fix: Enhance author handling in metadata payload and add currency conversion support in normalization

abogen/integrations/audiobookshelf.py

@@ -156,6 +156,14 @@ class AudiobookshelfClient:
             metadata_payload["chapters"] = list(chapters)
 
         if metadata_payload:
+            # Ensure authors is a list of strings in the JSON payload if it exists
+            if "authors" in metadata_payload:
+                authors_val = metadata_payload["authors"]
+                if isinstance(authors_val, str):
+                    metadata_payload["authors"] = [a.strip() for a in authors_val.split(",") if a.strip()]
+                elif isinstance(authors_val, list):
+                    metadata_payload["authors"] = [str(a).strip() for a in authors_val if str(a).strip()]
+
             try:
                 fields["metadata"] = json.dumps(metadata_payload, ensure_ascii=False)
             except (TypeError, ValueError):
@@ -603,6 +611,7 @@ class AudiobookshelfClient:
         if isinstance(authors, Iterable) and not isinstance(authors, (str, Mapping)):
             names = [str(entry).strip() for entry in authors if isinstance(entry, str) and entry.strip()]
             if names:
+                # ABS expects a comma-separated string for multiple authors.
                 return ", ".join(names)
         return ""
 

abogen/kokoro_text_normalization.py

@@ -6,10 +6,20 @@ import unicodedata
 from fractions import Fraction
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple
+import logging
+
+logger = logging.getLogger(__name__)
+
 try:  # pragma: no cover - optional dependency guard
     from num2words import num2words
-except Exception:  # pragma: no cover - graceful degradation
-    num2words = None  # type: ignore
+except ImportError:
+    num2words = None
+    logger.warning("num2words library not found. Number normalization will be disabled.")
+except Exception as e:  # pragma: no cover - graceful degradation
+    num2words = None
+    logger.error(f"Failed to import num2words: {e}")
+
+HAS_NUM2WORDS = num2words is not None
 
 if TYPE_CHECKING:  # pragma: no cover - type checking only
     from abogen.llm_client import LLMCompletion
@@ -48,6 +58,7 @@ class ApostropheConfig:
     lowercase_for_matching: bool = True           # Normalize to lower for rule matching (not output)
     protect_cultural_names: bool = True           # Always keep O'Brien, D'Angelo, etc.
     convert_numbers: bool = True                  # Convert grouped numbers such as 12,500 to words
+    convert_currency: bool = True                 # Convert currency symbols to words
     number_lang: str = "en"                       # num2words language code
     year_pronunciation_mode: str = "american"     # off|american (extend if needed)
     contraction_categories: Dict[str, bool] = field(default_factory=lambda: dict(CONTRACTION_CATEGORY_DEFAULTS))
@@ -107,6 +118,11 @@ _FRACTION_SLASH_CLASS = re.escape(_FRACTION_SLASHES)
 _FRACTION_RE = re.compile(
     rf"(?<!\w)(?P<numerator>-?\d+)\s*[{_FRACTION_SLASH_CLASS}]\s*(?P<denominator>-?\d+)(?![\w{_FRACTION_SLASH_CLASS}])"
 )
+
+_CURRENCY_RE = re.compile(
+    r"(?P<symbol>[$£€¥])\s*(?P<amount>\d{1,3}(?:,\d{3})*(?:\.\d{1,2})?)(?!\d)"
+)
+
 _DECIMAL_NUMBER_RE = re.compile(
     rf"(?<![\w{_NUMBER_RANGE_CLASS}/])(?P<number>-?(?:\d{{1,3}}(?:,\d{{3}})+|\d+)\.(?P<fraction>\d+))(?![\w{_NUMBER_RANGE_CLASS}/])"
 )
@@ -1478,7 +1494,34 @@ def _normalize_grouped_numbers(text: str, cfg: ApostropheConfig) -> str:
         spoken = f"{integer_words} point {' '.join(digit_words)}"
         return f"minus {spoken}" if is_negative else spoken
 
