Add model explainability hooks and audit trail (fixes #676)#680
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…opt-in flags\n\nPartial implementation: lightweight local attributions; SHAP integration TODO (Smartdevs17#676)
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close#676
What: Adds explainability hooks for churn, pricing, and recommendations; records explanation audit trail to ml-service/explanations.json; exposes opt-in parameter on prediction endpoints.\n\nNotes: This is a first pass using lightweight attribution approximations (linear contributions / weighted components). Full SHAP integration, performance tuning, and API schema docs are TODO.\n\nFiles changed:\n- ml-service/model_registry.py\n- backend/ml/churnModel.py\n- backend/ml/pricingModel.py\n- ml-service/routers/churn.py\n- ml-service/routers/pricing.py\n- ml-service/routers/recommendations.py\n\nRelated: #676