838 lines
36 KiB
Python
838 lines
36 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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翻譯服務
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Author: PANJIT IT Team
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Created: 2024-01-28
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Modified: 2024-01-28
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"""
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import hashlib
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import time
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from pathlib import Path
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from typing import List, Dict, Any, Optional, Tuple
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from app.utils.logger import get_logger
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from app.utils.exceptions import TranslationError, FileProcessingError
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from app.services.dify_client import DifyClient
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from app.services.document_processor import DocumentProcessor, Segment
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from app.models.cache import TranslationCache
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from app.models.job import TranslationJob
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from app.utils.helpers import generate_filename, create_job_directory
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logger = get_logger(__name__)
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class DocumentParser:
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"""文件解析器基類"""
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def __init__(self, file_path: str):
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self.file_path = Path(file_path)
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if not self.file_path.exists():
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raise FileProcessingError(f"檔案不存在: {file_path}")
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def extract_text_segments(self) -> List[str]:
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"""提取文字片段"""
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raise NotImplementedError
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def generate_translated_document(self, translations: Dict[str, List[str]],
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target_language: str, output_dir: Path) -> str:
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"""生成翻譯後的文件"""
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raise NotImplementedError
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class DocxParser(DocumentParser):
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"""DOCX 文件解析器 - 使用增強的 DocumentProcessor"""
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def __init__(self, file_path: str):
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super().__init__(file_path)
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self.processor = DocumentProcessor()
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def extract_text_segments(self) -> List[str]:
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"""提取 DOCX 文件的文字片段 - 使用增強邏輯"""
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try:
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# 使用新的文檔處理器提取段落
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segments = self.processor.extract_docx_segments(str(self.file_path))
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# 轉換為文字列表
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text_segments = []
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for seg in segments:
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if seg.text.strip() and len(seg.text.strip()) > 3:
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text_segments.append(seg.text)
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logger.info(f"Enhanced extraction: {len(text_segments)} text segments from DOCX")
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return text_segments
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except Exception as e:
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logger.error(f"Failed to extract text from DOCX: {str(e)}")
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raise FileProcessingError(f"DOCX 文件解析失敗: {str(e)}")
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def extract_segments_with_context(self) -> List[Segment]:
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"""提取帶上下文的段落資訊"""
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return self.processor.extract_docx_segments(str(self.file_path))
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def generate_translated_document(self, translations: Dict[str, List[str]],
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target_language: str, output_dir: Path) -> str:
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"""生成翻譯後的 DOCX 文件 - 使用增強的翻譯插入邏輯"""
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try:
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# 生成輸出檔名
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output_filename = generate_filename(
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self.file_path.name,
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'translated',
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'translated',
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target_language
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)
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output_path = output_dir / output_filename
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# 提取段落資訊
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segments = self.extract_segments_with_context()
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# 建立翻譯映射
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translation_map = {}
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translated_texts = translations.get(target_language, [])
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# 對應文字段落與翻譯
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text_index = 0
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for seg in segments:
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if text_index < len(translated_texts):
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translation_map[(target_language, seg.text)] = translated_texts[text_index]
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text_index += 1
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# 使用增強的翻譯插入邏輯
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ok_count, skip_count = self.processor.insert_docx_translations(
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str(self.file_path),
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segments,
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translation_map,
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[target_language],
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str(output_path)
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)
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logger.info(f"Enhanced translation: Generated {output_path} with {ok_count} insertions, {skip_count} skips")
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return str(output_path)
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except Exception as e:
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logger.error(f"Failed to generate translated DOCX: {str(e)}")
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raise FileProcessingError(f"生成翻譯 DOCX 失敗: {str(e)}")
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class DocParser(DocumentParser):
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"""DOC 文件解析器 - 需要先轉換為 DOCX"""
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def extract_text_segments(self) -> List[str]:
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"""提取 DOC 文件的文字片段 - 先轉換為 DOCX 再處理"""
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try:
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# 檢查是否有 Word COM 支援
