,
maximum=1.0,
step=0.01,
value=float(default_engine_settings[TTS_ENGINES['BARK']]['text_temp']),
elem_id='gr_bark_text_temp',
info='Higher values lead to more creative, unpredictable outputs. Lower values make it more conservative.'
)
gr_bark_waveform_temp = gr.Slider(
label='Waveform Temperature',
minimum=0.0,
maximum=1.0,
step=0.01,
value=float(default_engine_settings[TTS_ENGINES['BARK']]['waveform_temp']),
elem_id='gr_bark_waveform_temp',
info='Higher values lead to more creative, unpredictable outputs. Lower values make it more conservative.'
)
gr_state_update = gr.State(value={"hash": None})
gr_read_data = gr.JSON(visible=False, elem_id='gr_read_data')
gr_write_data = gr.JSON(visible=False, elem_id='gr_write_data')
gr_tab_progress = gr.Textbox(elem_id='gr_tab_progress', label='Progress', interactive=False)
gr_group_audiobook_list = gr.Group(elem_id='gr_group_audiobook_list', visible=False)
with gr_group_audiobook_list:
gr_audiobook_vtt = gr.Textbox(elem_id='gr_audiobook_vtt', label='', interactive=False, visible=False)
gr_audiobook_sentence = gr.Textbox(elem_id='gr_audiobook_sentence', label='Audiobook', value='...', interactive=False, visible=True, lines=3, max_lines=3)
gr_audiobook_player = gr.Audio(elem_id='gr_audiobook_player', label='',type='filepath', autoplay=False, waveform_options=gr.WaveformOptions(show_recording_waveform=False), show_download_button=False, show_share_button=False, container=True, interactive=False, visible=True)
gr_audiobook_player_playback_time = gr.Number(label='', interactive=False, visible=True, elem_id="gr_audiobook_player_playback_time", value=0.0)
with gr.Row(elem_id='gr_row_audiobook_list'):
gr_audiobook_download_btn = gr.DownloadButton(elem_id='gr_audiobook_download_btn', label='↧', elem_classes=['small-btn'], variant='secondary', interactive=True, visible=True, scale=0, min_width=60)
gr_audiobook_list = gr.Dropdown(elem_id='gr_audiobook_list', label='', choices=audiobook_options, type='value', interactive=True, visible=True, scale=2)
gr_audiobook_del_btn = gr.Button(elem_id='gr_audiobook_del_btn', value='🗑', elem_classes=['small-btn'], variant='secondary', interactive=True, visible=True, scale=0, min_width=60)
gr_convert_btn = gr.Button(elem_id='gr_convert_btn', value='📚', elem_classes='icon-btn', variant='primary', interactive=False)
gr_modal = gr.HTML(visible=False)
gr_glass_mask = gr.HTML(f'
{glass_mask_msg}
')
gr_confirm_field_hidden = gr.Textbox(elem_id='confirm_hidden', visible=False)
gr_confirm_yes_btn = gr.Button(elem_id='confirm_yes_btn', value='', visible=False)
gr_confirm_no_btn = gr.Button(elem_id='confirm_no_btn', value='', visible=False)
def cleanup_session(req: gr.Request):
socket_hash = req.session_hash
if any(socket_hash in session for session in context.sessions.values()):
session_id = context.find_id_by_hash(socket_hash)
ctx_tracker.end_session(session_id, socket_hash)
def load_vtt_data(path):
if not path or not os.path.exists(path):
return None
try:
vtt_path = Path(path).with_suffix('.vtt')
if not os.path.exists(vtt_path):
return None
with open(vtt_path, "r", encoding="utf-8-sig", errors="replace") as f:
content = f.read()
return content
except Exception:
return None
def show_modal(type, msg):
return f'''
{msg}
{show_confirm() if type == 'confirm' else ''}
'''
def show_confirm():
return '''
'''
def show_rating(tts_engine):
def yellow_stars(n):
return "".join(
"★" for _ in range(n)
)
def color_box(value):
if value <= 4:
color = "#4CAF50" # Green = low
elif value <= 8:
color = "#FF9800" # Orange = medium
else:
color = "#F44336" # Red = high
return f"{value} GB"
rating = default_engine_settings[tts_engine]['rating']
return f"""