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Private Inference speaks the OpenAI Chat Completions format, so most tools that accept a custom OpenAI base URL work with zero code changes — set two values and you’re private by default across every model. 
Base URL:  https://api.t2000.ai/v1
API key:   sk-…        (create one at agents.t2000.ai/manage → API keys)
Get a key + add credit at agents.t2000.ai/manage (sign in with Google — same Passport + balance as Audric). Calls are metered per token and fail closed at a $0 balance. Browse models + pricing any time with GET /v1/models (public, no key).

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Environment variables (the universal swap)

Almost every OpenAI client reads these two variables. Set them once and the tool is repointed at t2000: 
export OPENAI_BASE_URL="https://api.t2000.ai/v1"
export OPENAI_API_KEY="sk-..."
Then pick a model from the catalog (e.g. zai/glm-5.2, anthropic/claude-sonnet-5, or a confidential phala/glm-5.2).

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OpenAI SDK

from openai import OpenAI

client = OpenAI(
    base_url="https://api.t2000.ai/v1",
    api_key="sk-...",
)

resp = client.chat.completions.create(
    model="zai/glm-5.2",
    messages=[{"role": "user", "content": "Hello from t2000"}],
)
print(resp.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.t2000.ai/v1",
  apiKey: process.env.T2000_API_KEY,
});

const resp = await client.chat.completions.create({
  model: "zai/glm-5.2",
  messages: [{ role: "user", content: "Hello from t2000" }],
});
console.log(resp.choices[0].message.content);

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Cursor

Cursor can route its chat models through any OpenAI-compatible endpoint:
  1. Settings → Models → API Keys → OpenAI API Key.
  2. Paste your sk-… key, expand Override OpenAI Base URL, and set it to https://api.t2000.ai/v1.
  3. Under Models, add the model IDs you want (e.g. zai/glm-5.2, anthropic/claude-sonnet-5), then Verify.
Cursor’s agentic features are tuned for specific frontier models. For a drop-in private chat model, add a model like zai/glm-5.2 or anthropic/claude-sonnet-5 and select it in the chat model picker.

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OpenAI Codex CLI

Add t2000 as a model provider in ~/.codex/config.toml: 
[model_providers.t2000]
name = "t2000"
base_url = "https://api.t2000.ai/v1"
env_key = "T2000_API_KEY"

[profiles.t2000]
model = "anthropic/claude-sonnet-5"
model_provider = "t2000"
Then run with the profile (export T2000_API_KEY=sk-… first): 
codex --profile t2000

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Vercel AI SDK

Use the OpenAI-compatible provider: 
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { generateText } from "ai";

const t2000 = createOpenAICompatible({
  name: "t2000",
  baseURL: "https://api.t2000.ai/v1",
  apiKey: process.env.T2000_API_KEY,
});

const { text } = await generateText({
  model: t2000("zai/glm-5.2"),
  prompt: "Hello from t2000",
});

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LangChain

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://api.t2000.ai/v1",
    api_key="sk-...",
    model="zai/glm-5.2",
)
print(llm.invoke("Hello from t2000").content)

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Other OpenAI-compatible clients

The same base URL + key works in any tool that targets OpenAI Chat Completions — coding agents like Kilo Code, Cline, Continue, and Aider (--openai-api-base), frameworks like LiteLLM (openai/<model>) and LlamaIndex, and most “bring your own OpenAI key” apps and agents. If a tool has an “OpenAI base URL” or “custom endpoint” field, point it at https://api.t2000.ai/v1, pick a model id from GET /v1/models, and every call is private by default — billed from your one balance.

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Anthropic-format tools (Claude Code)

Tools that speak the Anthropic Messages format (/v1/messages) — such as Claude Code — don’t talk to an OpenAI Chat Completions endpoint directly. Two options:
  • A translation proxy today — run LiteLLM (or a similar Anthropic↔OpenAI shim) pointed at https://api.t2000.ai/v1, and set the tool’s ANTHROPIC_BASE_URL to the proxy.
  • Native /v1/messages is on the roadmap (the additional-endpoints item) — when it ships, Anthropic-format tools will work with the base-URL swap alone.

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Good to know

  • Streaming works everywhere SSE does — set stream: true; pass stream_options: { include_usage: true } for a final usage chunk.
  • Model IDs are namespaced (provider/model); the live list is whatever GET /v1/models returns, each tagged private or confidential.
  • Keys are secrets — keep them server-side, one per app/environment so you can revoke independently. Don’t ship a raw key in a browser bundle.
  • Spend is bounded by your balance (and your auto-recharge threshold, if enabled). Each key is capped at 120 requests/minute.
See the Private Inference reference for the full endpoint, model, pricing, privacy, and error details.