model-configuration

To prevent configuration drift from hardcoded model IDs, consolidate AI model definitions into a single MODEL_CONFIG source of truth. This standardizes metadata across providers, ensuring all components reference consistent configurations during multi-model deployments.

Standardize model metadata for auto-router and gateway configurations by enforcing a centralized MODEL_CONFIG structure. This approach applies standardized naming and explicit gateway handling to ensure safe, maintainable model usage across applications.

Route AI model calls safely without hardcoding strings by using getModel and getModelWithGateway patterns. These patterns pull model IDs directly from the MODEL_CONFIG source, guaranteeing consistent selection and preventing misaligned deployments.

Yes, model-configuration works for managing pricing and capabilities across different providers. It consolidates these attributes into a standardized MODEL_CONFIG structure, ensuring all apps reference unified metadata for safe routing and upgrades.

You should use a single source of truth for model definitions to eliminate drift from hardcoded IDs and simplify upgrades. Centralizing MODEL_CONFIG prevents inconsistency across multi-model deployments, ensuring maintainable software engineering practices.