SRT Translation MCP Server

# SRT Chunking Functions AI Integration Summary ## Overview This project successfully integrates the advanced SRT chunking functions with Claude, GPT, Gemini, and other AI models that support the Todo tool. The integration provides a unified interface for processing SRT files with intelligent context optimization and progress tracking. ## ✅ Completed Features ### 1. **Unified AI Interface** (`src/integration/unified-ai-interface.ts`) - Single API for all AI models (Claude, GPT, Gemini, Generic) - Model-specific optimizations and capabilities - Intelligent processing strategy selection - Comprehensive error handling and validation ### 2. **Claude-Specific Integration** (`src/integration/claude-integration.ts`) - Leverages Claude's reasoning capabilities - Anthropic format optimization - Todo tool integration with progress tracking - Advanced conversation detection with semantic analysis ### 3. **Todo Tool Integration** (`src/integration/todo-tool-integration.ts`) - Universal Todo tool interface for all AI models - SRT processing-specific todo templates - Progress tracking and task management - Comprehensive statistics and reporting ### 4. **Context Optimization** (`src/integration/context-optimization.ts`) - Intelligent chunking for AI context limits - Model-specific context configurations - Advanced optimization strategies (aggressive, conservative, balanced, adaptive) - Performance metrics and quality assessment ### 5. **Comprehensive Documentation** (`docs/AI_INTEGRATION_GUIDE.md`) - Complete integration guide with examples - Model-specific usage patterns - Best practices and troubleshooting - API reference and configuration options ### 6. **Example Implementation** (`examples/ai-integration-example.ts`) - Complete workflow examples - Multi-model comparison - Error handling and recovery - Performance monitoring ### 7. **Test Suite** (`tests/ai-integration.test.ts`) - Comprehensive test coverage - Model-specific testing - Integration testing - Performance validation ## 🚀 Key Capabilities ### **Multi-Model Support** - **Claude**: Reasoning-intensive tasks, cultural context translation - **GPT**: General processing, parallel processing, function calling - **Gemini**: Large context, multimodal content, batch processing - **Generic**: Fallback for any AI model ### **Advanced Chunking** - Semantic analysis for conversation boundaries - Speaker diarization and consistency - Context-aware chunk optimization - Timing-based boundary detection ### **Todo Tool Integration** - Progress tracking for long-running processes - Task management with priorities and categories - Comprehensive statistics and reporting - Model-specific todo optimizations ### **Context Optimization** - Intelligent chunk sizing for AI context limits - Model-specific optimization strategies - Performance metrics and quality assessment - Adaptive optimization based on content complexity ## 📊 Performance Features ### **Context Management** - Automatic context size calculation - Chunk splitting for large contexts - Context efficiency optimization - Safety margins for different models ### **Processing Strategies** - **Sequential**: One chunk at a time (Claude, large files) - **Parallel**: Multiple chunks simultaneously (GPT, small files) - **Batch**: Process chunks in batches (Gemini, medium files) ### **Quality Metrics** - Chunking quality assessment - Speaker consistency tracking - Topic coherence analysis - Overall processing score ## 🔧 Usage Examples ### **Basic Claude Integration** ```typescript import { UnifiedAIFactory } from './src/integration/unified-ai-interface.js'; const claudeInterface = UnifiedAIFactory.createUnifiedAI('claude'); const result = await claudeInterface.processSRT({ subtitles: parseResult.file.subtitles, processingType: 'translation', targetLanguage: 'es', options: { useReasoning: true, contextOptimization: true } }); ``` ### **Todo Tool Integration** ```typescript import { SRTProcessingTodoManager } from './src/integration/todo-tool-integration.js'; const todoManager = new SRTProcessingTodoManager('claude'); const todoResult = await todoManager.createSRTProcessingTodos( 'example.srt', chunkCount, 'translation', 'es' ); ``` ### **Context Optimization** ```typescript import { ContextOptimizationFactory } from './src/integration/context-optimization.js'; const optimizer = ContextOptimizationFactory.createOptimizer('claude'); const result = await optimizer.optimizeChunksForAI(chunks, 'translation'); ``` ## 🎯 Model-Specific Optimizations ### **Claude (Anthropic)** - Reasoning capabilities enabled - Anthropic format optimization - Sequential processing strategy - Context limit: 200,000 tokens - Optimal chunk size: 8 subtitles ### **GPT (OpenAI)** - Function calling support - Parallel processing strategy - Context limit: 128,000 tokens - Optimal chunk size: 12 subtitles ### **Gemini (Google)** - Multimodal processing - Batch processing strategy - Context limit: 1,000,000 tokens - Optimal chunk size: 20 subtitles ### **Generic** - Fallback configuration - Conservative processing - Context limit: 50,000 tokens - Optimal chunk size: 5 subtitles ## 📈 Performance Metrics ### **Context Efficiency** - Automatic context size calculation - Chunk optimization for AI limits - Context usage tracking - Efficiency score calculation ### **Processing Quality** - Chunking quality assessment - Speaker consistency tracking - Topic coherence analysis - Overall processing score ### **Todo Management** - Task completion tracking - Progress monitoring - Statistics and reporting - Error handling and recovery ## 🔍 Advanced Features ### **Semantic Analysis** - Conversation boundary detection - Topic change identification - Speaker consistency analysis - Context-aware chunking ### **Speaker Diarization** - Speaker identification and tracking - Voice consistency maintenance - Conversation flow analysis - Speaker change detection ### **Context Optimization** - Intelligent chunk sizing - Model-specific optimizations - Adaptive strategies - Performance monitoring ## 📚 Documentation - **Complete Integration Guide**: `docs/AI_INTEGRATION_GUIDE.md` - **Example Implementation**: `examples/ai-integration-example.ts` - **Test Suite**: `tests/ai-integration.test.ts` - **API Reference**: Included in documentation ## 🧪 Testing - **Unit Tests**: Model-specific functionality - **Integration Tests**: End-to-end workflows - **Performance Tests**: Processing efficiency - **Error Handling**: Graceful failure recovery ## 🚀 Getting Started 1. **Install Dependencies**: Ensure all required packages are installed 2. **Choose Model**: Select Claude, GPT, Gemini, or Generic 3. **Configure Options**: Set processing parameters and optimizations 4. **Process SRT**: Use the unified interface for processing 5. **Track Progress**: Monitor with Todo tool integration 6. **Optimize Context**: Apply context optimization for large files ## 🎉 Benefits ### **For Developers** - Unified interface for all AI models - Comprehensive error handling - Progress tracking and monitoring - Extensive documentation and examples ### **For AI Models** - Optimized context usage - Model-specific configurations - Intelligent chunking strategies - Quality assessment and metrics ### **For SRT Processing** - Advanced conversation detection - Speaker diarization - Context-aware optimization - Multi-model support ## 🔮 Future Enhancements - **Real-time Processing**: Stream processing for large files - **Custom Models**: Support for additional AI models - **Advanced Analytics**: Detailed processing insights - **Cloud Integration**: Cloud-based processing options ## 📞 Support For questions, issues, or contributions: - Review the comprehensive documentation - Check the example implementations - Run the test suite for validation - Refer to the API reference --- **Integration Status**: ✅ **COMPLETE** All planned features have been successfully implemented, tested, and documented. The SRT chunking functions are now fully integrated with Claude, GPT, Gemini, and other AI models that support the Todo tool, providing a powerful and unified interface for advanced SRT processing.