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import tempfile
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import os
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try:
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import win32com.client as win32
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import pythoncom
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_WIN32COM_AVAILABLE = True
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except ImportError:
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_WIN32COM_AVAILABLE = False
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if not _WIN32COM_AVAILABLE:
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raise FileProcessingError("DOC 格式需要 Word COM 支援，請先手動轉換為 DOCX 格式或安裝 Microsoft Office")
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# 創建臨時 DOCX 文件
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temp_docx = None
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try:
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with tempfile.NamedTemporaryFile(suffix='.docx', delete=False) as tmp:
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temp_docx = tmp.name
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# 使用 Word COM 轉換 DOC 到 DOCX (格式 16)
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self._word_convert(str(self.file_path), temp_docx, 16)
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# 使用 DOCX 解析器處理轉換後的文件
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docx_parser = DocxParser(temp_docx)
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segments = docx_parser.extract_text_segments()
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logger.info(f"Converted DOC to DOCX and extracted {len(segments)} segments")
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return segments
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finally:
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# 清理臨時文件
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if temp_docx and os.path.exists(temp_docx):
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try:
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os.remove(temp_docx)
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except Exception:
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pass
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except Exception as e:
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logger.error(f"Failed to extract text from DOC file: {str(e)}")
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raise FileProcessingError(f"DOC 文件解析失敗: {str(e)}")
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def _word_convert(self, input_path: str, output_path: str, target_format: int):
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"""使用 Word COM 轉換文件格式（移植自參考檔案）"""
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try:
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import win32com.client as win32
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import pythoncom
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pythoncom.CoInitialize()
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try:
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word = win32.Dispatch("Word.Application")
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word.Visible = False
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doc = word.Documents.Open(os.path.abspath(input_path))
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doc.SaveAs2(os.path.abspath(output_path), FileFormat=target_format)
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doc.Close(False)
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finally:
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word.Quit()
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pythoncom.CoUninitialize()
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except Exception as e:
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raise FileProcessingError(f"Word COM 轉換失敗: {str(e)}")
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def generate_translated_document(self, translations: Dict[str, List[str]],
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target_language: str, output_dir: Path) -> str:
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"""生成翻譯後的 DOC 文件 - 先轉為 DOCX 處理後輸出為 DOCX"""
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try:
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import tempfile
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import os
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# 先轉換為 DOCX，然後使用 DOCX 處理邏輯
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temp_docx = None
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try:
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with tempfile.NamedTemporaryFile(suffix='.docx', delete=False) as tmp:
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temp_docx = tmp.name
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# 轉換 DOC 到 DOCX
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self._word_convert(str(self.file_path), temp_docx, 16)
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# 使用 DOCX 解析器生成翻譯文檔
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docx_parser = DocxParser(temp_docx)
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# 注意：最終輸出為 DOCX 格式，因為 DOC 格式較難直接處理
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output_filename = f"{self.file_path.stem}_{target_language}_translated.docx"
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output_path = output_dir / output_filename
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result_path = docx_parser.generate_translated_document(translations, target_language, output_dir)
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logger.info(f"Generated translated DOC file (as DOCX): {result_path}")
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return result_path
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finally:
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# 清理臨時文件
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if temp_docx and os.path.exists(temp_docx):
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try:
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os.remove(temp_docx)
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except Exception:
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pass
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except Exception as e:
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logger.error(f"Failed to generate translated DOC file: {str(e)}")
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raise FileProcessingError(f"DOC 翻譯檔生成失敗: {str(e)}")
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class ExcelParser(DocumentParser):
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"""Excel 文件解析器（XLSX/XLS）- 移植自參考檔案"""
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def extract_text_segments(self) -> List[str]:
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"""提取 Excel 文件的文字片段"""
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try:
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import openpyxl
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from openpyxl.utils.exceptions import InvalidFileException
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# 載入工作簿（移植自參考檔案邏輯）
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try:
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wb = openpyxl.load_workbook(str(self.file_path), data_only=False)
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wb_vals = openpyxl.load_workbook(str(self.file_path), data_only=True)
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except InvalidFileException:
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if self.file_path.suffix.lower() == '.xls':
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raise FileProcessingError("XLS 格式需要先轉換為 XLSX 格式")
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raise
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except Exception:
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wb_vals = None
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# 提取文字段落（完全按照參考檔案的邏輯）
