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Here’s a quick example of how to create a chat completion using the Inceptron API with different programming languages:

Stream

Python

import os
from openai import OpenAI

client = OpenAI(
  base_url="https://api.inceptron.io/v1",
  api_key=os.environ["INCEPTRON_API_KEY"],
)

completion = client.chat.completions.create(
  model="meta-llama/Llama-3.3-70B-Instruct",
  messages=[
      {
          "role": "user",
          "content": "How many moons are there in the Solar System?"
      }
  ],
)

print(completion.choices[0].message)

JavaScript

import { OpenAI } from "openai";

const client = new OpenAI({
baseURL: "https://api.inceptron.io/v1",
apiKey: process.env.INCEPTRON_API_KEY,
});

const chatCompletion = await client.chat.completions.create({
model: "meta-llama/Llama-3.3-70B-Instruct",
  messages: [
      {
          role: "user",
          content: "How many moons are there in the Solar System?",
      },
  ],
});

console.log(chatCompletion.choices[0].message);

cURL

curl https://api.inceptron.io/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $INCEPTRON_API_KEY" \
-d '{
  "model": "meta-llama/Llama-3.3-70B-Instruct",
  "messages": [
    {
      "role": "user",
      "content": "How many moons are there in the Solar System?"
    }
  ]
}'