PowerPoint Translator using Amazon Bedrock

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 Kiro. It translates PowerPoint presentations while preserving formatting and structure.

Features

• 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, text elements, and entire folders efficiently
• Selective Translation: Translate entire presentations, specific slides, or all files in a folder

Examples

Translation

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

Kiro MCP Examples

Usage Examples

Translate entire presentation:

uv run ppt-translate translate samples/en.pptx --target-language ko

Translate specific slides:

uv run ppt-translate translate-slides samples/en.pptx --slides "1,3" --target-language ko

Batch translate all PPT files in a folder:

# Translate all PPT files in samples/ folder to Korean (parallel processing)
uv run ppt-translate batch-translate samples/ --target-language ko

# Recursively translate all PPT files in subfolders (like reInvent-2025/session1/, session2/, etc.)
uv run ppt-translate batch-translate samples/ --target-language ko --recursive

# Specify output folder
uv run ppt-translate batch-translate samples/ -t ja -o output/

# Specify number of parallel workers (default: 4)
uv run ppt-translate batch-translate samples/ -t ko -w 4

# Recursive with custom output and workers
uv run ppt-translate batch-translate reInvent-2025/ -t ko -o translated/ --recursive -w 8

Get slide information:

uv run ppt-translate info samples/en.pptx

Prerequisites

• 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.)

AWS Credentials Setup

Before using this service, ensure your AWS credentials are properly configured. You have several options:

1. 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

2. AWS Profile Configuration:

   aws configure --profile your-profile-name
   

3. 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
   

4. 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.

Installation

1. Clone the repository:

   git clone https://github.com/daekeun-ml/ppt-translator
   cd ppt-translator
   

2. Install dependencies using uv (recommended):

   uv sync
   

   Or using pip:

   pip install -r requirements.txt
   

3. Set up environment variables: Edit .env file 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 .env file if you have already configured them using aws configure. The service will automatically use your AWS CLI credentials.

Usage

Standalone Command-Line Usage

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 --help

FastMCP Server Mode (for AI Assistant Integration)

Start the FastMCP server for integration with AI assistants like Kiro:

# Using uv (recommended)
uv run mcp_server.py

# Using python directly
python mcp_server.py

FastMCP Setup (Kiro)

If you haven't already installed Kiro, please refer to this:

• Kiro: https://kiro.dev
• Kiro-CLI: https://kiro.dev/cli

2. Configure FastMCP Server

Create or update your Q Developer FastMCP configuration file:

Kiro

User Level ~/.kiro/settings/mcp.json

Kiro CLI

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": "global.anthropic.claude-sonnet-4-5-20250929-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": "global.anthropic.claude-sonnet-4-5-20250929-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.

3. Use PowerPoint Translation

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.

Available MCP Tools

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)

• 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)

• 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

• 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)

• 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

Configuration

Environment Variables

• 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)

Supported Languages

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...

Troubleshooting

Common Issues

1. AWS Credentials Not Found:

   • Ensure AWS credentials are properly configured
   • Check AWS CLI configuration: aws configure list

2. Bedrock Access Denied:

   • Verify your AWS account has access to Bedrock
   • Check if the specified model is available in your region

3. 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

4. PowerPoint File Issues:

   • Ensure the input file is a valid PowerPoint (.pptx) file
   • Check file permissions for both input and output paths

5. Module Import Errors:

   • Use uv run to ensure proper virtual environment activation
   • Install dependencies: uv sync

Development

Project Structure

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

License

This project is licensed under the MIT License - see the LICENSE file for details.