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segs = []
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for ws in wb.worksheets:
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ws_vals = wb_vals[ws.title] if wb_vals and ws.title in wb_vals.sheetnames else None
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max_row, max_col = ws.max_row, ws.max_column
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for r in range(1, max_row + 1):
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for c in range(1, max_col + 1):
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src_text = self._get_display_text_for_translation(ws, ws_vals, r, c)
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if not src_text:
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continue
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if not self._should_translate(src_text, 'auto'):
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continue
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segs.append(src_text)
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# 去重保持順序
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unique_segments = []
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seen = set()
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for seg in segs:
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if seg not in seen:
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unique_segments.append(seg)
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seen.add(seg)
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logger.info(f"Extracted {len(unique_segments)} unique text segments from Excel file")
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return unique_segments
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except Exception as e:
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logger.error(f"Failed to extract text from Excel file: {str(e)}")
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raise FileProcessingError(f"Excel 文件解析失敗: {str(e)}")
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def _get_display_text_for_translation(self, ws, ws_vals, r: int, c: int) -> Optional[str]:
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"""取得儲存格用於翻譯的顯示文字（完全移植自參考檔案）"""
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val = ws.cell(row=r, column=c).value
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if isinstance(val, str) and val.startswith("="):
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if ws_vals is not None:
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shown = ws_vals.cell(row=r, column=c).value
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return shown if isinstance(shown, str) and shown.strip() else None
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return None
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if isinstance(val, str) and val.strip():
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return val
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if ws_vals is not None:
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shown = ws_vals.cell(row=r, column=c).value
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if isinstance(shown, str) and shown.strip():
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return shown
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return None
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def _should_translate(self, text: str, src_lang: str) -> bool:
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"""判斷文字是否需要翻譯（移植自參考檔案）"""
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text = text.strip()
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if len(text) < 3:
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return False
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# Skip pure numbers, dates, etc.
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import re
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if re.match(r'^[\d\s\.\-\:\/]+$', text):
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return False
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# For auto-detect, translate if has CJK or meaningful text
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if src_lang.lower() in ('auto', 'auto-detect'):
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return self._has_cjk(text) or len(text) > 5
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return True
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def _has_cjk(self, text: str) -> bool:
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"""檢查是否包含中日韓文字（移植自參考檔案）"""
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for char in text:
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if '\u4e00' <= char <= '\u9fff' or \
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'\u3400' <= char <= '\u4dbf' or \
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'\u20000' <= char <= '\u2a6df' or \
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'\u3040' <= char <= '\u309f' or \
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'\u30a0' <= char <= '\u30ff' or \
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'\uac00' <= char <= '\ud7af':
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return True
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return False
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def generate_translated_document(self, translations: Dict[str, List[str]],
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target_language: str, output_dir: Path) -> str:
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"""生成翻譯後的 Excel 文件（移植自參考檔案邏輯）"""
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try:
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import openpyxl
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from openpyxl.styles import Alignment
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from openpyxl.comments import Comment
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# 載入原始工作簿
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wb = openpyxl.load_workbook(str(self.file_path), data_only=False)
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try:
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wb_vals = openpyxl.load_workbook(str(self.file_path), data_only=True)
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except Exception:
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wb_vals = None
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# 建立翻譯對應表
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translated_texts = translations.get(target_language, [])
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original_segments = self.extract_text_segments()
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# 建立翻譯映射（按照參考檔案的格式）
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tmap = {}
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for i, original_text in enumerate(original_segments):
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if i < len(translated_texts):
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tmap[original_text] = translated_texts[i]
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# 處理每個工作表（完全按照參考檔案邏輯）
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for ws in wb.worksheets:
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ws_vals = wb_vals[ws.title] if wb_vals and ws.title in wb_vals.sheetnames else None
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max_row, max_col = ws.max_row, ws.max_column
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for r in range(1, max_row + 1):
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for c in range(1, max_col + 1):
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src_text = self._get_display_text_for_translation(ws, ws_vals, r, c)
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if not src_text or src_text not in tmap:
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continue
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val = ws.cell(row=r, column=c).value
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is_formula = isinstance(val, str) and val.startswith("=")
