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1️⃣ Real-time Web Search: Breaking LLM Time Limitations for More Accurate and Reliable Outputs

We’ve enhanced OpenAI and Gemini series models with the ability to access the latest information from the web, helping you:
  • ✅ Access Latest Information: Get real-time updates on current events, latest research, or live data
  • ✅ Eliminate Knowledge Gaps: Overcome the time limitations of LLM training data by accessing post-training information
  • ✅ Reduce Hallucinations: Provide fact-based answers through real-time web searches, significantly reducing AI confabulations
  • ✅ Improve Decision Quality: Make more confident decisions based on analysis and recommendations grounded in current facts
Supported Models: Currently supporting OpenAI and Gemini model series with two integration methods: 1. Models with Native Search Capabilities Gemini Series (Ground with Google search):
  • gemini-3.1-pro-preview-search
  • gemini-3-flash-preview-search
  • gemini-2.5-pro-search
  • gemini-2.5-flash-search
OpenAI Series (Search Preview):
  • gpt-4o-search-preview
  • gpt-4o-mini-search-preview
2. Parameter-Based Support Add the parameter web_search_options={} to enable web connectivity for Gemini and OpenAI models that support this parameter. If the API returns Unknown parameter: 'web_search_options', the current model or upstream API does not accept this parameter. Use one of the native search models above, or use the :surfing suffix described below. Gemini search pricing is subject to the console and model detail page.

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Usage Guide

Before using, run pip install -U openai to upgrade the openai package, and set your AIHubMix API Key as an environment variable: 
export AIHUBMIX_API_KEY="<AIHUBMIX_API_KEY>"
Windows PowerShell: 
setx AIHUBMIX_API_KEY "<AIHUBMIX_API_KEY>"
Example: 
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)

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2️⃣ Smart Surfing: Allowing AI to Explore the Internet Freely

By appending :surfing to the model id, any large language model can be equipped with search capabilities.
  • Simply append the suffix, no complex integration is required
  • This method will default to forwarding the user’s request to the Tavily search service, and the LLM will reference the search results for response
  • Search fee: $0.006 per search
  • The fee is currently deducted directly from the “credit change”, and the “log detail” does not list the search fee yet, but will be shown in the future
The model id can be copied from the model gallery.
Example: 
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 English 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}")
API Response Example: 
{
  "id": "chatcmpl-xxxx",
  "model": "gpt-5.5-2026-04-24",
  "object": "chat.completion",
  "created": 1760000000,
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "AIHubMix is an API platform that aggregates model capabilities from multiple providers. Its official website is https://aihubmix.com."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 220,
    "completion_tokens": 240,
    "total_tokens": 460,
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    },
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 196,
      "rejected_prediction_tokens": 0
    }
  }
}
Last updated: 2026-06-15