fix: 彻底移除MT批处理,qwen-mt模型会破坏所有文本分隔符
日志证实: \n\n---\n\n分隔符被MT模型破坏率82%(28/34批次) MT模型逐条翻译是唯一可靠方案,无法批处理 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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@@ -182,47 +182,6 @@ class SegmentsTranslateAgent(Agent):
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logger.error(f"原始prompt也不是有效的json格式: {original_segments}")
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return {"error": f"{original_segments}"}
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MT_BATCH_SEP = "\n\n---\n\n"
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def _batch_segments_for_mt(self, segments: list[str], chunk_size: int) -> tuple[list[str], list[list[int]]]:
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"""将 segments 按字符数分批,用分隔符连接。返回(批文本列表, 每批的索引列表)。"""
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batches = []
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index_groups = []
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current_parts = []
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current_indices = []
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current_size = 0
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sep = self.MT_BATCH_SEP
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sep_size = len(sep.encode('utf-8'))
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for i, seg in enumerate(segments):
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seg_size = len(seg.encode('utf-8'))
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add_size = (sep_size if current_parts else 0) + seg_size
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if current_parts and current_size + add_size > chunk_size:
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batches.append(sep.join(current_parts))
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index_groups.append(current_indices)
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current_parts = [seg]
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current_indices = [i]
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current_size = seg_size
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else:
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current_parts.append(seg)
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current_indices.append(i)
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current_size += add_size
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if current_parts:
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batches.append(sep.join(current_parts))
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index_groups.append(current_indices)
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return batches, index_groups
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def _mt_batch_result_handler(self, result: str, origin_prompt: str, logger: Logger) -> list[str]:
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"""MT batch: 按分隔符拆分翻译结果。"""
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return [p.strip() for p in result.strip().split(self.MT_BATCH_SEP)]
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def _mt_batch_error_handler(self, origin_prompt: str, logger: Logger) -> list[str]:
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"""MT batch error: 返回原文各段。"""
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return [p.strip() for p in origin_prompt.split(self.MT_BATCH_SEP)]
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def _mt_individual_result_handler(self, result: str, origin_prompt: str, logger: Logger) -> str:
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"""MT individual: 直接返回翻译结果。"""
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return result.strip()
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@@ -276,22 +235,15 @@ class SegmentsTranslateAgent(Agent):
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def send_segments(self, segments: list[str], chunk_size: int) -> list[str]:
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if self.is_mt_mode:
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# MT models (qwen-mt-*) destroy ALL text separators — batching is impossible.
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# Each segment must be sent individually for 100% reliable 1:1 mapping.
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if not segments:
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return []
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batch_texts, batch_indices = self._batch_segments_for_mt(segments, chunk_size)
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batch_results = super().send_prompts(
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prompts=batch_texts,
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result_handler=self._mt_batch_result_handler,
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error_result_handler=self._mt_batch_error_handler,
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return super().send_prompts(
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prompts=segments,
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result_handler=self._mt_individual_result_handler,
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error_result_handler=self._mt_individual_error_handler,
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)
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all_translated, mismatched = self._apply_mt_batch_results(
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segments, batch_results, batch_indices
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)
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if mismatched:
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retranslated = self._retranslate_mismatched(segments, mismatched)
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for idx, trans in retranslated.items():
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all_translated[idx] = trans
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return all_translated
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# Non-MT mode: JSON batch translation
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indexed_originals, chunks, merged_indices_list = segments2json_chunks(segments, chunk_size)
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@@ -331,26 +283,14 @@ class SegmentsTranslateAgent(Agent):
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async def send_segments_async(self, segments: list[str], chunk_size: int) -> list[str]:
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if self.is_mt_mode:
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# MT models destroy ALL text separators — each segment must be sent individually.
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if not segments:
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return []
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batch_texts, batch_indices = await asyncio.to_thread(
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self._batch_segments_for_mt, segments, chunk_size
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return await super().send_prompts_async(
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prompts=segments,
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result_handler=self._mt_individual_result_handler,
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error_result_handler=self._mt_individual_error_handler,
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)
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batch_results = await super().send_prompts_async(
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prompts=batch_texts,
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result_handler=self._mt_batch_result_handler,
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error_result_handler=self._mt_batch_error_handler,
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)
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all_translated, mismatched = self._apply_mt_batch_results(
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segments, batch_results, batch_indices
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)
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if mismatched:
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retranslated = await asyncio.to_thread(
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self._retranslate_mismatched, segments, mismatched
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)
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for idx, trans in retranslated.items():
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all_translated[idx] = trans
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return all_translated
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# Non-MT mode: JSON batch translation
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indexed_originals, chunks, merged_indices_list = await asyncio.to_thread(segments2json_chunks, segments,
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