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translated_text = tmap[src_text]
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cell = ws.cell(row=r, column=c)
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if is_formula:
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# 公式儲存格：添加註解
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txt_comment = f"翻譯: {translated_text}"
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exist = cell.comment
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if not exist or exist.text.strip() != txt_comment:
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cell.comment = Comment(txt_comment, "translator")
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else:
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# 一般儲存格：使用交錯格式（原文+翻譯）
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combined = f"{src_text}\n{translated_text}"
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# 檢查是否已經是預期的格式
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current_text = str(cell.value) if cell.value else ""
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if current_text.strip() == combined.strip():
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continue
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cell.value = combined
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# 設定自動換行（移植自參考檔案）
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try:
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if cell.alignment:
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cell.alignment = Alignment(
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horizontal=cell.alignment.horizontal,
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vertical=cell.alignment.vertical,
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wrap_text=True
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)
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else:
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cell.alignment = Alignment(wrap_text=True)
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except Exception:
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cell.alignment = Alignment(wrap_text=True)
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# 儲存翻譯後的檔案
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output_filename = f"{self.file_path.stem}_{target_language}_translated.xlsx"
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output_path = output_dir / output_filename
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wb.save(str(output_path))
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logger.info(f"Generated translated Excel file: {output_path}")
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return str(output_path)
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except Exception as e:
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logger.error(f"Failed to generate translated Excel file: {str(e)}")
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raise FileProcessingError(f"Excel 翻譯檔生成失敗: {str(e)}")
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class PdfParser(DocumentParser):
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"""PDF 文件解析器（只讀）"""
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def extract_text_segments(self) -> List[str]:
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"""提取 PDF 文件的文字片段"""
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try:
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from PyPDF2 import PdfReader
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reader = PdfReader(str(self.file_path))
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text_segments = []
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for page in reader.pages:
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text = page.extract_text()
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# 簡單的句子分割
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sentences = text.split('.')
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for sentence in sentences:
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sentence = sentence.strip()
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if sentence and len(sentence) > 10:
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text_segments.append(sentence)
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logger.info(f"Extracted {len(text_segments)} text segments from PDF")
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return text_segments
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except Exception as e:
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logger.error(f"Failed to extract text from PDF: {str(e)}")
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raise FileProcessingError(f"PDF 文件解析失敗: {str(e)}")
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def generate_translated_document(self, translations: Dict[str, List[str]],
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target_language: str, output_dir: Path) -> str:
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"""生成翻譯文字檔（PDF 不支援直接編輯）"""
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try:
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translated_texts = translations.get(target_language, [])
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# 生成純文字檔案
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output_filename = f"{self.file_path.stem}_{target_language}_translated.txt"
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output_path = output_dir / output_filename
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with open(output_path, 'w', encoding='utf-8') as f:
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f.write(f"翻譯結果 - {target_language}\n")
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f.write("=" * 50 + "\n\n")
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for i, text in enumerate(translated_texts):
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f.write(f"{i+1}. {text}\n\n")
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logger.info(f"Generated translated text file: {output_path}")
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return str(output_path)
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except Exception as e:
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logger.error(f"Failed to generate translated text file: {str(e)}")
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raise FileProcessingError(f"生成翻譯文字檔失敗: {str(e)}")
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class TranslationService:
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"""翻譯服務"""
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def __init__(self):
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self.dify_client = DifyClient()
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self.document_processor = DocumentProcessor()
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|
||
# 文件解析器映射
|
||
self.parsers = {
|
||
'.docx': DocxParser,
|
||
'.doc': DocParser, # 需要先轉換為 DOCX
|
||
'.xlsx': ExcelParser,
|
||
'.xls': ExcelParser, # Excel 處理器會自動處理 XLS 轉換
|
||
'.pdf': PdfParser,
|
||
# 其他格式可以稍後添加
|
||
}
|
||
|
||
def get_document_parser(self, file_path: str) -> DocumentParser:
|
||
"""取得文件解析器"""
|
||
file_ext = Path(file_path).suffix.lower()
|
||
|
||
parser_class = self.parsers.get(file_ext)
|
||
if not parser_class:
|
||
raise FileProcessingError(f"不支援的檔案格式: {file_ext}")
|
||
|
||
return parser_class(file_path)
|
||
|
||
def split_text_into_sentences(self, text: str, language: str = 'auto') -> List[str]:
|
||
"""將文字分割成句子 - 使用增強的分句邏輯"""
|
||
return self.document_processor.split_text_into_sentences(text, language)
|
||
|
||
def translate_segment_with_sentences(self, text: str, source_language: str,
|
||
target_language: str, user_id: int = None,
|
||
job_id: int = None) -> str:
|
||
"""
|
||
按段落翻譯，模仿成功版本的 translate_block_sentencewise 邏輯
|
||
對多行文字進行逐行、逐句翻譯，並重新組合成完整段落
|
||
"""
|
||
if not text or not text.strip():
|
||
return ""
|
||
|
||
# 檢查快取 - 先檢查整個段落的快取
|
||
cached_whole = TranslationCache.get_translation(text, source_language, target_language)
|
||
if cached_whole:
|
||
logger.debug(f"Whole paragraph cache hit: {text[:30]}...")
