Translate PPT#

Translate Chinese PowerPoint presentations (.pptx) to English with professional business styling.

Overview#

This skill translates Chinese PPTX files to English using any OpenAI-compatible LLM endpoint (local or cloud). It preserves all non-text content while:

• Preserving all non-text content (images, charts, shapes, tables, SmartArt, media)
• Adjusting fonts to Calibri family for consistent business styling
• Optimizing text box sizing and layout for English text (typically longer than Chinese)
• Maintaining original slide masters, layouts, animations, and transitions

Prerequisites#

• Python 3.8+
• Required packages: python-pptx, requests
• An LLM endpoint that supports OpenAI-compatible API (e.g., Qoderwork built-in models, Ollama, OpenAI, DeepSeek, etc.)

Quick Start#

Option A: Use with Qoderwork (Easiest — No Extra Setup)#

If you're running this skill within Qoderwork, models are already available. Just run:

bash

pip install python-pptx requests
python .qoder/skills/translate-ppt/scripts/translate_ppt.py input.pptx --api-base <qoderwork-endpoint> --model <available-model>

Option B: Use with Local Ollama#

1. Install Ollama: Download and install from https://ollama.com

2. Pull a recommended model: bash

   ollama pull qwen2.5:14b
   
   

3. Install Python dependencies: bash

   pip install python-pptx requests
   
   

4. Run translation: bash

   python .qoder/skills/translate-ppt/scripts/translate_ppt.py input.pptx
   
   

   If output path is not specified, defaults to <input_name>_en.pptx.

Option C: Use with Cloud API#

Run with your cloud endpoint:

bash

python .qoder/skills/translate-ppt/scripts/translate_ppt.py input.pptx --api-base https://api.openai.com/v1 --api-key sk-xxx --model gpt-4o

Translation Rules#

• Translate: All text content (titles, body text, notes, table cells, grouped shape text)
• Preserve: Images, charts data, embedded media, hyperlinks, original formatting
• Mixed content: Only translate Chinese portions of mixed Chinese/English text

Font & Layout Adjustments#

ElementFontStyleTitlesCalibriBoldBody textCalibriRegular

• Maintain original font sizes (with auto-shrink if text overflows)
• Adjust text box width up to 20% if English text is significantly longer
• Preserve original color scheme and text formatting (bold, italic, underline)

Business Style Guidelines#

• Consistent Calibri font family throughout
• Clean, professional spacing
• Preserved slide master/layout templates
• All animations and transitions intact

Recommended Models#

Translation quality varies significantly between models. Choose based on your setup:

Note for Qoderwork users: You can use whatever models are already configured in your client environment — no additional setup required.

ModelSizeQualitySpeedCommandqwen2.5:14b~9GB★★★★★ Best for ChineseFastollama pull qwen2.5:14b``qwen2.5:7b~4.7GB★★★★ Good balanceFasterollama pull qwen2.5:7b``llama3.1:8b~4.7GB★★★ DecentFastollama pull llama3.1:8b``gemma2:9b~5.4GB★★★ DecentFastollama pull gemma2:9b``qwen2.5:3b~2GB★★ BasicFastestollama pull qwen2.5:3b

Tip: For best results with Chinese-to-English business content, Qwen2.5 14B is strongly recommended as it has excellent Chinese language understanding. Smaller models may produce less accurate or less natural translations.

Command-Line Options#

OptionDescriptionDefault--fontOverride default fontCalibri--modelLLM model to useqwen2.5:14b--api-baseOpenAI-compatible API base URLhttp://localhost:11434/v1--api-keyAPI key (optional, not needed for local models)None--batch-sizeText segments per API call20--verbose, -vEnable detailed loggingFalse

Troubleshooting#

IssueSolutionConnection refusedCheck your API endpoint URL. For Ollama: ensure ollama serve is running. For cloud APIs: verify the URL is correct.Model not foundVerify the model name is correct for your endpoint. For Ollama: ollama pull <model>Corrupt PPTXVerify file opens in PowerPoint; try saving as new file firstFont not foundEnsure Calibri is installed on your systemAPI rate limitsReduce --batch-size or add delay between calls

Reference#

See reference.md for detailed API documentation and architecture.