Building a Multi-Model AI Router in Python with Novastack 🚀 When you’re building production AI applications, managing multiple API keys, endpoints, and client libraries for different LLM providers becomes a maintenance nightmare. Today I’ll show you how to unify access to three powerhouse models through a single endpoint using Novastack’s token-forwarding platform. Why a Multi-Model Router Matters Most AI applications benefit from using different models for different tasks. Maybe DeepSeek-V4-Pro handles your code generation while Claude-Opus-4.7 manages creative writing. But traditional setups require: Separate API keys for each provider Different client libraries and authentication methods Manual failover logic when a provider goes down Complex routing logic scattered throughout your codebase Novastack solves this elegantly by providing a single OpenAI-compatible endpoint that routes requests to the appropriate model based on your model parameter. One key, one endpoint, three models.…