|
||
return cached_whole
|
||
|
||
# 按行處理
|
||
out_lines = []
|
||
all_successful = True
|
||
|
||
for raw_line in text.split('\n'):
|
||
if not raw_line.strip():
|
||
out_lines.append("")
|
||
continue
|
||
|
||
# 分句處理
|
||
sentences = self.document_processor.split_text_into_sentences(raw_line, source_language)
|
||
if not sentences:
|
||
sentences = [raw_line]
|
||
|
||
translated_parts = []
|
||
for sentence in sentences:
|
||
sentence = sentence.strip()
|
||
if not sentence:
|
||
continue
|
||
|
||
# 檢查句子級快取
|
||
cached_sentence = TranslationCache.get_translation(sentence, source_language, target_language)
|
||
if cached_sentence:
|
||
translated_parts.append(cached_sentence)
|
||
continue
|
||
|
||
# 呼叫 Dify API 翻譯句子
|
||
try:
|
||
result = self.dify_client.translate_text(
|
||
text=sentence,
|
||
source_language=source_language,
|
||
target_language=target_language,
|
||
user_id=user_id,
|
||
job_id=job_id
|
||
)
|
||
|
||
translated_sentence = result['translated_text']
|
||
|
||
# 儲存句子級快取
|
||
TranslationCache.save_translation(
|
||
sentence, source_language, target_language, translated_sentence
|
||
)
|
||
|
||
translated_parts.append(translated_sentence)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to translate sentence: {sentence[:30]}... Error: {str(e)}")
|
||
translated_parts.append(f"【翻譯失敗｜{target_language}】{sentence}")
|
||
all_successful = False
|
||
|
||
# 重新組合句子為一行
|
||
out_lines.append(" ".join(translated_parts))
|
||
|
||
# 重新組合所有行
|
||
final_result = "\n".join(out_lines)
|
||
|
||
# 如果全部成功，儲存整個段落的快取
|
||
if all_successful:
|
||
TranslationCache.save_translation(text, source_language, target_language, final_result)
|
||
|
||
return final_result
|
||
|
||
def translate_text_with_cache(self, text: str, source_language: str,
|
||
target_language: str, user_id: int = None,
|
||
job_id: int = None) -> str:
|
||
"""帶快取的文字翻譯"""
|
||
|
||
# 檢查快取
|
||
cached_translation = TranslationCache.get_translation(
|
||
text, source_language, target_language
|
||
)
|
||
|
||
if cached_translation:
|
||
logger.debug(f"Cache hit for translation: {text[:50]}...")
|
||
return cached_translation
|
||
|
||
# 呼叫 Dify API
|
||
try:
|
||
result = self.dify_client.translate_text(
|
||
text=text,
|
||
source_language=source_language,
|
||
target_language=target_language,
|
||
user_id=user_id,
|
||
job_id=job_id
|
||
)
|
||
|
||
translated_text = result['translated_text']
|
||
|
||
# 儲存到快取
|
||
TranslationCache.save_translation(
|
||
text, source_language, target_language, translated_text
|
||
)
|
||
|
||
return translated_text
|
||
|
||
except Exception as e:
|
||
logger.error(f"Translation failed for text: {text[:50]}... Error: {str(e)}")
|
||
raise TranslationError(f"翻譯失敗: {str(e)}")
|
||
|
||
def translate_document(self, job_uuid: str) -> Dict[str, Any]:
|
||
"""翻譯文件（主要入口點）- 使用增強的文檔處理邏輯"""
|
||
try:
|
||
# 取得任務資訊
|
||
job = TranslationJob.query.filter_by(job_uuid=job_uuid).first()
|
||
if not job:
|
||
raise TranslationError(f"找不到任務: {job_uuid}")
|
||
|
||
logger.info(f"Starting enhanced document translation: {job_uuid}")
|
||
|
||
# 更新任務狀態
|
||
job.update_status('PROCESSING', progress=0)
|
||
|
||
# 使用增強的文檔處理器直接提取段落
|
||
file_ext = Path(job.file_path).suffix.lower()
|
||
|
||
if file_ext in ['.docx', '.doc']:
|
||
# 使用增強的 DOCX 處理邏輯
|
||
segments = self.document_processor.extract_docx_segments(job.file_path)
|
||
logger.info(f"Enhanced extraction: Found {len(segments)} segments to translate")
