Models - NeuralTrust Docs | TrustGate, TrustGuard, TrustTest

If the application also fronts your models, the same key configures the provider’s own client, including the base URL. That is the one value no client can work out for itself, because the LLM plane lives on a different host from the MCP one.

from openai import OpenAI
from trustgate import TrustGate

llm = TrustGate().llm()
openai = OpenAI(base_url=llm.base_url, api_key=llm.api_key)

import OpenAI from "openai"
import { TrustGate } from "@neuraltrust/trustgate"

const llm = await new TrustGate().llm()
const openai = new OpenAI({ baseURL: llm.baseUrl, apiKey: llm.apiKey })

Nothing is wrapped. The SDK hands over the values and steps aside, so streaming and every provider option work exactly as the provider’s own client implements them.

What `llm()` returns

Field	Python	TypeScript	Use
Base URL	`base_url`	`baseUrl`	The OpenAI client. It ends in `/v1`.
Anthropic base URL	`anthropic_base_url`	`anthropicBaseUrl`	Anthropic’s client, which adds `/v1/messages` itself.
API key	`api_key`	`apiKey`	Any provider client’s own key parameter.
Headers	`headers`	`headers`	`X-AG-API-Key`, for a client that takes headers instead.
Consumer	`consumer`	`consumer`	The LLM application’s slug, for logs and errors.

from anthropic import Anthropic

claude = Anthropic(base_url=llm.anthropic_base_url, api_key=llm.api_key)

import Anthropic from "@anthropic-ai/sdk"

const claude = new Anthropic({ baseURL: llm.anthropicBaseUrl, apiKey: llm.apiKey })

What goes in model depends on how the application routes: "auto" when it load-balances, otherwise a model name. See What goes in model.

Naming the user

The key identifies the application, not the person using it. To attribute a model call to one, send X-NeuralTrust-End-User with it. The value lands on the trace and in Activity, and grants nothing.

openai.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Hello"}],
    extra_headers={"X-NeuralTrust-End-User": "user_123"},
)

await openai.chat.completions.create(
  { model: "auto", messages: [{ role: "user", content: "Hello" }] },
  { headers: { "X-NeuralTrust-End-User": "user_123" } },
)

A key that reaches no LLM application raises PlaneUnavailableError. For the gateway side of the LLM plane, see Connect your application.

A person’s models

A person’s personal key reaches the models Access grants them, and llm() on TrustGateUser hands them over the same way. There is no application to route through, so the person picks the model.

from openai import OpenAI
from trustgate import TrustGateUser

llm = TrustGateUser().llm()  # reads TRUSTGATE_PERSONAL_KEY
openai = OpenAI(base_url=llm.base_url, api_key=llm.api_key)
openai.chat.completions.create(model="gpt-4.1", messages=[{"role": "user", "content": "Hello"}])

import OpenAI from "openai"
import { TrustGateUser } from "@neuraltrust/trustgate"

const llm = await new TrustGateUser().llm() // reads TRUSTGATE_PERSONAL_KEY
const openai = new OpenAI({ baseURL: llm.baseUrl, apiKey: llm.apiKey })
await openai.chat.completions.create({ model: "gpt-4.1", messages: [{ role: "user", content: "Hello" }] })

A model their level does not reach is refused with 403 model_not_allowed before any provider is called. The Employee portal lists what they have, and asks for the rest. Models take the key: a browser sign-in reaches the person’s tools only.

​What llm() returns

​Naming the user

​A person’s models

What `llm()` returns

Naming the user

A person’s models