A powerful PowerPoint translation tool that leverages Amazon Bedrock models for high-quality translation. This service can be used both as a standalone command-line tool and as a FastMCP (Fast Model Context Protocol) service for integration with AI assistants like Amazon Q Developer. It translates PowerPoint presentations while preserving formatting and structure.
- PowerPoint Translation: Translate text content in PowerPoint presentations
- Amazon Bedrock Integration: Uses Amazon Bedrock models for high-quality translation
- Format Preservation: Maintains original formatting, layouts, and styles
- Language-Specific Fonts: Automatically applies appropriate fonts for target languages
- Color & Style Preservation: Preserves original text colors and formatting even for untranslated content
- Standalone & MCP Support: Use as a command-line tool or integrate with AI assistants via FastMCP
- Multiple Languages: Supports translation between various languages
- Batch Processing: Can handle multiple slides and text elements efficiently
- Selective Translation: Translate entire presentations or specific slides
The PowerPoint Translator maintains the original formatting while accurately translating content:
![]() |
![]() |
| Original presentation slide in English with complex layout |
Same presentation translated to Korean with preserved formatting and layout |
Translate entire presentation:
uv run ppt-translate translate samples/en.pptx --target-language koTranslate specific slides:
uv run ppt-translate translate-slides samples/en.pptx --slides "1,3" --target-language koGet slide information:
uv run ppt-translate info samples/en.pptx- Python 3.11 or higher
- AWS Account with Bedrock access
- AWS CLI configured with appropriate credentials
- Access to Amazon Bedrock models (e.g., Claude, Nova, etc.)
Before using this service, ensure your AWS credentials are properly configured. You have several options:
-
AWS CLI Configuration (Recommended):
aws configure
This will prompt you for:
- AWS Access Key ID
- AWS Secret Access Key
- Default region name
- Default output format
-
AWS Profile Configuration:
aws configure --profile your-profile-name
-
Environment Variables (if needed):
export AWS_ACCESS_KEY_ID=your_access_key export AWS_SECRET_ACCESS_KEY=your_secret_key export AWS_DEFAULT_REGION=us-east-1
-
IAM Roles (when running on EC2 instances)
The service will automatically use your configured AWS credentials. You can specify which profile to use in the .env file.
-
Clone the repository:
git clone https://github.com/daekeun-ml/ppt-translator cd ppt-translator -
Install dependencies using uv (recommended):
uv sync
Or using pip:
pip install -r requirements.txt
-
Set up environment variables: Edit
.envfile with your configuration:# AWS Configuration AWS_REGION=us-east-1 AWS_PROFILE=default # Translation Configuration DEFAULT_TARGET_LANGUAGE=ko BEDROCK_MODEL_ID=us.anthropic.claude-3-7-sonnet-20250219-v1:0 # Translation Settings MAX_TOKENS=4000 TEMPERATURE=0.1 ENABLE_POLISHING=true BATCH_SIZE=20 CONTEXT_THRESHOLD=5 # Font Settings by Language FONT_KOREAN=맑은 고딕 FONT_JAPANESE=Yu Gothic UI FONT_ENGLISH=Amazon Ember FONT_CHINESE=Microsoft YaHei FONT_DEFAULT=Arial # Debug Settings DEBUG=false # Post-processing Settings ENABLE_TEXT_AUTOFIT=true TEXT_LENGTH_THRESHOLD=10
Note: AWS credentials (Access Key ID and Secret Access Key) are not needed in the
.envfile if you have already configured them usingaws configure. The service will automatically use your AWS CLI credentials.
The PowerPoint Translator can be used directly from the command line using the ppt-translate command:
# Translate entire presentation to Korean
uv run ppt-translate translate samples/en.pptx --target-language ko
# Translate specific slides (individual slides)
uv run ppt-translate translate-slides samples/en.pptx --slides "1,3" --target-language ko
# Translate slide range
uv run ppt-translate translate-slides samples/en.pptx --slides "2-4" --target-language ko
# Translate mixed (individual + range)
uv run ppt-translate translate-slides samples/en.pptx --slides "1,2-4" --target-language ko
# Get slide information and previews
uv run ppt-translate info samples/en.pptx
# Show help
uv run ppt-translate --help
uv run ppt-translate translate --help
uv run ppt-translate translate-slides --helpStart the FastMCP server for integration with AI assistants like Amazon Q Developer:
# Using uv (recommended)
uv run mcp_server.py
# Using python directly
python mcp_server.pyIf you haven't already installed Amazon Q Developer or Kiro, please refer to this:
- Amazon Q Developer CLI: https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/command-line-installing.html
- Kiro: https://kiro.dev
Create or update your Q Developer FastMCP configuration file:
User Level ~/.kiro/settings/mcp.json
On macOS/Linux: ~/.aws/amazonq/mcp.json
On Windows: %APPDATA%\amazonq\mcp.json
Add the PowerPoint Translator FastMCP server configuration:
Using uv:
{
"mcpServers": {
"ppt-translator": {
"command": "uv",
"args": ["run", "/path/to/ppt-translator/mcp_server.py"],
"env": {
"AWS_REGION": "us-east-1",
"AWS_PROFILE": "default",
"BEDROCK_MODEL_ID": "us.anthropic.claude-3-7-sonnet-20250219-v1:0"
},
"disabled": false,
"autoApprove": [
"translate_powerpoint",
"get_slide_info",
"get_slide_preview",
"translate_specific_slides"
]
}
}
}Alternative configuration using python directly:
{
"mcpServers": {
"ppt-translator": {
"command": "python",
"args": ["/path/to/ppt-translator/mcp_server.py"],
"env": {
"AWS_REGION": "us-east-1",
"AWS_PROFILE": "default",
"BEDROCK_MODEL_ID": "us.anthropic.claude-3-7-sonnet-20250219-v1:0"
},
"disabled": false,
"autoApprove": [
"translate_powerpoint",
"get_slide_info",
"get_slide_preview",
"translate_specific_slides"
]
}
}
}Important: Replace /path/to/ppt-translator/ with the actual path to your cloned repository.
