LLMBase | Docs

Quickstart

Make your first LLMBase API call in under two minutes.

Updated

LLMBase exposes an OpenAI-compatible REST API at https://api.llmbase.ai. Any client or SDK that works with OpenAI will work with LLMBase — just swap the base URL and your API key.

Base URL

https://api.llmbase.ai

Your first request

curl

curl https://api.llmbase.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMBASE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "zai-org/glm-5",
    "messages": [
      { "role": "user", "content": "Hello! What can you do?" }
    ]
  }'

Node.js — OpenAI SDK

import OpenAI from "openai";

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

const response = await client.chat.completions.create({
  model: "zai-org/glm-5",
  messages: [{ role: "user", content: "Hello! What can you do?" }],
});

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

Python — OpenAI SDK

from openai import OpenAI

client = OpenAI(
    base_url="https://api.llmbase.ai/v1",
    api_key=os.environ["LLMBASE_API_KEY"],
)

response = client.chat.completions.create(
    model="zai-org/glm-5",
    messages=[{"role": "user", "content": "Hello! What can you do?"}],
)

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

Streaming

Add "stream": true to receive tokens as they are generated using Server-Sent Events.

const stream = await client.chat.completions.create({
  model: "zai-org/glm-5",
  messages: [{ role: "user", content: "Write a haiku about inference." }],
  stream: true,
});

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

Next steps