+    def _replace_currency(match: re.Match[str]) -> str:
+        if num2words is None:
+            return match.group(0)
+            
+        symbol = match.group("symbol")
+        amount_str = match.group("amount").replace(",", "")
+        try:
+            amount = float(amount_str)
+        except ValueError:
+            return match.group(0)
+
+        currency_map = {
+            "$": "USD",
+            "£": "GBP",
+            "€": "EUR",
+            "¥": "JPY",
+        }
+        currency_code = currency_map.get(symbol, "USD")
+        
+        try:
+            words = num2words(amount, to="currency", currency=currency_code, lang=language)
+            return words
+        except Exception:
+            return match.group(0)
+
     normalized = text
+    if cfg.convert_currency:
+        normalized = _CURRENCY_RE.sub(_replace_currency, normalized)
     normalized = _NUMBER_RANGE_RE.sub(lambda m: _replace_number_range(m, language), normalized)
     normalized = _NUMBER_SPACE_RANGE_RE.sub(lambda m: _replace_space_separated_range(m, language), normalized)
     normalized = _FRACTION_RE.sub(lambda m: _replace_fraction(m, language), normalized)

abogen/normalization_settings.py

@@ -32,6 +32,7 @@ _SETTINGS_DEFAULTS: Dict[str, Any] = {
     "llm_context_mode": "sentence",
     "normalization_numbers": True,
     "normalization_numbers_year_style": "american",
+    "normalization_currency": True,
     "normalization_titles": True,
     "normalization_terminal": True,
     "normalization_phoneme_hints": True,
@@ -172,6 +173,7 @@ def build_apostrophe_config(
 ) -> ApostropheConfig:
     config = replace(base or ApostropheConfig())
     config.convert_numbers = bool(settings.get("normalization_numbers", True))
+    config.convert_currency = bool(settings.get("normalization_currency", True))
     config.year_pronunciation_mode = str(settings.get("normalization_numbers_year_style", "american") or "").strip().lower()
     config.add_phoneme_hints = bool(settings.get("normalization_phoneme_hints", True))
     config.contraction_mode = "expand" if settings.get("normalization_apostrophes_contractions", True) else "keep"

abogen/web/conversion_runner.py

@@ -22,7 +22,7 @@ import static_ffmpeg
 
 from abogen.constants import VOICES_INTERNAL
 from abogen.epub3.exporter import build_epub3_package
-from abogen.kokoro_text_normalization import ApostropheConfig, normalize_for_pipeline
+from abogen.kokoro_text_normalization import ApostropheConfig, normalize_for_pipeline, HAS_NUM2WORDS
 from abogen.normalization_settings import (
     build_apostrophe_config,
     build_llm_configuration,
@@ -125,7 +125,30 @@ def _simplify_heading_text(text: str) -> str:
 def _headings_equivalent(left: str, right: str) -> bool:
     simple_left = _simplify_heading_text(left)
     simple_right = _simplify_heading_text(right)
-    return bool(simple_left and simple_left == simple_right)
+    if not simple_left or not simple_right:
+        return False
+    
+    # Exact match
+    if simple_left == simple_right:
+        return True
+        
+    # Check if one is a prefix of the other (e.g. "Chapter 2" vs "Chapter 2: The Return")
+    # But be careful not to match "Chapter 1" with "Chapter 10"
+    # _simplify_heading_text removes "chapter" prefix, so we are comparing "2" vs "2thereturn"
+    
+    # If left is "2" and right is "2thereturn", left is prefix of right.
+    if simple_right.startswith(simple_left):
+        return True
+        
+    # If left is "2thereturn" and right is "2", right is prefix of left.
+    if simple_left.startswith(simple_right):
+        return True
+        
+    # Also check if the line is contained in the heading if it's long enough
+    if len(simple_left) > 5 and simple_left in simple_right:
+        return True
+        
+    return False
 
 
 def _format_spoken_chapter_title(title: str, index: int, apply_prefix: bool) -> str:
@@ -1247,6 +1270,15 @@ def run_conversion_job(job: Job) -> None:
         settings=normalization_settings,
         base=_APOSTROPHE_CONFIG,
     )
+    
+    if apostrophe_config.convert_numbers and not HAS_NUM2WORDS:
+        job.add_log(
+            "Number normalization is enabled but 'num2words' library is not available. "
+            "Numbers (including years) will NOT be converted to words. "
+            "Please install 'num2words' to enable this feature.",
+            level="warning"
+        )
+
     apostrophe_mode = str(normalization_settings.get("normalization_apostrophe_mode", "spacy")).lower()
     if apostrophe_mode == "llm":
         llm_config = build_llm_configuration(normalization_settings)