Build a Unified AI Gateway with LiteLLM and Ollama

Unify all your AI models - local and cloud - behind a single OpenAI-compatible API with LiteLLM and Ollama. LiteLLM is a proxy server that exposes 100+ LLM providers through one endpoint. Connect it to Ollama for local inference, and you get load balancing, cost tracking, rate limits, and automatic fallback routing. What You Need Python 3.9+ Ollama installed and running About 20 minutes Setup 1. Install LiteLLM pip install 'litellm[proxy]' 2. Create config.yaml model_list : - model_name : qwen3-local litellm_params : model : ollama/qwen3:14b api_base : http://localhost:11434 rpm : 30 - model_name : gpt-4o-mini litellm_params : model : openai/gpt-4o-mini api_key : os.environ/OPENAI_API_KEY general_settings : master_key : sk-your-key 3. Start the Proxy litellm --config config.yaml --port 4000 4. Use It from openai import OpenAI client = OpenAI ( api_key = " sk-your-key " , base_url = " http://localhost:4000/v1 " ) response = client . chat . completions . create ( model = " qwen3-local " , messages = [{ " role " : " user " , " content " : " Hello! " }]) Key Features Smart fallback - if local model fails, auto-route to cloud Load balancing - distribute across multiple GPU instances Cost tracking - per-model spend dashboard Rate limiting - control requests per user/key One API - use any tool that supports OpenAI format Cost vs Cloud LiteLLM + Ollama Direct Cloud APIs Gateway Free, self-hosted Free Local inference $0 N/A Model switching One endpoint Multiple SDKs Failover Automatic Manual Full guide with advanced config examples: https://everylocalai.com/stack/litellm-ollama-gateway