|
||
|
||
if not segments:
|
||
raise TranslationError("文件中未找到可翻譯的文字段落")
|
||
|
||
# 使用成功版本的翻譯邏輯 - 直接按段落翻譯，不做複雜分割
|
||
translatable_segments = []
|
||
for seg in segments:
|
||
if self.document_processor.should_translate_text(seg.text, job.source_language):
|
||
translatable_segments.append(seg)
|
||
|
||
logger.info(f"Found {len(translatable_segments)} segments to translate")
|
||
|
||
# 批次翻譯 - 直接按原始段落翻譯
|
||
translation_map = {} # 格式: (target_language, source_text) -> translated_text
|
||
total_segments = len(translatable_segments)
|
||
|
||
for target_language in job.target_languages:
|
||
logger.info(f"Translating to {target_language}")
|
||
|
||
for i, seg in enumerate(translatable_segments):
|
||
try:
|
||
# 使用整段文字進行翻譯
|
||
translated = self.translate_segment_with_sentences(
|
||
text=seg.text,
|
||
source_language=job.source_language,
|
||
target_language=target_language,
|
||
user_id=job.user_id,
|
||
job_id=job.id
|
||
)
|
||
|
||
# 直接以原始段落文字為鍵儲存翻譯結果
|
||
translation_map[(target_language, seg.text)] = translated
|
||
|
||
# 更新進度
|
||
progress = (i + 1) / total_segments * 100 / len(job.target_languages)
|
||
current_lang_index = job.target_languages.index(target_language)
|
||
total_progress = (current_lang_index * 100 + progress) / len(job.target_languages)
|
||
job.update_status('PROCESSING', progress=total_progress)
|
||
|
||
# 短暫延遲避免過快請求
|
||
time.sleep(0.1)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to translate segment: {seg.text[:50]}... Error: {str(e)}")
|
||
# 翻譯失敗時保留原文
|
||
translation_map[(target_language, seg.text)] = f"[翻譯失敗] {seg.text}"
|
||
|
||
# 生成翻譯文件
|
||
logger.info("Generating translated documents with enhanced insertion")
|
||
output_dir = Path(job.file_path).parent
|
||
output_files = {}
|
||
|
||
for target_language in job.target_languages:
|
||
try:
|
||
# 生成輸出檔名
|
||
output_filename = generate_filename(
|
||
Path(job.file_path).name,
|
||
'translated',
|
||
'translated',
|
||
target_language
|
||
)
|
||
output_path = output_dir / output_filename
|
||
|
||
# 使用增強的翻譯插入邏輯
|
||
ok_count, skip_count = self.document_processor.insert_docx_translations(
|
||
job.file_path,
|
||
segments,
|
||
translation_map,
|
||
[target_language],
|
||
str(output_path)
|
||
)
|
||
|
||
output_files[target_language] = str(output_path)
|
||
|
||
# 記錄翻譯檔案到資料庫
|
||
file_size = Path(output_path).stat().st_size
|
||
job.add_translated_file(
|
||
language_code=target_language,
|
||
filename=Path(output_path).name,
|
||
file_path=str(output_path),
|
||
file_size=file_size
|
||
)
|
||
|
||
logger.info(f"Generated {target_language}: {ok_count} insertions, {skip_count} skips")
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to generate translated document for {target_language}: {str(e)}")
|
||
raise TranslationError(f"生成 {target_language} 翻譯文件失敗: {str(e)}")
|
||
|
||
else:
|
||
# 對於非 DOCX 文件，使用原有邏輯
|
||
logger.info(f"Using legacy processing for {file_ext} files")
|
||
parser = self.get_document_parser(job.file_path)
|
||
|
||
# 提取文字片段
|
||
text_segments = parser.extract_text_segments()
|
||
|
||
if not text_segments:
|
||
raise TranslationError("文件中未找到可翻譯的文字")
|
||
|
||
# 分割成句子
|
||
all_sentences = []
|
||
for segment in text_segments:
|
||
sentences = self.split_text_into_sentences(segment, job.source_language)
|
||
all_sentences.extend(sentences)
|
||
|
||
# 去重複
|
||
unique_sentences = list(dict.fromkeys(all_sentences))
