There's a meaningful gap between "running a local LLM in a terminal" and "exposing it as an API that your team's apps can call." Ollama already provides a REST endpoint at localhost:11434 . The problem is that exposing it directly gives you zero authentication, no CORS handling, inconsistent error formats, and tight coupling to Ollama's specific response structure. When you change models, every client breaks. I solved this by wrapping Ollama with FastAPI, tested it in a sandbox, and this post documents what actually worked. What We'll Build A FastAPI server wrapping Ollama's REST API (Python 3.12 + FastAPI 0.136.3) Three endpoints: /health , /generate , /generate/stream NDJSON → SSE conversion for real-time streaming Docker Compose configuration for container deployment Real execution logs and response times from sandbox testing Tested on Ollama v0.20.5 with the yinw1590/gemma4-e2b-text model on an M1 MacBook Pro. Response time was ~14.9 seconds — CPU-only.…