Ollama serves models on infrastructure you control. Use it for local
development, private deployments, or workloads where you want to keep inference
inside your own network.
In Settings > Models, add Ollama and provide the endpoint URL. Ollama does
not require an API key. You can also set the endpoint as a deployment variable:
Use the Ollama service root, not its /v1 path. The local default is
http://127.0.0.1:11434; in a container deployment, use a hostname that
Roomote can resolve, such as http://ollama:11434.
After saving the provider, Roomote discovers available Ollama models. Enable the
models you need and select them using ollama/<model-name>, for example
ollama/qwen3-coder.
Connectivity and security
The Ollama endpoint must be reachable from the Roomote deployment. It does
not need to be exposed to every Roomote task sandbox. When Roomote and Ollama
run in separate containers, 127.0.0.1 points to the Roomote container, not
the Ollama container; use a shared network and service DNS instead.
Ollama normally accepts unauthenticated requests. Keep it bound to loopback or
a private network, and do not publish it directly to the internet. If traffic
must leave a trusted network, place a TLS-terminating, authenticated proxy in
front of Ollama and point Roomote at that private or protected endpoint.
Ollama listen address
Ollama listens only where its OLLAMA_HOST setting permits. To make it
reachable by another container on a private network, configure a listen address
that accepts the network connection, for example:
Do not use a public bind address without a protected reverse proxy or equivalent
network controls. Keep OLLAMA_BASE_URL pointed at the private service URL.
Cost behavior
Ollama does not charge a per-token provider price for locally served models.
Roomote can record model usage, but it cannot infer your hardware, electricity,
hosting, or capacity costs. Monitor GPU utilization and infrastructure spend
separately when comparing Ollama with hosted providers.
Verify setup
- pull a model with Ollama and confirm it appears in
ollama list
- save
OLLAMA_BASE_URL or the equivalent Settings value
- confirm the model appears in Settings > Models
- enable it, make it the default coding model, and start a small task
Common issues
- The model list is empty. Confirm Ollama is running, the model is pulled,
and Roomote can reach the configured endpoint.
- Connection refused in Docker. Use the Ollama service name instead of
127.0.0.1, and confirm both services share a network.
- Responses are slow or fail under load. Choose a smaller model, add GPU
capacity, or reduce concurrent task demand.