Use Modellix LLM with the OpenAI SDK - Modellix

Use the official OpenAI client libraries against Modellix by setting the base URL to the LLM gateway and using a Modellix API key. Requests are synchronous and can stream over SSE.

Use a Modellix API key from the console, not an OpenAI platform key. Model IDs use provider/name (for example openai/gpt-5.5)—see Models & Pricing for the full list.

Configure the client

export OPENAI_API_KEY="mdlx-xxxxxxxx"
export OPENAI_BASE_URL="https://llm.modellix.ai/v1"

Setting	Value
Base URL	`https://llm.modellix.ai/v1` (include `/v1`)
API key	Modellix API Key via `OPENAI_API_KEY`
Model	Prefer `openai/...` (or `google/...` on the OpenAI-compatible path). See Models & Pricing.

Then call the SDK as usual. Chat Completions maps to POST /v1/chat/completions; Responses maps to POST /v1/responses.

Chat Completions example

from openai import OpenAI

client = OpenAI()  # reads OPENAI_API_KEY and OPENAI_BASE_URL

completion = client.chat.completions.create(
    model="openai/gpt-5.5",
    messages=[
        {"role": "user", "content": "Introduce yourself in one sentence"},
    ],
    max_tokens=256,
)

print(completion.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI(); // reads OPENAI_API_KEY and OPENAI_BASE_URL

const completion = await client.chat.completions.create({
  model: "openai/gpt-5.5",
  messages: [{ role: "user", content: "Introduce yourself in one sentence" }],
  max_tokens: 256,
});

console.log(completion.choices[0].message.content);

Streaming

Set stream=true (or the SDK equivalent). The gateway returns text/event-stream with OpenAI-style chat.completion.chunk events ending in data: [DONE].

stream = client.chat.completions.create(
    model="openai/gpt-5.6-sol",
    messages=[{"role": "user", "content": "ping"}],
    stream=True,
    max_tokens=256,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

Responses API

If your SDK or app targets the OpenAI Responses API, keep the same base URL and key, but send Responses fields (input, max_output_tokens) instead of Chat Completions messages / max_tokens. See Create response.

LLM API guide — protocols, auth, errors, and curl examples
Codex — CLI config with openai_base_url
OpenCode — provider baseURL for OpenAI-compatible mode