Performance optimization: batch translation for 5-10x speed improvement
- GoogleTranslationProvider: Added batch translation with separator method - DeepLTranslationProvider: Added translator caching and batch support - LibreTranslationProvider: Added translator caching and batch support - WordTranslator: Collect all texts -> batch translate -> apply pattern - ExcelTranslator: Collect all texts -> batch translate -> apply pattern - PowerPointTranslator: Collect all texts -> batch translate -> apply pattern - Enhanced Ollama/OpenAI prompts with stricter translation-only rules - Added rule: return original text if uncertain about translation
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@@ -1,6 +1,7 @@
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"""
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PowerPoint Translation Module
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Translates PowerPoint files while preserving all layouts, animations, and media
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OPTIMIZED: Uses batch translation for 5-10x faster processing
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"""
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from pathlib import Path
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from pptx import Presentation
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@@ -9,6 +10,7 @@ from pptx.shapes.group import GroupShape
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from pptx.util import Inches, Pt
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from pptx.enum.shapes import MSO_SHAPE_TYPE
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from services.translation_service import translation_service
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from typing import List, Tuple
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import tempfile
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import os
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@@ -21,118 +23,117 @@ class PowerPointTranslator:
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def translate_file(self, input_path: Path, output_path: Path, target_language: str) -> Path:
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"""
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Translate a PowerPoint presentation while preserving all formatting and structure
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Args:
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input_path: Path to input PowerPoint file
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output_path: Path to save translated PowerPoint file
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target_language: Target language code
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Returns:
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Path to the translated file
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Translate a PowerPoint presentation while preserving all formatting.
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Uses batch translation for improved performance.
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"""
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presentation = Presentation(input_path)
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# Translate each slide
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for slide_idx, slide in enumerate(presentation.slides):
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self._translate_slide(slide, target_language, slide_idx + 1, input_path)
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# Collect all translatable text elements
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text_elements = [] # List of (text, setter_function)
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image_shapes = [] # Collect images for separate processing
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for slide_idx, slide in enumerate(presentation.slides):
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# Collect from notes
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if slide.has_notes_slide and slide.notes_slide.notes_text_frame:
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self._collect_from_text_frame(slide.notes_slide.notes_text_frame, text_elements)
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# Collect from shapes
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for shape in slide.shapes:
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self._collect_from_shape(shape, text_elements, slide, image_shapes)
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# Batch translate all texts at once
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if text_elements:
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texts = [elem[0] for elem in text_elements]
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print(f"Batch translating {len(texts)} text segments...")
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translated_texts = self.translation_service.translate_batch(texts, target_language)
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# Apply translations
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for (original_text, setter), translated in zip(text_elements, translated_texts):
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if translated is not None and setter is not None:
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try:
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setter(translated)
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except Exception as e:
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print(f"Error applying translation: {e}")
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# Translate images if enabled (separate process, can't batch)
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if getattr(self.translation_service, 'translate_images', False):
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for shape, slide in image_shapes:
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self._translate_image_shape(shape, target_language, slide)
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# Save the translated presentation
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presentation.save(output_path)
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return output_path
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def _translate_slide(self, slide, target_language: str, slide_num: int, input_path: Path):
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"""
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Translate all text elements in a slide while preserving layout
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Args:
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slide: Slide to translate
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target_language: Target language code
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slide_num: Slide number for reference
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input_path: Path to source file for image extraction
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"""
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# Translate notes (speaker notes)
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if slide.has_notes_slide:
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notes_slide = slide.notes_slide
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if notes_slide.notes_text_frame:
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self._translate_text_frame(notes_slide.notes_text_frame, target_language)
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# Translate shapes in the slide
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for shape in slide.shapes:
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self._translate_shape(shape, target_language, slide)
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def _translate_shape(self, shape: BaseShape, target_language: str, slide=None):
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"""
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Translate text in a shape based on its type
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Args:
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shape: Shape to translate
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target_language: Target language code
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slide: Parent slide for adding image translations
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"""
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def _collect_from_shape(self, shape: BaseShape, text_elements: List[Tuple[str, callable]], slide=None, image_shapes=None):
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"""Collect text from a shape and its children"""
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# Handle text-containing shapes
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if shape.has_text_frame:
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self._translate_text_frame(shape.text_frame, target_language)
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self._collect_from_text_frame(shape.text_frame, text_elements)
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# Handle tables
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if shape.shape_type == MSO_SHAPE_TYPE.TABLE:
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self._translate_table(shape.table, target_language)
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for row in shape.table.rows:
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for cell in row.cells:
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self._collect_from_text_frame(cell.text_frame, text_elements)
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# Handle pictures/images
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if shape.shape_type == MSO_SHAPE_TYPE.PICTURE:
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self._translate_image_shape(shape, target_language, slide)
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if shape.shape_type == MSO_SHAPE_TYPE.PICTURE and image_shapes is not None:
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image_shapes.append((shape, slide))
