PowerPoint Translator

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 Amazon Q Developer. 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
• 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

Examples

Translation

The PowerPoint Translator maintains the original formatting while accurately translating content:

Kiro MCP Examples

Usage Examples

Translate entire presentation:

Translate specific slides:

Get slide information:

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 <repository-url> cd ppt-translator
2. Install dependencies using uv (recommended):
   uv sync
   Or using pip:
   pip install -r requirements.txt
3. Set up environment variables:
   cp .env.example .env
   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 # Debug Settings DEBUG=false
   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:

FastMCP Server Mode (for AI Assistant Integration)

Start the FastMCP server for integration with AI assistants like Amazon Q Developer:

FastMCP Setup (Amazon Q Developer and Kiro)

If 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

2. Configure FastMCP Server

Create or update your Q Developer FastMCP configuration file:

Kiro

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

Amazon Q Developer

On macOS/Linux: ~/.aws/amazonq/mcp.json On Windows: %APPDATA%\amazonq\mcp.json

Add the PowerPoint Translator FastMCP server configuration:

Using uv:

Alternative configuration using python directly:

Important: Replace /path/to/ppt-translator/ with the actual path to your cloned repository.

3. Verify FastMCP Server

Test that the FastMCP server is working:

4. Use PowerPoint Translation

Once connected, you can use commands like (User input does not have to be in English):

Available FastMCP Tools

The FastMCP 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 server.py --mcp --test
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

Debug Mode

Enable debug logging:

Development

Project Structure

Using uv for Development

This project uses uv for dependency management:

License

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