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.
$ openshell provider create --name nvidia-prod --type nvidia --from-existing
This reads NVIDIA_API_KEY from your environment.
$ 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.
$ 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.localbackend.HTTPS only —
inference.localis intercepted only for HTTPS traffic.
Next Steps#
Explore related topics:
To understand the inference routing flow and supported API patterns, refer to About Inference Routing.
To control external endpoints, refer to Network Access Rules.
To manage provider records, refer to Providers.
To view
openshell inferencecommands, refer to CLI Reference.