Once connected, you can use commands like (User input does not have to be in English):
Please translate slides 10 to 13 of original.pptx into Korean.
The MCP server provides the following tools:
-
translate_powerpoint: Translate an entire PowerPoint presentation- Parameters:
input_file: Path to the input PowerPoint file (.pptx)target_language: Target language code (default: 'ko')output_file: Path for the translated output file (optional, auto-generated)model_id: Amazon Bedrock model ID (default: Claude 3.7 Sonnet)enable_polishing: Enable natural language polishing (default: true)
- Parameters:
-
translate_specific_slides: Translate only specific slides in a PowerPoint presentation- Parameters:
input_file: Path to the input PowerPoint file (.pptx)slide_numbers: Comma-separated slide numbers to translate (e.g., "1,3,5" or "2-4,7")target_language: Target language code (default: 'ko')output_file: Path for the translated output file (optional, auto-generated)model_id: Amazon Bedrock model ID (default: Claude 3.7 Sonnet)enable_polishing: Enable natural language polishing (default: true)
- Parameters:
-
get_slide_info: Get information about slides in a PowerPoint presentation- Parameters:
input_file: Path to the PowerPoint file (.pptx)
- Returns: Overview with slide count and preview of each slide's content
- Parameters:
-
get_slide_preview: Get detailed preview of a specific slide's content- Parameters:
input_file: Path to the PowerPoint file (.pptx)slide_number: Slide number to preview (1-based indexing)
- Parameters:
-
list_supported_languages: List all supported target languages for translation -
list_supported_models: List all supported Amazon Bedrock models -
get_translation_help: Get help information about using the translator
AWS_REGION: AWS region for Bedrock service (default: us-east-1)AWS_PROFILE: AWS profile to use (default: default)DEFAULT_TARGET_LANGUAGE: Default target language for translation (default: ko)BEDROCK_MODEL_ID: Bedrock model ID for translation (default: us.anthropic.claude-3-7-sonnet-20250219-v1:0)MAX_TOKENS: Maximum tokens for translation requests (default: 4000)TEMPERATURE: Temperature setting for AI model (default: 0.1)ENABLE_POLISHING: Enable translation polishing (default: true)BATCH_SIZE: Number of texts to process in a batch (default: 20)CONTEXT_THRESHOLD: Number of texts to trigger context-aware translation (default: 5)DEBUG: Enable debug logging (default: false)
The service supports translation between major languages including:
- English (en)
- Korean (ko)
- Japanese (ja)
- Chinese Simplified (zh)
- Chinese Traditional (zh-tw)
- Spanish (es)
- French (fr)
- German (de)
- Italian (it)
- Portuguese (pt)
- Russian (ru)
- Arabic (ar)
- Hindi (hi)
- And many more...
-
AWS Credentials Not Found:
- Ensure AWS credentials are properly configured
- Check AWS CLI configuration:
aws configure list
-
Bedrock Access Denied:
- Verify your AWS account has access to Bedrock
- Check if the specified model is available in your region
-
FastMCP Connection Issues:
- Verify the path in mcp.json is correct
- Check that Python and dependencies are properly installed
- Review logs in Q Developer for error messages
- Test the server:
uv run python mcp_server.py
-
PowerPoint File Issues:
- Ensure the input file is a valid PowerPoint (.pptx) file
- Check file permissions for both input and output paths
-
Module Import Errors:
- Use
uv runto ensure proper virtual environment activation - Install dependencies:
uv sync
- Use
ppt-translator/
├── mcp_server.py # FastMCP server implementation
├── main.py # Main entry point
├── ppt_translator/ # Core package
│ ├── __init__.py # Package initialization
│ ├── cli.py # Command-line interface
│ ├── ppt_handler.py # PowerPoint processing logic
│ ├── translation_engine.py # Translation service
│ ├── bedrock_client.py # Amazon Bedrock client
│ ├── post_processing.py # Post-processing utilities
│ ├── config.py # Configuration management
│ ├── dependencies.py # Dependency management
│ ├── text_utils.py # Text processing utilities
│ └── prompts.py # Translation prompts
├── requirements.txt # Python dependencies
├── pyproject.toml # Project configuration (uv)
├── uv.lock # Dependency lock file
├── .env # Environment variables template
├── Dockerfile # Docker configuration
├── docs/ # Documentation
├── imgs/ # Example images and screenshots
└── samples/ # Sample files
This project is licensed under the MIT License - see the LICENSE file for details.






