LLM Search

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"], # Replace with the key you generated in AiHubMix
    base_url="https://aihubmix.com/v1"
)

chat_completion = client.chat.completions.create(
    model="gemini-3.5-flash",
    # 🌐 Enable search
    web_search_options={},
    messages=[
        {
            "role": "user",
            "content": "Search for information about the AIhubmix LLM API platform, provide a brief introduction, and include relevant links."
        }
    ]
)

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

import OpenAI from 'openai';

const client = new OpenAI({
    apiKey: process.env.AIHUBMIX_API_KEY,
    baseURL: 'https://aihubmix.com/v1'
});

async function main() {
    const chatCompletion = await client.chat.completions.create({
        model: 'gemini-3.5-flash',
        // 🌐 Enable search
        web_search_options: {},
        messages: [
            {
                role: 'user',
                content: 'Search for information about the AIhubmix LLM API platform, provide a brief introduction, and include relevant links.'
            }
        ]
    });

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

main().catch(console.error);

curl "https://aihubmix.com/v1/chat/completions" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $AIHUBMIX_API_KEY" \
    -d '{
    "model": "gemini-3.5-flash",
    "web_search_options": {},
    "messages": [
        {
            "role": "user",
            "content": "Provide information about Van Gogh on the Google Arts & Culture website, with a brief introduction and relevant links."
        }
    ],
    "stream": false
}'

import requests
import json
import os

try:
    response = requests.post(
        url="https://aihubmix.com/v1/chat/completions",
        headers={
            "Authorization": f"Bearer {os.environ.get('AIHUBMIX_API_KEY')}",
            "Content-Type": "application/json",
        },
        json={
            "model": "gpt-5.5:surfing", # Append :surfing to the model id to support searching
            "messages": [
                {
                    "role": "user",
                    "content": "Search for recent AIHubMix model updates, return concise Portuguese bullet points with source links."
                }
            ],
            "stream": False
        },
        timeout=60
    )

    result = response.json()
    if response.status_code >= 400:
        print("Request failed:", response.status_code)
    print("API response:", json.dumps(result, ensure_ascii=False, indent=2))

except requests.exceptions.RequestException as e:
    print(f"Request error: {e}")
except json.JSONDecodeError as e:
    print(f"JSON decode error: {e}")
except Exception as e:
    print(f"Other error: {e}")