Skills translate-ppt

Name: translate-ppt
Author: openclaw

Translate Chinese PowerPoint presentations to English while preserving all images, charts, shapes, and media content. Adjusts fonts to Calibri and optimizes layout for professional business presentations. Use when the user asks to translate a PPT/PPTX file from Chinese to English, or mentions PPT translation, slide translation, or presentation localization.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/birkhoff-china/ppt-translate" ~/.claude/skills/openclaw-skills-translate-ppt && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/birkhoff-china/ppt-translate" ~/.openclaw/skills/openclaw-skills-translate-ppt && rm -rf "$T"

manifest: skills/birkhoff-china/ppt-translate/SKILL.md

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:

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

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

Pull a recommended model:

ollama pull qwen2.5:14b

Install Python dependencies:

pip install python-pptx requests

Run translation:

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:

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

Element	Font	Style
Titles	Calibri	Bold
Body text	Calibri	Regular

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.

Model	Size	Quality	Speed	Command
`qwen2.5:14b`	~9GB	★★★★★ Best for Chinese	Fast	`ollama pull qwen2.5:14b`
`qwen2.5:7b`	~4.7GB	★★★★ Good balance	Faster	`ollama pull qwen2.5:7b`
`llama3.1:8b`	~4.7GB	★★★ Decent	Fast	`ollama pull llama3.1:8b`
`gemma2:9b`	~5.4GB	★★★ Decent	Fast	`ollama pull gemma2:9b`
`qwen2.5:3b`	~2GB	★★ Basic	Fastest	`ollama 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

Option	Description	Default
`--font`	Override default font	Calibri
`--model`	LLM model to use	qwen2.5:14b
`--api-base`	OpenAI-compatible API base URL	http://localhost:11434/v1
`--api-key`	API key (optional, not needed for local models)	None
`--batch-size`	Text segments per API call	20
`--verbose` , `-v`	Enable detailed logging	False

Troubleshooting

Issue	Solution
Connection refused	Check your API endpoint URL. For Ollama: ensure `ollama serve` is running. For cloud APIs: verify the URL is correct.
Model not found	Verify the model name is correct for your endpoint. For Ollama: `ollama pull <model>`
Corrupt PPTX	Verify file opens in PowerPoint; try saving as new file first
Font not found	Ensure Calibri is installed on your system
API rate limits	Reduce `--batch-size` or add delay between calls

Reference

See reference.md for detailed API documentation and architecture.