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Physics MCP Server

by BlinkZer0
index.js2.29 kB
/** * Phase 6: ML/AI Augmentation Tool Package * Exports schemas, handlers, and tool definitions for machine learning capabilities */ export * from './schema.js'; export * from './handlers.js'; import { mlAugmentationSchema } from './schema.js'; /** * ML/AI Augmentation tool definition * Single consolidated tool with multiple ML methods */ export const mlAugmentationTool = { name: 'ml_ai_augmentation', description: `🧠 **ML/AI Augmentation Tool** - GPU-first machine learning capabilities for scientific computing with graphics-first outputs. Provides symbolic regression, PDE surrogates, pattern recognition, and derivation explanation. **Methods Available:** - **symbolic_regression_train**: Discover interpretable equations from data using PySR or genetic programming - **surrogate_pde_train**: Train physics-informed neural networks (PINNs) or data-driven PDE surrogates - **pattern_recognition_infer**: Detection/segmentation/classification on scientific imagery using YOLO/U-Net - **explain_derivation**: LLM-powered mathematical derivation and explanation with LaTeX output **GPU Acceleration:** - Automatic device selection (CUDA/HIP/MPS/XPU) with CPU fallback - VRAM monitoring and automatic batch size adjustment - Memory-efficient processing with configurable caps **Graphics-First Outputs:** - Training curves and loss plots for all methods - Prediction vs truth overlays and error visualizations - Confusion matrices for classification tasks - Optional MP4/WebM/GIF animations for PDE field evolution - Professional LaTeX formatting for mathematical explanations **Key Features:** - Caching by parameter hash for reproducibility - Early stopping and timeout protection - Comprehensive error handling and validation - Integration with Phase 5 visualization pipeline - Natural language interface ready`, inputSchema: mlAugmentationSchema }; /** * Build all ML tools (currently just the consolidated tool) */ export function buildMLTools() { return [mlAugmentationTool]; } /** * Legacy tool names for backward compatibility * Maps individual method names to consolidated tool calls */ export const legacyMLToolNames = [ 'symbolic_regression_train', 'surrogate_pde_train', 'pattern_recognition_infer', 'explain_derivation' ];

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