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89b6a21 127bfda 89b6a21 127bfda 89b6a21 127bfda 89b6a21 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | import re
from bot.byte_semantics_base import compact_message, format_chat_reply, normalize_text_for_scene
from bot.byte_semantics_constants import (
MAX_CHAT_MESSAGE_LENGTH,
MOVIE_TITLE_QUOTE_PATTERN,
MULTIPART_SEPARATOR,
)
def split_text_for_chat(
text: str, max_len: int = MAX_CHAT_MESSAGE_LENGTH, max_parts: int = 2
) -> list[str]:
clean_text = (text or "").strip()
if not clean_text:
return []
if len(clean_text) <= max_len:
return [clean_text]
parts: list[str] = []
remaining = clean_text
while remaining and len(parts) < max_parts:
if len(remaining) <= max_len:
parts.append(remaining.strip())
remaining = ""
break
cut = remaining.rfind("\n", 0, max_len + 1)
if cut < int(max_len * 0.5):
sentence_cuts = [
remaining.rfind(symbol, 0, max_len + 1) for symbol in (". ", "? ", "! ")
]
cut = max(sentence_cuts)
if cut < int(max_len * 0.5):
cut = remaining.rfind(" ", 0, max_len + 1)
if cut <= 0:
cut = max_len
chunk = remaining[:cut].strip()
if chunk:
parts.append(chunk)
remaining = remaining[cut:].strip()
if remaining:
if parts:
parts[-1] = compact_message(f"{parts[-1]} {remaining}", max_len=max_len)
else:
parts.append(compact_message(remaining, max_len=max_len))
return [part for part in parts if part][:max_parts]
def extract_multi_reply_parts(answer_text: str, max_parts: int = 2) -> list[str]:
if not answer_text:
return []
raw_parts = [
segment.strip() for segment in answer_text.split(MULTIPART_SEPARATOR) if segment.strip()
]
if len(raw_parts) >= 2:
normalized = [format_chat_reply(part) for part in raw_parts[:max_parts]]
return [part for part in normalized if part]
chunks = split_text_for_chat(answer_text, max_len=MAX_CHAT_MESSAGE_LENGTH, max_parts=max_parts)
normalized = [format_chat_reply(chunk) for chunk in chunks]
return [part for part in normalized if part]
def extract_movie_title(prompt: str) -> str:
quote_match = MOVIE_TITLE_QUOTE_PATTERN.search(prompt or "")
if quote_match:
return normalize_text_for_scene(quote_match.group("title"), max_len=80)
candidate_match = re.search(
r"ficha\s*t[eé]cnica(?:\s+(?:do|da|de)\s+filme)?(?:\s+(?:do|da|de))?\s+(?P<title>.+)$",
prompt or "",
re.IGNORECASE,
)
if not candidate_match:
return ""
candidate = candidate_match.group("title").strip(" ?!.:,;")
if not candidate:
return ""
lowered = candidate.lower()
generic_fragments = (
"que estamos vendo",
"que estamos assistindo",
"que estamos assistindo hoje",
"agora",
)
if any(fragment in lowered for fragment in generic_fragments):
return ""
if lowered in {"filme", "hoje", "agora"}:
return ""
return normalize_text_for_scene(candidate, max_len=80)
def build_movie_fact_sheet_query(movie_title: str) -> str:
return (
f"Monte uma ficha tecnica objetiva do filme '{movie_title}' para chat Twitch. "
"Responda em no maximo 4 linhas, sem markdown, com alta densidade e sem enrolacao. "
"Formato obrigatorio: "
"1) Titulo | Ano | Pais. "
"2) Direcao | Genero | Duracao. "
"3) Elenco principal (ate 3 nomes). "
"4) Nota media | Premios-chave (ou N/D). "
"Se nao houver confianca em algum dado, escreva N/D."
)
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