> ## Documentation Index > Fetch the complete documentation index at: https://docs.aihubmix.com/llms.txt > Use this file to discover all available pages before exploring further. # LLM Search ## 1️⃣ Real-time Web Search: Breaking LLM Time Limitations for More Accurate and Reliable Outputs We've enhanced OpenAI and Gemini series models com o ability to access o mais recente information a partir do 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 **Modelos Suportados:** 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** Adicione o parâmetro `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. ## Guia de Uso Before using, run `pip install -U openai` to upgrade the openai package, and set your AIHubMix API Key as an environment variable: ```shellscript theme={null} export AIHUBMIX_API_KEY="" ``` Windows PowerShell: ```powershell theme={null} setx AIHUBMIX_API_KEY "" ``` **Example:** ```py Python theme={null} 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) ``` ```ts Typescript theme={null} 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); ``` ```shell Curl theme={null} 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 }' ``` ## 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 é obrigatório * 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 a partir do "credit change", and the "log detail" does not list the search fee yet, but will be shown no future The model id can be copied a partir do [model gallery](https://aihubmix.com/models). **Example:** ```py Python theme={null} 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}") ``` **API Response Example:** ```json theme={null} { "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 } } } ``` *** Última atualização: 2026-06-15