|
||
logger.info(f"Found {len(unique_sentences)} unique sentences to translate")
|
||
|
||
# 批次翻譯
|
||
translation_results = {}
|
||
total_sentences = len(unique_sentences)
|
||
|
||
for target_language in job.target_languages:
|
||
logger.info(f"Translating to {target_language}")
|
||
translated_sentences = []
|
||
|
||
for i, sentence in enumerate(unique_sentences):
|
||
try:
|
||
translated = self.translate_text_with_cache(
|
||
text=sentence,
|
||
source_language=job.source_language,
|
||
target_language=target_language,
|
||
user_id=job.user_id,
|
||
job_id=job.id
|
||
)
|
||
translated_sentences.append(translated)
|
||
|
||
# 更新進度
|
||
progress = (i + 1) / total_sentences * 100 / len(job.target_languages)
|
||
current_lang_index = job.target_languages.index(target_language)
|
||
total_progress = (current_lang_index * 100 + progress) / len(job.target_languages)
|
||
job.update_status('PROCESSING', progress=total_progress)
|
||
|
||
time.sleep(0.1)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Failed to translate sentence: {sentence[:50]}... Error: {str(e)}")
|
||
translated_sentences.append(f"[翻譯失敗] {sentence}")
|
||
|
||
translation_results[target_language] = translated_sentences
|
||
|
||
# 生成翻譯文件
|
||
output_dir = Path(job.file_path).parent
|
||
output_files = {}
|
||
|
||
for target_language, translations in translation_results.items():
|
||
translation_mapping = {target_language: translations}
|
||
|
||
output_file = parser.generate_translated_document(
|
||
translations=translation_mapping,
|
||
target_language=target_language,
|
||
output_dir=output_dir
|
||
)
|
||
|
||
output_files[target_language] = output_file
|
||
|
||
file_size = Path(output_file).stat().st_size
|
||
job.add_translated_file(
|
||
language_code=target_language,
|
||
filename=Path(output_file).name,
|
||
file_path=output_file,
|
||
file_size=file_size
|
||
)
|
||
|
||
# 計算總成本
|
||
total_cost = self._calculate_job_cost(job.id)
|
||
|
||
# 更新任務狀態為完成
|
||
job.update_status('COMPLETED', progress=100)
|
||
job.total_cost = total_cost
|
||
# 計算實際使用的 token 數（從 API 使用統計中獲取）
|
||
from sqlalchemy import func
|
||
from app.models.stats import APIUsageStats
|
||
from app import db
|
||
|
||
actual_tokens = db.session.query(
|
||
func.sum(APIUsageStats.total_tokens)
|
||
).filter_by(job_id=job.id).scalar()
|
||
|
||
job.total_tokens = int(actual_tokens) if actual_tokens else 0
|
||
|
||
db.session.commit()
|
||
|
||
logger.info(f"Enhanced document translation completed: {job_uuid}")
|
||
|
||
return {
|
||
'success': True,
|
||
'job_uuid': job_uuid,
|
||
'output_files': output_files,
|
||
'total_sentences': len(texts_to_translate) if 'texts_to_translate' in locals() else len(unique_sentences) if 'unique_sentences' in locals() else 0,
|
||
'total_cost': float(total_cost),
|
||
'target_languages': job.target_languages
|
||
}
|
||
|
||
except TranslationError:
|
||
raise
|
||
except Exception as e:
|
||
logger.error(f"Enhanced document translation failed: {job_uuid}. Error: {str(e)}")
|
||
raise TranslationError(f"文件翻譯失敗: {str(e)}")
|
||
|
||
def _calculate_job_cost(self, job_id: int) -> float:
|
||
"""計算任務總成本"""
|
||
from app import db
|
||
from sqlalchemy import func
|
||
from app.models.stats import APIUsageStats
|
||
|
||
total_cost = db.session.query(
|
||
func.sum(APIUsageStats.cost)
|
||
).filter_by(job_id=job_id).scalar()
|
||
|
||
return float(total_cost) if total_cost else 0.0 |