NextChat

NextChat is a lightweight, self-hostable chat UI. It speaks the OpenAI schema, so it accepts CAPI through the standard base-URL and key variables.

Prerequisites

• NextChat deployed (Vercel, Docker, or local dev).
• A CAPI API key.

Docker

docker run -d \
  -p 3000:3000 \
  -e OPENAI_API_KEY="capi_sk_live_..." \
  -e BASE_URL="https://capi.ai/api/v1" \
  -e CUSTOM_MODELS="gpt-5.6,claude-opus-5,gemini-3.1-pro,deepseek-v4-flash" \
  -e DEFAULT_MODEL="gpt-5.6" \
  yidadaa/chatgpt-next-web

BASE_URL is the important one — without it NextChat talks to OpenAI's own endpoint.

Vercel

Add the same variables under Project → Settings → Environment Variables, then redeploy. Environment changes need a new deployment to take effect.

In-app settings

Users can override the endpoint per browser under Settings:

• API Key — their own CAPI key, if you do not want to share one.
• Custom Endpoint — https://capi.ai/api/v1.
• Custom Models — comma-separated IDs.

Per-user keys keep usage attributable, which matters when several people share an instance.

Model list

NextChat does not discover models. Curate the list to what the deployment needs:

Masks and templates

NextChat's prompt templates are client-side, so they compose with any model. A mask that sends a large system prompt costs more per turn — deepseek-v4-flash or gpt-5-mini keeps template-heavy usage affordable.

Access control

For a private instance, set CODE to require an access code before the UI is usable:

-e CODE="$(openssl rand -hex 8)"

This protects the chat UI, not the API key. Treat the key as the real boundary and scope it accordingly.

Troubleshooting

401 from the browser. The key is set in the deployment but the user overrode it with an empty value. Clear the per-user setting.

Model not in the dropdown. CUSTOM_MODELS must list exact catalog IDs.

Responses stop mid-stream. A reverse proxy is buffering. Disable proxy_buffering for the API route, or raise proxy_read_timeout.

Next steps

• Jan
• LLM API quickstart