UnrealBlueprintMCP

# LangChain Integration Examples This directory demonstrates advanced AI-powered blueprint generation using LangChain integration with the UnrealBlueprintMCP system. ## 🧠 AI-Powered Features ### 🗣️ Natural Language Blueprint Generation **File**: `nl_blueprint_generator.py` - Convert natural language descriptions to blueprints - Intelligent component selection based on description - Automatic property inference from context - Support for complex multi-component blueprints ### 🤖 Intelligent Assistant **File**: `blueprint_assistant.py` - Interactive AI assistant for blueprint development - Context-aware suggestions and optimizations - Automated code generation and property setup - Integration with existing project assets ### 🎯 Smart Template Generator **File**: `smart_template_generator.py` - Generate blueprint templates from game descriptions - Automatic architecture planning - Component dependency analysis - Performance optimization suggestions ### 🔍 Code Analysis and Suggestions **File**: `code_analyzer.py` - Analyze existing blueprints for improvements - Suggest optimizations and best practices - Identify potential issues and bugs - Generate documentation automatically ## 🚀 Quick Start 1. **Install Dependencies** ```bash pip install -r requirements.txt ``` 2. **Setup API Keys** ```bash export OPENAI_API_KEY="your-openai-api-key" # or echo "OPENAI_API_KEY=your-key" >> .env ``` 3. **Test Basic Functionality** ```bash python nl_blueprint_generator.py --description "A fast-moving enemy that shoots projectiles" ``` ## 📋 Configuration ```python # LangChain Configuration LANGCHAIN_CONFIG = { "model": "gpt-4", "temperature": 0.7, "max_tokens": 2000, "system_prompt": "You are an expert Unreal Engine blueprint developer..." } ``` ## 🎯 Usage Examples ### Natural Language Generation ```python from nl_blueprint_generator import NLBlueprintGenerator generator = NLBlueprintGenerator() result = await generator.generate_from_description( "Create a player character that can jump, run, and shoot. " "The character should have health and ammunition systems." ) ``` ### Interactive Assistant ```python from blueprint_assistant import BlueprintAssistant assistant = BlueprintAssistant() await assistant.start_session() # User: "I need a weapon that fires in burst mode" # Assistant will analyze, suggest components, and generate blueprint ``` ### Smart Template Generation ```python from smart_template_generator import SmartTemplateGenerator generator = SmartTemplateGenerator() template = await generator.create_game_template( game_type="platformer", features=["collectibles", "enemies", "power-ups"], complexity="medium" ) ``` ## 🧠 AI Prompt Engineering ### System Prompts The examples use carefully crafted system prompts for optimal results: ```python BLUEPRINT_EXPERT_PROMPT = """ You are an expert Unreal Engine blueprint developer with deep knowledge of: - Component architecture and best practices - Performance optimization techniques - Blueprint visual scripting patterns - Game development patterns and conventions When generating blueprints, always consider: 1. Performance implications 2. Maintainability and modularity 3. Unreal Engine best practices 4. Component relationships and dependencies """ ``` ### Context Management - Maintains conversation history for better understanding - Uses project-specific context when available - Adapts suggestions based on existing blueprints ## 🔧 Advanced Features ### Chain of Thought Processing ```python # Example of multi-step blueprint generation async def generate_complex_blueprint(description): # Step 1: Analyze requirements requirements = await analyze_requirements(description) # Step 2: Plan architecture architecture = await plan_architecture(requirements) # Step 3: Generate components components = await generate_components(architecture) # Step 4: Create blueprint blueprint = await create_blueprint(components) return blueprint ``` ### Multi-Agent Collaboration ```python # Different AI agents for different tasks class BlueprintTeam: def __init__(self): self.architect = ArchitectAgent() # High-level design self.implementer = ImplementerAgent() # Detailed implementation self.optimizer = OptimizerAgent() # Performance tuning self.reviewer = ReviewerAgent() # Quality assurance ``` ## 📊 Performance Optimization ### Token Usage Optimization - Use template-based prompts to reduce token consumption - Implement response caching for similar requests - Batch multiple operations when possible ### Response Quality Improvement - Use few-shot examples in prompts - Implement validation and retry logic - Use structured output formats (JSON schemas) ## ⚠️ Important Notes ### API Usage and Costs - Monitor API usage and costs carefully - Implement rate limiting for production use - Use caching to reduce redundant API calls - Consider using smaller models for simple tasks ### Quality Assurance - Always validate AI-generated blueprints - Test generated code in development environment - Implement human review for critical blueprints - Use version control for AI-generated assets ### Privacy and Security - Never send sensitive project data to external APIs - Use local models when possible for sensitive projects - Implement proper API key management - Review generated code for security implications ## 🔗 Integration with Other Examples - **Batch Operations**: Use AI to generate bulk blueprint specifications - **Web Dashboard**: Display AI suggestions in the web interface - **Game Setup**: Use AI to create initial project templates ## 📚 Additional Resources - [LangChain Documentation](https://python.langchain.com/) - [OpenAI API Reference](https://platform.openai.com/docs/) - [Unreal Engine Blueprint Best Practices](https://docs.unrealengine.com/5.0/en-US/blueprints-best-practices-in-unreal-engine/) - [AI-Assisted Game Development Patterns](../../docs/AI_DEVELOPMENT_PATTERNS.md)