Code examples

The examples on this page use https://api.llm.kiwi/v1 and the OpenAI-compatible chat completions interface.

Keep API keys on a trusted server. Never place a private key in public Git repositories or browser-side JavaScript.

Set your API key

macOS and Linux
Windows PowerShell

export LLM_KIWI_API_KEY="sk_kiwi_..."

$env:LLM_KIWI_API_KEY="sk_kiwi_..."

Basic chat completion

cURL
Python
Node.js

curl "https://api.llm.kiwi/v1/chat/completions" \
  -H "Authorization: Bearer $LLM_KIWI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "auto",
    "messages": [
      {"role": "user", "content": "Explain what an API is in one sentence."}
    ]
  }'

Install the package:

python -m pip install openai

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.llm.kiwi/v1",
    api_key=os.environ["LLM_KIWI_API_KEY"],
)

response = client.chat.completions.create(
    model="auto",
    messages=[
        {"role": "user", "content": "Explain what an API is in one sentence."}
    ],
)

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

Install the package:

npm install openai

Save this as chat.mjs:

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.llm.kiwi/v1",
  apiKey: process.env.LLM_KIWI_API_KEY,
});

const response = await client.chat.completions.create({
  model: "auto",
  messages: [
    { role: "user", content: "Explain what an API is in one sentence." },
  ],
});

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

node chat.mjs

System instructions

Use a system message to define the assistant’s role, output style, or constraints.

response = client.chat.completions.create(
    model="auto",
    messages=[
        {
            "role": "system",
            "content": "You are a patient tutor. Use short sentences and one example.",
        },
        {"role": "user", "content": "Explain recursion."},
    ],
)

Keep system instructions focused. If your application needs a strict format, validate the returned content instead of assuming the model always follows instructions perfectly.

Continue a conversation

The API is stateless: include relevant earlier messages on every request.

messages = [
    {"role": "user", "content": "My favorite color is green."},
    {"role": "assistant", "content": "Got it."},
    {"role": "user", "content": "What is my favorite color?"},
]

response = client.chat.completions.create(
    model="auto",
    messages=messages,
)

Stream a response

Streaming lets your application display text as it is generated.

Python
Node.js

stream = client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Write a short story."}],
    stream=True,
)

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

const stream = await client.chat.completions.create({
  model: "auto",
  messages: [{ role: "user", content: "Write a short story." }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

Croatian response

Select hrllm and write the request in Croatian:

response = client.chat.completions.create(
    model="hrllm",
    messages=[
        {"role": "system", "content": "Odgovaraj jasno i samo na hrvatskom jeziku."},
        {"role": "user", "content": "Objasni što je strojno učenje."},
    ],
)

Handle errors

import time
from openai import APIConnectionError, APIStatusError, RateLimitError

for attempt in range(3):
    try:
        response = client.chat.completions.create(
            model="auto",
            messages=[{"role": "user", "content": "Hello"}],
            timeout=30,
        )
        print(response.choices[0].message.content)
        break
    except RateLimitError:
        if attempt == 2:
            raise
        time.sleep(2 ** attempt)
    except APIConnectionError as error:
        print(f"Could not reach LLM.kiwi: {error}")
        break
    except APIStatusError as error:
        print(f"API returned {error.status_code}: {error.message}")
        break

Retry rate limits and temporary server errors with a delay. Do not automatically retry invalid requests or authentication errors.

SDK setup

Install and configure supported client libraries.

Troubleshooting

Fix authentication, request, and connection problems.

Get started

Build with LLM.kiwi

API reference

Help and resources

Set your API key

Basic chat completion

System instructions

Continue a conversation

Stream a response

Croatian response

Handle errors

SDK setup

Troubleshooting

​Set your API key

​Basic chat completion

​System instructions

​Continue a conversation

​Stream a response

​Croatian response

​Handle errors

SDK setup

Troubleshooting

Set your API key

Basic chat completion

System instructions

Continue a conversation

Stream a response

Croatian response

Handle errors