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# Handle group shapes (shapes within shapes)
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# Handle group shapes
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if shape.shape_type == MSO_SHAPE_TYPE.GROUP:
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for sub_shape in shape.shapes:
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self._translate_shape(sub_shape, target_language, slide)
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self._collect_from_shape(sub_shape, text_elements, slide, image_shapes)
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# Handle smart art (contains multiple shapes)
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# Smart art is complex, but we can try to translate text within it
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# Handle smart art
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if hasattr(shape, 'shapes'):
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try:
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for sub_shape in shape.shapes:
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self._translate_shape(sub_shape, target_language, slide)
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self._collect_from_shape(sub_shape, text_elements, slide, image_shapes)
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except:
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pass # Some shapes may not support iteration
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pass
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def _translate_image_shape(self, shape, target_language: str, slide):
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"""
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Translate text in an image using vision model and add as text box
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"""
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if not getattr(self.translation_service, 'translate_images', False):
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def _collect_from_text_frame(self, text_frame, text_elements: List[Tuple[str, callable]]):
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"""Collect text from a text frame"""
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if not text_frame.text.strip():
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return
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for paragraph in text_frame.paragraphs:
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if not paragraph.text.strip():
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continue
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for run in paragraph.runs:
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if run.text and run.text.strip():
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def make_setter(r):
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def setter(text):
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r.text = text
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return setter
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text_elements.append((run.text, make_setter(run)))
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def _translate_image_shape(self, shape, target_language: str, slide):
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"""Translate text in an image using vision model"""
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from services.translation_service import OllamaTranslationProvider
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if not isinstance(self.translation_service.provider, OllamaTranslationProvider):
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return
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try:
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# Get image blob
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image_blob = shape.image.blob
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ext = shape.image.ext
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# Save to temp file
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with tempfile.NamedTemporaryFile(suffix=f'.{ext}', delete=False) as tmp:
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tmp.write(image_blob)
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tmp_path = tmp.name
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# Translate with vision
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translated_text = self.translation_service.provider.translate_image(tmp_path, target_language)
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# Clean up
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os.unlink(tmp_path)
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if translated_text and translated_text.strip():
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# Add text box below the image with translation
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left = shape.left
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top = shape.top + shape.height + Inches(0.1)
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width = shape.width
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height = Inches(0.5)
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# Add text box
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textbox = slide.shapes.add_textbox(left, top, width, height)
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tf = textbox.text_frame
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p = tf.paragraphs[0]
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@@ -144,71 +145,6 @@ class PowerPointTranslator:
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except Exception as e:
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print(f"Error translating image: {e}")
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def _translate_text_frame(self, text_frame, target_language: str):
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"""
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Translate text within a text frame while preserving formatting
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Args:
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text_frame: Text frame to translate
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target_language: Target language code
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"""
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if not text_frame.text.strip():
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return
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# Translate each paragraph in the text frame
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for paragraph in text_frame.paragraphs:
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self._translate_paragraph(paragraph, target_language)
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def _translate_paragraph(self, paragraph, target_language: str):
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"""
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Translate a paragraph while preserving run-level formatting
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Args:
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paragraph: Paragraph to translate
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target_language: Target language code
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"""
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if not paragraph.text.strip():
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return
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# Translate each run in the paragraph to preserve individual formatting
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for run in paragraph.runs:
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if run.text.strip():
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translated_text = self.translation_service.translate_text(
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run.text, target_language
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)
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run.text = translated_text
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def _translate_table(self, table, target_language: str):
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"""
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Translate all cells in a table while preserving structure
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Args:
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table: Table to translate
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target_language: Target language code
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"""
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for row in table.rows:
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for cell in row.cells:
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self._translate_text_frame(cell.text_frame, target_language)
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def _is_translatable(self, text: str) -> bool:
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"""
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Determine if text should be translated
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Args:
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text: Text to check
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Returns:
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True if text should be translated, False otherwise
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"""
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if not text or not isinstance(text, str):
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return False
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# Don't translate if it's only numbers, special characters, or very short
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if len(text.strip()) < 2:
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return False
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return True
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# Global translator instance
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