Frameworks

Every framework on this page has an OpenAI-compatible client, so LowRouter plugs in with a base URL, a key and a model ID. The code snippets below are re-run every week against the versions named in each section.

All of them read the key from the environment:

Bash

export LOWROUTER_API_KEY=sk-lr-...

LangChain (Python)

Verified with langchain-openai 1.6.6.

Bash

pip install langchain-openai

ChatOpenAI takes the base URL directly. Tool binding works as it does against OpenAI:

Python

import os
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool

llm = ChatOpenAI(
    model="auto/mistralai/mistral-large-2512",
    base_url="https://api.lowrouter.ai/v1",
    api_key=os.environ["LOWROUTER_API_KEY"],
)

@tool
def get_weather(city: str) -> str:
    """Return the current weather for a city."""
    return f"Sunny in {city}"

msg = llm.bind_tools([get_weather]).invoke("What is the weather in Lyon?")
print(msg.tool_calls)

This sends Chat Completions requests. LangChain switches to the Responses API when you set use_responses_api=True or use a feature that needs it; LowRouter serves both endpoints.

lowrouter_metadata is not reachable through msg.response_metadata: langchain-openai copies a fixed set of keys off the response and drops unknown top-level ones. To read the per-request record (route, region, energy, carbon), take msg.id (the completion id) and fetch GET /v1/generation/{id} with the same key; see per-request metadata.

LlamaIndex

Verified with llama-index-llms-openai-like 0.8.0.

Bash

pip install llama-index-llms-openai-like

Use OpenAILike. LlamaIndex’s plain OpenAI class checks model names against OpenAI’s own list and rejects LowRouter IDs.

Python

import os
from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    model="auto/mistralai/mistral-large-2512",
    api_base="https://api.lowrouter.ai/v1",
    api_key=os.environ["LOWROUTER_API_KEY"],
    is_chat_model=True,
    is_function_calling_model=True,
    context_window=256000,
)

print(llm.complete("In one sentence, what is a vector database?"))

OpenAILike knows nothing about the model, so tell it. is_chat_model defaults to false, which sends requests to the legacy /completions endpoint; set it to true for Chat Completions. is_function_calling_model=True lets agents use tools. context_window defaults to 3,900 tokens; set the model’s real window from the model browser.

CrewAI

Verified with crewai 1.15.23.

Bash

pip install crewai

Python

import os
from crewai import LLM

llm = LLM(
    model="openai/auto/mistralai/mistral-large-2512",
    base_url="https://api.lowrouter.ai/v1",
    api_key=os.environ["LOWROUTER_API_KEY"],
)

print(llm.call("In one sentence, what is a vector database?"))

The openai/ prefix selects CrewAI’s OpenAI-compatible client, which strips it and sends the rest of the ID unchanged. Without the prefix CrewAI reads auto as a provider name, falls back to LiteLLM and fails unless LiteLLM is installed. Pass the LLM to each Agent with llm=llm.

Vercel AI SDK

Verified with ai 7.0.122 and @ai-sdk/openai-compatible 3.0.59.

Bash

npm install ai @ai-sdk/openai-compatible

TypeScript

import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { generateText } from "ai";

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

const { text } = await generateText({
  model: lowrouter("auto/mistralai/mistral-large-2512"),
  prompt: "In one sentence, what is a vector database?",
});
console.log(text);

This uses @ai-sdk/openai-compatible, which calls Chat Completions with whatever model ID you give it. The @ai-sdk/openai provider sends requests to the Responses API by default; LowRouter serves that endpoint too, but the compatible provider is the one checked weekly.

The compatible provider keeps unknown top-level response fields under providerMetadata, keyed by the name you passed to createOpenAICompatible. With name: "lowrouter" as above, lowrouter_metadata is at providerMetadata.lowrouter.lowrouter_metadata on the generateText result (and on the final finish part of streamText).

n8n

n8n’s OpenAI credential has a Base URL field. Create an OpenAI credential with Base URL https://api.lowrouter.ai/v1 and your sk-lr-... key, then use it in an OpenAI Chat Model node and pick or type a LowRouter model ID. The node loads its model list from LowRouter.

Recent versions of the node call the Responses API by default (the Use Responses API option). LowRouter serves both endpoints; turn the option off to use Chat Completions. n8n is a GUI, so this section is not re-run by the weekly check.

Picking a model

Any LowRouter model ID works in these snippets. For agents and tool use, pick one with the function-calling tag; the model browser filtered to them lists every one.