The outcome
You will create a private chat interface backed by a model runner you control. The browser UI, model service and public access boundary remain separate so each can be secured and replaced.
Architecture
Open WebUI provides the interface. Ollama runs the selected model. Caddy terminates HTTPS and should be the only public entry point. Do not expose Ollama port 11434 directly.
Cost and risk
Start with a model that fits measured RAM, disk and accelerator capacity. CPU-only evaluation is possible for smaller models, but production latency and concurrency require workload testing.
Operating model
Back up Open WebUI data and configuration, document model versions, restrict registration and monitor memory, disk and failed sign-ins.
From need to working outcome
Define privacy and workload boundaries
Decide who can access the assistant, whether prompts may leave the host, and the largest model the service must run.
Install and validate Ollama
Use the current official Linux guide, run a small test model and keep the API bound to a private interface.
Deploy Open WebUI with persistent data
Run the UI with a persistent volume and stable secret, then connect it to Ollama over a private network.
Add HTTPS and access controls
Place Caddy in front, disable public sign-up and restrict firewall access to internal service ports.
Test recovery before inviting users
Back up configuration and application data, restore them in a test location and document the rollback procedure.
AI tools for this workflow
Continue with technical deployment
Install Ollama on Linux and Expose It Safely
Install Ollama on Linux, run a first model, verify the local API and understand why port 11434 should not be exposed to the public internet without authentication.
Deploy Open WebUI with Docker and Persistent Storage
Run Open WebUI in Docker, persist application data, connect it to Ollama and add the production safeguards recommended by the project documentation.
What to know before you start
Does a private assistant require a GPU?
Not always. Small quantized models can run on CPU, but response speed, model size and concurrent use determine whether a GPU is practical.
Can I expose Ollama directly to the internet?
Do not expose its API without an authenticated protective layer. Keep it private and route users through the secured application interface.
What must be backed up?
Protect Open WebUI data, environment configuration, secrets and any custom knowledge files. Model files can usually be downloaded again.