Open WebUI

Open WebUI is a self-hosted chat interface with an OpenAI-compatible backend. CAPI slots in as a drop-in provider, which means one config change gives you Claude, GPT, Gemini, DeepSeek, and the whole catalog in one picker.

Prerequisites

• A running Open WebUI instance (Docker or bare metal).
• A CAPI API key from Settings → API Keys.

Configure with Docker

Pass the settings as environment variables:

docker run -d \
  -p 3000:8080 \
  -e OPENAI_API_BASE_URL="https://capi.minapp.xin/api/v1" \
  -e OPENAI_API_KEY="capi_sk_live_..." \
  -v open-webui:/app/backend/data \
  --name open-webui \
  ghcr.io/open-webui/open-webui:main

Restart the container after changing them.

Configure in the UI

If the instance is already running:

1. Open Admin Settings → Connections.
2. Under OpenAI API, set the base URL to https://capi.minapp.xin/api/v1.
3. Paste the API key.
4. Click the refresh icon next to the URL to import the model list.

Every model your key can reach appears in the model dropdown.

Verify

Send a message. If it fails:

• 401 — the key is wrong or has a trailing newline from copy-paste.
• Empty model list — the base URL is missing /v1. Open WebUI appends /models directly.
• Connection refused — the container cannot reach the internet; check its DNS.

Image generation

Open WebUI's image tool calls POST /v1/images/generations, which CAPI serves directly:

1. Admin Settings → Images.
2. Enable image generation.
3. Choose an engine with the same base URL and key.
4. Set the model, for example gpt-image-2-text-to-image.

Images then render inline in chat.

Mixing providers

Keep your local Ollama models alongside CAPI: add both connections and both model lists merge into one picker. Route sensitive prompts to the local models and everything else to CAPI.

Cost visibility

Open WebUI does not track spend. Check the CAPI dashboard under Usage, or set a spending cap on the key so a runaway conversation cannot overspend.

Tips

• Disable models you do not want offered, and expose only models enabled for your CAPI workspace.
• For team deployments, use a separate CAPI key per user group so usage is attributable.
• Vision requests depend on whether the selected channel and model accept image input.

Next steps

• LLM API quickstart
• AnythingLLM