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Python ↔ TypeScript Integration Guide

A single FastAPI server exposing all 6 model subsystems: - Skill Graph (Bayesian inference + message passing) - Alignment Scorer - Gravity/Mass Estimator - Life State Dynamics - Echelon Fusion - Scenario Generator & Evaluator

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### 1. Python FastAPI Server (`models/api/server.py`) **Status**: ✅ Complete - Ready to run A single FastAPI server exposing all 6 model subsystems: - Skill Graph (Bayesian inference + message passing) - Alignment Scorer - Gravity/Mass Estimator - Life State Dynamics - Echelon Fusion - Scenario Generator & Evaluator ### 2. TypeScript Python Client (`services/trajectory-core/src/python/`) **Status**: ✅ Complete **Files**: - `client.ts` - Main HTTP client class - `types.ts` - TypeScript types matching Python models - `index.ts` - Exports **Changes**: - Calls `pythonClient.updateSkillBelief()` for each piece of evidence - Calls `pythonClient.propagateBeliefUpdate()` to propagate through graph - Stores Bayesian posterior (mean, std) in database - Fallback to simple averaging if Python API unavailable

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