OpenShell/docs/inference/configure.md

title, description, topics, tags, content

title	description	topics	tags	content
page nav Configure Inference Routing Configure	Set up the managed local inference endpoint with provider credentials and model configuration.	Generative AI Cybersecurity	Inference Routing Configuration Privacy LLM Provider	type difficulty audience how_to technical_intermediate engineer

Configure Inference Routing

This page covers the managed local inference endpoint (https://inference.local). External inference endpoints go through sandbox network_policies — refer to Network Access Rules for details.

The configuration consists of two values:

Value	Description
Provider record	The credential backend OpenShell uses to authenticate with the upstream model host.
Model ID	The model to use for generation requests.

Step 1: Create a Provider

Create a provider that holds the backend credentials you want OpenShell to use.

:::::{tab-set}

::::{tab-item} NVIDIA API Catalog

$ openshell provider create --name nvidia-prod --type nvidia --from-existing

This reads NVIDIA_API_KEY from your environment.

::::

::::{tab-item} Local / self-hosted endpoint

$ openshell provider create \
    --name my-local-model \
    --type openai \
    --credential OPENAI_API_KEY=empty-if-not-required \
    --config OPENAI_BASE_URL=http://192.168.10.15/v1

Use --config OPENAI_BASE_URL to point to any OpenAI-compatible server running on your network. Set OPENAI_API_KEY to a dummy value if the server does not require authentication.

::::

::::{tab-item} Anthropic

$ openshell provider create --name anthropic-prod --type anthropic --from-existing

This reads ANTHROPIC_API_KEY from your environment.

::::

:::::

Step 2: Set Inference Routing

Point inference.local at that provider and choose the model to use:

$ openshell inference set \
    --provider nvidia-prod \
    --model nvidia/nemotron-3-nano-30b-a3b

Step 3: Verify the Active Config

Confirm that the provider and model are set correctly:

$ openshell inference get
Gateway inference:

  Provider: nvidia-prod
  Model: nvidia/nemotron-3-nano-30b-a3b
  Version: 1

Step 4: Update Part of the Config

Use update when you want to change only one field:

$ openshell inference update --model nvidia/nemotron-3-nano-30b-a3b

Or switch providers without repeating the current model:

$ openshell inference update --provider openai-prod

Use It from a Sandbox

After inference is configured, code inside any sandbox can call https://inference.local directly:

from openai import OpenAI

client = OpenAI(base_url="https://inference.local/v1", api_key="dummy")

response = client.chat.completions.create(
    model="anything",
    messages=[{"role": "user", "content": "Hello"}],
)

The client-supplied model is ignored for generation requests. OpenShell rewrites it to the configured model before forwarding upstream.

Use this endpoint when inference should stay local to the host for privacy and security reasons. External providers that should be reached directly belong in network_policies instead.

Verify the Endpoint from a Sandbox

openshell inference get confirms the configuration was saved, but does not verify the upstream endpoint is reachable. To confirm end-to-end connectivity, connect to a sandbox and run:

curl https://inference.local/v1/responses \
    -H "Content-Type: application/json" \
    -d '{
      "instructions": "You are a helpful assistant.",
      "input": "Hello!"
    }'

A successful response confirms the privacy router can reach the configured backend and the model is serving requests.

:::{note}

• Gateway-scoped — every sandbox on the active gateway sees the same inference.local backend.
• HTTPS only — inference.local is intercepted only for HTTPS traffic. :::

Next Steps

Explore related topics:

• To understand the inference routing flow and supported API patterns, refer to {doc}index.
• To control external endpoints, refer to Network Access Rules.
• To manage provider records, refer to {doc}../sandboxes/providers.