A comprehensive implementation guide for building a hybrid cloud-local LLM routing system in production. Covers a three-pillar routing model based on data sensitivity, task complexity, and system availability. The stack uses LiteLLM as a unified proxy gateway, Ollama for local model serving, Anthropic Claude as the cloud tier, LangChain for orchestration, and Next.js as the application layer. Includes full TypeScript code for routing logic, LangChain RunnableBranch chains, Next.js API route handlers with PII detection, LiteLLM YAML configuration, cost-benefit analysis with worked examples, Kubernetes deployment patterns (sidecar, dedicated GPU node pool, edge-local), and a production deployment checklist. Key architectural constraint: sensitive requests must fail closed and never fall back to cloud providers.
Table of contents
Table of ContentsWhy Hybrid LLM Architecture Is Now a Production NecessityHow to Build a Hybrid Cloud-Local LLM Routing SystemArchitecture Overview: The Three-Pillar Routing ModelTech Stack and Component RolesGateway Setup: Configuring LiteLLM with Local and Cloud ProvidersImplementing the Routing Layer with LangChainNext.js Integration: API Routes and Frontend StreamingCost-Benefit Analysis: When Hybrid Pays OffProduction Deployment PatternsObservability, Logging, and GovernanceProduction Deployment ChecklistThe Pragmatic Path ForwardSort: