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Docs: TINYDOC-3550 - Clarify on-premises AI quick-start configures only OpenAI; custom providers need PROVIDERS and MODELS
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modules/ROOT/pages/tinymceai-on-premises-getting-started.adoc

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@@ -181,7 +181,7 @@ Use the matching network name in `--network` below. First, load the `.env` file:
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set -a && source .env && set +a
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Then start the AI service container:
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Then start the AI service container. The `docker run` command maps the friendly `.env` names onto the service's own environment variables — for example, `AI_LICENCE_KEY` is passed to the container as `LICENSE_KEY`, and `MANAGEMENT_SECRET` as `ENVIRONMENTS_MANAGEMENT_SECRET_KEY`:
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[source,bash]
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registry.containers.tiny.cloud/ai-service-tiny:latest
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[IMPORTANT]
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====
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This launch command configures a single OpenAI provider, through the `PROVIDERS` value and `$OPENAI_API_KEY`. The AI service only receives the environment variables explicitly passed in the `docker run` command, so adding `PROVIDERS`, `MODELS`, or other provider settings to the `.env` file alone has no effect.
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To use any other provider — `openai-compatible` (for example Databricks, Ollama, or vLLM), Azure, Amazon Bedrock, or Google Vertex — edit the `docker run` command directly: replace the `PROVIDERS` value and add a `MODELS` array. The `MODELS` variable is required for every provider except direct OpenAI, Anthropic, and Google, which have built-in model routing. See xref:tinymceai-on-premises-providers.adoc[LLM providers] for the full `PROVIDERS` and `MODELS` configuration.
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====
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NOTE: The AI service contacts `license.containers.tiny.cloud` on startup to validate the license key. Ensure this endpoint is reachable from the container. No customer data is sent during this check.
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TIP: If the container already exists from a previous attempt, remove it first with `docker rm -f ai-service`.

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