Add text chunking and Persian language helpers
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TG_LIMIT = 4096
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def chunk_text(text: str, max_length: int = TG_LIMIT) -> list[str]:
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"""Split text into ≤max_length chunks, preferring newline then space boundaries."""
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if len(text) <= max_length:
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return [text]
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chunks: list[str] = []
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while text:
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if len(text) <= max_length:
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chunks.append(text)
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break
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split_at = text.rfind('\n', 0, max_length)
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if split_at == -1:
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split_at = text.rfind(' ', 0, max_length)
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if split_at == -1:
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split_at = max_length
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chunk = text[:split_at].strip()
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if chunk:
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chunks.append(chunk)
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text = text[split_at:].strip()
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return chunks
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import re
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import unicodedata
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# Normalize Arabic lookalikes to Persian
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_ARABIC_TO_PERSIAN = str.maketrans({
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'ي': 'ی', # Arabic ya → Persian ya
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'ك': 'ک', # Arabic kaf → Persian kaf
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'ى': 'ی', # Alef maqsura → Persian ya
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})
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_PUPPY_RE = re.compile(r'puppy|پاپی|پاپي', re.IGNORECASE | re.UNICODE)
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# Rough threshold: if >15% of chars are Arabic/Persian script → Persian
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_PERSIAN_BLOCK = re.compile(r'[-ۿ]')
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def normalize(text: str) -> str:
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text = unicodedata.normalize('NFC', text)
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text = text.translate(_ARABIC_TO_PERSIAN)
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text = text.replace('', '').replace('', '') # ZWNJ / ZWJ
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return text
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def is_puppy_mentioned(text: str) -> bool:
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if not text:
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return False
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return bool(_PUPPY_RE.search(normalize(text)))
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def detect_language(text: str) -> str:
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if not text:
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return 'en'
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persian_count = len(_PERSIAN_BLOCK.findall(text))
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return 'fa' if persian_count > len(text) * 0.15 else 'en'
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def strip_puppy_prefix(text: str) -> str:
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"""Remove 'Puppy/پاپی' name prefix from a command-style message."""
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cleaned = re.sub(
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r'^[\s]*(puppy|پاپی|پاپي)[،,:\s]+',
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'',
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normalize(text),
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flags=re.IGNORECASE | re.UNICODE,
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)
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return cleaned.strip() or text.strip()
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